Science of awakening, Volume 93 (International Review of Neurobiology.) - PDF Free Download (2024)

00:26 (1:07) 01:16 (1:54) 7:28 (1:18) 9:46 (2:01) 405.9 (84.4) 527.2 (90.9)

00:53 (1:02) 01:36 (1:38) 7:51 (1:09) 10:14 (1:45) 398.4 (77.1) 537.0 (107.9)

.01 n.s. .05 n.s. n.s. n.s.

22.4 (30.7) 0.5 (1.0) 3.2 (1.2)

18.6 (17.6) 0.4 (0.8) 2.7 (1.1)

n.s. n.s. .01

4.4 (2.9) 3.1 (2.3) 0.7 (1.0) 47.9 (8.8)

4.7 (2.4) 3.9 (2.0) 0.9 (1.4) 43.7 (8.1)

n.s. .01 n.s. .001

From Matsuura et al. (2002). a Results of analysis of variance (ANOVA). “n.s.” means “not significant” b 5: very comfortable–1: very uncomfortable




As previously noted, the ability to SA means that one is able to awaken at any time during a sleeping episode even when the target time differs from their usual awakening time. However, persons who reported to have the SA ability do not always self-awaken regularly in their daily lives. Matsuura (2010) revealed that 34.0% of 333 university students surveyed reported that they had SA ability, but only 8.7% of these reported having habitual SA. Students who had the SA ability regardless of SA habit had a higher tendency for morningness and they woke up earlier than those who had no such ability. However, of those who had the SA ability, students with a habit of SA awakened more comfortably and showed less daytime sleepiness, compared to those without the habit. This suggests that the higher daytime functioning which accompanies individuals who habitually selfawaken could be caused by the SA habit lifestyle, but not the personality characteristics of the SA ability. In a pattern that is similar to that characteristic of habitual SA, as people in the population age, they are increasingly more likely to acquire SA ability. Kaida et al. (2006b) reported that 75.7% of 410 elderly persons surveyed (66–89 years, mean 74.3 years) answered they have the ability to SA from nocturnal sleep.



VI. Factors of Successful Self-Awakening




The success rate shown in studies done on SA depends on many variables, such as selection of participants, ability or habit of SA, target time of awakening, trial number of each participants, criterion of success, reward to success, and so on. Therefore, the values reported in previous studies cannot be subject to a simple comparison. Nevertheless, the main findings can be summarized as follows: (1) people who report habitual SA ability can awake at target times more precisely than those without this ability; (2) some persons who report having no such ability can awake at a time close to the target time; (3) success rate increases when attempting SA at home; (4) success rate is high for those who have the SA habit when target waking time is set to their usual waking time. In order to exclude the possibility of NA, many studies set the target waking time earlier than the usual the waking time. Lavie et al. (1979) recorded PSG of four consecutive nights (one night was for adaptation, one night was for baseline, and the other two nights were SA nights). They instructed seven young adults (21–30 years), who reported having SA ability, to self-awaken at 3:30 or 5:30 a.m., all times earlier than their usual waking times. Over 14 nights, they found that these participants awakened within 10 min of the stipulated target during 5 nights (36%) and awa­ kened within 30 min of the target during 9 nights (64%). Zepelin (1986) also recorded PSG and asked for 15 persons (15–32 years) who reported to have SA ability (four persons) or to have willing to try SA (7 persons) to self-awaken at 3:00 or 4:00 a.m. Eleven of the participants (73%) were able to awaken successfully. When SA ability is not involved, the success rate of awakening at a given time decreases. Zung and Wilson (1971) recorded PSG for four consecutive nights (two nights were adaptation and other two nights were SA nights) and asked for 22 persons (20–45 years) who were not selected for concerning about SA ability to self-awaken at randomly from 2 to 5 a.m. Their participants could awaken within 10 min of 14 of 44 nights (31.8%). At home, about half of the participants in a study, regardless of their SA ability, were shown to be able to succeed in SA at a target waking time that was earlier than their usual waking time. Bell (1980) reported that 53% of 38 participants, who were not selected about SA ability, could awaken within 15 min of a target time set to be more than 45 min earlier than their usual waking time. Hawkins and Shaw (1990) asked 146 undergraduate students to log 8 non­ consecutive nights of sleep. For four of these nights, participants were told to selfawaken 60 min after they extinguished the lights and went to bed; for the other four nights they did 60 min before they really wanted to get up. The successful rates for the early and late trials were 50 and 60%, respectively.



When the target waking time was set to usual waking time, the success rate in meeting this target time is enhanced regardless of whether or not people report SA ability. Hawkins (1989) reported that 74% of 84 university students could awaken within 30 min of their usual waking time when at home. Ikeda (2009) asked 11 university students, who had no habit and no SA ability, self-awaken at their usual waking time every morning for 1 week at home. Seven participants (64%) awakened within 30 min of their usual waking time on the first night, and 9 (82%) did on the last night. The average difference between the waking time and the target time on the successful nights was 16.9 and 13.1 min on the first and the last nights, respectively. Moorcroft et al. (1997) asked 15 persons (19–62 years) who had habitual SA to self-awaken at home and at their usual waking time for three consecutive nights. Over 44 nights except for one night of recording failure, they could awaken within 15 and 30 min from the target time in the 28 (63.6%) and 35 (79.5%) nights, respectively. In half of the nights, the difference between the waking and target time was within 7 min, and the mean time of difference was 3 min and 27 s. In the sleep laboratory, where environmental factors such as light or noise were controlled, the success rate in meeting a target waking time decreased even if the target was set to a usual waking time. Matsuura and Hayashi (2009) recorded PSG of 17 university students who had the SA habit for more than four consecutive nights in a sleep laboratory. The first two nights were for adaptation and the third and forth nights were for either SA or FA nights. If the participants could not awaken in the FA nights within 30 min of the target time, then the participants tried SA again in the additional nights. Their participants could self-awaken within 30 min in 11 of 27 nights (40.7%). Ikeda and Hayashi (2010) also recorded PSG of 10 university students who reported having no SA ability or SA habit for five consecutive nights in a sleep laboratory. The first night was for adaptation, the second night was for FA, and the last three nights were for SA. The participants could self-awaken within 30 min of usual waking time in 9 of 30 SA nights (30%). In a study of daytime naps, Kaida and colleagues reported that the success rate of SA was higher for those who have SA ability than for those who do not. They asked for the university students to awaken 15 min after extinguishing the lights, and for the elderly (65–80 years) to awake at 20 min after lights out. Nine of 11 (81.8%; Kaida et al., 2003a) and 10 of 14 university students (71%; Kaida et al., 2003b), and 9 of 10 elderly persons (90%; Kaida et al., 2005) could self-awaken within 5 min of a target time.

B. PSYCHOLOGICAL STRESS Psychological stress is increased by attempting SA as previously mentioned. This stress is caused by a motivation to awake successfully or by anxiety about the



failure to wake up on time. In either case, to attempt SA degrades the content of nocturnal sleep. Matsuura and Hayashi (2009) reported that state anxiety was higher before bedtime, when the participants were told to try SA in the morning (SA condition), than when they were told that they would be awakened by the experimenter (FA condition). After awakening from a night’s sleep, state anxiety did not differ between SA and FA conditions. In addition, EEG arousals and sleep stage 1 increased during 1 h before awakening in the SA condition. Sleep efficiency also decreased, that is WASO increased, during that time. These results suggest that attempting SA increases arousal or the likelihood of waking during the latter half of sleep. Bell (1980) has claimed that waking during sleep is a crucial factor for success in SA. He considered two abilities; the one is “an ability to induce greater potential for awakening” during sleep, and the other is “the ability to use accurately the information gathered at these check points” during sleep (p. 507). Although the latter ability has not been confirmed, it is reported that preparatory changes occur in the SA night toward the end of sleep. These changes include, for example, increase in EEG arousal, WASO and sleep stage 1 (Matsuura and Hayashi, 2009), decline in sleep spindle activities (Ikeda and Hayashi, 2008b), increase of ACTH (Born et al., 1999), and sympathetic nervous system activities (Matsuura and Hayashi, 2009), as mentioned previously.




It has been pointed out that motivation is one of the crucial factors of successful SA (Hawkins, 1989; Lavie et al., 1979). In the several experimental studies, participants received rewards to increase their motivation and accuracy in meeting waking time targets (Lavie et al., 1979; Zepelin, 1986; Zung and Wilson, 1971). However, participants with habitual SA have been shown to be naturally highly motivated (Matsuura, 2010). Matsuura et al. (2002b) found that achievement motivation of university students with habitual SA was higher than the average level of achievement measured in university students. It has also been reported that self-efficacy was higher for those who reported SA ability for both young adults (Crabb, 2003; Matsuura, 2010) and the elderly (Kaida et al., 2006a). Self-efficacy is “the belief in one’s capabilities to organize and execute the courses of action required to manage prospective situations” (Bandura, 1995, p. 2). Crabb (2003) stated that “awakening to be on time is a social skill insofar as it coordinates individuals’ sleep wake cycle with the schedule of families, school, work, transportation, and other social systems” (p. 344). He also thought that those who self-awakened daily have high self-adjustment skills,



thus these people may also have high self-efficacy. Results of a survey of 417 university students appear to confirm this; self-efficacy was positively correlated with confidence in being able to self-awaken regularly (r = .392), while it was negatively correlated with willingness to use an alarm clock (r = –.412) or to be awakened by another person (r = –.207).

D. ENVIRONMENTAL FACTORS The success rate of SA is relatively high when participants attempted SA at home, compared to in the laboratory (as noted earlier). For example, if target waking time was set to the usual waking time, accuracy rate ranged from 64% (Ikeda, 2009; Moorcroft et al., 1997) to 74% (Hawkins, 1989) at the participants’ home, whereas it dropped to between 30% (Ikeda and Hayashi, 2010) and 40.7% (Matsuura and Hayashi, 2009) in the sleep laboratory. Ambient light, noise, or temperature is not available in the laboratory, suggesting that such environmental factors contribute to successful SA.




Moorcroft et al. (1997) queried participants with habitual SA how they awakened without an alarm or prior to the alarm time. The most common response was “an internal clock” (26%), and second was “habit or daily routine” (16%). Some researchers also postulated that SA is caused by an internal alarm clock (Bell, 1980; Zepelin, 1993; Zung and Wilson, 1971). Because biological ˚ kerstedt et al. (2002) pointed out that rhythms can function as an internal clock, A the circadian rhythm of body temperature and ultradian rhythm of NREM–REM sleep cycles are involved in the propensity to awaken from sleep. Circadian rhythm induces additional transition to wakefulness and creates a greater chance for the termination of sleep in the rising phase of the body temperature. The NREM–REM cycle connects with the high probability of awakening from REM sleep, which has been confirmed after normal nocturnal sleep, under the conditions of desynchronization without external time cues, forced desynchrony, or 60 h of bed-rest. As previously noted, however, the relationships between REM sleep and SA are not clear. The two-process model of sleep–wake regulation postulates roles for two different processes: a circadian rhythm mechanism and a homeostatic process



for determining the timing and structure of sleep (Borbey and Achermann, 1999). In this account, the EEG slow wave activity, which is representative of the homeostatic process, declines with the passage of time during sleep. This means that sleep pressure or sleep maintenance function declines with elapsed time from sleep onset. Thus circadian and homeostatic processes are involved in awakening from sleep, while the relationship between these processes and SA has not still been examined.

F. TIME PERCEPTION Bell (1980) has postulated internal, biological processes that check the elapsed time or duration of sleep. Although Zepelin (1986) denied the possibility of “time judgment” during sleep, it has been reported that we have the ability to estimate time during sleep. Aritake et al. (2009) reported that time estimation ability during sleep is related to elapsed time from sleep onset and that this is positively correlated with the amount of slow wave sleep (sleep stages 3 and 4). This was not related with acrophase of circadian body temperature rhythm, suggesting that time estimation during sleep is not regulated by the circadian system. It has also been reported that time estimation during sleep becomes more accurate when attempting SA. Ikeda et al. (2006) forced participants to awaken during sleep for two nights and asked them to estimate the clock time. These participants were previously instructed to try to self-awaken during one night (SA condition) and to awaken naturally in the morning during the other night (NA condition). To control the sleep stage at awakening, participants were awakened 5 min following REM sleep continued in each NREM–REM cycle. Error time between the real time and the estimated time was reduced in the SA condition, compared to the NA condition. This result supports the notion that more precise judgment of time near the target waking time is a factor contribut­ ing to successful SA. However, the mechanisms that are involved which help make the time perception precise are still unclear.

VII. Schematic Model of Self-Awakening

Figure 3 presents schematic outline of model of self-awakening. Attempts at SA are proposed to increase psychological stress, and this, in turn, affects cognitive and physiological functions during sleep. Time perception during


Before sleep


Tendency to awaken

Attempt to SA

Psychological stress

Cognitive function

Circadian factor Rise in body temperature

Accuracy of time perception Trigger of promoting arousal During sleep

Homeostatic factor Decline in sleep maintenance function

Environmental factors Light, noise, temperature, etc.

Increase of ACTH Enhancement of SNS Decline in waking Threshold immediately before awakening Decline in sleep spindle activities Increase of EEG arousal and WASO Lightening of sleep

Factors of habitual SA Personality Ability to SA Self-efficacy Achievement motivation Age Regular sleepwake habit morningness etc. Social factors Necessity to awake at specific time

After sleep


Improvement of waking function Decline in sleep inertia Enhancement of daytime activity level Decrease of daytime sleepiness

FIG. 3. Schema of self-awakening.

sleep becomes more accurate when SA is attempted; in addition, several events, such as an increase of ACTH and sympathetic nervous system activities, promote arousal during the latter half of sleep. These phenomena trigger a decline in waking threshold immediately before awakening; that is, they increase EEG arousal and WASO, lighten sleep, or decrease sleep spindle activities. As results described earlier have shown, this decline permits a smooth self-awakening from



sleep, and it reduces chances of sleep inertia immediately after awakening. Thus, the waking function is improved in daytime. Decline in waking threshold during sleep is also promoted by homeostatic, circadian, and environmental factors. In the latter half of a sleep period, the sleep maintenance function declines due to dissipation of homeostatic process during sleep, and arousal increases due to a rise in body temperature. In addition, environment factors, such as ambient light, noise, and temperature, enhance arousal during sleep. Both personality and social factors affect habitual SA. The ability to SA, high self-efficacy and achievement motivation, consistency of daily sleep length, and morningness chronotype are characteristics of those who have the habit of SA. In addition, the number of people who self-awaken daily increases with age. Finally, the necessity to awake at specific time is the most important social factor for SA, which differentiates SA from NA.

VIII. Conclusion

Many previous studies confirm that a number of people can successfully awaken at a desired time and they do so habitually by themselves without the aid of external means such as alarm clocks or other people. In addition, the attempt to self-awaken produces various kinds of preparatory changes over the course of a sleep period, including contributing to a decline in the waking threshold immediately before awakening. However, it remains unclear why and how such changes occur near the target waking time, why time perception becomes precise when attempting to self-awaken, or what type of internal clock affects SA apart from biological rhythms such as circadian rhythm and ultradian rhythm of NREM–REM cycle, among other issues. Further research in SA is required to clarify these clock mechanisms.


˚ kerstedt, T., Billiard, M., Bonnet, M., Ficca, G., Garma, L., Mariotti, M., Salzarulo, P., and Schulz, A H. (2002). Awakening from sleep. Sleep Med. Rev. 6, 267–286. American Sleep Disorders Association. (1992). EEG arousals: Scoring rules and examples. Sleep 15, 174–184. Aritake-Okada, S., Uchiyama, M., Suzuki, H., Tagaya, H., Kuriyama, K., Matsuura, M., Takahashi, K., Higuchi, S., and Mishima, K. (2009). Time estimation during sleep relates to the amount of slow wave sleep in humans. Neurosci. Res. 63, 115–121.



Bandura, A. (1995). Self-Efficacy in Changing Societies. Cambridge University Press, Cambridge, UK. Bell, C. R. (1980). Awakening from sleep at a pre-set time. Percept. Mot. Skills 50, 503–508. Borbey, A. A., and Achermann, P. (1999). Sleep homeostasis and models of sleep regulation. J. Biol. Rhythms 14, 557–568. Born, J., Hansen, K., Marshall, L., Mo¨lle, M., and Fehm, H. L. (1999). Timing the end of nocturnal sleep. Nature 397, 29–30. Crabb, P. B. (2003). Technology and self-regulation: The case of alarm clock use. Soc. Behav. Pers. 31, 343–348. Deinzer, R., Kirschbaum, C., Gresele, C., and Hellhammer, D. H. (1997). Adrenocortical responses to repeated parachute jumping and subsequent h-CRH challenge in inexperienced healthy subjects. Physiol. Behav. 61, 507–511. Ferrara, M., and De Gennaro, L. (2000). The sleep inertia phenomenon during the sleep-wake transition: Theoretical and operation issues. Aviat. Space Environ. Med. 71, 843–848. Fuller, K. H., Waters, W. F., Binks, P. G., and Anderson, T. (1997). Generalized anxiety and sleep architecture: A polysomnographic investigation. Sleep 20, 370–376. Harrison, Y., and Horne, J. A. (1996). Long-term extension to sleep – Are we really chronically sleep deprived? Psychophysiology 33, 22–30. Hawkins, J. (1989). Sleep disturbance in intentional self-awakenings: Behavior-genetic and transient factors. Percept. Mot. Skills 69, 507–510. Hawkins, J., and Shaw, P. (1990). Sleep satisfaction and intentional self-awakening: An alternative protocol for self-report data. Percept. Mot. Skills 70, 447–450. Hayashi, M., Chikazawa, Y., and Hori, T. (2004). Short nap versus short rest: Recuperative effects during VDT work. Ergonomics 47, 1549–1560. Hayashi, M., f*ckushima, H., and Hori, T. (2003a). The effects of short daytime naps for five consecutive days. Sleep Res. Online 5, 13–17. Hayashi, M., Masuda, A., and Hori, T. (2003b). The alerting effects of caffeine, bright light and face washing after a short daytime nap. Clin. Neurophysiol. 114, 2268–2278. Hayashi, M., Motoyoshi, N., and Hori, T. (2005). Recuperative power of a short daytime nap with or without stage 2 sleep. Sleep 28, 829–836. Hono, T., Hiroshige, Y., and Miyata, Y. (1991). Nocturnal sleep at a predetermined time in healthy undergraduate students. Kawasaki J. Med. 1, 209–215. ¨ stberg, O. (1976). A self-assessment questionnaire to determine morningness­ Horne, J. A., and O eveningness in human circadian rhythms. Int. J. Chronobiol. 4, 97–110. Ikeda, H. The effects of self-awakening on nocturnal sleep and arousal level after awakening. Doctoral dissertation, Hiroshima University, Japan, 2009. Ikeda, H., and Hayashi, M. (2008a). Effect of sleep inertia on switch cost and arousal level immedi­ ately after awakening from normal nocturnal sleep. Sleep Biol. Rhythms 6, 120–125. Ikeda, H., and Hayashi, M. (2008b). Electroencephalogram activity before self-awakening. Sleep Biol. Rhythms 6, 256–259. Ikeda, H., and Hayashi, M. (2010). The effect of self-awakening from nocturnal sleep on sleep inertia. Biol. Psychol. 83, 15–19. Ikeda, H., Miyaji, K., Hayashi, M., and Fujisawa, K. (2006). The effect of attempt at self-awakening on time assessment during sleep. Jpn. J. Physiol. Psychol. Psychophysiol. 24, 227–235. Kaida, K., Nakano, E., Nittono, H., Hayashi, M., and Hori, T. (2003a). The effects of self-awakening on heart rate activity in a short afternoon nap. Clin. Neurophysiol. 114, 1896–1901. Kaida, K., Nittono, H., Hayashi, M., and Hori, T. (2003b). Effects of self-awakening on sleep structure of a daytime short nap and on subsequent arousal levels. Percept. Mot. Skills 97, 1073–1084. Kaida, K., Ogawa, K., Hayashi, M., and Hori, T. (2005). Self-awakening prevents acute rise in blood pressure and heart rate at the time of awakening in elderly people. Ind. Health 43, 179–185.



Kaida, K., Ogawa, K., Matsuura, N., Takahashi, M., and Hori, T. (2006a). Relationship between the habit of napping with self-awakening and generalized self-efficacy. Jpn. J. Health Psychol. 19, 1–9. Kaida, K., Ogawa, K., Nittono, H., Hayashi, M., Takahashi, M., and Hori, T. (2006b). Selfawakening, sleep inertia, and P3 amplitude in elderly people. Percept. Mot. Skills 102, 339–351. Kamdar, B. B., Kaplan, K. A., Kezirian, E. J., and Dement, W. C. (2004). The impact of extended sleep on daytime alertness, vigilance, and mood. Sleep Med. 5, 441–448. Lavie, P., Oksenberg, A., and Zomer, J. (1979). “It’s time, you must wake up now.” Percept. Mot. Skills 49, 447–450. Matsuura, N. Studies on the effects of habit of self-awakening on nocturnal sleep and daytime arousal. Doctoral dissertation, Hiroshima University, Japan, 2010. Matsuura, N., and Hayashi, M. (2009). Effects of habitual self-awakening on nocturnal sleep, autonomic activity prior to awakening, and subjective condition after awakening. Sleep Biol. Rhythms 7, 172–180. Matsuura, N., Hayashi, M., and Hori, T. (2002a). Comparison of sleep/wake habits of university students with or without a habit of self-awakening. Psychiatry Clin. Neurosci. 56, 223–224. Matsuura, N., Hayashi, M., and Hori, T. (2002b). The effect of habitual self-awakening on sleep processes and subjective rating of nocturnal sleep. Jpn. J. Physiol. Psychol. Psychophysiol. 20, 61–69. Monk, T. H., Buysse, D. J., Rose, L. R., Hall, J. A., and Kupfer, D. J. (2000). The sleep of healthy people – a diary study. Chronobiol. Int. 17, 49–60. Montano, N., Ruscone, T. G., Porta, A., Lombardi, F., Pagani, M., and Malliani, A. (1994). Power spectrum analysis of heart rate variability to assess the changes in sympathovagal balance during graded orthostatic tilt. Circulation 90, 1826–1831. Moorcroft, W. H., Kayser, K. H., and Griggs, A. J. (1997). Subjective and objective confirmation of the ability to self-awaken at a self-predetermined time without using external means. Sleep 20, 40–45. Murphy, P. J., Rogers, N. L., and Campbell, S. S. (2000). Age differences in the spontaneous termination of sleep. J. Sleep Res. 9, 27–34. Polich, J., and Kok, A. (1995). Cognitive and biological determinants of P300: An integrative review. Biol. Psychol. 41, 103–146. Spa¨th-Schwalbe, E., Scho¨ller, T., Kern, W., Fehm, H. L., and Born, J. (1992). Nocturnal adreno­ corticotropin and cortisol secretion depends on sleep duration and decreases in association with spontaneous awakening in the morning. J. Clin. Endocrinol. Metab. 75, 1431–1435. Stepanski, E. J., and Burgess, H. J. (2005). The case for trait determinants of arousal and sleepiness. Sleep 28, 664–665. Tassi, P., and Muzet, A. (2000). Sleep inertia. Sleep Med. Rev. 4, 341–353. Ueda, K., Nittono, H., Hayashi, H., and Hori, T. (2001). Spatiotemporal changes of slow wave activities before and after 14 Hz/12 Hz sleep spindles during stage 2 sleep. Psychiatry Clin. Neurosci. 55, 183–184. Zepelin, H. (1986). REM sleep and the timing of self-awakenings. Bull. Psychon. Soc. 24, 254–256. Zepelin, H. (1993). Internal alarm clock. In: Encyclopedia of Sleep and Dreaming (M. A. Carskadon, ed.), Macmillan, New York, NY, p. 315. Zung, W. W. K., and Wilson, W. P. (1971). Time estimation during sleep. Biol. Psychiatry 3, 159–164.




Robert L. Matchock The Pennsylvania State University, Altoona, PA 16601-3794, USA

I. II. III. IV. V.

Introduction Time-of-Day and Cognition Time-of-Day Effects and Waking Up Length of Sleep Episode and SI Different Measures of Cognitive Functioning


The process of waking up from an episode of sleep can produce temporary deficits in cognitive functioning and low levels of alertness and vigilance, a process referred to as sleep inertia. Cognitive ability varies as a function of time-of-day; cognitive ability associated with sleep inertia also shows circadian influences with deleterious effects most pronounced when awakened from biological night, possibly paralleling the core body temperature minimum. The length of the sleep episode may contribute to the severity of sleep inertia. Short sleep episodes (<20 min) produce little cognitive impairment, probably because of a lack of slow-wave sleep in the sleep episode. With longer sleep episodes, aspects of sleep depth such as percentage of slow-wave sleep or total length of the sleep episode may be important. Finally, myriad tasks have been used to measure sleep inertia effects, and cognitive deficits associated with waking up have been demonstrated on both simple and complex tasks for both speed and accuracy. More research is needed on how the type of task may interact with sleep inertia. Tests that measure known specific aspects of cognition and that can be mapped to brain systems and neurotransmitters (e.g., the Attentional Network Test: ANT) are recommended to further under­ stand how information processing during the process of awakening is distinct from other aspects of awareness.

INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 93 DOI: 10.1016/S0074-7742(10)93006-7


Copyright 2010, Elsevier Inc. All rights reserved. 0074-7742/10 $35.00



I. Introduction

The time period shortly after awakening from an episode of sleep can, paradoxically, result in various deficits in cognitive and motor performance, confusion, disorientation, and hypovigilance, relative to the pre-sleep period (Ferrara and De Gennaro, 2000; Tassi and Muzet, 2000). Although sleep is usually considered to be restorative, task performance immediately after sleeping can be worse than it was prior to the sleep bout when sleep deprivation was greater (Wertz et al., 2006). This deleterious effect, experienced by almost all humans at least once per day, has been termed “sleep drunkenness” (Broughton, 1968) or, more commonly, sleep inertia (SI) (Lubin et al., 1976). Compared to falling asleep, relatively little is known about the process of waking up. This paucity of information is unfortunate because the beneficial effects of napping must be evaluated against any performance deficits that are associated with SI. In models of sleep/wake regulation, SI is referred to as “process W” and is con­ trasted with homeostatic mechanisms that negatively affect performance as a function of prior waking time (“process S”) and an endogenous sleep-independent circadian component (“process C”) (Borbely, 1982; Folkard and Akerstedt, 1992). See Fig. 1 for a representation of homeostatic, circadian, and sleep inertia processes on task performance. Myriad factors appear to modulate the severity of sleep inertia such as sleep stage prior to awakening (Bonnet, 1983), time-of-day (process C) (Dinges et al., 1985), prior sleep deprivation (process S) (Ferrara et al., 2000a), total length of the sleep bout (Matchock and Mordkoff, 2007), ultradian phase (Lavie and Weler, 1989), whether awakenings are forced or self-imposed (Ikeda and Hayashi, 2010; Kaida et al., 2006), as well as the type of task that is administered to participants (Matchock and Mordkoff, 2007; Tassi and Muzet, 2000). The current chapter will examine circadian and length of sleep bout factors on SI and the types of tasks that are commonly used to document any putative deficits in functioning, with the caveat that these aforementioned etiological factors are inexorably linked and may interact in complex not-well-understood ways.

II. Time-of-Day and Cognition

As an illustration, the simple relation between cognitive processing and timeof-day, without consideration of any SI influences, is not so simple (for reviews see Carrier and Monk, 2000; Schmidt et al., 2007). Early studies have indicated that circadian fluctuation in alertness and cognitive performance on tasks that had small cognitive loads paralleled the circadian rhythm of core body temperature



SI affected by:

Task performance

Only Process S

Only Process C

• • • • • • •

Both Processes S and C (observed)

Circadian factors Sleep deprivation Sleep stage upon awakening Percentage of SWS in bout Sleep bout length Type of task Thermoregulatory processes

7 h sleep

Process W sleep inertia (SI): lasting approximately 20 min to 2 h


24 h

48 h Time

FIG. 1. Diagrammatic representation of homeostatic, circadian, and sleep inertia processes on task performance. Homeostatic pressure due to sleep deprivation increases linearly as a function of time spent awake (approximately 48 h), which occurs against a backdrop of underlying circadian rhythmicity (process C). Process W is the brief period after an episode of sleep characterized by cognitive impairments and functioning that can be worse than performance prior to the sleep episode when homeostatic (and perhaps circadian) processes were greater.

(CBT) (Colquhoun, 1971; Kleitman, 1963). Later research has shown that this relationship may be more complex. One report found that self-rated alertness, using a visual analogue scale (VAS), was phase advanced (acrophase at 1200 h) relative to CBT (acrophase at 1900 h) (Monk et al., 1983). Ultradian 90 min rhythmicities in alertness and performance have been widely reported as well (Broughton, 1975; Conte et al., 1995; Kleitman, 1963; Lavie and Zomer, 1984), including ultradian differences between the two hemispheres (Iskra-Golec and Smith, 2006). Moreover, although self-reported alertness is likely to parallel simple perceptual speed (Colquhoun, 1971; Kleitman, 1963), it may not follow as closely more complex cognitive measures such as performance on a memorysearch task (Owens et al., 1998). According to some research (e.g., Kraemer et al.,



2000; Owens et al., 2000) it is becoming increasingly clear that different aspects of performance and attention, although still typically circadian in nature, follow different time-of-day patterns. Other research seems to suggest that the nature of the cognitive task is instru­ mental in determining optimal performance and that not all tasks are closely correlated with temperature (Carrier and Monk, 2000). For example, immediate memory (Folkard and Monk, 1980), acoustic processing (Folkard, 1979), and dichotic processing of digits (Morton and Kershner, 1991) appear to peak in the morning hours when body temperature is lower. Delayed memory (Folkard and Monk, 1980), semantic processing (Folkard, 1979), and tests of logical reasoning (Folkard, 1975) may be better if information is encoded later in the day when temperature is higher. Tasks that require simple processing (i.e., card sorting or letter cancellation) also peak late in the day and are more closely associated with body temperature (Carrier and Monk, 2000; Colquhoun, 1971). Folkard et al. (1983) suggested that performance measures might be under multi-oscillatory control, affected by a sleep/wake oscillator, a temperature oscillator, and an oscillator for working memory. It is plausible that the curvilinear relationship between arousal and task performance (i.e., Yerkes and Dodson, 1908) would provide an explanation for some of these results. Performance on complex tasks should peak earlier in the day when arousal is lower or at an intermediate level, while performance on simple tasks should peak later when arousal is higher. Indeed, Folkard et al. (1983) found that performance on a 1-letter cancellation task paralleled the body temperature rhythm, but not a 5-letter cancellation task. Kahneman (1973) argues that the mobilization of effort in a task is also controlled by the demands of the task itself, with difficult tasks increasing arousal more than easier tasks. Infrequent sampling, small sample sizes, exogenous factors impinging on subjects’ daily routines when not constantly restricted to the laboratory, and inadequate research designs may limit confidence in some of these results. Cognitive performance may decrease over time because of time spent awake, perhaps because of adenosine accumulation inhibiting arousal neurons of the basal forebrain (Porkka-Heiskanen, 1999) (process S), because circadian pace­ makers are currently producing a state of low arousal (or high) that is not optimal for performing the task, or because of both (either in an additive or in an interactive fashion). “Forced desynchronization (FD) protocols” allow researchers to disentangle homeostatic and circadian influences. Normally, endogenously generated rhythms from the suprachiasmatic nucleus (SCN) of the anterior hypothalamus are entrained to Zeitgebers (time givers) such as the light–dark cycle or photoperiod. Most humans fall asleep when CBT, which is circadian in nature (Scales et al., 1988), starts to decline. However, when subjects are main­ tained under long (e.g., 28 h) or short (e.g., 20 h) days in a laboratory setting with no time cues, entrainment is not possible and a desynchronization occurs between the endogenous circadian cycle and the sleep wake cycle, resulting in



sleep episodes that will occur at different circadian phases. This free-running condition allows researchers to control for circadian phase and sleep deprivation. Constant routine (CR) protocols, although not ideal for isolating circadian and homeostatic factors, are characterized by bed rest or inactivity, sleep deprivation, and equally spaced isocaloric snacks in an attempt to separate the effects of endogenous rhythms from exogenous factors. Results from FD designs suggest a much closer coupling of task performance with core body temperature. Johnson et al. (1992) found that subjective alertness and calculation performance were closely linked to CBT. Similarly, Wright et al. (2002) found that performance on various measures of cognitive performance such as the Digit Symbol Substitution Test (DSST), addition tasks, subjective alertness, and a Psychom*otor Vigilance Task, all positively correlated with body tempera­ ture. Another recent FD study (e.g., Lee et al., 2009) also found that performance on an addition task and a Psychom*otor Vigilance Task was poorest at the circadian nadir of CBT. Taken together, research strongly suggests that human cognition and performance are not uniform across the 24 h day, but vary in a rather systematic way that seems to roughly parallel, or be phase-locked to, endogenously generated rhythms of alertness and temperature (process C). This rhythmicity suggests that the processes associated with waking up from a sleep episode may also differ as a function of time-of-day.

III. Time-of-Day Effects and Waking Up

Immediate and important decisions upon awakening are common occurrences for people in many occupations (e.g., truck drivers, shift workers, emergency workers and military personnel on call, airline pilots, oil rig workers, college students taking naps before examinations). Moreover, these abrupt awakenings that require immediate attentional resources can potentially occur at any point of the 24 h day. As such, it would be extremely valuable to understand how, if at all, circadian regulatory mechanisms affect SI. Napping studies afford the opportunity to examine how the process of awakening can vary according to time-of-day. Most napping studies, though, are interested in the residual restorative properties of the nap and some studies test participants (or report data) after the period of SI has dissipated (e.g., Dinges et al., 1987; Hayashi et al., 1999; Taub et al, 1977). With this caveat in mind, what follows is a representative summary of studies that have manipulated the timing of naps. Naitoh (1981) found that a 2 h nap from 0400 to 0600 h near the circadian nadir (low CBT) had little recuperative value when performance was measured shortly after the nap compared to a 2 h nap from 1200 to 1400 h. Other studies



(e.g., Naitoh et al., 1982) have similarly found that short naps near the circadian nadir seem to have attenuated restorative properties immediately after the nap, presumably because of SI. Awakenings from short afternoon naps seem to produce fewer cognitive impairments than nighttime naps, although there may be a subjectively experienced increase in effort that is required to perform tasks which is not manifested in any detectable behavioral impairments (Asaoka et al., 2010). Bonnet and Arand (1995) found that psychom*otor performance after four 1 h naps in the middle of the night was more impaired than after a 4 h nap in the middle of the afternoon. Despite more SI associated with the nighttime naps during the circadian nadir, there was a delayed improvement in performance the following evening that was not observed with the afternoon nap. That is, naps during the circadian nadir during biological night may be more restorative in the long-term than daytime naps, perhaps because of more slow-wave sleep (SWS) (Takeyama et al., 2004), but may initially show more SI. In patients with narco­ lepsy, awakening from short 30 min daytime naps can show much SI, as measured by subtraction tasks and a four-choice reaction time (RT) task, probably because of SWS arousals (Mullington and Broughton, 1994). Much evidence suggests a drop in alertness and an increase in sleep propen­ sity during the afternoon, the so-called post-lunch dip (Bes et al., 2009; Busby and Broughton, 1983). Lavie and Weler (1989) allowed subjects a mid-afternoon, “sleep gate” nap (1500–1700 h) and an early evening, “forbidden zone” nap (1900–2100 h). Even though the mid-afternoon nap was characterized by more SWS, subjects had less SI as measured by mood scores and sleepiness data; performance data were not reported. Hayashi and colleagues found that 20 min naps during the late afternoon (post-lunch dip) and before the postlunch (early afternoon) dip both decreased sleepiness, but only the late afternoon nap resulted in increases in performance (Hayashi and Hori, 1998; Hayashi et al., 1999). Late afternoon naps may be restorative and may also be characterized by waking up processes that do not greatly interfere with task performance. These findings also suggest that ultradian cycles may be another potential variable to consider for researchers who study the awakening process. When comparing daytime and nighttime naps, it is important to note that when people are awakened during biological night, they are likely to have elevated melatonin. Melatonin secretion by the pineal gland occurs during biological night and has soporific (Wirz-Justice and Armstrong, 1996) and hypothermic properties (Hughes and Badia, 1997). Exogenously administered melatonin during the day has produced decrements on a Psychom*otor Vigilance Task (Graw et al., 2001) and a two-choice visual RT task (Rogers et al., 1998), although not on a letter cancellation task (Graw et al., 2001). The ability of exogenous melatonin to reduce CBT and increase sleepiness may be functionally related to its ability to promote vasodilation of distal skin surfaces (Cagnacci et al., 1997).



Indeed, some have postulated that the dissipation of SI is related to distal vasoconstriction, especially the distal-to-proximal skin temperature gradient (DPG; Kra¨ uchi et al., 2004). Kra¨ uchi et al. (2004) monitored subjective sleepiness, CBT, and proximal and distal skin temperatures in subjects before and after an 8 h sleep bout (2300–0700 h) and a 2 h nap (1600–1800 h). CBT dropped during the 8 h sleep bout but not during the nap. However, for both the longer sleep bout and the nap, distal temperature increased upon falling asleep and decreased shortly after awakening. The dissipation of subjective sleepiness (performance measures were not taken) correlated with the rate at which the extremities cooled (i.e., distal vasoconstriction). Sleep stage upon awakening was not associated with subjective sleepiness or the extent of vasoconstriction. The authors hypothesized that a 2 h relaxation period characterized by no sleep but with distal vasodilation would induce SI. Using a hybrid CR/FD procedure, Kra¨ uchi and colleagues (2006) found that although sleep deprivation (process S/homeostasis) increased sleep propensity and SWS rebound, homeostatic mechanisms had no effect on the thermoregulatory system (i.e., core, distal, and proximal temperature). In this study, the dissipation of SI also correlated well with the extent of distal vasoconstriction. Circadian aspects of sleepiness were highly correlated with CBT, and distal temperature changes were phase advanced (occurred earlier). That is, hypnagogic distal vasodilation and hypnopompic distal vasoconstriction (distal warming and cooling, respectively) may regulate both CBT and SI, at least as measured by subjective sleepiness. If further studies confirm these findings (e.g., cold water applications to the extremities in order to negate SI), this would lend support to the hypothesis that circadian factors can influence SI, even though the relation between CBT and distal temperature is inversely correlated (Gradisar and Lack, 2004; Kra¨uchi et al., 2006), and influences such as an afternoon nap may affect distal temperature but not CBT (Kra¨ uchi et al., 2004). As well, it would be informative for future investigations to examine how well distal thermo­ regulatory changes correlate with cognitive functions and task performance, in addition to self-reported sleepiness. At least one study (e.g., Werken et al., 2010) found a parallel between decreases in distal skin temperature, DPG, and decreases in subjective sleepiness and simple RT and improvements on an addition task. Artificial dawn simulation for the 30 min prior to awakening at 0700 h also improved all of these measures. Other studies have examined the process of awakening from a sleep episode primarily within the period of biological night. In perhaps the earliest attempt to examine this, Wilkinson and Stretton (1971) awakened naval service men either at 0030, 0130, 0330, or 0530 h and administered an addition task, a simple RT task, and a coordination task. All awakenings show impaired performance rela­ tive to an afternoon control condition. Although sleep bout length and circadian time were confounded, simple RT was impaired more early in the night and steadily improved across the sessions. Performance on the addition and coordi­ nation tasks were more impaired later in the night, although there was a sharp



improvement in performance in the 0530 h condition for the addition task. As partially suggested by the authors, simple RT appeared to be more of a function of depth of sleep (length of sleep bout or percentage of SWS), while the addition task appeared to be more circadian in nature (Fig. 1;Wilkinson and Stretton, 1971). That is, simple RT appeared to be influenced by process S and perfor­ mance on the adding task by process C (but see Matchock and Mordkoff, 2007 for an opposite pattern). Balkin and Badia (1988) had subjects go to sleep at 2400 h and were awakened at 0040, 0140, 0240, 0340, 0440, and 0540 h for a 20 min testing session for four consecutive days. Latency to fall asleep and performance on an addition test decreased across the night, and sleepiness ratings increased. This pattern of results is suggestive of a circadian influence. However, protocols characterized by frequent awakenings typically result in more degraded performance (Downey and Bonnet, 1987), and sleep deprivation can increase the percentage of SWS in a nap (Dinges et al., 1985; Matsumoto, 1981) and even rapid eye movement (REM) sleep (Matsumoto, 1981). Brief arousals that produce a transient burst of alpha activity on the electroencephalography (EEG) but do not fully awaken subjects nor reduce the time spent sleeping are characterized by diminished recuperative value (Levine et al., 1987). Tassi et al. (1992), using a spatial memory task, found increased RTs in a 1 h nap during the first part of the night (0100 h) compared to later in the night (0400 h), presumably because subjects were more likely to be awakened in SWS in the early-night nap. However, exposure to arousal-increasing noise abolished this SI in the 0100 h nap but not in the 0400 h nap. Gil and colleagues have also found more impaired performance upon awakening from a nap during the first part of the night (Gil et al., 1994, 1995). Dinges et al. (1985) awakened subjects after 2 h naps that were either in the peak or in the trough of circadian body temperature after 6, 18, 30, 42, or 54 h of sleep deprivation. Prior sleep deprivation increased the amount of SWS in naps. For simple RT (i.e., how long it took subjects to answer a phone), sleep stage upon awakening was associated with increased RTs. For a higher cognitive functioning using the descending subtraction task (DST), the total amount of SWS accumulated in the nap was a better predictor of performance. Finally, naps during the circadian trough of core body temperature (when it is easier to fall asleep) were associated with more severe cognitive decrements than naps during peak core body temperature with more sleep deprivation, suggesting that circa­ dian influences can counteract sleep deprivation. Other studies have produced results on the contrary. Naitoh et al. (1993) reasoned that since there is a best time to fall asleep quickly, there should also be an optimal time to wake up quickly. Experimental subjects were awake for 64 h and took a 20 min nap every 6 h, while control subjects were awake for 64 h without any napping. Performance on Baddleley’s logical reasoning task indi­ cated an SI effect with the experimental subjects performing worse than control subjects for number of problems attempted and accuracy. However, there were



no circadian time effects of SI, relative to the controls, despite performance on the reasoning task showing a circadian rhythm. This study, though, had a small sample size and only sampled logical reasoning every 6 h. These above results may be equivocal due to different dependent measures that are used to measure SI and the confounding effects of prior sleep deprivation and sleep stage upon awakening. In perhaps the best controlled study to date, Scheer et al. (2008) employed an FD protocol that desynchronized the sleep/wake cycle from the circadian cycle by using a 28 h “day.” The data clearly indicated an endogenous circadian rhythm of SI (as measured with a 2-digit serial addition task) with degraded performance during subjects’ biological night than the biological day, especially just prior to the CBT minimum. Neither sleep stage upon awakening nor the cumulative proportion of various sleep stages in an epoch were significant predictors of SI. In another study of SI that employed an FD protocol, Silva and Duffy (2008) found that older adults had impaired performance on the DSST when they were awakened during their biological night. Awakenings from non-REM sleep were also associated with worse performance than from REM sleep. Collec­ tively, these two well-controlled studies provide convincing evidence that circadian factors have an effect on SI, such that if participants are awakened at a time when their bodies indicate that they should be sleeping, cognitive impairments are greater. It may be somewhat premature to completely discount the effect of sleep stage upon awakening (see Silva and Duffy, 2008). The subtle effects may be missed when overall sleep depth (i.e., actual awakening while in SWS or percentage of SWS in bout) is not controlled. For example, awakenings from stage 2 or REM sleep (considered to be the same “depth” of sleep) at the same time of the night result in left hemisphere task enhancements (verbal memory) and right hemisphere task enhancements (spatial task), respectively (Lavie et al., 1984). Stickgold et al. (1999) used a semantic priming task to sample cognitions upon awakenings from REM and stage 2 NREM sleep. Priming was better for strongly associated word pairs (e.g., long–short) in NREM sleep and for weakly associated word pairs (e.g., thief–wrong) in REM, suggesting that the associative connections in a dream state may be different than in NREM or the waking state. Interestingly, this weak priming upon awakening from REM decreased in strength as the night progressed when the duration of REM episodes are known to increase. This attenuation may reflect the masking of stage-specific effects by more robust circadian influences.

IV. Length of Sleep Episode and SI

Researchers have devoted less attention to sleep parameters such as the total amount of REM, SWS, or the overall length of the sleep bout. Sleep episodes as short as 30 min (Brooks and Lack, 2006; Tietzel and Lack, 2001) to as long as 8 h



with no prior sleep deprivation (Jewett et al., 1999) can be followed by an SI period that can last up to 2 h (Jewett et al., 1999). The nature of the relationship between sleep bout length and SI upon awakening is not well understood and difficult to experimentally isolate. One way to partially address this issue is to examine the recuperative effects (or lack thereof) of naps of different durations. Afternoon naps as brief as 10 min are associated with improvements in subjective alertness and cognitive performance (Brooks and Lack, 2006; Tietzel and Lack, 2001), while longer 30 and 50 min naps are associated with impaired alertness and performance, followed by improvements after the SI period has dissipated (Brooks and Lack, 2006; Sallinen et al., 1998; Tietzel and Lack, 2001). This pattern of results seems to suggest that either longer total sleep periods, longer periods of time consisting of SWS, or awakening in SWS contributes to SI. Circadian factors are controlled for since these short naps occur at the same relative time (e.g., between 1400 and 1504 h in Brooks and Lack, 2006). Ultrabrief naps of 30 and 90 s appear not to have beneficial effects which downplay the role of stage 1 sleep onset as a mediator of the recuperative effect of naps (Tietzel and Lack, 2002), and to be restorative, the sleep episode should consist of at least 10 uninterrupted minutes (Downey and Bonnet, 1987). Stampi et al. (1990) allowed subjects 4 h of nocturnal sleep followed by either 20, 50, or 80 min daytime naps. The 80 min nap was followed by greater deficits on a DST, while the 50 min nap showed greater deficits on a Memory and Search Test; overall, SI was marginally more pronounced for the 50 min nap than the 80 min nap. The 20 min nap only produced mild deficits on both of these measures. It has been suggested (i.e., Tassi and Muzet, 2000) that perfor­ mance was worse following the 50 min nap because most awakenings were in SWS, and no awakenings from the 20 min nap were in SWS; the 80 min nap had a few REM awakenings. It could also be argued that percentage of SWS in the sleep episode explains the data equally well, especially when considering perfor­ mance on the DST (Stampi et al., 1990). In support of this, an analysis of short naps between 60 and 120 min in duration taken during a 16 h night shift revealed a positive linear correlation between nap length and self-reported fatigue (Takahashi et al., 1999). Although EEG measures were not obtained, the longer naps in this study, which had more self-reported fatigue, should have been less likely to have an SWS awakening. Ferrara et al. (2000b) suppressed SWS in subjects for two nights and administered a DST after sleeping 2, 5, and 7.5 h. Without the presence of SWS, there was a linear decrease in SI across the night (i.e., less SI in the early morning awakening/7.5 h sleep bout), especially for performance speed. During the recovery night with the SWS rebound effect, the early morning awakening had more severe SI, especially for performance accuracy. These results hint at the possibility that without the depth of sleep (total percentage of SWS) present, longer sleep episodes are associated with fewer cognitive impairments shortly after the sleep bout. When depth of sleep was



introduced again during the recovery night, longer sleep episodes (which have more total SWS) show greater cognitive impairments. In a way, these results mirror the findings of Matchock and Mordkoff (2007) who administered a flankers task with two levels of target-distractor spacing (0.75 and 1.50�) and three trial types (compatible, incompatible, and neutral) to participants after a 1 h sleep bout (2300 h), a 4 h sleep bout (0300 h), and a 7 h sleep bout (0600 h) in a repeated-measures design with length of sleep bout counterbalanced across participants. Specifically, for three consecutive nights, participants went to sleep at 2300 h and were awakened at either 2400, 0300, or 0600 h; thus, all participants obtained approximately 7.5 h of sleep each night and did not have any prior sleep deprivation or major sleep deprivation differ­ ences between the testing nights. Simple RT from neutral-flanker trials was slowest at 0300 h, appearing to parallel circadian body temperature; the trend was the same for near and far spacing trials (Fig. 2). RTs at 2400 h were not significantly different from the pre-sleep condition at 2100 h. It is plausible that process S at 2100 h (continuous waking for 14 h) and process W (SI) at 2400 h were similar in their magnitude. In contrast, the flanker effect, which is a measure of selective attention that is similar to Posner’s executive attention or conflict resolution (Posner and Peterson, 1990), increased linearly as a function of the length of the sleep bout; that is, longer sleep bouts were associated with larger flanker effects, for both the near and the far spacing conditions (Fig. 3).

Mean neutral RT (ms)



Near spacing Far spacing




410 2100




Time FIG. 2. Mean RT and SEM (vertical bars) for neutral flankers at near and far flanker spacing at 2100, 2400, 0300, and 0600 h (from Matchock and Mordkoff, 2007).




Mean flanker effect (ms)

Near spacing Far spacing 40




0 2100




Time FIG. 3. Mean flanker effect scores for far and near spacing conditions at 2100, 2400, 0300, and 0600 h (from Matchock and Mordkoff, 2007).

The finding of a flanker effect demonstrates that subjects are not able to selectively process only the target, even when the location of the target is known in advance and when the flankers are at such wide eccentricities so as to not normally affect performance in a high arousal awake state (Broadbent et al., 1989). Similar results have been reported in an earlier study which had a broader focus (see Matchock and Mordkoff, 2005), suggesting that this pattern may not be an anomaly. Taking into consideration the limitations of this study, depth of sleep (as defined as total percentage of SWS in a sleep episode) seemed to have a more deleterious effect on selective attention, while circadian factors modulated simple RT. Of theoretical interest is that exogenously administered melatonin, which when secreted naturally by the pineal gland closely follows body temperature (Cagnacci et al., 1992), has produced decrements on a psychom*otor vigilance task (Graw et al., 2001) and a two-choice visual RT task (Rogers et al., 1998), which is similar to the Matchock and Mordkoff’s (2007) analysis of neutral-trial flankers. Exogenously administered melatonin did not affect performance on a letter cancellation task (Graw et al., 2001), which is better measure of attention rather than simple RT. Tassi et al. (2006) also manipulated length of sleep bout and measured attention, albeit with different results. Participants were tested with the Stroop test for 1 h upon awakening at 0700 h. However, one group of participants was not sleep deprived, going to sleep at 2300 h (8 h sleep bout) and the other group



was sleep deprived, going to sleep at 0500 h (2 h sleep bout). The participants in the 8 h sleep bout experienced no detrimental SI effect, and the 2 h sleep bout participants had increased RT for the first half of the testing session (but a return to normal during the second half hour) and an increase in error rate during the second half of the testing session. Task differences (Stroop vs. Flankers task) and design differences (between-subjects vs. within-subjects) could explain differences in the Tassi et al. (2006) and Matchock and Mordkoff (2007) studies, respectively. In the Tassi et al. (2006) study, sleep bout length and amount of prior sleep deprivation are confounded, while circadian time is better controlled. In the Matchock and Mordkoff (2007) study, sleep bout length and circadian time are confounded, while prior sleep deprivation is better controlled. Moreover, although both studies measured attention, the Tassi et al. (2006) study appears to report overall RT from the Stroop, rather than subtract RT scores on congruent trials from non-congruent trials which is a measure of interference that more closely approximates the flankers task. Many contemporary cognitive psychologists argue that button-press Stroop tests are not really Stroop tests, but a flankers task (Mordkoff, personal communication, June 12, 2010). Stroop tasks are those where the irrelevant information overlaps with both the relevant information (e.g., written word and ink color) and the irrelevant information also overlaps with the response to be made (e.g., written word and spoken name). If the procedures only have only the first type of overlap, then it is a flankers task. If the procedures have only the second type of overlap, then it is a Simon task. The rationale for these distinctions is that the underlying mechanism for the effects of the two types of overlap is thought to be different, so it is thought to be important to keep track of which type or types of overlap one has in a given experiment (Kornblum, 1994; Kornblum et al., 1999; Mordkoff, personal com­ munication, June 12, 2010). Finally, in the well-controlled FD protocol of Scheer et al. (2008), participants slept for approximately 8 h under free-running conditions. Participants were awa­ kened at three different equally spaced times during these 8 h episodes and tested. For the first two 20 min SI testings 1/3 and 2/3 into the sleep episode, participants went back to sleep after the testing; upon the last testing, participants stayed awake and continued with their normal day. As mentioned previously in this chapter, there was a strong circadian effect of SI, but an analysis of the tertiaries or length of time into the sleep episode was not significant. In this respect, each SI testing would be akin to an increased sleep bout length, albeit fragmented. However, as pointed out by the authors (Scheer et al., 2008), an increase in the cumulative prior sleep duration during the later testings (which could impair cognitive performance) coupled with the decrease in homeostatic sleep pressure (which could enhance cognitive performance) could offset each other. Taken together, depth of sleep, especially SWS (either at the time of awaken­ ing or at the total percentage) seems to play a role in how humans process



information after awakening from a sleep bout. It may be that sleep­ stage-at-awakening effects are more robust after shorter sleep episodes and when not masked by more powerful circadian influences. Another component of depth of sleep may be total percentage of SWS in a sleep episode. This component may be more salient when examining longer sleep bouts and could operate in a manner similar to process S (time spent awake), except that this factor is time spent sleeping, process S0 . Process S0 may not be as linear as process S and could be curvilinear or level off at a horizontal asymptotic level when participants are completely sated after extremely long sleep episodes (>8 h) in comfortable environments, a condition not frequently encountered in SI studies. More research is needed in order to better clarify the role that sleep episode length has on SI.

V. Different Measures of Cognitive Functioning

In the published literature, myriad tasks have been administered to assess cognitive impairments following an episode of sleep. This variability is likely to capture different aspects of cognition and attention, but it may also contribute to unclear and inconsistent findings concerning task performance upon awakening. Researchers most familiar with the validity and other psychometric properties of cognitive tasks (e.g., cognitive psychologists) are traditionally not the same researchers who study sleep and awakening (e.g., biologists or physiological psychologists). Furthermore, whether a task is subject-paced or experimenterpaced may affect results. In order to study cognitive impairments upon awakening, researchers have used (emphasizing specific tasks below rather than the number of studies that used each task) the Stanford Sleepiness Scale (Hofer-Tinguely et al., 2005), other measures of self-reported sleepiness or fatigue (Bonnet and Arand, 1995; Ferrara et al., 2000a; Jewett et al., 1999), Baddeley’s Logical Reasoning Task (Bonnet and Arand, 1995), auditory simple RT (Hofer-Tinguely et al., 2005), visual simple RT (Miccoli et al., 2008), finger tapping (Ferrara and De Gennaro, 2000), addition tasks (HoferTinguely et al., 2005; Wertz et al., 2006), subtraction tasks (Dinges et al., 1985), digit symbol substitution tasks (Bonnet and Arand, 1995; Silva and Duffy, 2008); tests of spatial memory (Tassi et al., 1992), Flanker’s tasks (Matchock and Mordkoff, 2007), Psychom*otor Vigilance Task or other measures of self-reported alertness (Achermann et al., 1995; Van Dongen et al., 2001), letter cancellation tasks (Tietzel and Lack, 2001), P3 amplitude/latency (Kaida et al., 2006), Stroop tests (Tassi et al., 2006), grip strength (Jeannaret and Webb, 1963), time estimation of sleep intervals (Carlson et al., 1978), return to sleep latencies (Balkin and Badia, 1988), oculomotor performance (Ferrara et al., 2000a), semantic priming (Stickgold et al., 1999), event-related potentials (Asaoka et al.,



2010; Ferrara et al., 2001), “decision-making” tasks (Bruck and Pisani, 1999), and the Arrow-orientation task (Asaoka et al., 2010). Williams et al. (1959) suggested that in sleep-deprived subjects, speed should be most affected in subject-paced tasks, but accuracy most affected in experi­ menter-paced tasks. Some researchers have theorized (Tassi and Muzet, 2000), and research has supported the idea (Bruck and Pisani, 1999; Tassi et al., 2006), that performance deficits because of SI are distinct from deficits due to sleep deprivation (sleepiness) and that SI may primarily affect processing speed. Others (e.g., Balkin and Badia, 1988) have also suggested that SI and sleepiness are distinct but that SI alone should affect accuracy more so than speed, which has also been documented in the literature (Tassi et al., 2003). However, sleep deprivation and SI are often confounded as increasing sleep deprivation (process S or sleepi­ ness) also exacerbates later SI effects. To better elucidate the nature of this distinction, Miccoli et al. (2008) compared an uninterrupted sleep group (which measures only SI), a total sleep deprivation group (which measures sleepiness only), and a partial sleep reduction group (which measures both sleepiness and SI) for mean response time and number of lapses on a visual simple RT task. Although error rates were not directly accessed, RTs increased in all groups. The number of lapses (i.e., microsleeps) only increased in the sleep deprivation (sleepiness) group, thus still suggesting a distinction between sleepiness and SI. Apparently, the process of awakening (progressing toward wakefulness) is differ­ ent than sleepiness (progressing toward sleep). Finally, the time course for recov­ ery of performance over the initial hour of awakening from sleep has been shown to vary depending on the task (Hofer-Tinguely et al., 2005; Tassi et al., 2006). Taken together, how well people perform shortly after awakening may depend, in part, on what they are asked to do. Complex tasks purport to measure higher cognitive processes, but these processes are not always well understood or salient. On the one hand, to measure a complex task, such as the executive functions component of attention, may require more infrequently administered tasks that are novel and require goal-directed behavior by the prefrontal cortex (Blatter et al., 2005; Schmidt et al., 2007). On the other hand, it has been suggested that the slower paced delivery of some complex tasks (compared to tasks in which stimuli are frequently presented to subjects) may not be as sensitive to SI or sleepiness-induced impairments (Dinges and Kribbs, 1991). Frequently delivered simple RT trials have been recom­ mended as optimal for detecting SI or sleepiness deficits, such as cognitive lapses (Miccoli et al., 2008). However, real-life tasks that people have to perform shortly after awakening may differ markedly from tasks that only measure simple RT. For example, a truck driver, pilot, or air traffic controller may have to scan many aspects of the visual scene searching for relevant information (e.g., a passing car in the rear view mirror, airspeed indicators and altimeters, or a novel blip on a radar screen) and then suddenly narrowly focus on this aspect of the visual scene



while simultaneously ignoring other irrelevant information, followed by a wellinformed logical decision. This former process can best be described as visual selective attention. Numerous methods for measuring selective attention can hinder attempts to quantify process C or W-associated changes in this variable. Nonetheless, research has indicated that there are time-of-day fluctuations in selective atten­ tion. Responding to a specific aspect of a color shape (Zuber and Ekehammar, 1988), negative priming of word pairs in older subjects (Intons-Peterson et al., 1998) and pencil and paper letter cancellation tasks (Casagrande et al., 1997) have shown increases in performance near the circadian peak in CBT. Results can vary, though, depending upon cognitive load (i.e., the number of target letters to cancel) and sleep deprivation (Babkoff et al., 1988; Mikulincer et al., 1989). Using a cued reaction time task (CRTT), Casagrande et al. (2005) found that although RT increased in sleep-deprived subjects, performance was not differentially affected for valid, invalid, and neutral trials. This pattern of results indicates a decrease in vigilance or alertness, but not in attention-orienting mechanisms. In contrast, Versace et al. (2006) found that RTs significantly increased on invalidly cued trials but not on validly cued trials, suggesting deficits in selective orienting. Few studies have attempted to measure SI with more fine-grained analyses that allow delineation of different stages of information processing and different components of attention. For example, identification of underlying informationprocessing stages can be gleaned by using Donder’s (1868/1969) subtraction method. Donders postulated that by measuring Simple RT (e.g., responding to any stimulus), Go/no-go RT (i.e., responding to one stimulus but not to another), and Choice RT (e.g., responding with one hand in response to one stimulus but the other hand in response to a different stimulus) that the duration of various underlying cognitive stages could be inferred. Presumably, each task is comprised of different hypothetical stages (e.g., Simple: stimulus detection and motor execution; Go/no-go: stimulus detection, stimulus discrimination, and motor execution; and Choice: stimulus detection, stimulus discrimination, response selection, and motor execution). Thus, Go/no-go RT—Simple RT should be a measure of stimulus discrimination, while Choice RT—Go/no-go RT should be a measure of response selection. The subtraction method has been criticized, in part, because of its dependence upon certain assumptions (e.g., Luce, 1986; Sternberg, 1969). First, it is assumed that the underlying stages occur sequentially; second, that the stages are functionally distinct from each other with only one stage being activated at a time; and third, the assumption that stages can be added or deleted without affecting the other stages (i.e., “pure insertion”). The first two assumptions have received fairly strong support (McClelland, 1979; Miller, 1988), although pure insertion has been the most criticized (Sternberg, 1969). Despite this criticism, recent research has emerged that appears to support



pure insertion as well (Gottsdanker and Shragg, 1985; Miller and Low, 2001; Ulrich et al., 1999). Moreover, the basic logic of subtracting one RT task from another RT task to identify underlying mechanisms is employed in widely used measures of attention such as the Attentional Network Test (ANT: Fan et al., 2002), and subtraction, in general, is at the crux of functional magnetic resonance imaging studies. A recommendation is that future studies on the process of awakening and SI use tasks like the flankers task or tests like the Attentional Network Test (ANT) (Fan et al., 2002). The ANT combines spatial cuing with a modified version of the flankers task (Eriksen and Eriksen, 1974). Tests such as the ANT can be fre­ quently delivered to ensure that they are sensitive to SI and sleepiness deficits such as attentional lapses. Moreover, simple RT can be measured, as well as other higher cognitive functions (e.g., executive control, orienting, and alerting) that have been fairly well mapped to known brain areas and neurotransmitter sys­ tems. The executive function component of attention involves the anterior cingulate cortex (ACC) and lateral prefrontal cortex (Bush et al., 2000; Fan et al., 2003, 2005; MacDonald et al., 2000; Tanji and Hoshi, 2008), and the alerting response has been associated with the frontal and parietal regions of the right hemisphere (Posner and Peterson, 1990) and the reticular formation (Sturm and Willmes, 2001). The orienting response is associated with the superior colliculus, frontal eye fields, and superior and temporal parietal areas (Fan et al., 2005). Neurochemically, two brain regions associated with executive func­ tion are both input areas from the tegmental dopaminergic system, implicating dopamine (see, e.g., Benes, 2000). The cholinergic system, originating in the basal forebrain area, is implicated in orienting (Beane and Marrocco, 2004), and norepinephrine in the locus coeruleus is implicated in the alerting component (Foote et al., 1991; Witte and Marrocco, 1997). Limited information from neuroimaging studies is available on the underlying brain changes that are associated with the process of awakening. One study found that blood flow first increased in the brain stem and thalamus within 5 min after awakening from a sleep episode, followed by gradual increases in cerebral blood flow to the prefrontal cortical regions 20 min later (Balkin et al., 2002). Of interest is that flanker effects activate areas of the brain associated with executive control such as the dorsolateral frontal cortex and ACC (Botvinick et al., 1999, 2004; Bunge et al., 2002; Casey et al., 2000; Fan et al., 2003; Hazeltine et al., 2003). Reduced prefrontal cortex activity may underlie the large SI-induced flanker effects observed in the Matchock and Mordkoff (2007) study. As yet, no neuroi­ maging study has examined specific characteristics of the sleep episode such as length or timing. Process W has been an under-investigated area in the field of sleep/wake research. Given the many unanswered questions in this area, the process of awakening should warrant, and is ripe for, future investigations of contributing factors.




Achermann, P., Werth, E., Diijk, D. J., and Borbely, A. A. (1995). Time course of sleep inertia after nighttime and daytime sleep episodes. Arch. Ital. Biol. 134, 109–119. Asaoka, S., Masaki, H., Ogawa, K., Murphy, T. I., f*ckuda, K., and Yamazaki, K. (2010). Perfor­ mance monitoring during sleep inertia after a 1-h daytime nap. J. Sleep Res. Advance online publication. doi: 10.1111/j.1365–2869.2009.00811.x. Babkoff, H., Mikulincer, M., Caspy, T., Kampisky, D., and Singh, H. (1988). The effects of 72 hours of sleep deprivation: A memory search task. Quart. J. Exp. Psychol. 40A, 737–756. Balkin, T. J., and Badia, P. (1988). Relationship between sleep inertia and sleepiness: Cumulative effects of four nights of sleep disruption/restriction on performance following abrupt nocturnal awakenings. Biol. Psychol. 27, 245–258. Balkin, T. J., Braun, A. R., Wesensten, N. J., Jeffries, K., Varga, M., Baldwin, P., Belenky, G., and Herscovitch, P. (2002). The process of awakening: A PET study of regional brain activity patterns mediating the re-establishment of alertness and consciousness. Brain 125, 2308–2319. Beane, M., and Marrocco, R. T. (2004). Norepinephrine and acetylcholine mediation of the compo­ nents of reflexive attention: Implication for attention deficit disorders. Prog. Neurobiol. 74, 167–181. Benes, F. M. (2000). Emerging principles of altered neural circuitry in schizophrenia. Brain Res. Rev. 31, 251–269. Bes, F., Jobert, M., and Schulz, H. (2009). Modeling napping, post-lunch dip, and other variations in human sleep propensity. Sleep 32, 392–398. Blatter, K., Opwis, K., Munch, M., Wirz-Justice, A., and Cajochen, C. (2005). Sleep loss-related decrements in planning performance in healthy elderly depend on task difficulty. J. Sleep Res. 14, 409–417. Bonnet, M. H. (1983). Memory for events occurring during arousal from sleep. Psychophysiology 20, 81–87. Bonnet, M. H., and Arand, D. L. (1995). Consolidated and distributed nap schedules and perfor­ mance. J. Sleep Res. 4, 71–77. Borbely, A. A. (1982). A two-process model of sleep regulation. Hum. Neurobiol. 1, 95–204. Botvinick, M. M., Cohen, J. D., and Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: An update. Trends Cogn. Sci. 8, 539–546. Botvinick, M., Nystrom, L. E., Fissell, K., Carter, C. S., and Cohen, J. D. (1999). Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature 402, 179–181. Broadbent, D. E., Broadbent, M.H.P., and Jones, J. L. (1989). Time of day as an instrument for the analysis of attention. Eur. J. Cog. Psychol. 1, 69–94. Brooks, A., and Lack, L. (2006). A brief afternoon nap following nocturnal sleep restriction: Which nap duration is most recuperative? Sleep 29, 831–840. Broughton, R. J. (1968). Sleep disorders: Disorders of arousal? Science 159, 1070–1078. Broughton, R. (1975). Biorhythmic variations in consciousness and psychological functions. Canad. Psychol. Rev. 16, 217–239. Bruck, D., and Pisani, D. L. (1999). The effects of sleep inertia on decision-making performance. J. Sleep Res. 8, 95–103. Bunge, S. A., Hazeltine, E., Scanlon, M. D., Rosen, A. C., and Gabrieli, J. D. (2002). Dissociable contributions of prefrontal and parietal cortices to response selection. NeuroImage 17, 1562–1571. Busby, K. A., and Broughton, R. J. (1983). Waking ultradian rhythms of performance and motility in hyperkinetic and normal children. J. Abnorm. Child Psychol. 11, 431–442. Bush, G., Luu, P., and Posner, M. I. (2000). Cognitive and emotional influences in the anterior cingulate cortex. Trends Cogn. Sci. 4, 215–222.



Cagnacci, A., Elliott, J. A., and Yen, S. S. (1992). Melatonin: A major regulator of the circadian rhythm of core temperature in humans. J. Clin. Endocrinol. Metab. 75, 447–452. Cagnacci, A., Krauchi, K., Wirz-Justice, A., and Volpe, A. (1997). Homeostatic versus circadian effects of melatonin on core body temperature in humans. J. Biol. Rhythms 12, 509–517. Carlson, V. R., Feinberg, I., and Goodenough, D. R. (1978). Perception of the duration of sleep intervals as a function of EEG sleep stage. Psychophysiol. Psychol. 6, 497–500. Carrier, J., and Monk, T. H. (2000). Circadian rhythms of performance: New trends. Chronobiol. Int. 17, 719–732. Casagrande, M., Martella, D., Di Pace, E., Pirri, F., and Guadalupi, F. (2005). Orienting and alerting: Effect of 24 h of prolonged wakefulness. Exp. Brain Res. 171, 184–193. Casagrande, M., Violani, C., Curcio, G., and Bertini, M. (1997). Assessing vigilance through a brief pencil and paper letter cancellation task (LCT): Effects of one night of sleep deprivation and of the time of day. Ergonomics 40, 613–630. Casey, B. J., Thomas, K. M., Welsh, T. F., Badgaiyan, R. D., Eccard, C. H., Jennings, J. R., and Crone, E. A. (2000). Dissociation of response conflict, attentional selection, and expectancy with functional magnetic resonance imaging. Proc. Natl. Acad. Sci. U.S.A. 97, 728–8733. Colquhoun, W. P. (1971). Biological Rhythms and Human Performance. Academic Press, London, UK. Conte, S., Ferlazzo, F., and Renzi, P. (1995). Ultradian rhythms of reaction times in performance in vigilance tasks. Biol. Psychol. 39, 159–172. Dinges, D. F., and Kribbs, N. B. (1991). Performing while sleepy: Effects of experimentally-induced sleepiness. In: Sleep, Sleepiness and Performance (T. H. Monk, ed.), John Wiley and Sons, Chichester, UK, pp. 97–128. Dinges, D. F., Orne, M. T., and Orne, E. C. (1985). Assessing performance upon abrupt awakening from naps during quasi-continuous operations. Behav. Res. Meth. Inst. Comp. 17, 37–45. Dinges, D. F., Orne, M. T., Whitehouse, W. G., and Orne, E. C. (1987). Temporal placement of a nap for alertness: Contributions of circadian phase and prior wakefulness. Sleep 10, 313–329. Donders, F. C. (1969). Over de snelheid van psychische processen [On the speed of mental processes]. (W. Koster, Trans.). Attention and Performance II (W. G. Koster, ed.), North Holland, Amster­ dam, The Netherlands, pp. 412–431 (Original work published in 1868). Downey, R., and Bonnet, M. H. (1987). Performance during frequent sleep disruption. Sleep 10, 354–363. Eriksen, B. A., and Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Percept. Psychophys. 16, 143–149. Fan, J., Flombaum, J. I., McCandliss, B. D., Thomas, K. M., and Posner, M. I. (2003). Cognitive and brain consequences of conflict. NeuroImage 18, 42–57. Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., and Posner, M. I. (2005). The activation of attentional networks. NeuroImage 26, 471–479. Fan, J., McCandliss, B. D., Sommer, T., Raz, A., and Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. J. Cog. Neurosci. 14, 340–347. Ferrara, M., and De Gennaro, L. (2000). The sleep inertia phenomena during the sleep-wake transition: Theoretical and operational issues. Aviat. Space Environ. Med. 71, 843–848. Ferrara, M., De Gennaro, L., and Bertini, M. (2000a). Voluntary oculomotor performance upon awakening after total sleep deprivation. Sleep 23, 801–811. Ferrara, M., De Gennaro, L., Casagrande, M., and Bertini, M. (2000b). Selective slow-wave sleep deprivation and time-of-night effects on cognitive performance upon awakening. Psychophysiology 37, 440–446. Ferrara, M., De Gennaro, L., Ferlazzo, F., Curcio, G., Barattucci, M., and Bertini, M. (2001). Auditory evoked responses upon awakening from sleep in human subjects. Neurosci. Lett. 310, 145–148.



Folkard, S. (1975). Diurnal variation in logical reasoning. Br. J. Psychol. 66, 1–8. Folkard, S. (1979). Time of day and level of processing. Mem. Cog. 7, 247–252. Folkard, S., and Akerstedt, T. (1992). A three-process model of the regulation of alertness-sleepiness. In: Sleep, Arousal, and Performance (R. Ogilivie and R. Broughton, eds.), Birkhouse, Boston, MA, pp. 11–26. Folkard, S., and Monk, T. H. (1980). Circadian rhythms in human memory. Br. J. Psychol. 71, 295–307. Folkard, S., Wever, R. A., and Wildgruber, C. M. (1983). Multi-oscillatory control of circadian rhythms in human performance. Nature 305, 223–226. Foote, S. L., Berridge, C. W., Adams, L. M., and Pineda, J. A. (1991). Electrophysiological evidence for the involvement of the locus coeruleus in alerting, orienting, and attending. Prog. Brain Res. 88, 521–532. Gil, V., Lue, F., Moldofsky, H., Angus, R., and Radomski, M. (1994). Reaction time measures of sleep inertia in a study of a series of early versus late nocturnal naps. Sleep Res. 23, 123. Gil, V., Lue, F., Moldofsky, H., Angus, R., and Radomski, M. (1995). Performance versus subjective ratings of sleep inertia in early versus late nocturnal naps. Sleep Res. 24, 98. Gottsdanker, R., and Shragg, G. P. (1985). Verification of Donder’s subtraction method. J. Exp. Psychol. Hum. Percept. Perform. 11, 765–776. Gradisar, M., and Lack, L. (2004). Relationships between circadian rhythms of finger temperature, core temperature, sleep latency, and subjective sleepiness. J. Biol. Rhythms 19, 157–163. Graw, P., Werth, E., Krauchi, K., Gutzwiller, F., Cajochen, C., and Wirz-Justice, A. (2001). Early morning melatonin administration impairs psychom*otor vigilance. Behav. Brain Res. 121, 167–172. Hayashi, M., and Hori, T. (1998). The effects of a 20-min nap before post-lunch dip. Psychiatry Clin. Neurosci. 52, 203–204. Hayashi, M., Watanabe, M., and Hori, T. (1999). The effect of a 20 min nap in the mid-afternoon on mood, performance and EEG activity. Clin. Neurophysiol. 110, 272–279. Hazeltine, E., Bunge, S. A., Scanlon, M. D., and Gabrieli, J. D. (2003). Material-dependent and material-independent selection processes in the frontal and parietal lobes: An event-related fMRI investigation of response competition. Neuropsychologia 41, 1208–1217. Hofer-Tinguel, G., Achermann, P., Landolt, H.-P., Regel, S. J., Retey, J. V., Durr, R., Borbely, A. A., and Gottselig, J. M. (2005). Sleep inertia: Performance changes after sleep, rest and active waking. Cog. Brain Res. 22, 323–331. Hughes, R. J., and Badia, P. (1997). Sleep-promoting and hypothermic effects of daytime melatonin administration in humans. Sleep 20, 124–131. Ikeda, H., and Hayashi, M. (2010). The effect of self-awakening from nocturnal sleep on sleep inertia. Biol. Psychol. 83, 15–19. Intons-Peterson, M. J., Rocchi, P., West, T., McLellan, K., and Hackney, A. (1998). Aging, optimal testing times, and negative priming. J. Exp. Psychol. Learn. Mem. Cog. 24, 362–376. Iskra-Golec, I., and Smith, L. (2006). Ultradian and asymmetric rhythms of hemispheric processing speed. Chronobiol. Int. 23, 1229–1239. Jeannaret, P. R., and Web, W. B. (1963). Strength of grip on arousal from full night’s sleep. Percept. Mot. Skills 17, 759–761. Jewett, M. E., Wyatt, J. K., Ritz-De Cecco, A., Khalsa, S. B., Dijk, D. J., and Czeisler, C. A. (1999). Time course of sleep inertia dissipation in human performance and alertness. J. Sleep Res. 8, 1–8. Johnson, M. P., Duffy, J. F., Dijk, D. J., Ronda, J. M., Dyal, C. M., and Czeisler, C. A. (1992). Shortterm memory, alertness and performance: A reappraisal of their relationship to body tempera­ ture. J Sleep Res. 1, 24–29. Kahneman, D. (1973). Attention and Effort. Prentice-Hall, Englewood Cliffs, NJ. Kaida, K., Ogawa, K., Nittono, H., Hayashi, M., Takahashi, M., and Hori, T. (2006). Selfawakening, sleep inertia, and P3 amplitude in elderly people. Percept. Mot. Skills 102, 339–351.



Kleitman, N. (1963). Sleep and Wakefulness. University of Chicago Press, Chicago, IL. Kornblum, S. (1994). The way irrelevant dimensions are processed depends on what they overlap with: The case of Stroop- and Simon-like stimuli. Psychol. Res. 56, 130–135. Kornblum, S., Stevens, G. T., Whipple, A., and Requin, J. (1999). The effects of irrelevant stimuli: 1. The time course of stimulus-stimulus and stimulus-response consistency effects with Stroop-like stimuli, Simon-like tasks, and their factorial combinations. J. Exp. Psychol. Hum. Percept. Perform. 25, 688–714. Kraemer, S., Danker-Hopfe, H., Dorn, H., Schmidt, A., Ehlert, I., and Herrmann, W. M. (2000). Time-of-day variations on indicators of attention: Performance, physiologic parameters, and selfassessment of sleepiness. Biol. Psychiatry 48, 1069–1080. Krauchi, K., Cajochen, C., and Wirz-Justice, A. (2004). Waking up properly: Is there a role of thermoregulation in sleep inertia? J. Sleep Res. 13, 121–127. Krauchi, K., Knoblauch, V., Wirz-Justice, A., and Cajochen, C. (2006). Challenging the sleep homeostat does not influence the thermoregulatory system in men: Evidence from a nap vs. sleep-deprivation study. Am. J. Physiol. Regul. Integr. Comp. Physiol. 290, R1052–R1061. Lavie, P., Matanya, Y., and Yehuda, S. (1984). Cognitive asymmetries after waking from REM and NONREM sleep in right handed females. Int. J. Neurosci. 23, 111–115. Lavie, P., and Weler, B. (1989). Timing of naps: Effects on post-nap sleepiness levels. Electroencephalogr. Clin. Neurophysiol. 72, 218–224. Lavie, P., and Zomer, J. (1984). Ultrashort sleep-waking schedule. II. Relationship between ultradian rhythms in sleepability and the REM-NONREM cycles and effects of the circadian phase. Electroencephalogr. Clin. Neurophysiol. 57, 35–42. Lee, J. H., Wang, W., Silva, E. J., Chang, A.-M., Scheuermaier, K. D., Cain, S. W., and Duffy, J. F. (2009). Neurobehavioral performance in young adults living on a 28-h day for 6 weeks. Sleep 32, 905–913. Levine, B., Roehrs, T., Stepanski, E., Zorick, F., and Roth, T. (1987). Fragmenting sleep diminishes its recuperative value. Sleep 10, 590–599. Lubin, A., Hord, D. J., Tracy, M. L., and Johnson, L. C. (1976). Effect of exercises, bedrest and napping on performance decrement during 40 hours. Psychophysiology 13, 334–339. Luce, R. D. (1986). Response Times: Their Role in Inferring Elementary Organization. Oxford University Press, Oxford, UK. MacDonald, A. W., Cohen, J. D., Stenger, V. A., and Carter, C. S. (2000). Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science 288, 1835–1838. Matchock, R. L., and Mordkoff, J. T. (2005). Selective attention in young women awakened from nocturnal sleep. Aviat. Space Environ. Med. 76, 985–988. Matchock, R. L., and Mordkoff, J. T. (2007). Visual attention, reaction time, and self-reported alertness upon awakening from sleep bouts of varying lengths. Exp. Brain Res. 178, 228–239. Matsumoto, K. (1981). Effects of nighttime naps on body temperature changes, sleep patterns, and self-evaluation of sleep. J. Hum. Ergol. 10, 173–184. McClelland, J. L. (1979). On the time relations of mental processes: A framework for analyzing processes in cascade. Psychol. Rev. 86, 287–330. Miccoli, L., Versace, F., Koterle, S., and Cavallero, C. (2008). Comparing sleep-loss sleepiness and sleep inertia: Lapses make the difference. Chronobiol. Int. 25, 725–744. Mikulincer, M., Babkoff, H., Caspy, T., and Singh, H. (1989). The effects of 72 hours of sleep loss on psychological variables. Br. J. Psychol. 80, 145–162. Miller, J. O. (1988). Discrete and continuous models of human information processing: Theoretical distinctions and empirical results. Acta Psychol. 67, 191–257. Miller, J. O., and Low, K. (2001). Motor processes in simple, go/no-go, and choice reaction time tasks: A psychophysical analysis. J. Exp. Psychol. Hum. Percept. Perform. 27, 266–289. Monk, T. H., Folkard, S., Leng, V. C., and Weitzman, E. D. (1983). Circadian rhythms in subjective alertness and core body temperature. Chronobiologia 10, 49–55.



Morton, L. L., and Kershner, J. R. (1991). Time-of-day effects on neuropsychological behaviors as measured by dichotic listening. Int. J. Neurosci. 59, 241–251. Mullington, J., and Broughton, R. (1994). Daytime sleep inertia in narcolepsy-cataplexy. Sleep 17, 69–76. Naitoh, P. (1981). Circadian cycles and restorative powers of naps. In: Biological Rhythm, Sleep, and Shiftwork (L. C. Johnson, D. I. Tepas, W. P. Colqhoun, and M. J. Colligan, eds.), SP Medical and Scientific Books, New York, NY, pp. 553–580. Naitoh, P., Englund, C. E., and Ryman, D. (1982). Restorative power of naps in designing continuous work schedules. J. Hum. Ergol. (Tokyo) 11, 259–278. Naitoh, P., Kelly, T., and Babkoff, H. (1993). Sleep inertia: Best time not to wake up? Chronobiol. Int. 10, 109–118. Owens, D. S., Macdonald, I., Tucker, P., Syntik, N., Minors, D., Waterhouse, J., Totterdell, P., and Folkard, S. (1998). Diurnal trends in mood and performance do not all parallel alertness. Scand. J. Work Environ. Health 24(Suppl. 3), 109–114. Owens, D. S., Macdonald, I., Tucker, P., Sytnik, N., Totterdell, P., Minors, D., Waterhouse, J., and Folkard, S. (2000). Diurnal variations in the mood and performance of highly practised young women living under strictly controlled conditions. Br. J. Psychol. 91, 41–60. Porkka-Heiskanen, T. (1999). Adenosine in sleep and wakefulness. Ann. Med. 31, 125–129. Posner, M. I., and Petersen, S. E. (1990). The attention system of the human brain. Ann. Rev. Neurosci. 13, 25–42. Rogers, N. L., Phan, O., Kennaway, D. J., and Dawson, D. (1998). Effect of daytime oral melatonin administration on neurobehavioral performance in humans. J. Pineal Res. 25, 47–53. Sallinen, M., Harma, M., Akerstedt, T., Rosa, R. ,, and Lillqvist, O. (1998). Promoting alertness with a short nap during a night shift. J. Sleep Res. 7, 240–247. Scales, W. E., Vander, A. J., Brown, M. B., and Dluger, M. J. (1988). Human circadian rhythms in temperature, trace metals, and blood variables. J. Appl. Physiol. 65, 1840–1846. Scheer, F.A.J.L., Shea, T. J., Hilton, M. F., and Shea, S. A. (2008). An endogenous circadian rhythm in sleep inertia results in greatest cognitive impairment upon awakening during the biological night. J. Biol. Rhythms 23, 353–361. Schmidt, C., Collette, F., Cajochen, C., and Peigneux, P. (2007). A time to think: Circadian rhythms in human cognition. Cog. Neuropsychol. 24, 755–789. Silva, E. J., and Duffy, J. F. (2008). Sleep inertia varies with circadian phase and sleep stage in older adults. Behav. Neurosci. 122, 928–935. Stampi, C., Mullington, J., Rivers, M., Campos, J. P., and Broughton, R. (1990). Ultra-short sleep schedules: Sleep architecture and recuperative value of 80-, 50- and 20-minutes naps. In: Sleep ’90 (J. Horne, ed.), Pontenagel Press, Bochum, Germany, pp. 71–74. Sternberg, S. (1969). The discovery of processing stages: Extension of Donder’s method. Acta Psychol. 30, 276–315. Stickgold, R., Scott, L., Rittenhouse, C., and Hobson, J. A. (1999). Sleep-induced changes in associative memory. J. Cog. Neurosci. 11, 182–193. Sturm, W., and Willmes, K. (2001). On the functional neuroanatomy of intrinsic and phasic alertness. NeuroImage 14(1 Pt 2), S76–S84. Takahashi, M., Arito, H., and f*ckuda, H. (1999). Nurse’s workload associated with 16-h night shifts. II. Effects of a nap taken during the shifts. Psychiatry Clin. Neurosci. 53, 223–225. Takeyama, H., Matsumoto, S., Murata, K., Ebara, T., Kubo, T., Tachi, N., and Itani, T. (2004). Effects of the length and timing of nighttime naps on task performance and physiological function. Rev. Sa�ude P�ublica 38(Suppl.), 32–37. Tanji, J., and Hoshi, E. (2008). Role of the lateral prefrontal cortex in executive behavioral control. Physiol. Rev. 88, 37–57.



Tassi, P., Bonnefond, A., Engasser, O., Hoeft, A., Eschenlauer, R., and Muzet, A. (2006). EEG spectral power and cognitive performance during sleep inertia: The effect of normal sleep duration and partial sleep duration. Physiol. Behav. 87, 177–184. Tassi, P., Bonnefond, A., Hoeft, A., Eschenlauer, R., and Muzetand, A. (2003). Arousal and vigilance: Do they differ? Study in a sleep inertia paradigm. Sleep Res. Online 5, 83–87. Tassi, P., and Muzet, A. (2000). Sleep inertia. Sleep Med. Rev. 4, 341–353. Tassi, P., Nicolas, A., Dewasmes, G., Eschenlauer, R., Ehrhart, J., Salame, P., Muzet, A., and Libert, J. P. (1992). Effects of noise on sleep inertia as a function of circadian placement of a one-hour nap. Percept. Mot. Skills 75, 291–302. Taub, J. M., Tanguay, P. E., and Rosa, R. R. (1977). Effects of afternoon naps on physiological variables performance and self-reported activation. Biol. Psychol. 5, 191–210. Tietzel, A. J., and Lack, L. C. (2001). The short-term benefits of brief and long naps following nocturnal sleep restriction. Sleep 24, 293–300. Tietzel, A. J., and Lack, L. C. (2002). The recuperative value of brief and ultra-brief naps on alertness and cognitive performance. J. Sleep Res. 11, 213–218. Ulrich, R., Mattes, S., and Miller, J. (1999). Donder’s assumption of pure insertion: An evaluation on the basis of response dynamics. Acta Psychol. 102, 43–75. Van Dongen, H. P., Price, N. J., Mullington, J. M., Szuba, M. P., Kapoor, S. C., and Dinges, D. F. (2001). Caffeine eliminates psychom*otor vigilance deficits from sleep inertia. Sleep 24, 813–819. Versace, F., Cavallero, C., De Min Tona, G., Mozzato, M., and Stegagno, L. (2006). Effects of sleep reduction on spatial attention. Biol. Psychol. 71, 248–255. Werken, M. V., Gimenez, M. C., De Vries, B., Beersma, D.G.M., Van Someren, E.J.W., and Gordijn, M.C.M. (2010). Effects of artificial dawn on sleep inertia, skin temperature, and the awakening cortisol response. J. Sleep Res. Advance online publication. doi: 10.1111/ j.1365–2869.2010.00828.x. Wertz, A. T., Ronda, J. M., Czeisler, C. A., and Wright, K. P. (2006). Effects of sleep inertia on cognition. J. Am. Med. Assoc. 295, 163–164. Wilkinson, R. T., and Stretton, M. (1971). Performance after awakening at different times of the night. Psychonom. Soc. 23, 283–285. Williams, H. L., Lubin, A., and Goodnow, J. J. (1959). Impaired performance with acute sleep loss. Psychol. Monogr. 73, 1–26. Wirz-Justice, A., and Armstrong, S. M. (1996). Melatonin: Nature’s soporific? J. Sleep Res. 5, 137–141. Witte, E. A., and Marrocco, R. T. (1997). Alteration of brain noradrenergic activity in rhesus monkeys affects the alerting component of covert orienting. Psychopharmacology 132, 315–323. Wright, K. P., Hull, J. T., and Czeisler, C. A. (2002). Relationship between alertness, performance, and body temperature in humans. Am. J. Physiol. Regul. Integr. Comp. Physiol. 283, R1370–R1377. Yerkes, R. M., and Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habitformation. Comp. Neurolog. Psychol. 18, 459–482. Zuber, I., and Ekehammar, B. (1988). Personality, time of day and visual perception: Preferences and selective attention. Pers. Individ. Dif. 9, 345–352.


Angela Clow, Frank Hucklebridge†, and Lisa Thorn

Department of Psychology, University of Westminster, London W1B 2UW, UK Department of Human and Health Sciences, University of Westminster, London, W1W 6UW, UK


Introduction History of the Investigation of the CAR Distinct Regulation of the CAR and Relationship with the SCN The CAR as an Awakening Process CAR and Cognitive Awakening CAR and Immunological Awakening CAR and Behavioral Awakening Measurement of the CAR Conclusions References

The cortisol awakening response (CAR) is a crucial point of reference within the healthy cortisol circadian rhythm, with cortisol secretion typically peaking between 30 and 45 min post awakening. This chapter reviews the history of investigation into the CAR and highlights evidence that its regulation is relatively distinct from cortisol secretion across the rest of the day. It is initiated by awakening, under the influence of the hypothalamic suprachiasmatic nucleus, and “fine tuned” by a direct neural input to the adrenal cortex by the sympathetic nervous system. This chapter also examples the CAR in relation to other awakening-induced processes, such as restoration of consciousness, attainment of full alertness, changes in other hor­ mones, changes in the balance of the immune system, and mobilization of the motor system, and speculates that there is a role for the CAR in these processes.

I. Introduction

The cortisol awakening response (CAR) is a period of increased cortisol secretory activity initiated by morning awakening and typically peaking between 30 and 45 min post awakening (Pruessner et al., 1997; Wilhelm INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 93 DOI: 10.1016/S0074-7742(10)93007-9


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et al., 2007). The CAR is recognized as a crucial point of reference within the healthy cortisol circadian rhythm but is generally studied in isolation from other awakening-induced processes (e.g., restoration of consciousness, attain­ ment of full alertness, changes in other hormones, changes in the balance of the immune system, and mobilization of the motor system). In psychobiolo­ gical research the CAR has frequently been used as a biomarker of hypotha­ lamic pituitary adrenal axis (HPA) status. However, evidence indicates that regulation of the CAR is relatively distinct from cortisol secretion across the rest of the day. The CAR is not a straightforward measure of HPA respon­ sivity (such as the Trier Social Stress Test), it is initiated by awakening, under the influence of the hypothalamic suprachiasmatic nucleus (SCN) and “fine tuned” by a direct neural input to the adrenal cortex by the sympa­ thetic nervous system (Buijs et al., 2003; Clow et al., 2010). Thus although different patterns of the CAR have been associated with different psycho­ pathologies, it is not entirely clear what these different patterns tell us about the underlying biological basis of the condition being studied. Furthermore as there is currently no clear understanding about the role of the CAR it is not clear what the downstream consequences of aberrant patterns of the CAR may be. It is becoming increasingly understood that circadian coordination via the central body clock is crucial for physical and mental flourishing and that disruption of circadian function is linked with multiple downstream negative physiological, psychological, and clinical consequences (Eismann et al., 2010). One of the main ways the SCN communicates with peripheral target tissues is via the neuroendocrine system and secretion of the hormones melatonin (at night) and cortisol (most prominent during the day). In this way the SCN coordinates peripheral cellular rhythms important for health. The dual SCN-mediated awakening-induced regulatory input to the CAR (i.e., via the HPA axis and the sympathetic nervous system) may make it a more accurate marker of the function of the central biological clock than examina­ tion of the HPA axis alone and account for its well-documented sensitivity to psychosocial and health variables. This chapter discusses the history and the use of the CAR as a biological marker of psychosocial status and health. Further, we aim to contextualize the CAR within the process of normal healthy awakening by exploring it in relation to other processes of awaken­ ing. The CAR is not an isolated response to awakening, rather it is part of a well-orchestrated physiology closely tuned to circadian cycles and essential for healthy functioning. Unhealthy states are often associated with poor circadian coordination and these can potentially be detected by exam­ ination of the CAR. Using this approach we hope to advance understanding of the CAR as well as potentially enlighten its physiological meaning and roles.



II. History of the Investigation of the CAR

Glucocorticoids (cortisol in humans) are secreted in response to stress, affect multiple organ systems, and have a wide range of physiological and behavioral effects (Evanson et al., 2010; Sapolsky et al., 2000). Chronic stress and aging are associated with changes in the HPA axis and other glucocorticoid sensitive brain regions (e.g., the hippocampus) with consequent changes in the basal circadian pattern of cortisol secretion (Hsiao et al., 2010; Lightman, 2008). Aberrant basal patterns of cortisol secretion have been implicated in a range of psychological and somatic disease (Eismann et al., 2010; Minton et al., 2009; Sephton et al., 2000; Yehuda, 2001). Hence, there is a need for a thorough understanding of the components of the circadian pattern of cortisol secretion in order to develop meaningful biomarkers able to advance clinical and research studies involving this neuroendocrine system. A healthy basal pattern of cortisol secretion is characterized by a distinct circadian rhythm, largely controlled by the hypothalamic SCN, which influences adrenocortical activity via input to the paraventricular nuclei (PVN) of the hypothalamus (Buijs et al., 2003; Dickmeis, 2009; Kalsbeek et al., 2006; Krout et al., 2002). Under the influence of the SCN HPA axis activity gradually increases toward the end of nighttime sleep and gradually falls from a postawakening acrophase to a 24 h nadir in the early hours of sleep. This cyclical pattern of cortisol secretion can generate 14- to 15-fold changes in salivary free cortisol concentration across the day (e.g., Evans et al., 2007). Obviously the dynamic nature of the pattern of cortisol secretion makes it difficult to capture basal cortisol status accurately. Measures derived from a single blood sample taken in the early morning have been used frequently in assessment of adreno­ cortical status, particularly in clinical situations. However, these single point measures have low intra-individual stability (Schulz and Knabe, 1994), and hence limited utility. Twenty-four hour urinary measures of cortisol excretion provide a more reliable clinical index of overall cortisol secretion. However, this measure lacks subtlety in terms of the insight provided (different patterns of secretion could give identical results) as well as collection methodology (unplea­ sant and demanding on the participants). The adoption of saliva as the medium of choice for repeated measurement of cortisol across the day provided both a participant-friendly sample collection regime and the opportunity to look at dynamic change in cortisol secretion over the entire day and over short periods of time within the day (Kirschbaum and Hellhammer, 1994). As this approach was developed observations from multiple sleep research studies suggested that reported variability in cortisol levels stemmed from a stimulatory effect of awakening on HPA activity (Linkowski et al., 1993; Spathsch­ walbe et al., 1991, 1992; Vancauter et al., 1994; Weitzman et al., 1974). For



example, Spath-Schwalbe et al. (1992) obtained polysomnographic recordings and 15 min blood sampling via forearm catheter from participants in a sleep laboratory. These authors revealed that the transition from sleep to wakefulness in the morning provoked brief elevations in plasma cortisol, a phenomenon later to be called the CAR (until recently also sometimes called the awakening cortisol response: ACR or even the cortisol awakening rise). However, it was Pruessner and colleagues (1995), then working at the Uni­ versity of Trier in Germany, who first brought the CAR into widespread notice. They reported that the concentration of salivary free cortisol showed a 50–100% increase within 30 min following awakening in healthy participants on five con­ secutive days. A more comprehensive account of the CAR was published by the same group two years later (Pruessner et al., 1997). This was the first paper to report intra-individual stability of the CAR over consecutive days and weeks in children, young, and older adults. In all three age groups the increase in salivary cortisol levels peaked at 30 min post awakening and the increase was relatively consistent, exhibiting good intra-individual stability. It was concluded that the CAR pro­ vided a reliable estimation of adrenocortical activity (Pruessner et al., 1997). Further evidence for intra-individual consistency, both in the overall levels of post-awakening cortisol secretion and the dynamic of the CAR, followed (Edwards et al., 2001a; Wuest et al., 2000b). Subsequent studies demonstrated that the CAR was not associated with postural change, sleep duration, or mode of awakening (see Clow et al., 2004). However, one noteworthy feature of the CAR to emerge from this early literature was that although overall cortisol secretion during the first 45 min follow­ ing awakening was representative of (i.e., correlated with) underlying diurnal cortisol secretory activity measured over the rest of the day the dynamic of the CAR did not, implying that they were in some way independent measures (Edwards et al., 2001a; Schmidt-Reinwald et al., 1999). Perhaps this was the first evidence that the CAR is a complex phenomenon, fine tuned by HPA-independent mechanisms, and therefore is not a simple index of HPA activity. This early evidence was supported by reports that the CAR was more closely associated with genetic variables than cortisol secretion across the rest of the day (Wuest et al., 2000a). This complex phenomenon has continued to be used as a simple biomarker of HPA axis activity in relation to health and psychosocial variables. Since the first papers concerning the CAR were published some 13 years ago, interest in this specific aspect of salivary cortisol secretion in humans has grown steadily, with a total of 280 outputs published up until the present, i.e., July 2010 (see Fig. 1). However, perhaps the full impact of work on the CAR can be best described from an analysis of the number of times each paper has been cited. There are a total of 4720 citations of the currently published 280 papers. This represents an impressive average citation count of 16.86 for each CAR paper. This means that





0 19 9 19 7 9 19 8 99 20 0 20 0 0 20 1 0 20 2 0 20 3 0 20 4 0 20 5 0 20 6 0 20 7 0 20 8 09

Number of peer-reviewed publications


Year FIG. 1. Peer-reviewed publications about the CAR in humans per year.

if all the CAR papers were published in the same journal it would have an impact factor of 16.86, which is in excess of Nature Neuroscience (which has an impact factor of just 14.345)! The conclusion from this analysis is that the findings from the relatively small set of CAR outputs are of interest to a wide range of people outside the area. The year by year increase in citations of the currently published CAR papers is shown in Fig. 2. Studies have examined the CAR in relation to a very diverse range of individual differences in psychosocial variables and health and there have been a multitude of interesting findings. However, the literature is by no means straightforward: there are inconsistent results about associations with different

Number of times cited

1400 1200 1000 800 600 400 200


9 19 7 9 19 8 9 20 9 0 20 0 01 20 0 20 2 0 20 3 0 20 4 0 20 5 0 20 6 0 20 7 0 20 8 09

Year FIG. 2. Average citations per year for papers published on the CAR.



patterns of the CAR. The confusion in the literature may stem from causes such as participant non-adherence to protocol; different experimental designs; differ­ ences in group demographics such as gender, age, and genotype; subtle difference in the psychosocial and health measures. Furthermore a full interpretation of the findings is not yet possible as the role or roles for the CAR has not yet been clarified. Indeed it is as if the role of the CAR is being deduced from these crosssectional studies (e.g., if the CAR is attenuated in condition X then it must be related to causes of condition X). This is a rather precarious approach and a more systematic analysis of the direct physiological correlates of the CAR, preferably in healthy participants in the first instance, would be helpful and inform cross-sectional studies more accurately. It is not the purpose if this chapter to fully review the disparate findings of studies examining between-subject differences in the CAR (reviewed in Chida and Steptoe, 2009; Clow et al., 2004; Fries et al., 2009). However, it is noteworthy that increasing age (Kudielka and Kirschbaum, 2003) as well as a range of conditions, e.g., cardiovascular disease, autoimmune conditions, slow wound healing, clinical depression, mild cognitive impairment, Alzheimer’s disease, and attachment anxiety, are associated with a high first waking sample and an attenuated dynamic increase following awakening (e.g., Arsenault-Lapierre et al., 2010; Buske-Kirschbaum et al., 2007; Ebrecht et al., 2004; Huber et al., 2006; Kudielka and Kirschbaum, 2003; Quirin et al., 2008). A notable and consistent exception to this pattern is post-traumatic stress disorder which is characteristically associated with an attenuated CAR with a low first waking sample (Fries et al., 2009). What is clear from the literature is that, despite early reports of individual day-to-day consistency, the CAR is not a simple trait measure as it is also prone to significant state influences (Hellhammer et al., 2007). It seems that healthy individuals can unknowingly modify their CAR in response to previous day’s experiences and in anticipation of the forthcoming day ahead (Adam et al., 2006; Dahlgren et al., 2009; Doane and Adam, 2010; Stalder et al., 2009). Indeed, anticipation of the time of awakening is known to impact upon the neuroendo­ crine system (Born et al., 1999) so it may not be surprising that anticipation of the day ahead can have similar effects. This corresponds to the reported weekday/ weekend differences in the CAR, where the CAR is typically reported to be attenuated at the weekend, when it is assumed that most people have fewer obligations (Kunz-Ebrecht et al., 2004; Schlotz et al., 2004). However, it has recently been reported that a better measure of positive psychosocial status is not the size of the CAR but rather greater day-to-day variation (Mikolajczak et al., 2010). In other words it is suggested that healthy functioning is associated with efficient anticipatory physiological responding that is flexible. It is also clear that the CAR is sensitive to non-psychological factors such as gender (Wright and Steptoe, 2005), time of awakening (Edwards et al., 2001b;



Kudielka and Kirschbaum, 2003; Stalder et al., 2009), light (Scheer and Buijs, 1999; Thorn et al., 2004), hippocampal volume (e.g., Buchanan et al., 2004; Wolf et al., 2005), glucocorticoid receptor feedback (Pruessner et al., 1999), and genotype (van Leeuwen et al., 2010). These multiple factors again testify to the complexity of the CAR and the difficulty drawing meaningful conclusions about its role from cross-sectional studies in humans.

III. Distinct Regulation of the CAR and Relationship with the SCN

In a recent review the authors have argued that the CAR is subject to a complex range of physiological influences that facilitate the rapid increase in cortisol secretion initiated by awakening in healthy people (see Clow et al., 2010). In addition to awakening-induced SCN activation of the HPA axis (Wilhelm et al., 2007) direct sympathetic innervation from the SCN to the adrenal gland by the splanchnic nerve (Edwards and Jones, 1993; EhrhartBornstein et al., 1998; Engeland and Arnhold, 2005; Sage et al., 2002; UlrichLai et al., 2006) is implicated in the fine tuning of the CAR. In the immediate pre-awakening period there is evidence that this pathway induces reduced adrenal sensitivity to rising levels of adrenocorticotropic hormone (ACTH) (Bornstein et al., 2008; Buijs et al., 2003). The process of awakening is associated with “flip-flop” switching of regional brain activation (Braun et al., 1997; Lu et al., 2006; Saper et al., 2001; Sil’kis, 2009) which, it has been argued, initiates activation of the HPA axis. At the same time the SCN orchestrates a reversal of pre-awakening reduced adrenal sensitivity to ACTH (Bornstein et al., 2008; Buijs et al., 1997, 2003; Fehm et al., 1984). Indeed in the immediate post-awakening period adrenal sensitivity to ACTH is increased in response to light, a function again mediated by a SCN extrapituitary pathway (Buijs et al., 2003). Thus the SCN plays a pivotal role in the determination of the CAR by a combination of pre- and post-awakening influences operationalized via a dual control system: the HPA axis and the direct neural input to the adrenal cortex (see Fig. 3 for a diagrammatic representation of these pathways). One of the most consistent findings from the literature is that the hippocampus appears to play a permissive role in the regulation of the CAR (see Fries et al., 2009). This conclusion is derived from studies of clinical populations in which the hippocampus is impaired and the CAR attenuated (e.g., Buchanan et al., 2004; Wolf et al., 2005). In addition brain imaging studies have demonstrated positive associations between hippocam­ pal volume and the CAR (Bruehl et al., 2009; Pruessner et al., 2007). This



Hippocampus Retina Light

PVN Negative feedback by cortisol


CRH Anterior pituitary

Dual SCN-mediated regulatory input to the CAR

ACTH Cortisol secretion

Adrenal cortex

FIG. 3. Simplified diagrammatic representation of some proposed regulatory inputs to the CAR. The hypothalamic suprachiasmatic nucleus (SCN) influences the secretion of cortisol via input to the paraventricular nucleus (PVN) and the HPA axis cascade (CRH and ACTH). In addition the SCN has a direct neural input to the adrenal cortex via the splanchnic nerve of the sympathetic nervous system; a pathway that may also be modulated by activity of the hippocampus (see text). Upon awakening the SCN enhances cortisol secretion in response to light.

evidence, although not extensive, suggests a causal linkage between func­ tional integrity of the hippocampus and the CAR. This is a feasible hypoth­ esis as there are anatomical and functional pathways linking the hippocampus to the SCN (Krout et al., 2002; Pace-Schott and Hobson, 2002; Stranahan et al., 2008). However, the hippocampus is known to have inhibitory effects on HPA axis activity (Herman and Cullinan, 1997; Herman et al., 2005). Thus the ambiguity as to why the hippocampus is permissive for the CAR has yet to be adequately explained. It has been argued (see Clow et al., 2010) that the role of the hippocampus in the regulation of the CAR occurs prior to awakening. This possibility is consistent with the fact that rapid eye movement (REM) sleep (typically dominant in the later stages of sleep and immediately pre-awakening) is associated with marked hippocampal activation which provides inhibitory tone on cortisol secretion, whereas awakening is associated with switching off of hippocampal activation (Balkin et al., 2002; Braun et al., 1997). It is speculated that pre-awakening activation of the hippocampus restrains pre-awakening cortisol secretion. Again it is possible that this regulation may be related to the SCN-mediated extrapituitary fine tuning of adrenal sensitivity to ACTH in the pre-awakening period, as described above. Although speculative there is sufficient circum­ stantial evidence to merit further investigation of these relationships in their role in the determination of the CAR.



IV. The CAR as an Awakening Process

As its name suggests the CAR is a response to awakening. Although awakening corresponds to the transition between sleep and wakefulness, i.e., a clear disconti­ nuity of an ongoing sleep episode (Salzarulo et al., 2002), the physiological data available clearly show that the sleep-to-wake transition is not a rapid shift from one state of consciousness to another, but a complex process that takes some time to be completed. Awakening initiates the CAR, but the CAR may play a role in this transition from sleep to full alertness, awakening both the mind and the body in preparation for daytime activity. Cortisol is one of the most potent hormones of human physiology; virtually all of the body’s cells are potential targets for cortisol. It provides one of the means by which the circadian message from the SCN is transmitted to peripheral tissues. The peak of cortisol following awakening may play a particular part in synchronizing the body to both the sleep–wake and light–dark cycles via a range of nongenomic actions (Evanson et al., 2010). Further, it is becoming increasingly understood that circadian rhythms, particularly that of cortisol, transcribe the time of day message to the immune system. Circadian coordination is crucial for healthy physical and mental flourishing and disruption of circadian function is linked with multiple downstream negative physiological, psychological, and clinical consequences (Eismann et al., 2010). As detailed above, however, the CAR has generally been studied as an isolated phenomenon; it has rarely been considered as one of the physiological processes involved in the complex process of awakening. In fact, the CAR literature is characterized by an absence of a discourse on its role in the awaken­ ing process. Therefore, there is a need to re-contextualize the CAR as part of the awakening process. Here we are concerned with spontaneous morning awaken­ ing at the end of nocturnal sleep, leading to long-lasting and consistent awakening representing the termination of a full nocturnal sleep episode and a new beha­ vioral state. Other chapters in this volume (see Moul from Chapter 5 and Voss from Chapter 8) describe the difficulties in defining and identifying awakening. Voss proposes that as well as physiological markers, an awakening is accompa­ nied by behavioral responsiveness and the ability to think and the capacity for rational decision making and reflective awareness. Interestingly, these criteria for awakening are fully met in the measurement of the CAR which requires selfcollection of saliva samples. Participants are usually instructed to take the first sample as soon as they are conscious of being awake, which involves a cognitive component (“I am awake”) and a behavioral component (taking the saliva sample). Indeed difficulty in determining the precise time of awakening and delays in attainment of behavioral responsiveness may contribute to inaccuracies in its measurement and variation in the CAR literature. Below we review the potential role of the CAR in cognitive, immune, and also behavioral awakening.



V. CAR and Cognitive Awakening

Hormones other than cortisol show a distinct circadian rhythm, most notably melatonin (Benloucif et al., 2005), which along with core body temperature, is a classic circadian rhythm marker. Melatonin has sleep-promoting effects in humans (Pandi-Perumal et al., 2008). The timing of melatonin secretion is closely associated with the timing of sleep propensity and it also coincides with decreases in core body temperature, alertness, and performance. Exogenous melatonin administered during the day has soporific effects; it lowers body temperature, induces fatigue, and generates a brain activation pattern resembling that which occurs during sleep (see Cajochen, this volume). In humans, melatonin secretion increases soon after the onset of darkness, peaks in the middle of the night (between 2 and 4 a.m.), and gradually falls during the second half of the night. In other words it has the opposing rhythm to that of cortisol, with melatonin promoting sleep and cortisol promoting wakefulness. At awakening, when cortisol levels rise, melatonin levels are falling. Although studies have observed that administration of melatonin alters the timing of circadian rhythms including that of cortisol (Arendt and Skene, 2005), no study to date has explored the explicit relationship between the rise in cortisol following awakening and the decline in melatonin. As both these hormones are regulated by the SCN and are controlled by the same underlying mechanism, an inverse relationship could be hypothesized. The attainment of consciousness following sleep constitutes cortical arousal/ activation. Switching of brain circuitry associated with the transition between sleep and consciousness may be associated with initiation of the CAR as such switching is known to be actively initiated by the process of awakening (Spathschwalbe et al., 1992; Vancauter et al., 1994; Wilhelm et al., 2007). Studies of brain activity support the notion that brain activation levels upon awakening largely differ from those characterizing wakefulness, and that awakening is a process. Both EEG and brain imaging studies have revealed that although awakening from sleep comprises rapid reestablishment of consciousness, the reestablishment of alertness is relatively slow. For example, Ferrara et al. (2006) demonstrated that visual evoked potentials (VEP) recorded upon awakening have decreased amplitude and increased latency of 100–300 ms components relative to the pre-sleep waking state. The sleep–wake transition is characterized by an EEG pattern of decreased beta power and of increased power in the delta-theta-lower alpha range for the first 10 min following awakening. Balkin et al. (2002) used positron emission tomography (PET) methodology to examine changes in regional cerebral blood flow during the transition to wakefulness and full alertness revealing that upon awakening reactivation in the brainstem, thalamus, basal ganglia, and anterior cingulate cortex was rapid, for example, the reactivation of the thalamus was complete at 5 min post awakening. Taken together these studies confirm that a



state of cortical hypoarousal characterizes the early awakening. As detailed else­ where in this volume, this period between regaining consciousness (i.e., awakening) but before attainment of full alertness is described as “sleep inertia”: a transitory period of impaired arousal and behavioral performance lasting between 15 and 60 min (Ferrara et al., 2006; Ikeda and Hayashi, 2008). It seems that the initiation of the CAR is temporally associated with the attainment of consciousness and that the dynamic of the CAR closely parallels that of reactivation of the prefrontal cortex and attainment of full alertness. This temporal association could be considered simply as two parallel processes linked by the same underlying mechanism. However, there is some evidence indicating that the CAR may indeed play a role in the attainment of alertness following awakening. Indirect support is provided by the relatively consistent finding that acute bursts of cortisol have a stimulatory influence on psychological arousal and lead to a reduction of fatigue. This effect has been confirmed using self-report measures (Tops et al., 2006), arousal ratings in response to non-arousing stimuli (Abercrombie et al., 2005), as well as electro­ encephalographic (EEG) indicators of central alertness (Chapotot et al., 1998). Additionally, in sleep-deprived individuals early morning exposure to bright light induced an immediate elevation of cortisol levels, suppressed melatonin secretion, and limited the deterioration of alertness assessed by computerized vigilancesensitive performance tasks (Leproult et al., 2001). Few studies have directly tested the hypothesis that the CAR is associated with state arousal or levels of physiological activation. However, the results available to date have been supportive of a role for the CAR in the regaining of arousal, suggesting a positive association between state arousal at 45 min post awakening and post-awakening cortisol levels (Thorn et al., 2004) as well as the dynamic of the CAR (Thorn et al., 2009). This finding is also in general agree­ ment with results of Adam et al. (2006) showing an association between a larger mean CAR and lower average fatigue levels over a 3-day period. State arousal/ anticipations of a busy day ahead at 45 min post awakening have also been shown to relate positively with the CAR (Stalder et al., 2009). In addition high levels of sleepiness were associated with lower levels of cortisol 15 min after awakening in healthy office workers (Dahlgren et al., 2009). In summary the proposition for causal linkages between the CAR and recovery from sleep inertia, although speculative, certainly deserve further investigation. As well as general effects on alertness a further role for the CAR in awakening cognition can be discerned through its effects on memory retrieval. Rimmele et al. (2010) suppressed the CAR via administration of the cortisol synthesis inhibitor metyrapone. Participants were asked to recall emotional and neutral texts and pictures learned 3 days prior at 30 min following awakening. The metyraponeinduced cortisol suppression significantly impaired free recall in comparison to placebo. This finding corresponds to the view that memory-related processes are



of importance for the CAR. Wilhelm et al. (2007) speculate that the CAR may play a role in the “booting” of memory representations in the organization of personality, identity, and the self, as well as of representations that have remained preactivated from more acute experiences. This idea is endorsed by research showing that the CAR is attenuated in patients with hippocampal damagerelated memory disorders (Buchanan et al., 2004; Wolf et al., 2005).

VI. CAR and Immunological Awakening

According to Dimitrov et al. (2009) circadian rhythms have been underinvestigated in relation to the processes underlying the regulation of the immune system. Evidence indicates that both enumerative and functional immune mea­ sures exhibit circadian rhythmicity and these rhythms seem to be closely asso­ ciated with the circadian rhythm of cortisol (Kronfol et al., 1997). Hence, disruption of circadian endocrine rhythms has been found to be associated with many disease states, including cancer. In fact evidence points toward circadian disruption as a risk factor for tumor initiation and accelerated progression (Eismann et al., 2010). The relationship between cortisol and the immune system is complex. Corti­ sol and melatonin appear to counter-regulate the Th1/Th2 balance by inhibiting Th1 and promoting Th2 immune responses (Cutolo et al., 2006). There is a bias toward Th1 responses during the night and Th2 responses during the day. The circadian rhythm of cortisol may play an important role in regulating the diurnal rhythmicity of Th1 and Th2 immunity. In particular it has been suggested that a primary role of the increase in free cortisol in response to awakening may be to switch the immune system from nighttime Th1 to daytime Th2 domination (Hucklebridge et al., 1999). In support of this hypothesis there is evidence that the Th1 cytokine profile during nocturnal sleep is switched to a Th2 cytokine profile on awakening (Petrovsky and Harrison, 1997). Furthermore these authors reported that the degree of switch correlated with cortisol levels measured at the time the cytokine switch was detected. This immune-switching hypothesis has yet to be investigated in any systematic way. However, in a more recent study Dimitrov et al. (2009) demonstrated that the regulation of circadian rhythms in T cell populations is tightly controlled by the rhythms of cortisol and catecholamines. Interestingly, epinephrine appears also to exhibit a response to awakening. Dodt et al. (1997) observed that during REM–NONREM sleep both epinephrine and norepinephrine were significantly lower than earlier sleep stages. On morning awakening epinephrine concentrations gradually began to increase, whereas norepinephrine levels were not affected by



awakening, but were enhanced by change to an upright body position. Dimitrov et al. (2009) report similar findings with both epinephrine and norepinephrine reaching peak levels following awakening in the morning. Furthermore in this study, administration of both cortisol and epinephrine at low doses, purportedly mimicking the endogenous morning increase in these hormones, produced mark­ edly differential effects on the T cell subpopulations. For example cortisol infusion decreased naive T cell counts by approximately 40%, whereas administration of epinephrine produced an increase in circulating effector CD8þ T cells. Further investigation is warranted to explore the relationship between the shift in two major hormones following awakening in the morning and also their effect on immune parameters, particularly in relation to day and nighttime immunity.

VII. CAR and Behavioral Awakening

One of the functions of awakening (planned or otherwise) is to be able to respond to environmental cues by initiation of appropriate behavioral responses. Behavior requires coordinated and efficient motor function. This section pro­ poses a potential role for the CAR on the facilitation of voluntary motor function. Sleep states (especially REM sleep) are associated with inhibition of motor function called “sleep atonia.” This paralysis of most skeletal muscles is essential to ensure physical passivity during the periods of dynamic brain activation associated with dream states. Muscle atonia during sleep results from descending inhibitory projections to the spinal motor neurons from the caudal dorsolateral pontine tegmentum (Jones, 1991). Interestingly, an inability to initiate muscle atonia during REM sleep is increasingly being interpreted as an early sign of a range of neurodegenerative conditions (Boeve et al., 2001). As described earlier the process of awakening, in healthy individuals, involves the rapid switching off of these inhibitory pathways to restore the full waking state including voluntary motor function (Hobson, 2009). It is possible that the CAR may play a supplementary role in the reactivation of motor function post awakening as acute bursts of cortisol administration (similar in time course to the CAR) in humans have been shown to increase the excitability of the motor cortex as well as increase variability in motor cortex excitability (Milani et al., 2010). In their study Milani and colleagues examined motor-evoked potentials (MEPs) in the thumb in response to transcranial magnetic stimulation of the appropriate part of the motor cortex. Participants were assessed before and after either an injection of 20 mg of hydro­ cortisone or saline solution. Mean plasma cortisol levels rose rapidly and peaked around 10 min after hydrocortisone injection, at which time the mean MEP ampli­ tude and mean standard deviation of MEPs were significantly greater than pre­



injection levels. Thus, although this study does not examine the CAR per se it does demonstrate that an equivalent acute burst in cortisol can have marked effects on the excitability of the motor cortex, effects that would facilitate voluntary movement. Currently the full significance of cortisol-induced increases in the variability of the excitability of the motor cortex is not fully understood. However, it is plausible that this state would facilitate appropriate motor responses to novel patterns of behavior, i.e., the capacity to explore and try out new motor skills. There is some supportive evidence for this theory showing that acute, physiologically relevant, corticosterone administration to rats rapidly increased exploratory locomotor activity when the animals were placed into a new activity cage but that the same dose of corticosterone failed to increase locomotion when administered to rats that had been previously exposed to the activity cage (Sandi et al., 1996). It has been suggested that this increase in locomotor activity may relate to risk-assessment behavior, which is also rapidly increased after treatment with corticosterone, without any change in anxi­ ety-like behavior or general locomotion in rats (Mikics et al., 2005). In contrast to its effects on motor cortical excitability, reported above, it is known that cortisol inhibits neural plasticity in the human motor cortex. Motor plasticity is associated with consolidation of learnt skills and the efficiency of plasticity is lowest in the morning and inhibited by acute bursts of cortisol administration (Sale et al., 2008). It is possible, and speculated here, that explora­ tory behavior (associated with increased motor cortical excitability and variabil­ ity) is facilitated by cortisol secretion in the morning, whereas consolidation of these actions (associated with neural plasticity) is facilitated later in the day when cortisol levels are low and in a steady state. Thus it seems plausible that the CAR may play a part in rapidly inducing specific behavioral adjustments to meet the immediate requirements set by the challenge of awakening. These speculations resonate with the observation that the dynamic of the CAR has been shown to be greater with more anticipated obligations in the day ahead: the CAR may play a role in literally “preparing for action.” Of course a role for the CAR in this type of motor function, although plausible, is speculative. It would be interesting to test this hypothesis by examin­ ing the impact of overnight cortisol synthesis inhibition (which abolishes the CAR) upon post-awakening motor cortical excitability in healthy participants.

VIII. Measurement of the CAR

Within the literature the CAR is most frequently derived from saliva samples taken by the participants themselves, within the domestic setting. This confers ecological validity but also lacks rigor in terms of reassurance that the sampling




regime is strictly adhered to (especially problematic due to the occurrence cogni­ tive deficits immediately post awakening). Instructions are typically given to collect samples on awakening and at a number of subsequent time points, e.g., 15, 30, and 45 (sometimes even 60) min post awakening. Due to the difficulties in accurately capturing this dynamic aspect of cortisol secretion within the domestic setting it is advisable to collect samples from each participant on more than one day as this allows for examination of day-to-day consistency, which should always be reported. Furthermore measures to assess and take account of participant adher­ ence to protocol, a notorious problem with this area of research (Broderick et al., 2004; Kudielka et al., 2003; Kupper et al., 2005) should be employed. The CAR is sometimes used as an umbrella term to describe both overall levels of cortisol secretion as well as the dynamic change in cortisol post awakening; these different elements are illustrated in Fig. 4. The area under the curve with reference to ground: AUCG (sample 2 þ s3 þ (s1 þ s4)/2) gives a good measure of overall cortisol secreted whereas the area under the curve with reference to the first waking sample: AUCI (sample 2 þ s3 – (2 * s1) þ ((s4 – s2)/2)) or the mean increase: MnInc (sample 2 þ s3 þ s4)/3 – s1) provide closely correlated measures of the dynamic change in cortisol following awakening. (The dynamic change in post waking cortisol is also sometimes calculated as levels 30 min post awakening minus the waking value, or the maximum concentration minus the first waking sample.) We would argue that the CAR is by its very nature a “response” to awakening and thus should always be presented as the change in concentration from the first waking sample rather than the overall AUCG. The main reason for this is that identical measures of AUCG can be derived from completely different, indeed even oppo­ site patterns of secretion, e.g., a high first sample and low last sample would equate



Time FIG. 4. Graphical representation of the area under the curve with reference to increase (AUCI) and the first sample on awakening (S1). The area under the curve with reference to ground (AUCG) is the sum of the AUCi and the area under the curve with reference to base (AUCB).



with low fist sample and high last sample. While AUCG may be informative under some circ*mstances, e.g., overall low as compared to overall high levels of cortisol secretion; it does little to enlighten knowledge of patterns of post-awakening cortisol secretion. We recommend that the most meaningful data to present from studies of the CAR are both the fist waking sample (S1) plus a measure of the change in cortisol secretion following awakening: AUCI or MnInc (the com­ posites from which the AUCG are derived). It is interesting to note that high levels of cortisol in S1 are sometimes associated with an attenuated CAR (Adam et al., 2006; Dahlgren et al., 2009; Stalder et al., 2009; Vreeburg et al., 2009; Wilhelm et al., 2007). However, this inverse association is not always the case (e.g., Evans et al., 2007) implying that the relationship between S1 and the AUCI is not fixed. Indeed it has been argued that S1 (if collected correctly) represents a measure of pre-awakening cortisol secretion, whereas AUCI or MnInc are post-awakening measures of cortisol secretion (Clow et al., 2010). As pre- and post-awakening cortisol secretions are under different types of regulatory control (see earlier) it is possible that dysfunc­ tion in either or both of these regulatory systems could affect the pattern of the CAR. For example a high first sample could implicate hypofunctioning of the hippocampus and/or SCN pathways to the adrenal (e.g., inefficient pre-awaken­ ing inhibition of adrenal sensitivity to ACTH). If S1 is in normative range but the AUCI is attenuated this could implicate a role for post-awakening processes (e.g., a role for light and the SCN). If both the S1 and the AUCI are affected then this might imply a role for the HPA axis more generally (e.g., low availability of ACTH and consequent low cortisol secretion). In order to help determine which of the CAR pathways are implicated in any particular pattern of post-awakening cortisol secretion, it would be helpful to have additional measures of cortisol from across the day. If the CAR is aberrant yet the rest of the diurnal pattern is not (e.g., Evans et al., 2007; Oskis et al., 2010) then this would imply that a CAR-specific mechanism is implicated, rather than HPA axis more generally. If, however, both the CAR and the rest of the diurnal cycle are aberrant then this might implicate a more general HPA axis-related phenomenon. It may also be useful to look at post-awakening patterns of salivary dehydroepiandrosterone (DHEA) (note that DHEA sticks to some types of saliv­ ettes, so care is required in choice of saliva collection methodology). DHEA does not mount an awakening response (Hucklebridge et al., 2005). This has been attributed to the fact that cortisol is synthesized predominantly in the adrenal zona fasciculata, whereas DHEA is synthesized in the zona reticularis only. In contrast to the reticularis, the zona fasciculata is subject to sympathetic innerva­ tion, a pathway that might form the light-sensitive extra-pituitary input to the adrenal cortex that contributes to the CAR (discussed earlier; see Fig. 3). As a consequence levels of post-awakening DHEA are a “cleaner” index of ACTH availability than the more complex CAR.



More recently it has been suggested that the best way to capture individual differences in the CAR is to assess day-to-day variability, i.e., a measure of the flexibility of the CAR (Mikolajczak, 2010). This may be a promising new approach although work along these lines is in the early stages of verification. If adopting this strategy it is still necessary to ensure accurate measures of S1 and AUCI. It will be interesting to see how different degrees of variability in the CAR are related to different patterns of CAR. We would hypothesize that those with the most advantageous psychosocial profiles would typically present with a moderate S1 followed by a responsive AUCI and would also be capable of the most day-to-day variability, i.e., generate appropriate CARs in response to anticipation of the forthcoming demands of the day.

IX. Conclusions

Awakening from sleep can be a “hazy” phenomenon. Recently, when we asked people to recall and describe their first waking thoughts they said things like: I experienced a flow of disconnected thoughts; A woolly awareness; My thoughts were incoherent and jumpy. Indeed many of those asked to recall their first waking thoughts were unable to do so. This haziness belies the range of dynamic physiological activities that accompany the process of awakening and the restora­ tion of full waking alertness and function. In this chapter we have attempted to review the status of the CAR within the field of psychobiological research, summarize some of its distinctive regulatory characteristics, and contextualize it in relation to other post-awakening changes. There can be little doubt that the CAR holds great promise as a biomarker, but it represents more than an index of HPA axis function. Evidence is presented for dual control links with the hypothalamic SCN nucleus. It is increasingly apparent that physical and psychological flourishing is associated with close coordination of physiological functioning around the 24-h day (Eismann et al., 2010). It is argued that the CAR is part of a SCN-synchronized response to morning awakening in healthy participants. We propose that the CAR may play a part in the restoration of alertness and cognitive function, immune system balance, and voluntary motor function following nighttime sleep. Indeed evi­ dence is presented that the CAR can vary within an individual in response to the anticipated demands of the forthcoming day in order to meet those demands, both physically and mentally. Evidence is presented that individual differences in psychological and physi­ cal status (e.g., chronic stress, aging, and gender) are associated with the pattern of the CAR in distinct ways. These effects could be mediated by any of the



regulatory pathways that affect the CAR, e.g., ACTH availability via the HPA axis, SCN-related mechanisms, hippocampal function, and provide a window into the brain that is broader than examination of the HPA axis alone. The relative ease by which the CAR can be measured in salivary samples enables large-scale population studies and can provide useful insight into risk factors. However, such work needs to pay attention to the particular issues associated with self-collection of saliva immediately upon awakening, to ensure that data collection is as free from non-adherence to protocol as possible. In addition due to the complex regulation of the CAR it is recommended that all studies should present data on the first waking sample (as a measure of pre-awakening cortisol secretion) and the dynamic of the cortisol rise post awakening. These measures are the two key determinants of the CAR and different states and regulatory pathways may be associated with either or both of these measures. Research on the CAR is making a wide impact upon the psychobiological research community and its significance and use is set to increase. We hope that in the near future greater clarification on the regulation and roles of the CAR in healthy participants will emerge. It is plausible that it plays a part in a range of functions as discussed in this chapter. These hypotheses are yet to be fully tested, but once we have a clearer view of its regulation and roles this biomarker will surely become even more significant. For example, in the future, it is possible that distinct patterns or characteristics of the CAR will be recognized biomarkers for different patterns of functioning associated with distinct brain system and neuroendocrine dysfunction (e.g., SCN-related mechanisms, hippocampal function, as well as of the HPA axis) and also point to downstream consequences in relation to health, cogni­ tion, and function. If this is the case then the measurement of the CAR will prove to be an increasingly valuable tool in the armory of researchers and clinicians alike.


Abercrombie, H. C., Kalin, N. H., and Davidson, R. J. (2005). Acute cortisol elevations cause heightened arousal ratings of objectively nonarousing stimuli. Emotion 5, 354–359. Adam, E. K., Hawkley, L. C., Kudielka, B. M., and Cacioppo, J. T. (2006). Day-to-day dynamics of experience-cortisol associations in a population-based sample of older adults. Proc. Natl. Acad. Sci. U.S.A. 103, 17058–17063. Arendt, J., and Skene, D. J. (2005). Melatonin as a chronobiotic. Sleep Med. Rev. 9, 25–39. Arsenault-Lapierre, G., Chertkow, H., and Lupien, S. (2010). Seasonal effects on cortisol secretion in normal aging, mild cognitive impairment and Alzheimer’s disease. Neurobiol. Aging 31(6), 1051–1054. Balkin, T. J., Braun, A. R., Wesensten, N. J., Jeffries, K., Varga, M., Baldwin, P., Belenky, G., and Herscovitch, P. (2002). The process of awakening: A PET study of regional brain activity patterns mediating the re-establishment of alertness and consciousness. Brain 125, 2308–2319.



Benloucif, S., Guico, M. J., Reid, K. J., Wolfe, L. F., L’Hermite-Baleriaux, M., and Zee, P. C. (2005). Stability of melatonin and temperature as circadian phase markers and their relation to sleep times in humans. J. Biol. Rhythms 20, 178–188. Boeve, B. F., Silber, M. H., Ferman, T. J., Lucas, J. A., and Parisi, J. E. (2001). Association of REM sleep behavior disorder and neurodegenerative disease may reflect an underlying synucleino­ pathy. Mov. Disord. 16, 622–630. Born, J., Hansen, K., Marshall, L., Molle, M., and Fehm, H. L. (1999). Timing the end of nocturnal sleep. Nature 397, 29–30. Bornstein, S. R., Engeland, W. C., Ehrhart-Bornstein, M., and Herman, J. P. (2008). Dissociation of ACTH and glucocorticoids. Trends Endocrinol. Metab. 19, 175–180. Braun, A. R., Balkin, T. J., Wesensten, N. J., Carson, R. E., Varga, M., Baldwin, P., Selbie, S., Belenky, G., and Herscovitch, P. (1997). Regional cerebral blood flow throughout the sleep-wake cycle: An (H2O)-O-15 PET study. Brain 120, 1173–1197. Broderick, J. E., Arnold, D., Kudielka, B. M., and Kirschbaum, C. (2004). Salivary cortisol sampling compliance: Comparison of patients and healthy volunteers. Psychoneuroendocrinology 29, 636–650. Bruehl, H., Wolf, O. T., and Convit, A. (2009). A blunted cortisol awakening response and hippo­ campal atrophy in type 2 diabetes mellitus. Psychoneuroendocrinology 34, 815–821. Buchanan, T. W., Kern, S., Allen, J. S., Tranel, D., and Kirschbaum, C. (2004). Circadian regulation of cortisol after hippocampal damage in humans. Biol. Psychiatry 56, 651–656. Buijs, R. M., van Eden, C. G., Goncharuk, V. D., and Kalsbeek, A. (2003). The biological clock tunes the organs of the body: Timing by hormones and the autonomic nervous system. J. Endocrinol. 177, 17–26. Buijs, R. M., Wortel, J., Van Heerikhuize, J. J., and Kalsbeek, A. (1997). Novel environment induced inhibition of corticosterone secretion: Physiological evidence for a suprachiasmatic nucleus mediated neuronal hypothalamo-adrenal cortex pathway. Brain Res. 758, 229–236. Buske-Kirschbaum, A., Krieger, S., Wilkes, C., Rauh, W., Weiss, S., and Hellhammer, D. H. (2007). Hypothalamic-pituitary-adrenal axis function and the cellular immune response in former preterm children. J. Clin. Endocrinol. Metab. 92, 3429–3435. Chapotot, F., Gronfier, C., Jouny, C., Muzet, A., and Brandenberger, G. (1998). Cortisol secretion is related to electroencephalographic alertness in human subjects during daytime wakefulness. J. Clin. Endocrinol. Metab. 83, 4263–4268. Chida, Y., and Steptoe, A. (2009). Cortisol awakening response and psychosocial factors: A systematic review and meta-analysis. Biol. Psychol. 80, 265–278. Clow, A., Hucklebridge, F., Stalder, T., Evans, P. and Thorn, L. (2010). The cortisol awakening response: more than a measure of HPA axis function. Neurosci. Biobehav. Rev. special issue: Psychophysiological Biomarkers of Health 35, 97–103. Clow, A., Thorn, L., Evans, P., and Hucklebridge, F. (2004). The awakening cortisol response: Methodological issues and significance. Stress 7, 29–37. Cutolo, M., Sulli, A., Pizzorni, C., Secchi, M. E., Soldano, S., Seriolo, B., Straub, R. H., Otsa, K., and Maestroni, G. J. (2006). Circadian rhythms—Glucocorticoids and arthritis. In: Basic and Clinical Aspects of Neuroendocrine Immunology in Rheumatic Diseases ( M. Cutolo, ed.), Blackwell Publishing, Oxford, UK, 289–299. Dahlgren, A., Kecklund, G., Theorell, T., and Akerstedt, T. (2009). Day-to-day variation in saliva cortisol–relation with sleep, stress and self-rated health. Biol. Psychol. 82, 149–155. Dickmeis, T. (2009). Glucocorticoids and the circadian clock. J. Endocrinol. 200, 3–22. Dimitrov, S., Benedict, C., Heutling, D., Westermann, J., Born, J., and Lange, T. (2009). Cortisol and epinephrine control opposing circadian rhythms in T cell subsets. Blood 113, 5134–5143. Doane, L. D., and Adam, E. K. (2010). Loneliness and cortisol: Momentary, day-to-day, and trait associations. Psychoneuroendocrinology, 35(3), 430–441.



Dodt, C., Breckling, U., Derad, I., Fehm, H. L., and Born, J. (1997). Plasma epinephrine and norepinephrine concentrations of healthy humans associated with nighttime sleep and morning arousal. Hypertension 30, 71–76. Ebrecht, M., Hextall, J., Kirtley, L. G., Taylor, A., Dyson, M., and Weinman, J. (2004). Perceived stress and cortisol levels predict speed of wound heating in healthy male adults. Psychoneuroendo­ crinology 29, 798–809. Edwards, S., Clow, A., Evans, P., and Hucklebridge, F. (2001a). Exploration of the awakening cortisol response in relation to diurnal cortisol secretory activity. Life Sci. 68, 2093–2103. Edwards, S., Evans, P., Hucklebridge, F., and Clow, A. (2001b). Association between time of awakening and diurnal cortisol secretory activity. Psychoneuroendocrinology 26, 613–622. Edwards, A. V., and Jones, C. T. (1993). Autonomic control of adrenal function. J. Anat. 183, 291–307. Ehrhart-Bornstein, M., Hinson, J. P., Bornstein, S. R., Scherbaum, W. A., and Vinson, G. P. (1998). Intraadrenal interactions in the regulation of adrenocortical steroidogenesis. Endocr. Rev. 19, 101–143. Eismann, E. A., Lush, E., and Sephton, S. E. (2010). Circadian effects in cancer-relevant psychoneur­ oendocrine and immune pathways. Psychoneuroendocrinology 35, 963–976. Engeland, W. C., and Arnhold, M. M. (2005). Neural circuitry in the regulation of adrenal corticos­ terone rhythmicity. Endocrine 28, 325–331. Evans, P., Forte, D., Jacobs, C., Fredhoi, C., Aitchison, E., Hucklebridge, F., and Clow, A. (2007). Cortisol secretory activity in older people in relation to positive and negative well-being. Psychoneuroendocrinology 32, 922–930. Evanson, N. K., Herman, J. P., Sakai, R. R., and Krause, E. G. (2010). Nongenomic actions of adrenal steroids in the central nervous system. J. Neuroendocrinol. 22, 846–861. Fehm, H. L., Klein, E., Holl, R., and Voigt, K. H. (1984). Evidence for extrapituitary mechanisms mediating the morning peak of plasma-cortisol in man. J. Clin. Endocrinol. Metab. 58, 410–414. Ferrara, M., Curcio, G., Fratello, F., Moroni, F., Marzano, C., Pellicciari, M. C., and De Gennaro, L. (2006). The electroencephalographic substratum of the awakening. Behav. Brain Res. 167, 237–244. Fries, E., Dettenborn, L., and Kirschbaum, C. (2009). The cortisol awakening response (CAR): Facts and future directions. Int. J. Psychophysiol. 72, 67–73. Hellhammer, J., Fries, E., Schweisthal, O. W., Schlotz, W., Stone, A. A., and Hagemann, D. (2007). Several daily measurements are necessary to reliably assess the cortisol rise after awakening: State and trait components. Psychoneuroendocrinology 32, 80–86. Herman, J. P., and Cullinan, W. E. (1997). Neurocircuitry of stress: Central control of the hypotha­ lamo-pituitary-adrenocortical axis. Trends Neurosci. 20, 78–84. Herman, J. P., Ostrander, M. M., Mueller, N. K., and Figueiredo, H. (2005). Limbic system mechanisms of stress regulation: Hypothalamo-pituitary-adrenocortical axis. Prog. Neuropsycho­ pharmacol. Biol. Psychiatry 29, 1201–1213. Hobson, J. A. (2009). REM sleep and dreaming: Towards a theory of protoconsciousness. Nat. Rev. Neurosci. 10, U803–U862. Hsiao, F. H., Yang, T. T., Ho, R.T.H., Jow, G. M., Ng, S. M., Chan, C.L.W., Lai, Y. M., Chen, Y. T., and Wang, K. C. (2010). The self-perceived symptom distress and health-related conditions associated with morning to evening diurnal cortisol patterns in outpatients with major depressive disorder. Psychoneuroendocrinology 35, 503–515. Huber, T. J., Issa, K., Schik, G., and Wolf, O. T. (2006). The cortisol awakening response is blunted in psychotherapy inpatients suffering from depression. Psychoneuroendocrinology 31, 900–904. Hucklebridge, F., Clow, A., Abeyguneratne, T., Huezo-Diaz, P., and Evans, P. (1999). The awaken­ ing cortisol response and blood glucose levels. Life Sci. 64, 931–937. Hucklebridge, F., Hussain, T., Evans, P., & Clow, A. (2005). The diurnal patterns of the adrenal steroids cortisol and dehydroepiandrosterone (DHEA) in relation to awakening. Psychoneuroendo­ crinology, 30, 51–57.



Ikeda, H., and Hayashi, M. (2008). Effect of sleep inertia on switch cost and arousal level immediately after awakening from normal nocturnal sleep. Sleep Biol. Rhythms 6, 120–125. Jones, B. E. (1991). Paradoxical sleep and its chemical/structural substrates in the brain. Neuroscience 40, 637–656. Kalsbeek, A., Palm, I. F., La Fleur, S. E., Scheer, F., Perreau-Lenz, S., Ruiter, M., Kreier, F., Cailotto, C., and Buijs, R. M. (2006). SCN outputs and the hypothalamic balance of life. J. Biol. Rhythms 21, 458–469. Kirschbaum, C., and Hellhammer, D. H. (1994). Salivary cortisol in psychoneuroendocrine research—recent developments and applications. Psychoneuroendocrinology 19, 313–333. Kronfol, Z., Nair, M., Zhang, Q., Hill, E. E., and Brown, M. B. (1997). Circadian immune measures in healthy volunteers: Relationship to hypothalamic-pituitary-adrenal axis hormones and sympa­ thetic neurotransmitters. Psychosom. Med. 59, 42–50. Krout, K. E., Kawano, J., Mettenleiter, T. C., and Loewy, A. D. (2002). CNS inputs to the suprachiasmatic nucleus of the rat. Neuroscience 110, 73–92. Kudielka, B. M., Broderick, J. E., and Kirschbaum, C. (2003). Compliance with saliva sampling protocols: Electronic monitoring reveals invalid cortisol daytime profiles in noncompliant sub­ jects. Psychosom. Med. 65, 313–319. Kudielka, B. M., and Kirschbaum, C. (2003). Awakening cortisol responses are influenced by health status and awakening time but not by menstrual cycle phase. Psychoneuroendocrinology 28, 35–47. Kunz-Ebrecht, S. R., Kirschbaum, C., Marmot, M., and Steptoe, A. (2004). Differences in cortisol awakening response on work days and weekends in women and men from the Whitehall II cohort. Psychoneuroendocrinology 29, 516–528. Kupper, N., de Geus, E.J.C., van den Berg, M., Kirschbaum, C., Boomsma, D. I., and Willemsen, G. (2005). Familial influences on basal salivary cortisol in an adult population. Psychoneuroendocrinology 30, 857–868. Leproult, R., Colecchia, E. F., L’Hermite-Baleriaux, M., and Van Cauter, E. (2001). Transition from dim to bright light in the morning induces an immediate elevation of cortisol levels. J. Clin. Endocrinol. Metab. 86, 151–157. Lightman, S. L. (2008). The neuroendocrinology of stress: A never ending story. J. Neuroendocrinol. 20, 880–884. Linkowski, P., Vanonderbergen, A., Kerkhofs, M., Bosson, D., Mendlewicz, J., and Vancauter, E. (1993). Twin study of the 24-h cortisol profile—evidence for genetic-control of the human circadian clock. Am. J. Physiol. 264, E173–E181. Lu, J., Sherman, D., Devor, M., and Saper, C. B. (2006). A putative flip-flop switch for control of REM sleep. Nature 441, 589–594. Mikics, E., Barsy, B., Barsvari, B., and Haller, J. (2005). Behavioral specificity of non-genomic glucocorticoid effects in rats: Effects on risk assessment in the elevated plus-maze and the openfield. Horm. Behav. 48, 152–162. Mikolajczak, M., Quoidbach, J., Vanootighem, V., Lambert, F., Lahaye, M., Fillee, C., and de Timary, P. (2010). Cortisol awakening response (CAR)’s flexibility leads to larger and more consistent associations with psychological factors than CAR magnitude. Psychoneuroendocrinology 35, 752–757. Milani, P., Piu, P., Popa, T., Della Volpe, R., Bonifazi, M., Rossi, A., and Mazzocchio, R. (2010). Cortisol-induced effects on human cortical excitability. Brain Stimuli. 3, 131–139. Minton, G. O., Young, A. H., McQuade, R., Fairchild, G., Ingram, C. D., and Gartside, S. E. (2009). Profound changes in dopaminergic neurotransmission in the prefrontal cortex in response to flattening of the diurnal glucocorticoid rhythm: Implications for bipolar disorder. Neuropsychophar­ macology 34, 2265–2274. Oskis, A., Loveday, C., Hucklebridge, F., Thorn, L., Clow, A. (2010). Anxious attachment style and salivary cortisol dysregulation in healthy female children and adolescents. J Child Psychol Psychiatry. 2010 Jul 31. [Epub ahead of print]



Pace-Schott, E. F., and Hobson, J. A. (2002). The neurobiology of sleep: Genetics, cellular physiology and subcortical networks. Nat. Rev. Neurosci. 3, 591–605. Pandi-Perumal, S. R., Trakht, I., Srinivasan, V., Spence, D. W., Maestroni, G. J. M., Zisapel, N., and Cardinali, D. P. (2008). Physiological effects of melatonin: Role of melatonin receptors and signal transduction pathways. Prog. Neurobiol. 85, 335–353. Petrovsky, N., and Harrison, L. C. (1997). Diurnal rhythmicity of human cytokine production—A dynamic disequilibrium in T helper cell type 1/T helper cell type 2 balance? J. Immunol. 158, 5163–5168. Pruessner, J. C., Hellhammer, D. H., and Kirschbaum, C. (1999). Burnout, perceived stress, and cortisol responses to awakening. Psychosom. Med. 61, 197–204. Pruessner, J. C., Kirschbaum, C., and Hellhammer, D. (1995). Waking up—the first stressor of the day? Free cortisol levels double within minutes after awakening. J. Psychophysiol. 9, 365. Pruessner, M., Pruessner, J. C., Hellhammer, D. H., Pike, G. B., and Lupien, S. J. (2007). The associations among hippocampal volume, cortisol reactivity, and memory performance in healthy young men. Psychiatry Res. 155, 1–10. Pruessner, J. C., Wolf, O. T., Hellhammer, D. H., Buske-Kirschbaum, A., von Auer, K., Jobst, S., Kaspers, F., and Kirschbaum, C. (1997). Free cortisol levels after awakening: A reliable biological marker for the assessment of adrenocortical activity. Life Sci. 61, 2539–2549. Quirin, M., Pruessner, J. C., and Kuhl, J. (2008). HPA system regulation and adult attachment anxiety: Individual differences in reactive and awakening cortisol. Psychoneuroendocrinology 33, 581–590. Rimmele, U., Meier, F., Lange, T., and Born, J. (2010). Suppressing the morning rise in cortisol impairs free recall. Learn. Mem. 17, 186–190. Sage, D., Maurel, D., and Bosler, O. (2002). Corticosterone-dependent driving influence of the suprachiasmatic nucleus on adrenal sensitivity to ACTH. Am. J. Physiol. Endocrinol. Metab. 282, E458–E465. Sale, M. V., Ridding, M. C., and Nordstrom, M. A. (2008). Cortisol inhibits neuroplasticity induction in human motor cortex. J. Neurosci. 28, 8285–8293. Salzarulo, P., Giganti, F., fa*gioli, I., and Ficca, G. (2002). Early steps of awakening process. Sleep Med. 3(Suppl. 2), S29–S32. Sandi, C., Venero, C., and Guaza, C. (1996). Novelty-related rapid locomotor effects of corticosterone in rats. Eur. J. Neurosci. 8, 794–800. Saper, C. B., Chou, T. C., and Scammell, T. E. (2001). The sleep switch: Hypothalamic control of sleep and wakefulness. Trends Neurosci. 24, 726–731. Sapolsky, R. M., Romero, L. M., and Munck, A. U. (2000). How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21, 55–89. Scheer, F., and Buijs, R. M. (1999). Light affects morning salivary cortisol in humans. J. Clin. Endocrinol. Metab. 84, 3395–3398. Schlotz, W., Hellhammer, J., Schulz, P., and Stone, A. A. (2004). Perceived work overload and chronic worrying predict weekend- weekday differences in the cortisol awakening response. Psychosom. Med. 66, 207–214. Schmidt-Reinwald, A., Pruessner, J. C., Hellhammer, D. H., Federenko, I. S., Rohleder, N., Schurmeyer, T. H., and Kirschbaum, C. (1999). The cortisol response to awakening in relation to different challenge tests and a 12-hour cortisol rhythm. Life Sci. 64, 1653–1660. Schulz, P., and Knabe, R. (1994). Biological uniqueness and the definition of normality 2. The endocrine fingerprint of healthy-adults. Med. Hypotheses 42, 63–68. Sephton, S. E., Sapolsky, R. M., Kraemer, H. C., and Spiegel, D. (2000). Diurnal cortisol rhythm as a predictor of breast cancer survival. J. Natl. Cancer Inst. 92, 994–1000. Sil’kis, I. G. (2009). Characteristics of the functioning of the hippocampal formation in waking and paradoxical sleep. Neurosci. Behav. Physiol. 39, 523–534.



Spathschwalbe, E., Gofferje, M., Kern, W., Born, J., and Fehm, H. L. (1991). Sleep disruption alters nocturnal ACTH and cortisol secretory patterns. Biol. Psychiatry 29, 575–584. Spathschwalbe, E., Scholler, T., Kern, W., Fehm, H. L., and Born, J. (1992). Nocturnal adrenocorticotropin and cortisol secretion depends on sleep duration and decreases in association with spontaneous awakening in the morning. J. Clin. Endocrinol. Metab. 75, 1431–1435. Stalder, T., Hucklebridge, F., Evans, P., and Clow, A. (2009). Use of a single case study design to examine state variation in the cortisol awakening response: Relationship with time of awakening. Psychoneuroendocrinology 34, 607–614. Stranahan, A. M., Lee, K., and Mattson, M. P. (2008). Contributions of impaired hippocampal plasticity and neurodegeneration to age-related deficits in hormonal pulsatility. Ageing Res. Rev. 7, 164–176. Thorn, L., Hucklebridge, F., Esgate, A., Evans, P., and Clow, A. (2004). The effect of dawn simulation on the cortisol response to awakening in healthy participants. Psychoneuroendocrinology 29, 925–930. Thorn, L., Hucklebridge, F., Evans, P., and Clow, A. (2009). The cortisol awakening response, seasonality, stress and arousal: A study of trait and state influences. Psychoneuroendocrinology 34, 299–306. Tops, M., Van Peer, J. M., Wijers, A. A., and Korf, J. (2006). Acute cortisol administration reduces subjective fatigue in healthy women. Psychophysiology 43, 653–656. Ulrich-Lai, Y. M., Arnhold, M. M., and Engeland, W. C. (2006). Adrenal splanchnic innervation contributes to the diurnal rhythm of plasma corticosterone in rats by modulating adrenal sensitivity to ACTH. Am. J. Physiol. Regul. Integr. Comp. Physiol. 290, R1128–R1135. van Leeuwen, N., ku*msta, R., Entringer, S., de Kloet, E. R., Zitman, F. G., DeRijk, R. H., et al. (2010). Functional mineralocorticoid receptor (MR) gene variation influences the cortisol awa­ kening response after dexamethasone. Psychoneuroendocrinology, 35, 339–349. Vancauter, E., Polonsky, K. S., Blackman, J. D., Roland, D., Sturis, J., Byrne, M. M., and Scheen, A. J. (1994). Abnormal temporal patterns of glucose-tolerance in obesity: Relationship to sleeprelated growth hormone secretion and circadian cortisol rhythmicity. J. Clin. Endocrinol. Metab. 79, 1797–1805. Vreeburg, S. A., Kruijtzer, B. P., van Pelt, J., van Dyck, R., DeRijk, R. H., Hoogendijk, W. J. G., Smit, J. H., Zitman, F. G., and Penninx, B. (2009). Associations between sociodemographic, sampling and health factors and various salivary cortisol indicators in a large sample without psychopathology. Psychoneuroendocrinology 34, 1109–1120. Weitzman, E. D., Nogeire, C., Perlow, M., f*ckushim., D., Sassin, J., McGregor, P., Gallaghe, Tf., and Hellman, L. (1974). Effects of a prolonged 3-hour sleep-wake cycle on sleep stages, plasma cortisol, growth hormone and body temperature in man. J. Clin. Endocrinol. Metab. 38, 1018–1030. Wilhelm, I., Born, J., Kudielka, B. M., Schlotz, W., and Wust, S. (2007). Is the cortisol awakening rise a response to awakening? Psychoneuroendocrinology 32, 358–366. Wolf, O. T., Fujiwara, E., Luwinski, G., Kirschbaum, C., and Markowitsch, H. J. (2005). No morning cortisol response in patients with severe global amnesia. Psychoneuroendocrinology 30, 101–105. Wright, C. E., and Steptoe, A. (2005). Subjective socioeconomic position, gender and cortisol responses to waking in an elderly population. Psychoneuroendocrinology 30, 582–590. Wuest, S., Federenko, I. S., Hellhammer, D. H., and Kirschbaum, C. (2000a). Genetic factors, perceived chronic stress, and the free cortisol response to awakening. Psychoneuroendocrinology 25, 707–720. Wuest, S., Wolf, J., Hellhammer, D. H., Federenko, I. S., Schommer, N., and Kirschbaum, C. (2000b). The cortisol response to awakening—normal values and confounds. Noise Health 7, 77–85. Yehuda, R. (2001). Biology of posttraumatic stress disorder. J. Clin. Psychiatry 62, 41–46.



Amy Jo Schwichtenberg and Beth Goodlin-Jones University of California, Davis, M.I.N.D. Institute, M.I.N.D. Institute, Sacramento,

CA 95819, USA

I. Parenting Practices A. Bedtime Settling Routines B. Co-sleeping C. Breastfeeding D. Sleep Aid Use E. Culture II. Family Context A. Socioeconomics B. Parental Psychopathology III. Child Characteristics A. Temperament B. Parent–Child Interactions and Attachment C. Developmental Problems and Diagnoses IV. Summary


Night awakenings are a normative part of early development. In the first year, night awakenings are associated with birth order, feeding route, sleep aid use, sleep location, infant temperament and development, infant–parent attachment, family socioeconomics, and cultural norms. In the second year, additional factors build on these foundational features, including parenting practices and object attachment. As children grow, contextual factors like preschool entry or changes in family member status may influence the continuation or exacerbation of awakenings. Future research should consider the multitude of factors that influ­ ence not only awakenings but also parental perceptions, family dynamics, and cultural norms. Night awakenings in young children are a normative part of development (Goodlin-Jones et al., 2001; Iglowstein et al., 2003; Sadeh et al., 2009). Children are born with a homeostatic drive for sleep based on their hunger–satiety cycles and gradually entrain to light–dark cycles (i.e., circadian cycles) in the first months of development. Entrainment marks the beginning of a shift from equally

INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 93 DOI: 10.1016/S0074-7742(10)93008-0


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distributed sleep to gradually more sleep at night and less during the day. Sleep consolidation at night is an evolutionally driven change that is highly amendable to contextual and biological pressures. Gradually from 3 to 12 months children sleep for longer periods of time at night, and as they develop they require less sleep per day–night cycle. By 12 months of age, the duration of an infant’s nighttime sleep stabilizes. After 15–18 months of age, developmental shifts toward less sleep per sleep-wake cycle are primarily seen in the reduction and cessation of naps (Iglowstein et al., 2003). Throughout early childhood middle-of-the-night arousals occur on a nightly basis, for some children these arousals develop into awakenings. Some nighttime awakenings are normative through to 5 years of age (Iglowstein et al., 2003). Night awakenings become problematic with increased frequency and/or duration and when there is daytime impairment due to sleepiness in either the parent or the child (e.g., Snyder et al., 2008). There have been many attempts to define problematic night awakenings with no clear agreement yet developed (Anders et al., 2000; Buckhalt and El-Sheikh, in press; Galland and Mitchell, in press; Goodlin-Jones et al., 2000; Ivanenko and Gururaj, 2009). Regardless of definition issues, most studies indicate that 15–20% of toddlers and preschool children have problematic night awakenings (Goodlin-Jones et al., 2009; Ivanenko and Gururaj, 2009). Within this chapter we will not discuss/define what constitutes proble­ matic nighttime awakenings or the clinical nomenclature (for a discussion of these issues, see Moul, Chapter 5 of this volume). Rather we will review the literature on the causes and correlates of problematic night awakenings in young children. In most research studies, night awakenings are indexed by parent report and they assess awakenings on a continuum with more and longer awakenings generally perceived with more concern (Goodlin-Jones et al., 2001; Santos et al., 2008; Schwichtenberg and Poehlmann, 2009; St James-Roberts and Plewis, 1996). Because parent-report indices are the most common, many studies include the bias/confound of parental perceptions. When sleep schedules are the focus of the study, this bias appears minimal (Sadeh, 2008). However, if sleep quality is the critical feature, the bias and confound of parental report may be significant. Both objective assessments (e.g., actigraphy, polysomnography) and parental report (e.g., questionnaires, diaries) will be included in the discussion that follows. Problematic nighttime awakenings occur for many reasons. For most children night awakenings are associated with learned patterns of behavior and not linked with specific medical conditions (Sadeh et al., 2010). Within this chapter, psycho­ logical, behavioral, and developmental factors are discussed and other causal factors are briefly reviewed (e.g., medical conditions). Medical concerns may involve the presence of reflux, pain due to infection or injury, obstructive sleep apnea, chronic conditions such as asthma or cystic fibrosis, or a neurological disorder such as restless leg syndrome. Each of these medical factors may have numerous impacts that increase night awakenings and require medical attention.



The recommended treatments may also involve medications that further pre­ cipitate frequent sleep arousals (Givan, 2004). Most often early childhood night awakening problems are linked to behavioral factors and are amendable to behaviorally based treatments. Therefore, this chapter will focus on nighttime awakenings that are not a result of specific medical conditions. Within a devel­ opmental context, the correlates and predictors of night awakenings are reviewed below by parent/contextual and child factors (Fig. 1).

I. Parenting Practices

Parenting practices are the most commonly studied element of infant night awakenings. Parenting practices encompass a wide range of behaviors and may include bedtime settling routines, sleep location (e.g., co-sleeping), feeding route, sleep aid use, and culture. Each of these realms is reviewed below with attention to their role in night awakenings.

A. BEDTIME SETTLING ROUTINES One of the most studied factors in night awakenings is the role parents play in the beginning of the night. Parenting practices at bedtime that require the


3 Months

6 Months

12 Months 18 Months 24 Months 36 Months 48 Months

Culture (values pertaining to sleep, parenting, childcare, pre-school) Sociodemographics (family income, neighborhood, parent work status, changes in family membership) Maternal Mental Health (Parenting beliefs, depression, anxiety) Birth Status (health, birth order) Feeding Route (breast, bottle) Soothing Object Use (pacifier, thumb) Parent-Child Interactions (parenting practices, bedtime routines) Sleep Location (solitary crib, family bed, inconsistent locations) Temperament (adaptability, rhythmicity) Attachment (secure, insecure, disorganized)

Reactive co-sleeping (parents consistently sleep with child after an awaking)

Object Attachment (blanket, dolly)

FIG. 1. Conceptual figure of the developmental progression of factors that play a role in sleep behaviors.



presence or assistance of parent(s) for the child’s transition to sleep have been associated with longer and more night awakenings (Mindell and Owens, 2003; Sadeh et al., 2009). These activities, sometimes called negative sleep-onset asso­ ciations, may include feeding, car rides, lying next to a parent or being cuddled, being held by a parent, pacifier use, and sleep aid use (Anuntaseree et al., 2008; Fehlings et al., 2001). It is unclear if the association between parenting practices at bedtime and elevated awakenings is mediated by or interacts with child char­ acteristics (e.g., temperament). However, the relationship between parenting practices and infant awakenings is likely bi-directional and it is not likely causal, although this has also been debated within the field. Additionally, it is unclear if the type of parenting activity used to assist the child’s transition to sleep impacts this relationship or if it is being placed in their nighttime sleep location asleep (DeLeon and Hildebrandt Karraker, 2007). Many studies, including clinical studies, have demonstrated that focusing on parents as a means for change at the beginning of the night can create change in children’s sleep in the middle of the night. The important role for parent behavior continues during middle­ of-the-night awakenings. Parental actions following an awakening that include active settling techniques have been associated with elevated awaken­ ings (Mindell and Owens, 2003). Active settling techniques may include removal from the child’s sleep location, walking, rocking, feeding, or reposi­ tioning. During awakenings, parental latency to respond has also been studied (Burnham et al., 2002a). In this study, maternal response to infant signaling ranged from immediate to 27 min later. Interestingly, parents who responded with slower (longer) latencies at 3 months of age were more likely to have infants self-soothing at 12 months of age (Burnham et al., 2002a). Another factor to consider is paternal involvement, which is less common during middle-of-the-night parenting. For example, in a recent study more parental involvement in general caregiving predicted fewer night awakenings at 6 months of age (Tikotzky et al., 2010).

B. CO-SLEEPING Cultural expectations and socioeconomic conditions often influence early childhood sleeping practices, especially in co-sleeping practices. Numerous studies report elevated night awakenings in families that co-sleep when compared to families that practice solitary infant sleeping (e.g., in their own room alone) (f*ckumizu et al., 2005; Mao et al., 2004; St. James-Roberts et al., 2006). However, multiple considerations must be noted when inter­ preting these findings. Most studies that report more night awakenings in



families who co-sleep assess infant sleep via parent report. Parents who co­ sleep are physically closer to their infant are therefore more likely to notice and report an awakening. Additionally, there are multiple types of co­ sleeping arrangements (McKenna and McDade, 2005; Taylor et al., 2008). Some parents co-sleep by choice (e.g., the family bed, a sleeping room) and others co-sleep to accommodate their child’s frequent bids at night, some­ times called reactionary co-sleeping. Consistent co-sleeping is associated with less maternal depression, longer breastfeeding, and less infant temperamental intensity (Taylor et al., 2008). Whereas co-sleep in response to a reactive or bidding child (part-night co-sleeping) is not linked with these positive corre­ lates. Grouping all co-sleeping arrangements into one group creates a hetero­ geneous group and makes interpretation difficult. A culturally sensitive developmental perspective on co-sleeping may provide a clearer picture of how, when, and why young children co-sleep and its relation to night awakenings. Cultural aspects of co-sleeping and awakenings are discussed in more detail below. Regarding the developmental progression of co­ sleeping and night awakenings, a longitudinal study in Switzerland of 493 families found relativity low levels of co-sleeping early in development (10%) with a gradual increase in co-sleeping through 4 years of age (38%) (Jenni et al., 2005). They reported a similar pattern in night awakenings with gradually more children waking from 6 months to 4 years and a consistent positive relationship between co-sleeping and parent-reported night awaken­ ings. However, the relationship between co-sleeping and parent-reported night awakenings is not consistently found in cultures where co-sleeping is the most popular sleeping agreement (see Section I.E). Studies of co-sleeping that move beyond parent report are sparse. To our knowledge, there is only one research team that has assessed infant and mother sleep in co-sleeping dyads using polysomnography. Within their study, Mosko and colleagues (1997) reported more nighttime arousals in young infants who co-slept. These arousals were more often led by the child and then followed by a parent arousal. A study using actigraphy and diaries confirmed this finding (Mao et al., 2004). More research on physiological correlates of co-sleeping across numerous co-sleeping “types” is needed.

C. BREASTFEEDING Studies assessing infant sleep via maternal report sleep logs or diaries have found more night waking and less nighttime sleep among breastfed infants when compared to bottle-fed infants (DeLeon and Hildebrandt Karraker, 2007; Wolke et al., 1995). In a study of 41 healthy 9-month-old infants, DeLeon and



Hildebrandt Karraker (2007) reported that breastfed infants spent more time awake at night (i.e., more night waking and less nighttime sleep). Researchers have hypothesized that breastfed infants are awake more at night because of shorter hunger–satiety cycles. Although numerous studies have found links between feeding route and night awakening (Messer and Richards, 1993; Schwichtenberg and Poehlmann, 2009), little support has emerged for an asso­ ciation between breastfeeding and infant sleep problems. In addition, a study by Doan and associates (Doan et al., 2007) found that parents of healthy 3-month-old infants slept more at night than parents of formula-fed or combination fed infants, as indexed by actigraphy.

D. SLEEP AID USE Although many parenting resources (e.g., Brazelton and Sparrow, 2003; Ferber, 1985; Mindell, 1997) recommend sleep aid use (e.g., a blanket, pacifier, baby doll) empirical studies of sleep aid use and night awakenings in young children are limited. In 1998, Jencius and Rotter reported fewer night awaken­ ings among infants who consistently used a sleep aid in their study of 16 families (Jencius and Rotter, 1998). In a larger sample of infants studied in a crosssectional design, a majority of 3- to 15-month-old infants used a sleep aid during the night, yet its use was not related to self-soothing after an awakening (Burnham et al., 2002b). It is unclear if sleep aid use itself is associated with fewer awakenings or if factors common among infant who use sleep aids are contributing factors. For example, Green and colleagues (2004) reported less parent contact at night among infants who consistently used a sleep aid (Green et al., 2004). Similarly, Wolf and Lozoff (1989) presented a robust association between sleep aid use and parent presence at sleep onset. Infants who fell asleep with a parent present were less likely to use a transition object (Wolf and Lozoff, 1989). Differences in family sociodemographic factors have also been associated with sleep aid use (Litt, 1981; Milan et al., 2007). In a study of 285 children, Litt (1981) report substantially higher rates of sleep aid use in upper-middle class Caucasian children when compared to lower-middle class African American children. In a more recent study, Milan et al. (2007) reported similar results with higher rates of sleep aid use in Caucasian children when compared to African American children. Although sleep aid use is associated with fewer night awakenings, an intervention study that introduced a sleep aid as an intervention tool found no significant changes in infant sleep when the novel sleep aid was used (Burnham et al., 2002b). Future research in sleep aid use should work to disentangle the relations between object use, parenting practices, and family sociodemographic factors.



E. CULTURE A discussion of parenting practices/behaviors should be based within the con­ text of culture. Multiple studies (Latz et al., 1999; Mindell et al., 2010) report that culture moderates the relationships between parenting behaviors and night awaken­ ings. For example, Latz et al. (1999) reported a stronger association between co­ sleeping and night awakenings in the US when compared to families in Japan. Similarly, Mindell and colleagues (2010) reported that within primarily Caucasian cultures co-sleeping is associated with more awakenings; however, this relationship is weaker in primarily Asian cultures where co-sleeping is the most common sleep arrangement. Cultural practice may also dictate common parenting practices that consistently relate to more awakenings. In a study of 174 families, St. James-Roberts and colleagues (2006) reported that “infant led” parenting practices (like those common in Copenhagen and Denmark) were associated with more awakenings when compared to more “Western” parenting practices (i.e., sleep independently in another room) (St James-Roberts et al., 2006).

II. Family Context

As stated above, the primary factors that influence awakenings are negative sleep associations. Negative sleep associations are conditions present at sleep onset that require parental presence (e.g., rocking or swinging). In contrast, positive sleep associations are those conditions that do not require parental presence and can be completed by the individual child (e.g., thumb sucking). The development of negative sleep associations and problematic night awaken­ ings are impacted by several ecological or familial characteristics such as interparental conflict, employment status, education levels of parents, and the general stability of the home environment.

A. SOCIOECONOMICS Socioeconomic conditions influence parental psychological health and parenting behaviors. For example, parental response to nighttime awakenings and the pattern of letting a child “cry it out” was more common in middle class parents while working class parents responded immediately (Scott and Richards, 1990). Mothers who work outside the home during the day reported that their infants woke more at night (Scher et al., 1995; Van Tassel, 1985). More recent results continue to support the negative statistical association between lower socioeconomic status (SES) and elevated



awakening problems in infants, toddlers, and preschoolers (Brown and Low, 2008; Lozoff et al., 1996; Santos et al., 2008). Crowding, clutter, and lack of daily routines have been found in families of lower SES samples, and these conditions have also been associated with parent-reported sleep problems in 3 year olds (Koulouglioti et al., 2008). However, a recent infant study at 9 months of age suggested no relation of family SES and night waking problems (Bayer et al., 2007).

B. PARENTAL PSYCHOPATHOLOGY Parental psychological features, particularly depression and marital conflict, may be related to socioeconomic status but they have also been studied as independent factors impacting sleep behavior. There is a fairly extensive litera­ ture that links early childhood sleep problems to maternal psychopathology. Multiple studies have suggested that mothers with poor well-being have children with higher levels of parent-reported behavior problems, including night waking sleep problems (Bayer et al., 2007; El-Sheikh et al., 2007; Goodman and Gotlib, 1999; Hoffman et al., 2006; Richman, 1981a; Shang et al., 2006; Zuckerman et al., 1987). Snyder and colleagues (2008) highlight how a constellation of factors in the family context (marital conflict and poor maternal mental health) play a role in the development of sleep night waking problems (Snyder et al., 2008). These patterns of association begin early life, as indicated by research by sleep research­ ers in Australia (Armstrong et al., 1998; Bayer et al., 2007; Hisco*ck and Wake, 2001). In general, throughout the first year, mothers who endorse high rates of night waking problems reported more difficulties with mental health concerns and negative correlation coefficients are reported between child sleep problems and marital conflict and poor mental health in mothers. Maternal depression is the primary mental health condition studied in rela­ tion to childhood sleep problems (e.g., Armstrong et al., 1998; Richman, 1981b; Sadeh et al., 2010). Mothers who endorse depressive symptoms have young children with higher rates of night waking (Bayer et al., 2007; Morrell and Steele, 2003). The related constructs of maternal separation anxiety and parental sleeprelated cognitions have also been implicated in night waking problems (Scher, 2008; Tikotzky and Sadeh, 2010). Toddlers and older children of affectively ill mothers also had more disrupted sleep (Stoleru et al., 1997). In an observational study with actigraphic-measured infant sleep at 10 months of age, mothers with higher levels of separation anxiety from their infants had infants with more disrupted sleep. This pattern of night waking still remained significantly asso­ ciated with the mother’s own separation anxiety after infant temperamental fussiness was controlled for statistically (Tikotzky and Sadeh, 2010). However, in a relatively large study with 80 infants measured objectively on nighttime



waking behavior, there were no consistent differences in parental well-being and night waking behavior (Goodlin-Jones et al., 2001). Other researchers have also reported negligible evidence of maternal mood or mental health on young children’s sleep patterns once environmental context is controlled for statistically (Morrell and Steele, 2003; Van Tassel, 1985). Maternal depression or anxiety may alter cognitions and parenting behavior in a dramatic manner. However, frequent night awakenings may clearly impact parental well-being in a bi-directional manner, leading to feelings of incompe­ tence and low self-esteem as a parent. Exhausted parents feel the challenge of parenting more intensely. Hence, the multiple factors underlying sleep problems are clearly bi-directional. Parental beliefs and cognitions about their child’s competence to self-sooth play a role in these interactions. The link of parental cognitions to childhood sleep problems is assumed to be mediated through the way parents behave with their children (Sadeh et al., 2009). Sadeh and colleagues have completed recent studies that describe one developmental route to night waking problems. Specifically, if a parent was upset about a child’s demands or if the parent reported more difficulty in limit setting than parents’ also reported more nighttime parent involvement and more night waking episodes (Sadeh et al., 2007; Tikotzky and Sadeh, 2010).

III. Child Characteristics

Multiple child factors may impact night awakenings. Factors present from birth (e.g., gender, birth order) may influence awakenings as well as factors that develop over time (e.g., temperament, attachment). For example, Scher and Blumberg (1999) found that first born children were more likely than later born children to signal upon waking at 12 months of age (Scher and Blumberg, 1999). A few studies report more night awakenings in male children (Anuntaseree et al., 2008; Goodlin-Jones et al., 2001). For example, Goodlin-Jones et al. (2001) reported that male children were more likely to signal upon waking in a crosssectional sample from 3- to 12-month-old infants; however, they found no gender difference in signaling behavior or vocalizing rate. This indicated that the vocalizations were specific to awakenings. Future research is warrant to address gender differences in night awakenings; the elevated rates of awakenings in male infants are not a consistent finding. Behavioral research on child characteristics and nighttime sleep generally focuses on three areas: temperament, attachment (parent–child relations), and other developmental problems. We address each below with specific attention to night awakenings.



A. TEMPERAMENT Temperamental characteristics are considered important intrinsic factors of the individual by many developmental researchers. Sleep studies have investigated the contribution of infant temperament with two methods: parent-report indices and observational assessments. Most commonly, studies rely on parental report of infant temperament while a minority of researchers measure infant temperament with direct assessments. Both methods show greater agreement on positive ratings of temperament (e.g., adaptability) and greater divergence on the negative dimen­ sions of temperament (Stifter et al., 2008). However, negative temperament dimen­ sions are more commonly implicated with night waking problems. For example, the temperament characteristic of poor rhythmicity (or poor regularity of behavior) has been associated with more night awakenings in parent-report studies (Atkinson et al., 1995; Jimmerson, 1991) of young children. However, it is possible that a sleep-deprived parent rate their children in a less positive manner. During early infancy, infants rated with more negative mood were reported to waken more often in the middle of the night (Kelmanson and Adulas, 2004; Schaefer, 1990; Scher et al., 1998). Halpern et al. (1994) reported that infants who spent more of the night awake at 3 weeks of age were more irritable at 3 months according to parental report (Halpern et al., 1994). Most researchers do not support a direct link between temperament and sleep problems, however, given the reporter bias involved in parent reports. Indeed, issues of rater bias were described in a study that observed different associations between sleep and temperament depending upon whether the raters were mothers or fathers (Keener et al., 1988).




Previous research on infant sleep and infant–mother attachment presents mixed findings (Benoit et al., 1992; McNamara et al., 2003; Morrell and Steele, 2003; Scher and Asher, 2004). Benoit and colleagues (1992) drew attention to infant sleep and infant–mother attachment when they reported that 100% of their clinic sample referred for infant sleep problems were classified as insecurely attached on the Adult Attachment Interview. Concurrently, Anders (1994) high­ lighted the undeniable resemblance between infant–parent bedtime separations and the separations seen in the strange situation. However, later studies do not report robust relationships between sleep behaviors and infant–mother attach­ ment classification in healthy infants. Scher and Asher (2004) reported no significant relationships between actigraph measured infant sleep and concurrent attachment Q-set scores in healthy 12-month-old infants. Conversely, Morrell



and Steele (2003) reported a modest but significant relationship between parentreported sleep problems and ambivalent attachment. In a longitudinal study, McNamara and colleagues (2003) found more frequent and longer lasting parentreported nighttime awakenings in infants who were classified as insecure resis­ tant, when compared to infants classified as insecure avoidant in the Strange Situation. Although the previous literature in this area is limited, it appears that parent perceptions of infant sleep may be more indicative of later attachment than more objective measures.

C. DEVELOPMENTAL PROBLEMS AND DIAGNOSES Frequent night awakenings often co-occur with other developmental problems or medical conditions. For example, infant feeding problems may impact nighttime sleep as infant hunger–satiety cycles are shorter or irregular (Thunstrom, 1999). Similarly, frequent night awakenings are more common among children with neurodevelopmental conditions, such as Down syndrome. The cranial–facial fea­ tures common in Down syndrome place these children at increased risk for sleep apnea, as many as 55% of children with Down syndrome suffer from frequent apnea-related night awakenings (de Miguel-Diez et al., 2003; Marcus et al., 1991). A recent study of preschoolers with neurodevelopmental disorders studied sleep patterns with actigraphy and observed longer night awakenings in preschoolers with developmental delay, which included Downs syndrome, compared to pre­ schoolers with autism or with typical development (Goodlin-Jones et al., 2009). Other common childhood diagnoses associated with frequent night awakenings include autism (Krakowiak et al., 2008), Smith-Magenis syndrome (Boudreau et al., 2009), intrauterine growth retardation (Leitner et al., 2002), cerebral palsy (Pruitt and Tsai, 2009), Chiari malformations (Gosalakkal, 2008), and many more. Sleep is a universal and fundamental element of development; disrupted or alternative paths in development are often associated with atypical sleep patterns (which commonly include frequent night awakenings). Consistent consolidated sleep requires the coordination of several neurological and biological systems, alterations in one or more system often lead to disturbed sleep.

IV. Summary

Night awakenings in early in life are a normative part of development. However, night awakenings that increase with frequency and duration as chil­ dren develop may negatively impact families and later developmental outcomes.



As children grow, the number of factors that affect their sleep builds, leading to an increasingly more complex picture (Fig. 1). Researcher, clinicians, and inter­ ventionists need to consider the multitude of factors that could influence not only the child’s sleep behaviors (night awakening) but also parental perceptions, family dynamics, and cultural norms. References

Anders, T. (1994). Infant sleep, nighttime relationships, and attachment. Psychiarty 57, 11–21. Anders, T., Goodlin-Jones, B. L., and Sadeh, A. (2000). Sleep disorders. In: Handbook of Infant Mental Health (C. H. Zeanah, ed.), The Guilford Press, New York, NY. Anuntaseree, W., Mo-suwam, L., Vasiknanote, P., Kuasirikul, S., Ma-a-lee, A., and Chaprapawan, C. (2008). Night waking in Thai infants at 3 months of age: Association between parental practices and infant sleep. Sleep Med. 9, 564–571. Armstrong, K., O’Donnell, H., R., M., and Dadds, M. (1998). Childhood sleep problems: Association with prenatal factors and maternal distress/depression. J. Paediatr. Child Health 34, 263–266. Atkinson, E., Vetere, A., and Garayson, K. (1995). Sleep disruption in young children. The influence of temperament on the sleep patterns of pre-school children. Child Care Health Dev. 21, 233–246. Bayer, J., Hisco*ck, H., Hampton, A., and Wake, M. (2007). Sleep problems in young infants and maternal mental and physical health. J. Paediatr. Child Health 43, 66–73. Benoit, D., Zeanah, C., Boucher, C., and Minde, K. (1992). Sleep disorders in early childhood: Association with insecure maternal attachment. J. Am. Acad. Child Adolesc. Psychiatry 31, 86–93. Boudreau, E., Johnson, K., Jackman, A., Blancato, J., Huizing, M., Bendavid, C., Jones, M., Chandrasekharappa, S., Lewy, A., Smith, A., and Meagenis, R. (2009). Review of disrupted sleep patterns in Smith-Magenis syndrome and normal melatonin secretion in a patient with Atypical Interstitial 17q11.2 deletion. Am. J. Med. Genet. 149A, 1382–1391. Brazelton, T., and Sparrow, J. (2003). Sleep: The Brazelton Way. Perseus, Cambridge, MA. Brown, E., and Low, C. (2008). Chaotic living conditions and sleep problems associated with children’s responses to academic challenge. J. Fam. Psychol. 22, 920–923. Buckhalt, J., and El-Sheikh, M. (eds.) (in press). Assessment and Intervention for Sleep Problems. National Association of School Psychologists and Corwin Press. Burnham, M. M., Goodlin-Jones, B. L., Gaylor, E. E., and Anders, T. F. (2002a). Nighttime sleepwake patterns and self-soothing from birth to one year of age: A longitudinal intervention study. J. Child Psychol. Psychiatry 43, 713–725. Burnham, M. M., Goodlin-Jones, B. L., Gaylor, E. E., and Anders, T. F. (2002b). Use of sleep aids during the first year of life. Pediatrics 109, 594–601. DeLeon, C., and Hildebrandt Karraker, K. (2007). Intrinsic and extrinsic factors associated with night waking in 9-month-old infants. Infant Behav. Dev. 30, 596–605. de Miguel-Diez, J., Villa-Asensi, J., and Alvarez-Sala, J. (2003). Prevalence of sleep-disorder breathing in children with Down syndrome: Polygraphic findings in 108 children. Sleep 26, 1006–1009. Doan, T., Gardiner, A., Gay, C., and Lee, K. (2007). Breast-feeding increases sleep duration of new parents. J. Perinat. Neonatal Nurs. 21, 200–206. El-Sheikh, M., Buckhalt, J. A., Mark Cummings, E., and Keller, P. (2007). Sleep disruptions and emotional insecurity are pathways of risk for children. J. Child Psychol. Psychiatry 48, 88–96. Fehlings, D., Weiss, S., and Stephens, D. (2001). Frequent night awakings in infant and preschool children referred to a sleep disorders clinic: The role of nonadaptive sleep associations. Child Health Care 30, 43–55.



Ferber, R. (1985). Solve Your Child’s Sleep Problems. Simon & Schuster, New York, NY. f*ckumizu, M., Kaga, M., Kohyama, J., and Hayes, M. (2005). Sleep-related nighttime crying (Yonaki) in Japan: A community-based study. Pediatrics 115, 217–224. Galland, B., and Mitchell, E. (2010). Helping children sleep. Arch. Dis. Child [Epub ahead of print] doi:10.1136/abc.2010.162974 Givan, D. (2004). The sleepy child. In: Pediatric Clinics of North America (M. Splaingard, ed.), Vol. 51, Elsevier, Philadelphia, PA. Goodlin-Jones, B., Burnham, M., Gaylor, E., and Anders, T. (2001). Night waking, sleep-wake organization, and self-soothing in the first year of life. J. Dev. Behav. Pediatr. 22, 226–233. Goodlin-Jones, B., Schwichtenberg, A., Iosif, A., Tang, K., Liu, J., and Anders, T. (2009). Six-month persistence of sleep problems in young children with autism, developmental delay and typical development. J. Am. Acad. Child Adolesc. Psychiatry 48, 847–854. Goodlin-Jones, B. L., Burnham, M. M., and Anders, T. F. (2000). Sleep and sleep disturbances: Regulatory processes in infancy. In: Handbook of Developmental Psychopathology (A. J. Sameroff, M. Lewis, and S. M. Miller, eds.), Kluwer Academic Publishers, New York, NY; Dordrecht, Netherlands, pp. 309–325. Goodman, S., and Gotlib, I. (1999). Risk for psychopathology in the children of depressed parents: A developmental approach to the understanding of mechanisms. Psychol. Rev. 106, 458–490. Gosalakkal, J. (2008). Sleep-disordered breathing in Chiari malformation type 1. Pediatr. Neurol. 39, 207–208. Green, K., Groves, M., and Tegano, D. (2004). Parenting practices that limit transitional object use: An illustration. Early Child Dev. Care. 174, 427–436. Halpern, L., Anders, T., Garcia Coll, C., and Hua, J. (1994). Infant temperament: Is there a relation to sleep-wake sates and maternal nighttime behavior? Infant Behav. Dev. 17, 255–263. Hisco*ck, H., and Wake, M. (2001). Infant sleep problems and postnatal depression: A communitybased study. Pediatrics 107, 1317–1322. Hoffman, C., Crnic, K., and Baker, J. (2006). Maternal depression and parenting: Implications for children’s emergent emotion regulation and behavioral functioning. Parent. Sci. Pract. 6, 271–295. Iglowstein, I., Jenni, O., Morinari, L., and Largo, R. (2003). Sleep duration form infancy to adolescence: Reference values and generational trends. Pediatrics 111, 302–307. Ivanenko, A., and Gururaj, B. (2009). Classification and epidemiology of sleep disorders. Child Adolesc. Psychiatr. Clin. N. Am. 18, 839–848. Jencius, M., and Rotter, J. (1998). Bedtime rituals and their relationship to childhood sleep distur­ bance. Fam. J. 6, 94–105. Jenni, O. G., Fuhrer, H. Z., Iglowstein, I., Molinari, L., and Largo, R. H. (2005). A longitudinal study of bed sharing and sleep problems among Swiss children in the first 10 years of life. Pediatrics 115, 233–240. Jimmerson, K. (1991). Maternal, environmental, and temperamental characteristics of toddlers with and toddlers without sleep problems. J. Pediatr. Health Care 5, 71–77. Keener, M., Zeanah, C., and Anders, T. (1988). Infant temperament, sleep organization, and night­ time parental interventions. Pediatrics 81, 762–771. Kelmanson, I. A., and Adulas, E. I. (2004). Environmental characteristics and sleep in two-month-old infants. Klin. Padiatr. 216, 259–263. Koulouglioti, C., Cole, R., and Kitzman, H. (2008). Inadequate sleep and unintentional injuries in young children. Publ. Health Nurs. 25, 106–114. Krakowiak, P., Goodlin-Jones, B., Hertz-Picciotto, I., Croen, L. A., and Hansen, R. L. (2008). Sleep problems in children with autism spectrum disorders, developmental delays, and typical devel­ opment: A population-based study. J. Sleep Res. 17, 197–206. Latz, S., Wolf, A., and Lozoff, B. (1999). Cosleeping in context: Sleep practices and problems in young children in Japan and the United States. Arch. Pediatr. Adolesc. Med. 153, 339–346.



Leitner, Y. A. B., Sadeh, A., Neuderfer, O., Tikotsky, L., Fattal-Valevski, A., and Harel, S. (2002). Sleepwake patterns in children with intrauterine growth retardation. J. Child Neurol. 17, 872–876. Litt, C. (1981). Children’s attachment to transitional objects: A study of two pediatric populations. Am. J. Orthopsychiatry 51, 131–139. Lozoff, B., Askew, G. L., and Wolf, A. W. (1996). Cosleeping and early childhood sleep problems: Effects of ethnicity and socioeconomic status. J. Dev. Behav. Pediatr. 17, 9–15. Mao, A., Burnham, M. M., Goodlin-Jones, B. L., Gaylor, E. E., and Anders, T. F. (2004). A comparison of the sleep-wake patterns of cosleeping and solitary-sleeping infants. Child Psy­ chiatry Hum. Dev. 35, 95–105. Marcus, C., Keens, T., Bautista, D., von Pechmann, W., and Ward, S. (1991). Obstructive sleep apnea in children with Down syndrome. Pediatrics 88, 132–139. McKenna, J., and McDade, T. (2005). Why babies should never sleep alone: A review of co-sleeping controversy in relation to SIDS, bedsharing and breast feeding. Paediatr. Respir. Rev. 6, 134–152. McNamara, P., Belsky, J., and Fearon, P. (2003). Infant sleep disorders and attachment: Sleep problems in infant with insecure-resistant versus insecure-avoidant attachments to mother. Sleep Hypn. 5, 17–25. Messer, D., and Richards, M. (1993). The Development of Sleeping Difficulties. Infant Crying, Feeding, and Sleeping: Development, Problems, and Treatments. Harvester Wheatsheaf, New York, NY. Milan, S., Snow, S., and Belay, S. (2007). The context of preschool children’s sleep: Racial/ethnic differences in sleep locations, routines, and concerns. J. Fam. Psychol. 21, 20–28. Mindell, J. (1997). Sleep through the Night. HarperCollins, New York, NY. Mindell, J., and Owens, J. (2003). A Clinical Guide to Pediatric Sleep: Diagnosis and Management of Sleep Problems. Lippincott Williams & Wilkins, Philadelphia, PA. Mindell, J., Sadeh, A., Kohyama, J., and How, T. (2010). Parental behaviors and sleep outcomes in infant and toddlers: A cross-cultural comparison. Sleep Med. 11, 393–399. Morrell, J., and Steele, M. (2003). The role of attachment security, temperament, maternal perception, and care-giving behavior in persistent infant sleeping problems. Infant Ment. Health J. 24, 447–468. Mosko, S., Richard, C., and McKenna, J. (1997). Infant arousals during mother-infant bedsharing: Implications for infant sleep and Sudden Infant Death Syndrome. Pediatrics, 100, 841–849. Pruitt, D., and Tsai, T. (2009). Common medical comorbidities associated with cerebral palsy. Phys. Med. Rehabil. Clin. N. Am. 20, 453–467. Richman, N. (1981a). A community survey of characteristics of one- to two- year-olds with sleep disruptions. J. Am. Acad. Child Psychiatry 20, 281–291. Richman, N. (1981b). Sleep problems in young children. Arch. Dis. Child. 56, 491–493. Sadeh, A. (2008). Commentary: Comparing actigraphy and parental report as measures of children’s sleep. J. Ped. Psy., 33, 406–407. Sadeh, A., Flint-Ofir, E., Tirosh, E., and Tikotsky, L. (2007). Infant sleep and parental sleep-related cognitions. J. Fam. Psychol. 21, 74–87. Sadeh, A., Mindell, J., Luedtke, K., and Weigand, B. (2009). Sleep and sleep ecology in the first 3 years: A web-based study. J. Sleep Res. 18, 60–73. Sadeh, A., Tikotzky, L., and Scher, A. (2010). Parenting and infant sleep. Sleep Med. Rev. 14, 89–96. Santos, I., Mota, D., and Matijasevich, A. (2008). Epidemiology of co-sleeping and nighttime waking at 12 months in a birth cohort. J. Pediatr. 84, 114–122. Schaefer, C. (1990). Night waking and temperament in early childhood. Psychol. Rep. 67, 192–194. Scher, A. (2008). Maternal separation anxiety as a regulator of infants’ sleep. J. Child Psychol. Psychiatry 49, 618–625. Scher, A., and Asher, R. (2004). Is attachment security relate to sleep-wake regulation? Mothers’ reports and objective sleep recordings. Infant Behav. Dev. 27, 288–302. Scher, A., and Blumberg, O. (1999). Night waking among 1-year olds: A study of maternal separation anxiety. Child Care Health Dev. 25, 323–334.



Scher, A., Tirosh, E., Jaffe, M., Rubin, L., Sadeh, A., and Lavie, P. (1995). Sleep patterns of infants and young children in Israel. Int. J. Behav. Dev. 18, 701–711. Scher, A., Tirosh, E., and Lavie, P. (1998). The relationship between sleep and temperament revisited: Evidence for 12-month olds: A research note. J. Child Psychol. Psychiatry 39(5), 785–788. Schwichtenberg, A. J., and Poehlmann, J. (2009). A transactional model of sleep-wake regulation in infants born preterm or low birthweight. J. Pediatr. Psychol. 34, 837–849. Scott, G., and Richards, M. (1990). Night waking in one-year-old children in England. Child Care Health Dev. 16, 283–302. Shang, C., Gau, S., and Soong, W. (2006). Association between childhood sleep problems and perinatal factors, parental mental distress and behavior problems. J. Sleep Res. 15, 63–73. Snyder, D., Goodlin-Jones, B., Pionk, M., and Stein, M. (2008). Inconsolable night-time awakenings: Beyond night terrors. J. Dev. Behav. Pediatr. 29, 311–314. St James-Roberts, I., Alvarez, M., Csipke, E., Abramsky, T., Goodwin, J., and Sorgenfrei, E. (2006). Infant crying and sleeping in London, Copenhagen and when parents adopt a “proximal” form of care. Pediatrics 117, 1146–1155. St James-Roberts, I., and Plewis, I. (1996). Individual differences, daily fluctuations, and develop­ mental changes in amounts of infant waking, fussing, crying, feeding, and sleeping. Child Dev. 67, 2527–2540. Stifter, C., Willoughby, M., and Towe-Goodman, N. (2008). Agree or agree to disagree? Assessing the convergence between parents and observers on infant temperament. Infant Child Dev. 17, 407–426. Stoleru, S., Nottelmann, E., Belmont, B., and Tonsaville, D. (1997). Sleep problems in children of affectively ill mothers. J. Child Psychol. Psychiatry 38, 831–841. Taylor, N., Donovan, W., and Leavitt, L. (2008). Consistency in infant sleeping arrangements and mother-infant interaction. Infant Ment. Health J. 29, 77–94. Thunstrom, M. (1999). Severe sleep problems among infants in a normal population in Sweden: Prevalence, severity and correlates. Acta Paediatr. 88, 1356–1363. Tikotzky, L., and Sadeh, A. (2010). Maternal sleep-related cognitions and infant sleep: A longitudinal study from pregnancy through the 1st year. Child Dev. 80, 860–874. Tikotzky, L., Sadeh, A., and Glickman-Gavrieli, T. (2010). Infant sleep and parental involvement in infant caregiving during the first 6 months of life. J. Pediatr. Psychol. [Epub ahead of print] PMID: 20444853. Van Tassel, E. (1985). The relative influence of child and environmental characteristics on sleep disturbances in the first and second years of life. J. Dev. Behav. Pediatr. 6, 81–85. Wolf, A., and Lozoff, B. (1989). Object attachment, thumbsucking and passage to sleep. J. Am. Acad. Child Adolesc. Psychiatry 28, 287–292. Wolke, D., Meyer, R., Ohrt, B., and Riegel, K. (1995). The incidence of sleeping problems in preterm and fullterm infants discharged from neonatal special care units: An epidemiological longitudinal study. J. Child Psychol. Psychiatry 36, 203–223. Zuckerman, B., Stevenson, J., and Bailey, V. (1987). Sleep problems in early childhood: Continuities, predictive factors, and behavioral correlates. Pediatrics 80, 664–671.


Douglas E. Moul Sleep Disorders Center, Neurological Institute, Cleveland Clinic, Cleveland OH 44195; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA

I. Chronic Insomnia: Syndromes of Pathological Awakenings A. Clinical Context B. Classification of “Pure” Insomnias C. Limitation of Explanatory Ambitions for the Defined Syndromes of Chronic Insomnia II. Background Conceptual Features of Analysis of Realities About Sleep A. Ambiguity of “Awakening” and “Sleep” in Ordinary English B. Mereological Ambiguities of the Term “Sleep State” C. Process S and Process C as Empirically Necessary but Contradictory Explanatory Principles for Understanding Sleep Regulation D. Necessary Inter-Level Theoretical Vaguenesses and Incommensurate Temporalizations E. Other Temporalizations Relevant to Understanding Chronic Insomnia Patients F. The Mnemonic and Integrative Duties of Sleep III. The Spielman three-factor High-Level Model of Insomnia and Mid-Level Therapeutic The­ ories of Insomnia Therapies A. The Spielman Model: Implications for Cognitive Behavioral Therapists B. Nonignorable Psychologically Based Mid-Level Theories IV. Cautions About Conceptual Transitions to the Theory Level of Neuronal Processes V. An Aristotelian Method of Review A. Correlation with Spielman Factors B. Problems Emerging from Relating Theories from Different Conceptual Levels C. Substantial Causes (i.e., Substances) D. Formal Causes (i.e., Structures) E. Efficient Causes (i.e., Processes, Contemporarily Understood “Causes”) F. Telic Causes (Telos, Final Causes, Limit Cycles, Outcomes, Goals, and Needs) VI. Conclusion References

Limit cycle-based mid-level theories that rationalize effective clinical treat­ ments for chronic insomnia have empirical support from whole-organism studies of sleep physiology, but their relation to network-level and cellular neurobiologies remains obscure. The neurobiology of pharmacological treatments for insomnia has been increasingly understood, but has not been fully integrated with INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 93 DOI: 10.1016/S0074-7742(10)93009-2


Copyright 2010, Elsevier Inc. All rights reserved. 0074-7742/10 $35.00



psychological theories or electroencephalographic descriptions of sleep. Better clinical diagnostic and treatment frameworks will require both greater conceptual clarity as to what an “awakening” is descriptively and detailed investigations to relate fundamental neuroscience to clinical technologies can be both accessible and diagnostically useful to clinicians. Out, damned spot! Out, I say! One - two - why then ‘tis time to do’t. Hell is murky. ––Lady Macbeth The clinical topic of awakenings is indeed murky. For many chronic insomnia patients, awakenings are hellish. Awakening can give rise to an impulse to take some actions to address being awake. When such actions fail, their failure may occasion self-loathing, amplifying the awakening further. Stress about awakening may cause further despair and further wakefulness. Actions to end wakefulness yield then only more wakefulness.

I. Chronic Insomnia: Syndromes of Pathological Awakenings

A. CLINICAL CONTEXT Chronic insomnia is quite common (Ohayon, 2002). If without another clinically identifiable cause, it is called primary insomnia. Primary insomnia is thought to affect 6% of the general population. Women harbor chronic insomnia twice as much as men and have major depression and anxiety disorders twice as frequently as well (Balter and Uhlenhuth, 1992; Robins and Regier, 1991; Taylor et al., 2005). Comorbid forms of insomnia, as associated with affective, anxiety, and other disorders, affect an additional 10–20% of the general population. Often insomnia persists for long periods of time (Buysse et al., 2008a). Some evidence (Breslau et al., 1996; Chang et al., 1997; Ford and Kamerow, 1989) suggests that chronic insomnia is a longer-term risk factor for major depression. Chronic insomnia is associated with older age, female gender, low socioeconomic status, and medical comorbidity. Insomnia is a potential co-occurring symptom in many mental and somatic disorders. This fact places a premium on understanding the pathophysiology of primary insomnia, an “only insomnia” disorder, since in all other disorders, the potential exists that insomnia has syndrome-specific features that could confound one’s understanding of awakenings or arousals.






From the electroencephalographic (EEG) perspective, awakenings considered as such are not pathological by themselves. From an evolutionary perspective, nocturnal awakenings may have been functionally important for insuring that the sleeper will have sufficient awareness during the night to monitor for nocturnal threats (e.g., predators), or simply to avoid going into coma (Halasz et al., 2004). Insomnia researchers who consider awakenings from an EEG perspective might try to generalize awakenings as difficulties either with getting to sleep (initially, or if awakened) or with waking up too much. Yet awakenings are common in noncom­ plaining sleepers. Some are culturally or seasonally normative. So what is the “damn spot” here? Are awakenings pathological even if people may not know they are having them? Are only certain kinds of awakenings pathological, or are awakenings just false groundings for other heterogeneous psychological complaints? Insomnias have sometimes been subclassified by whether the patient suffers from a difficulty falling asleep (DFA), difficulty maintaining sleep (DMA), or early morning arousal (EMA), with some notion that DFA may suggest an anxiety diathesis, whereas EMA an endogenous depressed one. However, evidence (Hohagen et al., 1994) has indicated that insomnias do not breed true over time: A person may switch between DFA, DMA, and EMA over time or in various combinations. Diagnostic conventions take awakenings seriously (and not merely as epiphe­ nomena of other underlying conditions) in the construction of scientific and nosological approaches to studying insomnia and awakenings, by considering time-based metrics of sleep and of awakenings in diagnostic definitions despite DFA, DMA, and EMA being unstable subtypes. The DSM-IV generic definition of chronic insomnias (American Psychiatric Association. Task Force on DSM-IV, 2000) includes (1) “The predominant com­ plaint is difficulty initiating or maintaining sleep, or non-restorative sleep, for at least 1 month,” and (2) “The sleep disturbance (or associated daytime fatigue) causes clinically significant distress or impairment in social, occupational, or other important areas of functioning,” with the proviso that the complaint is not best described by another sleep disorder. Note that in this definition sleep variations and poor sleep quality considered unto themselves are necessary, but not sufficient, criteria for claims of sleep pathologies or of pathological awakenings. To meet this and related defini­ tions of chronic insomnia, daytime pathological consequences are also required. But even daytime effects are not enough either: The patient must actually complain. So there is an implied speech act (Searle, 1969) requirement in the definition. Indeed, there is no reason to suppose that there are not persons who awaken at night and have daytime consequences, but who do not complain. In other words, the present psychiatric definition of a pure “disorder of awakenings” is based upon a person’s recall about a sleep period’s characteristics as related to a causal interpretation he/she may have upon an assessment of his/her daytime functioning and additional ability



or willingness to make these assessments known to a clinician. When comorbid conditions (e.g., depression, stress) are present, one’s ability to relate any possible awakenings directly back to neurobiological explanations becomes murkier. The International Classification of Sleep Disorders (American Academy of Sleep Medicine, 2005) defines insomnia similarly to the DSM-IV; however, its definition also specifies that there be adequate opportunity and circ*mstances for sleep (to distinguish it from sleep restriction), and there be at least one of the daytime consequences: fatigue or malaise; attention, concentration, or memory impairment; social or vocational dysfunction or poor school performance; mood disturbance or irritability, daytime sleepiness (taken to be generally more subjectively experienced than objectively demonstrated); motivation, energy, or initiative reduction; proneness for errors or accidents at work or while driving; tension, headaches, or gastrointestinal symptoms in response to sleep loss; and concerns or worries about sleep. The ICD-10 (World Health Organization, 2007) definition of nonorganic insomnia stipulates clinical features of (1) DFA, maintaining sleep, or poor sleep quality; (2) sleep disturbance at least 3 times per week for at least 1 month; (3) patient’s preoccupation with sleeplessness and excessive concern over its conse­ quences at night and during the day; and (4) the unsatisfactory quantity and/or quality of sleep either causes marked distress or interferes with ordinary activities in daily living. Insomnia may or may not occur with comorbid conditions.




From the perspective of polysomnogram (PSG) recordings in good sleepers, the insomnia complaint can be framed in relation to sleep architectures of initial and middle insomnia, in which the inability to go to sleep can be observed on the PSG. The traditional (Rechtschaffen and Kales, 1968) and recently updated (Iber et al., 2007) approaches to analyzing sleep both utilize fixed-length epochs in scoring sleep. This places awakenings under the hegemony of the fixed-epoch conception as a “Truth” to which self-reports can be compared. Such approaches have led to doubts about the validity of self-reported accounts about sleeping. However, extolling such validity problems begs the question about the validity of the fixed-epoch approach to measurement, particularly if awakening is considered to be a process. When is an awakening considered as a process true or false? It is not clear. The nosological measurement problem concerning the validity of awakenings can be illustrated by attempts to measure the sleep onset process (SOP) in small epochs. In the experimental approach, the SOP is investigated from a starting point of research subjects’ being definitely awake. Using a fixed, small epoch approach for classifying small sleep epochs during the SOP, Hori and colleagues



(1994; Tanaka et al., 1996) constructed a labor-intensive method for classifying intermediate epoch types during the SOP. However, it is not clear how such an intensive system could be easily implemented in clinical research studies, or be at all practicable for everyday clinical work. A similar-spirited attempt at classifying small epochs was put forward by Moul and colleagues (2007a), but while this is a simpler approach, it nonetheless faces similar criticisms. By contrast, as regards the awakening process, added difficulties follow from various sleep stages becom­ ing the process starting points into awakenings of various kinds. It will be difficult for awakening onset process (AOP) researchers to stipulate the temporal location for the start of an awakening process amidst manifold sleep processes. The dimensioning of time is a key experimental conundrum. The limited available literature on the EEG-based SOP studies on primary insomnia has produced a variety of approaches of dealing with time. Perusal of Table I illustrates various attempts. Some investigators have tried to look at the problem as one of shortening the epoch size (Lamarche and Ogilvie, 1997; Merica and Gaillard, 1992; Merica et al., 1998; Moul et al., 2007a; Staner et al., 2003), if only to perform artifact rejection (Marzano et al., 2008). Others have utilized relativized time (Lamarche and Ogilvie, 1997; Staner et al., 2003), in relation to starting points and endpoints, and framing the analysis according to percentage of clock time elapsed. Others (Bonato, 1997; Buysse et al., 2008b; Perlis et al., 2001) have looked at the frequency distributions or wave forms present during an initial sleep period to give some data about relative speed to which sleep becomes deep. The various epoch­ series studies (Bonato, 1997; Freedman, 1986; Jacobs et al., 1993; Lamarche and Ogilvie, 1997; Marzano et al., 2008; Merica and Gaillard, 1992; Merica et al., 1998; Moul et al., 2007a; Staner et al., 2003) point to the SOP differing between insomnia patients and controls, but specific findings differ across studies. The prospects for generalizability in this SOP domain already look dim; those for the AOP domain will be yet more problematic. Review of these various efforts points to an additional discouraging metho­ dological insight. To test subject-group contrasts statistically imposes the con­ straint that only outcome variables (as determinate nominal, ordinal, or continuous values) can be utilized, not processes as processes. Statistical analysis cannot utilize process data streams irrespective of temporal startpoints, cutpoints, or endpoints, if and when time is treated as a latent variable. Time can only be modeled and never be measured as a real intensive phenomena (e.g., like temperature). The nature of the neurological processes about which clinical interventions are constructed will likely elude the methodological requirement for “outcoming” these neuronal processes. This statistical intractability of pro­ cesses will make it difficult to validate statistical generalities about subject-group differences in processes or sleep state transitions. The fixed-epoch-size approach to measurement has statistically afforded making some attempts at group comparisons; however, these comparisons may

Table I



Freedman (1986)

SOI Ctrl 1M, 11F; 31.8 4M, 8F; 27.8

PPI Ctrl Merica and Gaillard (1992) CL Ctrl Merica et al. (1998)

Gender; mean age


Sleep onset definition

Time metric (zero =)

Age group

Stage 1

Sleep stage (GNT)

5M, 7F; 35.911M, 17F; 30.0

Age group

Stage 1

8M; 12F; 30.2 9M; 10F; 25.3

Age group

NREM onset without prior wake Stage 1

Jacobs et al. (1993)

SOI Ctrl 5M, 7F; 37.8 Age group 5M, 9F; 36.9

Lamarche and Ogilvie (1997)

PPI PDS 3M, 3F; 27.8 Age group Ctrl 3M, 3F; 31.5 6M, 9F; 27.8

First 5 min of stage 2


Data analysis




Delta onsets in PI versus controls

First nonIncreased 1 Hz artifact power awake minute of with eyes each sleep closed stage Real (SO) Digitally filtered Slower increase 10 s with with later smoothing lower power in NREM Percentile NREM FFT Slower increase of means of four in delta (and NREM 4-s epochs theta) episode (SO) 5-min FFTs: 5-min Not reported wake vs awake/eyes stage 1 shut and (SO) stage 1 Quartiles Mean 14-s FFT No increase in and absolute first 3 min sleep powers quartiles; stages binned by overall slower (GNT) ordinal time increase

Beta onsets in PI versus controls

Other in PI versus controls

Higher beta in wake with eyes open and stage 1

Decreased alpha in awake eyes closed

Hard to show slower decrease

Higher beta/ delta ratio instability

Same initial decrease yet higher in NREM

Lower power in bands slower than beta

Higher presleep waking with eyes closed

Reduction in beta with behavioral treatment Low baseline and no change in alpha at all by quartile

Highest during wake stage; no overall group effect by quartile

(continued )

Bonato (1997)

Staner et al. (2003)

PPI Ctrl

6M; 9F; 34.0 Age and sex First Sleep all rightilndividual 15 min stage handed of (GNT) 6M, 9F; stage 2 34.1 PI MDD 11M, 7F; Age and sex First 30-s. Ordinal Ctrl 40.5 11M, group epoch of (GNT); 10F; 46.5 stage 2 real 11M, 10F; (SO) 44.3

Moul et al. PI Ctrl (2007)

Marzano et al. (2008)

PdI Ctrl

5M, 6 F; 45.3 Age and sex Both stage Real (SO) 5M, 6F; individual 1 and 44.8 stage 2 (1-min epochs) 4M, 6 F; 30.0 Age and sex First 20-s Real (SO) 4M, 6F; epoch of 30.2 stage 2

Stage-wise period amplitude

Less half wave; less full and half wave in stages 1–2

More full wave and first derivative in stage 2

Medians of 2-s FFTs at quantiles by each minute

No delayed increase

No beta (13–21.5 Hz) change from low baseline with ordinal time Delayed power decrease

4-s epoch visual Delayed power score and increase in FFT relative power modeling 4-s epoch FFT No differences; 5 min prepost both had SO anterior-toposterior progress

More alpha full wave in stage 1 and half wave overall Alpha decrease no different

Other power bands not informative

Higher beta in Lower sigma in PdI, also in Cz anterior sites on second night

CI, Chronic insomnia; Ctrl, control; Def’n, definition; Dx, diagnoses; FFT, fast Fourier transform; GNT, good night time (lights out); MDD, major depressive disorder; PdI, paradoxical insomnia; PDS, psychiatric disorders; PI, primary insomnia; PPI, psychophysiological insomnia; SO, sleep onset; SOI, sleep onset insomnia



be temporal distortions of underlying sleep and wakening processes. Utilizing one standard time metric, or even just a fixed time-epoch measurement scheme, is a metaphysical choice, and possibly out of tune with underlying neuronal reality. Researchers of the SOP have yet to decide on the metaphysical “correct” temporal measurement perspective, even when starting the analysis from wake­ fulness. Researchers studying awakening processes face a worse metaphysical quagmire. So group-comparison generalizability showing differences between normal sleepers and poor sleepers is currently only a wish. The absence of plausible supporting neurobiological theory about group-level neuronal process differences (to guide the construction of a plausible statistical approach) makes general conclusions inappropriate. And even if statistically appropriate methods for treating processes could be established, there still remain serious concerns (Buysse et al., 1994) about misclassification biases affecting sleep disorder diag­ noses. With all this considered, proposing specific between-group generalities now would have high liability to making false claims to knowledge. Marzano and colleagues (2008) are correct to insist that drug effects be absent in the research subjects, if the bases for the SOP and awakening abnormalities are to be known in unmedicated subjects. But most patients come with the prior drug exposures. So it will be difficult to know how studies on drug-naı¨ ve patients would be generalizable to most patients.

II. Background Conceptual Features of Analysis of Realities About Sleep








Understanding “awakening” as a temporal word is a key issue. Like other temporal aspect words (Vendler, 2005) that allow flexibility in temporal refer­ ence, “awakening” is capable of being interpreted either as a process in which the endstate of being awake is not yet fully attained (e.g., as an activity now-moving toward getting awake), or as the endstate itself (e.g., the “being awake”). The former connotes a process-toward-waking with the outcome left unspecified, or elided. This permits the application of adjectives like “partial” or “failed” to some incomplete awakening event trains like that which occur in sleepwalking, or another parasomnia. Parasomnias are described as “partial awakenings” as a way of describing these ambiguous, in-between, brain “states.” Additionally, there are prepotent awakenings as well, as exemplified by awakening specifically to one’s child’s crying at night, made possible by a selective vigilance maintained during sleep. The K-complex itself is a well-known example of this diathesis. Other modes of intentional agency over the process of awakening also obtain.



Latent intensional states (e.g., depression, anxiety), servicing as quasi-agencies, are said to harass deep sleep or sleep continuity. Such quasi-agential explanatory treatment of awakenings, as partial or intentional, loosens up possibilities of attributing awakenings’ causation(s) to temporally distant conscious intentions, processes, or states occurring during the daytime, and conversely, with awaken­ ings causing daytime disturbances. On the other hand, “awakening” can refer to the endstate of the arousing process from some state of sleep: One underwent a now-past arousing process, but now has arrived at being awake. In this usage, the endstate is the main conceptual focus, not the antecedent process, nor the antecedent state. The simple fact of an “awakening” means one was previously asleep, but gives no specifics about the previous kind of sleep or previous process(es). Taking “awakening” in this way treats awakening as an accomplishment, like winning a race. A sleep endstate is a complex entity, defined by the presence of several cotem­ poraneous values of intensive variables typical of that modeled state. It is a beha­ vioral state heralded by relative behavioral quiescence, postural recumbency, and reduced responsivity to environmental stimuli. The normative wake state, by con­ trast, is evidenced by a state of discriminative awareness, quick responsivity to environmental stimuli, and fluid, self-monitored enactment of complex behaviors. For many practical life problems, distinguishing between these sleep and wake states so defined has worked very well. But perhaps sleep and wake have been too obvious (few critical cross-cultural linguistic studies of sleep and wakefulness have been done). Perhaps sleep and wake are dogmatic constructs. Pathologically “awakening” could have been legislated free of its “partial” aspects in some discussions, in the service of some doctrinal mind–body (i.e., wake–sleep) dualism. In such a dualism, sleep and wake could then be seen as having stigmatized forms. Patients with such forms of experience would be subject to interpersonal stigmatization or self-stigma­ tization. From focus groups we have learned that this stigmatization is a real risk that patients have faced (Carey et al., 2005). But happily, one finds that “sleep,” “wake,” and other sleep/wake-related words at best refer to obscure accomplish­ ments even in good sleepers.




In biological descriptions, “state” language cannot be taken literally. Organisms as alive are outcome-less processes in dynamic equilibria. Live organisms are not outcomed, dead, thermodynamic equilibria. But it is permissible to say organisms are in “dynamic states” if this phrase is understood as a figure of speech. At the neural level, the contradictory term “dynamic state” means that neurons express ongoing discharge patterns during both wake and sleep. These



processes exist as dynamic equilibria conformable to Onsager equations (Katch­ alsky and Curran, 1965), but not as static chemical equilibria. Accordingly, “behavioral sleep state” refers to molar, “whole-organism” behavioral variables that seem grossly constant; while, in contrast, “neuronal sleep state” refers indirectly to fluctuating EEG waveforms. Awakening and sleeping, then, considered as idealized endstates according to a conventionalized ontology derived from phenomenal rules of classification, are not states when the analysis shifts to ontologies that involve discussions of the voltage behavior of neurons. Stipulating this conceptual antinomy is necessary to relate sleep states to the real-time behavior of dynamic neural networks without the risk of sophom*oric contradictions. However, ranging across the ontological domains of gross behavioral descriptions down through genetic determinants of awakenings, such a discussion does unmask metaphysical contrasts. The different levels of causal analysis of awakenings invoke plural ontologies at different levels of description that require mereological vagueness in their interrelating, and also invoke plural temporalities that might arguably be mutually inconsistent. So it is important to recognize “awakenings” not only as having many common-lan­ guage usages, but also that various theories related to awakenings will have different state and process commitments that will be mutually incommensurable. When such incommensurate commitments arise, attempts at forming broader understandings will demand the use of “hand-waving” mereological treatments, so that there can be partially coherently relationships set up between the “parts” of the temporalized process-state coagulum to the “whole” of the explanandum. (Whether to consider light as a wave or as a particle is a familiar example of the part-to-whole problems in theories.) The two-process model of sleep regulation (Borbely, 1982, 2009) is a central example of a framework in which such metaphysical awareness plays a role in one’s ability to comprehend sleep/wake regulation.

C. PROCESS S AND PROCESS C AS EMPIRICALLY NECESSARY BUT CONTRADICTORY EXPLANATORY PRINCIPLES FOR UNDERSTANDING SLEEP REGULATION Process C and Process S have been elaborately verified. Process C refers to the Circadian timing of sleep propensity. Process S refers to the homeostatic regulation of Sleep that builds up from periods of unbroken wakefulness. These processes are described elsewhere in this volume, along with the nuclei and biology that supports them. Process C invokes an image of circular time, while Process S invokes that of a linear, Newtonian time. These two juxtaposed molar processes and their anatomic seats illustrate well the need for metaphysical awareness when teaching patients about their sleep problems. It is hard to



imagine giving scientifically grounded advice about sleep problems without reference to them. The model invokes these process principles as hegemonic forces, but not as the totalized set of forces governing sleep. Such forces can be modified (Borbely, 2009) or overridden at times. Some investigators propose an additional process force of generalized hyperarousal at work in chronic insomnia patients, partially counteracting Processes C and S. So to relate these processes together in one unitary explanation, vague­ nesses of references to physiological forces are presumed, and artfulness at melding fundamentally incommensurable temporalities is required. An under­ standable metaphysical framework of discussion is needed, so that the clinician and the patient can both form an understanding of why the clinician is prescrib­ ing specific treatments.

D. NECESSARY INTER-LEVEL THEORETICAL VAGUENESSES AND INCOMMENSURATE TEMPORALIZATIONS With available clinico-pathological correlations between nuclei and physio­ logical functions, constructing an integrated understanding of Process S and Process C now requires the relation of two ontologies, one referencing particular neurons and neuronal subparts, to another referencing abstract principles/ forces that can be discussed with patients. However, the part-to-whole relation­ ships between the neurons’ behaviors and the whole-person functions involve vaguenesses, if only because of the need to address other physiological proces­ ses—possibly a disposition to vaguely referenced hyperarousal at this theoretical level—as well as the influence of random situational influences over sleep and wake. Similarly, how time is treated in this explanation requires some tolerance for side-by-side temporalizations. Process S connotes a conception of time as similar to linear clock time, according to the linear buildup of sleep pressure as the continuous time duration awake increases. This evokes a quasi-Newtonian con­ ception of time, as if time were a reified dimension existing without ambiguity across the universe. The Newtonian conception is consistent with the McTaggart B-series (McTaggart, 1993), which involves placing events in linear relations of before and after, from past to future, without repetition. By contrast, Process S connotes time as circular. While some anti-Kantians (Le Poidevin, 2003) abjure the possibility of circular time, circular time is a metaphysically necessary biolo­ gical reality. (Biological process–event identities deflate the presumed necessity of place–time identities of atomic states.) So within the two-process model are two conceptions of time that are mutually incommensurable, yet required, in the understanding of sleep propensity and awakenings.



E. OTHER TEMPORALIZATIONS RELEVANT TO UNDERSTANDING CHRONIC INSOMNIA PATIENTS Not included in the two-process explanation is the McTaggart A-series of ordered past, present, and future. This is the “tensed” version of temporality. This more psychological kind of time assumes that a healthy person places herself into a fluidly complex, self-referencing temporal context. Despite claims to the unreality of tense (Mellor, 1993), most patients will implicitly think of their symptoms in relation to tense, rather than in a “clocktimed” way as autistic patients are wont to do (Boucher, 2001) Consistent with this notion, item-response theory analysis of the 65-item Pittsburgh Insomnia Rating Scale items has suggested (Moul et al., 2007b) that items querying the clocktimes of nocturnal events are not as important to patients in the grading of insomnia severity as are tensed items that ask about sleep quality and daytime fatigue. As the nosological definitions of chronic insomnia require, patients’ accounts about their awakening symptoms will bring into view their other temporalities that bear on their organization of narratives (Ricœur, 1984), grammars of role structures (ter Meulen, 1995), and resulting disabilities (Leger et al., 2002). Such accounts will also be subject to various modifications arising from neurobiological constraints on time-referencing memory functions, compromising the literal truth value of any symptom account. So the clinician’s additional task will be to relate patients’ verbal accounts about awakening events, as they are experienced and reported, to a more general, science-based account of sleep and wakefulness. In order to motivate patients to comply with treatments, the clinician needs to be able to invent artful, individualized metaphysical treatments of patients’ complex tensed understandings in order to engage them with underpinning mid-level and neurobiological principles that rationalize clinical interventions. Patients need to be understood and engaged metaphysically if pathological awakenings are to be addressed and treated.






Sleep has a duty to assist memory functions. During sleep, memory traces are strengthened, synapses pruned, and experiences integrated at the neuronal level (Walker, 2009). Sleep serves the hegemonic force of memory consolidation and integration. But unlike the account for whole-brain processes, memory processes during sleep are local and specific to brain areas that were active during a prior wakeful­ ness. At the EEG level, this is noted by local/regional changes in neuronal



discharges during non-rapid eye movement (NREM) sleep (Hanlon et al., 2009) (yet another form of “partial awakening”?). Memory processing involves EEG dis­ charges in the gamma frequency band, surprisingly observed during NREM sleep (Destexhe et al., 2007; Steriade and McCarley, 2005). Such gamma band discharges are typical of wakefulness and neuronal “activation”, but during NREM sleep can occur on top of a slow oscillation typical of NREM sleep (Le Van Quyen et al., 2010). So the “day” jumps into the “night” during NREM sleep, both figuratively and literally. And since narrative dreams mostly occur during REM sleep, traumatic nightmares that replay past psychological traumas are also evi­ dence for the natural “wake-like” processes of neuronal memory processing during REM sleep. The success of nightmare therapy in treating nightmares (Krakow et al., 2001) is coherent with this general notion. Apparently sleep makes the consolidation and integration of memories more efficient, but locally to particular brain regions. Given each night’s specific local neuronal “activations,” sleep is never abso­ lutely self-identical from night to night, or moment to moment; Mutatis mutandis, neither are awakenings. During each night’s sleep, the presentist and localist neural activations tending toward awakenings in normal memory processing play along the nonlocal, network-wide sleep-propensity waveguides of Processes S and C. And so memory functioning complicates sleep metaphysics yet further. For the purposes of effectively classifying and treating chronic insomnias, a key problem will become that of deciding what rules of relative identity and of boundary conditions should apply to candidate awakening events, despite the gamma-band “micro-awakenings,” and other fast activities, associated with nocturnal memory management.

III. The Spielman three-factor High-Level Model of Insomnia and Mid-Level Therapeutic Theories of Insomnia Therapies

A. THE SPIELMAN MODEL: IMPLICATIONS FOR COGNITIVE BEHAVIORAL THERAPISTS One relatively successful attempt at finding a whole-person metaphysical systematization of causes of insomnia in chronic insomnia patients is Spielman’s 3-factor model (Spielman et al., 1987a). It is a metaphysical framework because these factors are classes of causes, rather than actual causes. Actual causes group together into these classes in this general stress-diathesis framework (Perlis et al., 2005). The three factors are predisposing factors, precipitating factors, and perpetuating factors. Predisposing factors include a person’s genetic and epigenetic makeup, but Spielman also includes general factors such as psychological temperament.



Temperament would be seen as a general and more remote causal influence over chronic insomnia. Being female might be an example. Other predisposing causes might be longer-term processes shaping probabilities for insomnia over many years, but be elided in some explanations. Their effects might be considered only as developmental, socialization, or allostatic backgrounds. Preexisting psychiatric disorders such as previous posttraumatic stress disorder (PTSD), mood or anxiety disorders, or psychotic conditions are clearly predisposing. A person’s lifetime allostatic load of past nonpsychiatric stressors (Bliwise, 2005) might also be included among the predisposing factors, along with situations of emotional strain (e.g., being a caregiver, having a troubled work life, being in adverse socio­ economic circ*mstances). Whether a cause is predisposing or precipitating may amount to the choice of time period thought to be relevant for the particular explanation. Precipitating factors include the proximal causes of insomnia getting started. They include concretely experienced life events (e.g., significant losses, antici­ pated threats, excitements, pain, etc.). Most precipitating factors cannot be addressed clinically because by the time a clinician is consulted, they have already had their effects. So they are comparatively irrelevant as factors to be addressed or treated. Perpetuating factors are the sleep clinician’s focus. The wise clinician does not try to stamp out all isolated nights of poor sleep and awakenings, but rather, to treat those causes that serve to keep insomnia going from night to night to night (Spielman et al., 1987a). Perpetuating factors in essence invoke a temporal circularity of causes, i.e., limit cycles, which serve to keep the patient in a selfsustaining do-loop of insomnia and reactive counterresponding. The limit cycle has a telic attractor of chronic insomnia directed at “its” own self-perpetuation. Lady Macbeth’s limit cycle of worry and self-accusation is a related literary example. The clinical goal is to break up the perpetuating limit cycle, to allow other, healthier forces (i.e., Processes S and C) to be the major influences over sleep and wakefulness.

B. NONIGNORABLE PSYCHOLOGICALLY BASED MID-LEVEL THEORIES 1. Discriminate Stimuli as Leading to Awakenings Consistent with Spielman’s conceptual framework, mid-level theorists have proposed ways in which chronic insomnia patients get stuck in the chronic insomnia limit cycle. Bootzin (1972; Bootzin and Perlis, 1992) proposed a stimu­ lus control therapy model, based upon principles of conditioning, in which arousal responses are cued by stimuli associated with the bed or the bedroom. In this scenario, the chronic insomnia patient gets stuck trying to sleep in bed



while awakening due to the somatic and other arousal habits cued by being in the bed. His treatment model of only allowing sleep and sex in bed is one of the most effective for chronic insomnia (Morgenthaler et al., 2006), even though its neu­ robiological mechanisms have not been confirmed experimentally (and may never be, since the stimulus–response linkages may be person specific). Spielman himself proposed sleep restriction therapy (Spielman et al., 1987b), in which a patient’s time in bed (TIB) is reduced even to the point of causing some sleep deprivation (in essence, squeezing out awakenings). By restricting TIB, the patient is placed into a regimen where sleep deprivation may override a variety of mechanisms perpetuating the insomnia, among them stimulus control limit cycling, but also others.

2. Limit-Cycling Cognitions Affecting Sleep Other theorists have focused on 24-h limit cycles. Morin’s systematized cognitive behavioral approach (Morin, 1993; Morin and Espie, 2003) focuses on the way that many insomnia patients’ cognitive distortions about sleeping lead to mental overactivation about poor sleeping that then leads to poor sleep, and further continued insomnia. This effective (Morgenthaler et al., 2006) therapy targets changing the distorted cognitions. Harvey (2002) has extended the cognitive behavioral conception further by a discussion of the psychology of safety behaviors (i.e., actions taken to ensure against the feared consequences) that insomnia patients employ. These behaviors ironically set up limit cycles of insomnia. For example, one “defensive” safety behavior is often to go to bed early, in the hope that giving oneself more TIB would permit sleep. But doing this only runs in the face of the forbidden zone of sleep (Lavie, 1986) that occurs in the early evening. Trying to sleep during this “forbidden” time only causes frustration, mental activation, and further insom­ nia. Her model encourages patients to de-cycle these effects by learning more about sleep, and by disconfirming their own theories for themselves through supervised behavioral experiments.

3. Sleep Behaviors and Cognitions Follow Operant Principles of Reinforcement For mid-level theorists, perpetuating factors are limit cycles, the “goals” of the pathological processes. Operant principles of conditioning are part of the psy­ chological mechanics of these limit cycles, particularly in reference to how extinction bursting “protects” the pathological limit cycle. There is commonly an extinction response burst increasing the to-be-extinguished behavior(s) just after non-reinforcement is imposed on an old habit and before the old frequency of responding decreases (Kearney, 2008; Lerman and Iwata, 1995). It is as if the



old habit will “fight to survive.” This tendency gives rise to a behavioral inertia to keep an old habit when trying to change it. A key insight is that habits can be not only in behaviors, but also in feelings and thoughts. The limit cycle of habits leading to awakenings are no exception, so that awakenings can get worse before they get better, as one is breaking a habit of awakening. To get better from insomnia, a patient must get past the extinction barrier “put up” by the old habit. The sleep restriction approach nicely enhances the homeostatic drive to sleep (Process S) for a period imposed long enough to get past the habit barrier, overwhelming cognitive or other habit factors that have set up separate persisting limit cycles. But for other cycle-breaking interventions, patience and persistence are required. Alternatively, habit substitution may work. Side effects from extinc­ tion bursting can be fewer if additional treatments are included (Lerman et al., 1999). The method of paradoxical intention has the patient try the habit of staying just barely awake, instead of trying hard to go to sleep, so as to break the paradox (i.e., limit cycle) of having the high effortfulness toward sleep cause general bedtime arousal and awakening. Espie (Espie et al., 2006) has described a pattern in many insomnia patients in which the active intention to sleep is the paradoxical roadblock to sleeping. Intentions can be habits, too. Alas, insomnia is often not about sleep deprivation as such as it is about breaking weird limitcycles, when the insomnia is not due to brain trauma, toxicities, or neurodegen­ erative changes. 4. Mid-Level Theory Dependencies on the Notion of “ Hyperarousal” The forms of limit cycles are often felt to be insufficient by themselves as explanations, as some theorists want there to be a motive force that “turns the cranks” of the limit cycles. This often is “hyperarousal,” a word that provides political cover against the encroachments of reductionism. Some controlled comparisons of insomnia patients against matched controls have supported the conclusion that insomnia patients have more whole-body metabolic activity across 24 h (Bonnet and Arand, 1995) and brain glucose update during NREM sleep (Nofzinger et al., 2004), lending support to the idea of “hyperarousal.” While being cast as a force, this hyperaroused disposition is also thought of as an endstate to be changed so as to improve sleep. Riemann and colleagues (2010) provide a recent review of evidence for the hyperarousal literature. While hyperarousal theory may be now popular, the relationship between this dispositional “hyperaroused” endstate and the individual nighttime awaken­ ings is obscure, both because the ontological status of the one endstate to the other is not clarified experimentally and because the mereological relation between the 24-h circular conception of temporality and the linear temporality of the nighttime awakenings is unaddressed. To address the various proposed



mid-level theories without vague appeals to hyperarousal, the decomposition of their temporal cycles into their component linearly temporalized parts will be necessary, as will the determinate references to physiological processes. (This has been done in a limited way for the linear processes within the transcription–translation limit cycle of the SCN in relation to the circadian limit cycle—see elsewhere, this volume.) To address the predictions of mid-level theories, experimental methods will be needed to confirm or test how the particular neurobiologies of stimulus–response pairings, semantic functions, fron­ tal executive functions, etc., are connected in one or more temporal linearity(ies) in series to explain the one or more causal–temporal circularities perpetuating a speci­ fically clinical insomnia-related pathology. Till now, mid-level theorists have used “hyperarousal” as a heuristic anchor point to permit hermeneutic spelunking into neurobiological realms. Obtaining more practical and grounded descriptions of chronic insomnia, though, will involve moving the focus of studies to the real-time behavior of neural networks during sleep and wakefulness—further away from the semantic anchor point of “hyperarousal.” By itself, “hyperarousal” is too nonspecific a characterization to be applicable to all chronic insomnia patients. Saying that insomnia patients are “hyperaroused” is well meaning, but not very helpful in practice.

IV. Cautions About Conceptual Transitions to the Theory Level of Neuronal Processes

With a change of focus to neural network-level of explanations, however, one cannot automatically assume that the nouns and verbs used in the therapeutically productive mid-level theories will have mereologically con­ cise relationships to processes and endstates as they can be described for neuronal discharge patterns and synaptic relationships. First, the behavioral endstates of sleep and wakefulness are not static endstates for the neurons themselves, but rather differing regimens of ongoing electrical activity. Sleep is an endstate in the mid-level theory, but a process in the neural network level of explanation. Inattention to exact references can give rise to misapplications of nouns (e.g., “state”) or of predicates (e.g., “aroused”) between theoretical levels, and result in muddled thinking. Similarly, care needs to be taken not to confuse findings across temporal domains (linear versus circular) and scale (sleep macrostructure versus sleep microstructure). It is bad enough that the mereological arrangements between levels of theories will demand vagueness in explanations, but it will be worse if one cannot be precise about what future theory levels are being discussed and how they may be best conceptually linked.



V. An Aristotelian Method of Review




Spielman’s factors are three of the four categories of causes that Aristotle described in the Metaphysics (Aristotle, 1968). Aristotle’s four categories are sub­ stantial, formal, efficient, and final (telos in Greek). The first two of these cate­ gories do not implicate time, while the later two do. (for Aristotle, a cause was a principle that could be cited for why a think exists, or has Being.) Spielman’s predisposing factors are substantial causes, his precipitating factors are the effi­ cient causes, and the perpetuating factors are final causes (the “goal” or telos of the insomnia limit cycle). DFA, middle-of-night awakenings (MNAs), and EMA are formal-structural causes in this rendering. Aristotelian style review enables one to be more conscious of the need to consider main categories in an overall expla­ natory scheme. Honoring Aristotle, I will use his categories to review briefly other theoretical levels as well, particularly about NREM sleep, but with the stipulation that a given entity may be placed into one Aristotelian category at one theory level, but be placed into another category at another level (e.g., “awakening” as endstate-telos versus as process-efficient cause). The mereological coordination of theories requires such flexibility.

B. PROBLEMS EMERGING FROM RELATING THEORIES FROM DIFFERENT CONCEPTUAL LEVELS Several background problems can be anticipated. First, we cannot “abandon” or dismiss useful clinical theories simply because they are at super­ ordinate levels of explanation. All explanatory domains (even the ones I myself do not like) will need to be somehow related to one another if research and clinical practices are to be mutually adapted. Second, many causal categories will be relevant, but be of different types. Third, probabilistic causations should be preferred over presupposing law-like causations. Awakenings should be framed in relation to their probabilities. (Part of the insight into cognitive behavioral therapy is that patients want to suppose that there are laws of sleep that they can master, but these “laws” are just cognitive distortions that interfere with sleeping.) Fourth, use of 1:1 mappings of causes to phenomenal effects is probably unrea­ listic. One should avoid considering EEG signals as rigid 1:1 causal maps of awakenings or sleep. Finally, one can anticipate theories (Perlis et al., 1997) that describe feedback loops between a patient’s cognitions and neurobiological factors, even though they implicate the use of radically different explanatory



ontologies. Harvey’s observation that the false-causality cognitions driving many insomnia patients’ safety behaviors act at odds with Processes C and S is already a clear example of this at the macrotheoretical level. The remaining parts of this chapter discuss ontologies below mid-level theories.

C. SUBSTANTIAL CAUSES (I.E., SUBSTANCES) For a clinician, a substantial cause of sleep and wakefulness would be chemi­ cals (substances) that affect sleep–wake functioning in some way. The pharma­ cology of awakenings is described elsewhere in this volume.

D. FORMAL CAUSES (I.E., STRUCTURES) 1. Nuclear Structures Other chapters describe more completely key normatively formal relation­ ships between brain nuclei that bear on sleep and awakenings in psychiatric patients. Among these are the general ascending reticular activating system, with its rostrally projecting neurotransmitter pathways; the relationships between the ventro-lateral preoptic nuclei, the hypocretin system, and the brainstem nuclei; the SCN-governed circadian control system and its circuit output channels; and the pontine control system for the NREM/REM cycling. Several internuclear linkages appear to have relations of bi-stable switching (Saper et al., 2001; Siegel, 2005), which in turn help to explain normal limit cycles found in wakefulness and sleep. There are also linkages between the hippocampus and brain cortical regions (O’Neill et al., 2010) that subserve nocturnal memory consolidation and likely have some role in nocturnal awakenings. Damage to or frailty of the formal elements of brain circuitry undoubtedly leads to fragmented sleep/wake states with awakenings, circadian misalignments, or frank sleep/wake arrhythmicity. Ancillary structures are also pertinent to consider in an account about pathological awakenings. When considering the causes of insomnia, one cannot avoid considering the biology of fear responding for its relevance for awakenings. Fear-related awakenings are a frequent problem for patients with PTSD and other psychiatric disorders. Fear responding is partly regulated by the amygdala. Studies support its role in biasing the sleep/wake system toward constant vigi­ lance against threat, even during sleep (Benca et al., 2000). There are mutual innervations between amygdala and brainstem nuclei (Price, 2003), so that the amygdala’s physiological functions have regulatory influence affecting stress responding in the hypothalamus and pons. An overactive amygdala has axonal



outflow channels to bias the sleep/wake system toward wakefulness and awakening. People also worry. Worrying responses can arise without overt environmental stimuli and may not necessarily be aversive for the worrier. Worrying may at times be ego-syntonic and appetitive. There is a distinction between normal and pathological worry. The neural circuitry involved in worrying will likely involve several cortical regions. Worrying is partly linked to intentional semantic proces­ sing. Imaging studies (Paulesu et al., 2010; Schienle et al., 2009) point to increased general brain activity in the anterior cingulate and orbital prefrontal cortex in pathological worriers, a group who are likely to suffer from chronic insomnia. Brain regions that mediate semantic processing are also relevant for the under­ standing of pathological awakenings, if only by reason of the fact that semanti­ cally based worrying interferes with sleep, and worrying involves memory processing. What neurophysiological observations might support the stimulus control theory of insomnia? As far as acquisition of a stimulus–response association is concerned, it would seem difficult to pin down any one brain region as the culprit, since many brain regions aside from the hippocampus are involved in forming stimulus–response associations. However, candidate areas might be those linked more tightly to threat responding to neural pathways with high bandwidth, or to nuclei that are proximal to the regulation of NREM sleep. However, it may be more important (per Spielman’s rationale, discussed above) to identify the nuclei involved in impaired habit extinction. Mouse and human genetic variants of brain-derived neurotrophic factor point to atypical frontoamygdala activity in these subjects (Soliman et al., 2010); however, other evidence points to involvement of the mediodorsal nucleus of the thalamus, orbital prefrontal cortex, and amygdala, but not the nucleus accumbens (Izquierdo and Murray, 2010). Extinction may depend partly upon factors related to REM sleep (Spoormaker et al., 2010). The amygdala has metacircuit influences from the prefrontal cortex, which allows a person a means to override automatic fear responding. In PTSD patients, some evidence (Shin et al., 2006) points to frailty in this controlling circuit, affecting both the inability to decondi­ tion from fear stimuli and also possibly the inability to sleep without awakenings. While studies are pointing to abnormalities in the prefrontal-to-thalamic circuit that are involved in impairments to extinction, the semantic maps that provide discrimination to the fear responding also need better clarification. Psychothera­ pies often address such cognitive/affective mappings. Since worry involves a kind of self-sustaining habit-like semantic processing, it seems that linkages to and from language processing circuits will be involved with the extinction of sleepimpairing worrying. Also, since patients experience their symptoms in semantic tenses, any pathophysiology involved with abnormalities of the tensing of experiences needs development too. Furthermore, while worry is often habitual,



semi-intentional, and sometimes appetitive, the role that executive frontal regions play in selecting for the appetitive aspects of worry remains obscure. Some neuroimaging studies (Nofzinger et al., 2004, 2006) suggest that chronic insomnia patients suffer from persistent frontal metabolic activation. It is also possible that cerebellar, labyrinthine, or other brain regions may be important for understanding the persistence of awakenings and insomnia in some patients. This brief review of possible structural–psychological–functional rela­ tionships implicated in chronic insomnia suggests that clinicians cannot assume that only one kind of regional neuropathology will be involved across all patients with chronic insomnia.

2. Some Relevant Network and Neuron Structures Sleep medicine has used the EEG to measure sleep more objectively. To understand the EEG waveforms in NREM sleep, an understanding of the thalamocortical circuit between particular cell types is required. Figure 1 displays the thalamocortical circuit as depicted by Amzica and Steriade (2002). Cells from the reticular nucleus of the thalamus (RTN) provide gamma-amino butyric acid (GABAergic) stimulus to thalamocortical (ThCx) cells. ThCx cells have main glutamatergic output to cortical (Cx) cells, but also back-collaterals to RTN cells. Cx cells in turn have glutamaturgic feedback axons to both ThCx and RTN cells (Steriade and McCarley, 2005). Of special note, RTN cells have dendrodentritic synapses with each other, which greatly enhance their characteristic of coordi­ nated, en masse burst firing during NREM sleep. These connections are relevant for understanding observable EEG sig­ nals. The connections between the thalamus and other areas inaccessible to EEG observation are less researched. Limbic–thalamic connections may be distinct, or nonexistent, in relation to sleep spindles or other NREM EEG waveforms in humans (Nakamura et al., 2003). If so, then a person could be defined as asleep by conventional PSG criteria, but self-report that he/she “did not sleep at all,” and be truthful! Since limbic cortex is involved with emotional functioning, this may be where one “feels” sleep, sleepiness, or fatigue. Or, intriguingly, recently Buysee (personal communication) has a potential finding that suggests it might be in the precuneus nucleus where sleep perception may occur. Wherever it may be located, a hidden sleepperception “nucleus” might explain the biological basis for the diagnosis of paradoxical insomnia (American Sleep Disorders Association, 2005)—a com­ plaint of not having slept despite behavioral and/or PSG evidence for having slept. If hidden biology is the structural cause, then paradoxical insomnia would be just another mundane example of partial awakening rather than a target for stigmatization and clinical puzzlement.




KC + spindle Cx Cx b-c





ThCx b



KC + delta ThCx Cx Cx





a+ a



ThCx b


KC + delta Cx Cx d�


d d


FIG. 1. (Continued )





Another structural level is worth discussing in more detail. At the neuronal level of explanation, hyperpolarization-induced T-type calcium-channel depolar­ ization in some neuron types plays key roles in sleep physiology. When opened, this ion channel will stay “stuck” open for a microperiod, letting a calcium ion influx to activate calcium-dependent potassium ion channels (Steriade and McCarley, 2005). These in turn set in motion a membrane voltage depolarizing cascade. This membrane voltage behavior occurs more spontaneously in RTN cells than in ThCx or Cx cells. The hyperpolarization gating of the calcium current in RTN cells sets up a kind of membrane voltage cycling, as follows. The gradual depolarization leads to a low-threshold spike that gives rise to a brief burst of repetitive action potentials. This burst spiking is followed by rehyper­ polarization and cycle repetition. This cycling occurs both in RTN cells and, with RTN cell GABAergic stimulus, also in ThCx cells. In the millisecond domain, these series of events are linearly chained processes, and their circular chaining serves as a limit cycle time structure, or cell membrane clock. On the EEG this limit cycle behavior is observed as a sleep spindle. Changes in ion channel behavior change the membrane clock’s behavior. Three are worth mentioning here. First, in RTN and ThCx cell dendrites, benzodiazepine receptor occupancy will cause normal GABA-mediated chlor­ ide-channel openings to be more persistent than otherwise, giving rise to a hyperpolarization of the postsynaptic membrane. The clock’s frequency is increased. This is one reason why benzodiazepine receptor agonists (BZRAs) are used as sleeping pills, in that they encourage the hyperpolarization associated with initiating NREM sleep. These agents cause an increased rate of spindles on the EEG (Bazil, 2002), the EEG sequela of ThCx cell spike-bursting. Second, evidence exists for the nuclear specificity of benzodiazepine receptors. In rats, zolpidem has been shown to predominantly modulate the ThCx cell and not the RTN cell, whereas eszopiclone modulates the RTN but not the ThCx cell (Jia et al., 2009). Differential changes in the membrane clocks of the RTN and ThCx cells may set up conditions for a higher rate of parasomnias with zolpidem than with eszopiclone (Dolder and Nelson, 2008). Third, the Cx-to-ThCx glutama­ turgic circuit is thought to be metabotropic rather than ionotropic (Crunelli and

FIG. 1. Several modes of electrical relationships between thalamocortical circuit elements. The thalamocortical (ThCx) cell, cortical (Cx) cell, and thalamic reticular (RE in figure) nucleus cell form a network involved in forming sleep spindles and other wave forms observed on the EEG channel of a PSG. RE cells have dendrodentritic synapses with each other, whereas ThCx and Cx cells do not. Cx cells have feedback axons to RE and ThCx cells. ThCx cells have feedback axons to RE cells. In panels A, B, and C, different microtemporal connections are in force, as separately depicted. In each case, the discharge patterns can bear a surface resemblance to each other as slow or delta waves, but arise from differing microtemporal conditions of cellular response in the three circuit components (copied with permission from Amzica and Steriade, 2002).



Hughes, 2010). This is thought to facilitate the relative cross-coordination of spindle expression in relation to K-complexes (see below) insofar as the alteration in ion channel behavior would affect how fast one part of the cell membrane clock would run through its portion of the limit cycle.

E. EFFICIENT CAUSES (I.E., PROCESSES, CONTEMPORARILY UNDERSTOOD “CAUSES”) In contemporary parlance (contra Aristotle), “causes” are conventionally limited to Aristotle’s efficient (“process”) causes occurring in linear time. It is statistically impossible to study processes as processes (see above), so usually process causes are statistically modeled as dyadic contrasts between antecedent and consequent event “states.” In clinical contexts, the efficient causes of awa­ kenings are taken to be events like obstructive apneas or other measurable events. In this construction, awakenings are taken to be the simple results of the pre­ sumed processes originating from the antecedent events. Clinical arousals and awakenings are conceptualized in relation to small time epochs with prompt antecedent–consequent linkages. However, awakenings are also considered in relation to longer epochs extending from the prior day’s experiences (being unable to sleep well after an exciting day, etc.). Longer time periods during “aroused” sleep have been documented by greater high-frequency EEG power during sleep, even for the “first night effect” in first night of PSG studies. Shortand long-period processes causing arousals thus appear abundant, but their actual process details remain obscure. For the SOP itself, we do know that at sleep onset the hyperpolarizing of the thalamic cells is partly the result of the disfacilitation of wakefulness arising from reduced depolarizing stimulation from the brain stem (Timofeev et al., 2001). Additionally, there is evidence for direct hyperpolarizing stimuli from the ante­ rior hypothalamus (Steriade and McCarley, 2005). When RTN cells reach sufficiently hyperpolarizing voltages, their cell membrane clocks set up coordi­ nated burst-mode firing that delivers inhibitory postsynaptic potentials (IPSPs) to the ThCx cell. The volley of IPSPs further hyperpolarizes the ThCx cell, and leads to its own burst-mode firing, now coordinated with the RTN mass-coordi­ nated firing pattern. On the cortex this is observed as a spindle: The patient is now in stage N2 sleep. As part of the NREM sleep process, the neocortex has its own intrinsic slow (<1 Hz) rhythm (Crunelli and Hughes, 2010) that becomes more apparent during NREM sleep. In this slow rhythm, the Cx cell goes through a DOWN phase, which is a period of action potential silence, followed by an UP phase, a period of comparable depolarization. This is in essence another, but slower, cell membrane clock behavior. The back-connections to RTN and ThCx cells from Cx cells are



already becoming active as NREM is getting underway, so that the thalamic cells are exposed to a metabotropic stimulus at the frequency of the slow (~0.5 Hz) rhythm. The RTN and ThCx cells are also thought to be capable of slow rhythms, but as dependent upon the cross-coordination provided by metabotro­ pic stimulation from Cx cells. With sufficient momentum into NREM sleep, the thalamocortical network finds modes of temporalized firing resonance, as depicted in Fig. 1 (Amzica and Steriade, 2002), back and forth between the cortex and the thalamus. Depending on the specific timing, a given signaling from one neuronal group to another may give rise to mass cortical discharging observed on the EEG as coordinated slow waves (as in a K-complex), as delta (1–4 Hz) waves, or as spindles. Since the momentary responsiveness of a circuit element is semi-chaotic, the EEG patterns are not rigidly stereotyped, but have semi-regularities. One such semi-regularity is that of a sleep spindle following along the UP phase of a slow wave, riding on a K-complex. Since its discovery, the K-complex was known to be inducible by environ­ mental stimuli. Researchers long puzzled over whether the K-complex is not a micro-awakening. Yet it is one of the desiderata of stage N2 sleep! How can a micro-awakening be a marker of solid sleep? The functional telos of the K-complex has been debated from the time of its first observation (Colrain, 2005). There have been other persisting clinical puzzles. Why is it true that for some patients, BZRAs are arousing, rather than sleep promoting? They increase spindling, but why then do they tend to decrease N3 sleep (i.e., deeper NREM sleep) and increase the level of beta power in the EEG (Bazil, 2002). For mice, low-dose BZRAs are activating, whereas higher doses are sedating (Pellow and File, 1987). Some patients say that BZRAs give some but not especially restora­ tive sleep: Does this mean that BZRAs have hidden awakening properties? As already mentioned, zolpidem, an alpha-1-specific BZRA acting on ThCx cells, does not inhibit deeper stages of sleep as much, but tends to give rise to para­ somnias. These paradoxes about BZRAs as hyperpolarizing agents not having causal determinacy in inducing deep sleep (many patients’ fondest wish!), and indeed sometimes causing arousal-like events, call into question the idea that NREM sleep can be thought of simply as a hyperpolarized “state.” Along this line of skepticism, Terzano and others (2005) advocated that there is actually a pattern of “activation” seen in sleep called the cyclic alternating pattern (CAP). CAPs are widely enough observed that a scoring atlas (Terzano et al., 2002) has been published for them. In a CAP event, an initial series of deltawave bursts occurs in NREM sleep, followed after a few seconds by a quick frequency shift up to beta (16þ Hz) frequencies for a short period of several seconds. A CAP has been proposed as a kind of short awakening, particularly because of the fast activity associated with it. CAP events can be graded for their severity, so that more frequent and longer CAPs are associated with insomnia



(Terzano et al., 2003), bruxism (Kato et al., 2003; Zucconi et al., 1995), and other clinical problems. These CAPs are thought to occur even in the absence of other external causes of awakenings. The presence of CAPs may not affect scoring judgments about stages of sleep. They may occur during conventionally scored, architecturally “sound” sleep. One can suppose a general interpretive direction in understanding K-complexes and CAPs if one can consider, in reference ideas depicted in Fig. 1, a process-understanding of the EEG waveforms. It has been proposed that for “stimulated” K-complex events, the stimulus “hits” the cortex at the right prepotent moment during its slow rhythm cycle, so as to time-synchronize the thalamocortical network to produce a K-complex and its trailing elements (Amzica and Steriade, 2002; Colrain, 2005). Often spindles can be seen occurring in the rebound-negative portion of the K-complex, implying that the spindle was time-locked by the K-complex. This is thought to occur because of Cx-to-ThCx cell depolarizing stimulation (Crunelli and Hughes, 2010). When considering that the RTN, ThCx, and Cx neurons mutually influence each other’s synaptic responding, one could expect membrane time-linked response coordination between them. But to expect this, one would also expect that NREM sleep is not a literal “clamped” voltage state for neurons, but rather a membrane voltage response process that involves rhythmic membrane-voltage cycling under certain conditions of circuit resonance. Fig. 1 presents some network response scenarios of Amzica and Steriade concerning NREM EEG wave packets. It is remarkable that several different patterns of network connectivity can give rise to nominally equivalent slow and delta waves, as far as conventional EEG scoring is concerned. Considering this multiplicity of connectivities, it is hard to say that there could be a simple identity proposed between a specific waveform sequence (say CAP) and a “conventional awakening.” “Conventional awakening” seems conceptually and linguistically impoverished here, yet apparently some sequences of waveforms like CAPs, if they occur too much, make people feel poorly during the daytime. While possibly pathological, these CAP transients do not conform to sleep or wake state classi­ fication: They are literally neither “state,” and yet both “states,” at the same “time.” Being too attached to “state” language may have obscured our understanding of BZRA actions. Trying to make chronic insomnia patients feel better by giving them BZRAs to drive them into a sleep “state” may have been missing the therapeutic target. The constant, unremitting state-domain presence of a BZRA on its receptor may not be biologically natural for neurons, if the normal biology of neurons during NREM sleep implicates that both (1) the individual neurons are not usually in a substance-induced membrane voltage clamp that prevents them from toggling naturally between relatively hyperpolarized and depolarized membrane voltages and (2) the network of neurons electrically



interacting with each other is hindered in their mutual reactivity if voltage clamped by BZRAs, so as to prevent certain wave packets from forming across the neuronal circuit. That most BZRAs would increase spindling rate at the expense of deltawave expression would therefore be expected, if Amzica and Steriade’s proposal is correct. Similarly, the prevention of circuit resonance in delta frequencies might appear as increased beta frequency power, or prevent some individuals from getting therapeutically essential resonance patterns of NREM sleep itself. It would also be no surprise that an agent that acts only on one portion of the circuit (e.g., zolpidem) would make possible circuit responses that would be abnormal enough to lead to sleepwalking. Across the night, the pattern of normal responses may well involve moments of “partial awakening” in a time-limited voltage series, but which would then be prone to finding limit cycles of more durable partial awakening, if the right drugs are present. This suggests that too much stable limit cycle resonance, without any developing resonance entropy, would be undesirable (e.g., causing sleepwalking) or dangerous (i.e., causing seizures) during NREM sleep (Pearlmutter and Houghton, 2009). Some “Nicomachean” moderation of circuit resonance alongside circuit disresonance may be vital to healthy sleep, a circ*mstance which might mereologically impli­ cate some ironic neuroprotective role for “arousals.” These considerations point to the need to conceptualize sleep as involving milli- or micro-temporalities. It might be best to avoid conceptualizing sleep, even microstructurally, as a synchronic state. Rather, it may be better to conceptualize “objective” EEG sleep as an inordinate ensemble of time-limited mass-action neuronal firing processes that appear on EEG channels as epiphenomenal pat­ terns, as classified in conventionalized, fixed-time epochs (e.g., 30 s). Such is a “state” only in a manner of speaking. Exemplifying the diachronic perspective is the CAP phenomena. CAPs can be scored for their severity, into types A1, A2, and A3 (see Fig. 2). These are graded types where the higher grades of CAPs contain more dramatic slow waves and more prolonged “arousal-like” phenomena. CAP researchers have presented data pointing to CAP rate increases occurring in insomnia patients (Terzano et al., 2003), and there is some evidence that sleep bruxism is more associated specifically with CAP type A3 (Kato et al., 2003). By the description of CAPs, part of the process involves “deeper sleep” waves followed by “arousal” wave patterns. The diachronous features of CAPs are used as the data for their classification, and their grades relate to the pathology of the phenomena of complaints, but not necessarily to gross awakening “states.” If one consider the processes described in Fig. 1 in relation to the structural fact that ThCx cells do not have the dendrodentritic connections with each other the way RTN cells do, then it becomes easier to understand how a delta-wave Cx–ThCx resonance in a CAP would be more likely to decompose after several “beats” of a delta-wave rhythm, if the population of ThCx cells came to be







100 µV


FIG. 2. Grades of cyclic alternating pattern (CAP). A1, A2, and A3 describe grades of increasing severity of CAPs. In a CAP A phase, there is an initial alteration in the EEG signal characteristics toward expression of delta (1–4 Hz) or slow (<1 Hz) waves, followed by some expression of faster activity in the EEG signal. In the progression of severity from A1 to A3, a key diachronic difference is the time length of the faster activity, before the EEG signal returns to a more normal NREM background (copied with permission from Terzano et al., 2002).

mistimed to each other. In such a circ*mstance, their depolarizing output to cortex would also become disresonant, and potentially give rise to a greater likelihood that Cx cells would migrate into a brief depolarized, or simply dis­ organized, pattern of discharging. This disordered resonance would appear on the EEG as a faster, desynchronized wave pattern appearing to be more like an awakening or arousal. But, owing to NREM background influences, this cortical de-resonance would eventually be overcome by the pressure to return to coordi­ nated firing and return to the usual NREM EEG appearance. This may or may not be akin to an awakening returning to sleep. The irony in this account would be that the initial “stimulus” to get to these disorganized CAP “microarousals” were delta waves in the initial portions of the CAP that one would suppose to be deeper “sleep,” if one were to suppose that delta waves necessarily represent a deeper sleep “state.” However, these “deeper sleep delta-wave packets” may well be driven by autochthonous cortical slow wave processes. That is, it may be wrong to presuppose that Cx cells do not



normally have the effect of setting in motion electrical events that would be deeper sleep but for the discoordination that might well occur in any large, massively distributed signaling network like the glomerularized thalamocortical network. In such a scenario it would be as erroneous to claim that a CAP represented a teleological cortical “arousal” as it would be to claim that it represented a teleological “intention to sleep more deeply.” At the neural net­ work level, it is simply a process, without reference to the English words “arousal” or “sleep.” The prevalence of various types of CAPs during a night may reflect latent pathological network processes that extend over an entire sleep cycle. This might result in higher power in higher EEG frequency domains across a sleep cycle (Buysse et al., 2008b), but would not allow distinguishing whether its causation would be a more distal “mental activity during sleep” or just a proximal neuronal circuit resonance abnormality. For the consideration of CAP rates, the neuro­ cognitive model (Perlis et al., 1997) might be quite plausible, but, without a developed account of neurocognitive biology, such a model will remain largely speculative, in a similar way to how the stimulus-control theory is plausible, but remains neurobiologically obscure.

F. TELIC CAUSES (TELOS, FINAL CAUSES, LIMIT CYCLES, OUTCOMES, GOALS, AND NEEDS) Final causes are entities taken to be self-evidently justified and finalizing of a complete explanation. A telic cause can be considered as a conceptual organizing principle, binding an explanation together in an intelligible and practical, but only virtual package. Aristotle meant telos was as an entity moving things toward it “from the future,” but such is not what is meant in current usage. In Mayr’s (1988) consideration of telic causes in discussions about biological evolution, he instead used the term “teleonomic” to describe the general telic cause notion, and offered the term “teleomatic” for cases where the teleonomic explanation appeared especially compelling. A example of a teleomatic cause would be that of moths changing their coloration when residing in soot-infested trees: The process involved is that the sooty-appearing moths are less vulnerable to pre­ dators because of their coloration, but the teleomatic “shorthand” construction would have the soot “causing” the moths to change their coloration, yet without the teleological privilege Aristotle might have supposed for the soot’s causal “power.” Teleonomic explanatory arrangements are, therefore, as a practical matter, unavoidable in biologically relevant explanations, but are not to be understood as anything mystical arising from some intention originating in the future (e.g., future fitness of the species).



Understood in this qualified sense, a telic cause can be considered as a selfevident static endstate of an antecedent efficient causal process, but with such prior process details elided. Or it can be considered as a stable circular-temporal process pattern following a telic attractor of linearly looped efficient causes (e.g., like the loop of transcription/translation events in the SCN, or as a system of mutually balanced but antagonistic energies residing in a chemical equili­ brium). Without something like a telic cause in an explanation, no explanation would be practicable, as there would be no intermediate or final outcomes in which to orient the explanation. Unanchored processes would simply go on and on and on without an end-of-process reference, that is, without an outcome to orient a causal story. From psychiatric and sleep medicine standpoints, the nocturnal awakenings of patients are a central clinical issue for numerous disorders. These awakenings are (telic) outcomes, whether considered as intermediate or as essential targets of treatment interventions. For the primary insomnia patient, DFA, MNAs, and EMAs can be intermediate outcomes giving rise to bitter complaints, affecting impaired mindfulness and motivations (also outcomes) during the daytime, as described in official definitions. In sleep medicine, other kinds of complete or partial outcome awakenings include those for sleep apnea, sleepwalking, and REM behavior disorder, among others. For psychiatric disorders more generally, the impacts of objective and perceived stressors include nighttime awakenings across more complex disorders of major depression disorder, manic phase of bipolar illness, generalized anxiety disorder, PTSD, and other disorders. But these disorders only add to the collection of limit cycles (i.e., outcomes) of daytime and nighttime events locked into patterns of circular telic causation. Not all disorders causing nocturnal outcome awakenings, judging from their symptom pictures and neurobiologies, are the same, so their processes of producing these outcome awakenings cannot be assumed to be the same either. But as foreshadowed in the DSM-IV definition of primary insomnia, there is also a distinction between hard outcomes and soft outcomes (Checkland, 1981). One can measure the objective presence of a frequency change on an EEG channel (i.e., a hard outcome); but in clinical practice what often counts is the appraisal (i.e., a soft outcome) that the patient makes about awakenings, even if measured objectively. The temporal difference is that the hard outcome, whether viewed from past, present, or future, never changes in its limits or description; whereas the appraisal for the same event (e.g., how one thinks about a specific past experience to lead to speech acts about it) may indeed change. To address awakenings as clinical problems involves their conceptualization as both hard and soft outcomes. So the antinomy of outcome types gives rise to chronic problems for validating diagnoses and treatment strategies. Telic awakenings span across a wide range of supervenient clinical syn­ dromes. The efficient causes (process mechanisms) of different syndromes that



accomplish telic awakenings are surely heterogeneous. Many unexplored neuro­ nal process heterogeneities probably underlie not only awakenings, but also other syndromal outcomes. We now work mostly on just the PSG’s EEG channels. With this limitation, we are faced with Plato’s analogy of the cave, but with two additional complications, regarding diagnostic typing of the awakenings. On the EEG one sees only the shadows of neuron network processes, but the “arousals” one sees might be outside the realms of “sleep” and “wake” as we normally understand them, and what may be most clinically important is not the objective phenomena we can see, but the neurobiology of the patient’s appraisals about the events, however characterized. It seems that for advancements in the understanding of what “awakening” means clinically that there be a effort to develop some clinical nosology, as anchored at least in the microstructural (<5 s epoch) domain, for subjunctively classifying neurotemporal events associated with suspected awakenings. In doing such a nosology, the phasic patterns in the EEG signal stream during NREM sleep will need to be related to putative thalamocortical network electrical event series that have some basis in empirical neuroscience. Such a project may not be practicable now, but continuing to look at EEG waveform patterns as a way of understanding awakenings without doing so will not be any more diagnostic than it has already been (Morgenthaler et al., 2006). Developing this nosology will be a laborious bootstrap process, in which it will undergo many subjunctive respeci­ fications over historical time. Present methods of studying person-level awaken­ ings will be unlikely to shed much new light on understanding or managing clinical conditions in which awakenings, in the common-English sense, are a major teleonomic component. The nosology will need to be also constructed with a view that normal memory consolidation processes may play a role in nocturnal awakenings. While this review has focused on NREM awakenings, similar con­ ceptual concerns arise for the domain of REM sleep awakenings.

VI. Conclusion

Psychotherapies for insomnia reduce awakenings, but the psychology-based mid-level theories underpinning them remain relatively separated from theories of neuronal network functioning. Brain-regional explanations of sleep–wake functioning are helping to move clinical understanding into biological domains of explanation. Theories of neuronal network function are starting to relate basic neuroscience concepts to problems of pathological awakenings, now increasingly clarified with network-level theories. Naturally enough, further research work needs doing on these separate levels, both conceptually and empirically. But as



new results come in, practicing clinicians will require better meta-theories to relate the different theories to each other, if biological and psychological thera­ pies are to be interdigitated in practice. Developing better practical, integrative rationalities for the discriminative uses of psychotherapies, medications, and other interventions for particular sleep medicine and psychiatric disorders remains a priority. In developing these new understandings, new conceptual frameworks will need to be invented, and old concepts may need to be histor­ icized. Among these historicized concepts is that of the generic awakening itself. Out damn awakening! The future of “awakening” may be just that of an expletive, in which concept specificity is elided in favor of affect display.


American Academy of Sleep Medicine. (2005). The International Classification of Sleep Disorders: Diagnostic & Coding Manual. American Academy of Sleep Medicine, Westchester, IL. American Psychiatric Association. Task Force on DSM-IV. (2000). Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR. American Psychiatric Association, Washington, DC. American Sleep Disorders Association. (2005). The International Classification of Sleep Disorders: Diagnostic and Coding Manual. American Sleep Disorders Association, Rochester, MN. Amzica, F., and Steriade, M. (2002). The functional significance of K-complexes. Sleep Med. Rev. 6, 139–149. Aristotle(1968). The Metaphysics, Book 1. Harvard University Press, Cambridge, MA. Balter, M. B., and Uhlenhuth, E. H. (1992). New epidemiologic findings about insomnia and its treatment. J. Clin. Psychiatry 53(Suppl.), 34–39. Bazil, C. W. (2002). Effects of anticonvulsants on the EEG. In: Sleep and Epilepsy: The Clinical Spectrum ( C. W. Bazil, B. A. Malow, and M. R. Sammaritano, eds.), Elsevier, Amsterdam, The Netherlands, pp. 195–201. Benca, R. M., Obermeyer, W. H., Shelton, S. E., Droster, J., and Kalin, N. H. (2000). Effects of amygdala lesions on sleep in rhesus monkeys. Brain Res. 879, 130–138. Bliwise, D. L. (2005). Normal aging. In: Principles and Practice of Sleep Medicine ( M. H. Kryger, T. Roth, and W. C. Dement, eds.), Elsevier, Philadelphia, PA, pp. 24–38. Bonato, R. (1997). Electroencephalographic Correlates of Sleep Onset in Chronic Psychophysiological Insomniacs and Normal Sleepers. Psychology. Carleton University, Ottawa, Canada. Bonnet, M. H., and Arand, D. L. (1995). 24-Hour metabolic rate in insomniacs and matched normal sleepers. Sleep 18, 581–588. Bootzin, R. R. (1972). A stimulus control treatment for insomnia. Proc. Am. Psychol. Assoc. 7, 395–396. Bootzin, R. R., and Perlis, M. L. (1992). Nonpharmacologic treatments of insomnia. J. Clin. Psychiatry 53(Suppl.), 37–41. Borbely, A. A. (1982). A two process model of sleep regulation. Hum. Neurobiol. 1, 195–204. Borbely, A. A. (2009). Refining sleep homeostasis in the two-process model. J. Sleep Res. 18, 1–2. Boucher, J. (2001). ‘Lost in a sea of time’: Time-parsing and autism. In: Time and Memory: Issues in Philosophy and Psychology ( C. ho*rl, and T. McCormack, eds.), Clarendon Press, New York, NY, pp. 1772–2168. Breslau, N., Roth, T., Rosenthal, L., and Andreski, P. (1996). Sleep disturbance and psychiatric disorders: A longitudinal epidemiological study of young adults. Biol. Psychiatry 39, 411–418.



Buysse, D. J., Angst, J., Gamma, A., Ajdacic, V., Eich, D., and Rossler, W. (2008a). Prevalence, course, and comorbidity of insomnia and depression in young adults. Sleep 31, 473–480. Buysse, D. J., Germain, A., Hall, M. L., Moul, D. E., Nofzinger, E. A., Begley, A., Ehlers, C. L., Thompson, W., and Kupfer, D. J. (2008b). EEG spectral analysis in primary insomnia: NREM period effects and sex differences. Sleep 31, 1673–1682. Buysse, D. J., Reynolds, C. F.3rd, Hauri, P. J., Roth, T., Stepanski, E. J., Thorpy, M. J., Bixler, E. O., Kales, A., Manfredi, R. L., Vgontzas, A. N., et al.. (1994). Diagnostic concordance for DSM-IV sleep disorders: A report from the APA/NIMH DSM-IV field trial. Am. J. Psychiatry 151, 1351–1360. Carey, T. J., Moul, D. E., Pilkonis, P., Germain, A., and Buysse, D. J. (2005). Focusing on the experience of insomnia. Behav. Sleep Med. 3, 73–86. Chang, P. P., Ford, D. E., Mead, L. A., Cooper-Patrick, L., and Klag, M. J. (1997). Insomnia in young men and subsequent depression. The Johns Hopkins Precursors Study. Am. J. Epidemiol. 146, 105–114. Checkland, P. (1981). Systems Thinking, Systems Practice. John Wiley, New York, NY. Colrain, I. M. (2005). The K-complex: A 7-decade history. Sleep 28, 255–273. Crunelli, V., and Hughes, S. W. (2010). The slow (<1 Hz) rhythm of non-REM sleep: A dialogue between three cardinal oscillators. Nat. Neurosci. 13, 9–17. Destexhe, A., Hughes, S. W., Rudolph, M., and Crunelli, V. (2007). Are corticothalamic ‘up’ states fragments of wakefulness? Trends Neurosci. 30, 334–342. Dolder, C. R., and Nelson, M. H. (2008). Hypnosedative-induced complex behaviours: Incidence, mechanisms and management. CNS Drugs 22, 1021–1036. Espie, C. A., Broomfield, N. M., MacMahon, K. M., Macphee, L. M., and Taylor, L. M. (2006). The attention-intention-effort pathway in the development of psychophysiologic insomnia: A theore­ tical review. Sleep Med. Rev. 10, 215–245. Ford, D. E., and Kamerow, D. B. (1989). Epidemiologic study of sleep disturbances and psychiatric disorders. An opportunity for prevention? J. Am. Med. Assoc. 262, 1479–1484. Freedman, R. R. (1986). EEG power spectra in sleep-onset insomnia. Electroencephalogr. Clin. Neurophy­ siol. 63, 408–413. Halasz, P., Terzano, M., Parrino, L., and Bodizs, R. (2004). The nature of arousal in sleep. J. Sleep Res. 13, 1–23. Hanlon, E. C., Faraguna, U., Vyazovskiy, V. V., Tononi, G., and Cirelli, C. (2009). Effects of skilled training on sleep slow wave activity and cortical gene expression in the rat. Sleep 32, 719–729. Harvey, A. G. (2002). Identifying safety behaviors in insomnia. J. Neural. Eng. 190, 16–21. Hohagen, F., Kappler, C., Schramm, E., Riemann, D., Weyerer, S., and Berger, M. (1994). Sleep onset insomnia, sleep maintaining insomnia and insomnia with early morning awakening–temporal stability of subtypes in a longitudinal study on general practice attenders. Sleep 17, 551–554. Hori, T., Hayashi, M., and Morikawa, T. (1994). Topographical EEG changes and the hypnagogic experience. In: Sleep Onset: Normal and Abnormal Processes ( R. D. Ogilvie, and J. R. Harsh, eds.), American Psychological Association, Washington, DC, pp. 237–253. Iber, C., Ancoli-Israel, S., Chesson, A. L.Jr., and Quan, S. F. (2007). The AASM Manual for the Scoring of Sleep and Associated Events. American Academy of Sleep Medicine, Westchester, IL. Izquierdo, A., and Murray, E. A. (2010). Functional interaction of medial mediodorsal thalamic nucleus but not nucleus accumbens with amygdala and orbital prefrontal cortex is essential for adaptive response selection after reinforcer devaluation. J. Neurosci. 30, 661–669. Jacobs, G., Benson, H., and Friedman, R. (1993). Home-based central nervous system assessment of a multifactor behavioral intervention for chronic sleep-onset insomnia. Behav. Ther. 24, 159–174. Jia, F., Goldstein, P. A., and Harrison, N. L. (2009). The modulation of synaptic GABA(A) receptors in the thalamus by eszopiclone and zolpidem. J. Pharmacol. Exp. Ther. 328, 1000–1006.



Katchalsky, A., and Curran, P. F. (1965). Nonequilibrium Thermodynamics in Biophysics. Harvard University Press, Cambridge, MA. Kato, T., Montplaisir, J. Y., Guitard, F., Sessle, B. J., Lund, J. P., and Lavigne, G. J. (2003). Evidence that experimentally induced sleep bruxism is a consequence of transient arousal. J. Dent. Res. 82, 284–288. Kearney, A. J. (2008). Understanding Applied Behavior Analysis: An Introduction to ABA for Parents, Teachers, and Other Professionals. Jessica Kingsley Publishers, Philadelphia, PA. Krakow, B., Hollifield, M., Johnston, L., Koss, M., Schrader, R., Warner, T. D., Tandberg, D., Lauriello, J., McBride, L., Cutchen, L., Cheng, D., Emmons, S., Germain, A., Melendrez, D., Sandoval, D., and Prince, H. (2001). Imagery rehearsal therapy for chronic nightmares in sexual assault survivors with posttraumatic stress disorder: A randomized controlled trial. J. Am. Med. Assoc. 286, 537–545. Lamarche, C. H., and Ogilvie, R. D. (1997). Electrophysiological changes during the sleep onset period of psychophysiological insomniacs, psychiatric insomniacs, and normal sleepers. Sleep 20, 724–733. Lavie, P. (1986). Ultrashort sleep-waking schedule. III. “Gates” and “forbidden zones” for sleep. Electroencephalogr. Clin. Neurophysiol. 63, 414–425. Leger, D., Guilleminault, C., Bader, G., Levy, E., and Paillard, M. (2002). Medical and socio­ professional impact of insomnia. Sleep 25, 625–629. Le Poidevin, R. (2003). The beginning and end of time. Travels in Four Dimensions: The Enigmas of Space and Time. Oxford University Press, New York, NY, pp. 73–88. Le Van Quyen, M., Staba, R., Bragin, A., Dickson, C., Valderrama, M., Fried, I., and Engel, J. (2010). Large-scale microelectrode recordings of high-frequency gamma oscillations in human cortex during sleep. J. Neurosci. 30, 7770–7782. Lerman, D. C., and Iwata, B. A. (1995). Prevalence of the extinction burst and its attenuation during treatment. J. Appl. Behav. Anal. 28, 93–94. Lerman, D. C., Iwata, B. A., and Wallace, M. D. (1999). Side effects of extinction: Prevalence of bursting and aggression during the treatment of self-injurious behavior. J. Appl. Behav. Anal. 32, 1–8. Marzano, C., Ferrara, M., Sforza, E., and De Gennaro, L. (2008). Quantitative electroencephalogram (EEG) in insomnia: A new window on pathophysiological mechanisms. Curr. Pharm. Des. 14, 3446–3455. Mayr, E. (1988). The multiple meanings of teleological. In: Toward a New Philosophy of Biology: Observations of an Evolutionist ( E. Mayr, ed.), Harvard University Press, Cambridge, MA, pp. 38–66. McTaggart, J.M.E. (1993). The unreality of time. In: The Philosophy of Time ( R. Le Poidevin, and M. MacBeath, eds.), Oxford University Press, Oxford, UK; New York, NY, 23–34. Mellor, D. H. (1993). The unreality of tense. In: The Philosophy of Time ( R. Le Poidevin, and M. MacBeath, eds.), Oxford University Press, Oxford, UK; New York, NY, 47–59. Merica, H., Blois, R., and Gaillard, J. M. (1998). Spectral characteristics of sleep EEG in chronic insomnia. Eur. J. Neurosci. 10, 1826–1834. Merica, H., and Gaillard, J. M. (1992). The EEG of the sleep onset period in insomnia: A discriminant analysis. Physiol. Behav. 52, 199–204. Morgenthaler, T., Kramer, M., Alessi, C., Friedman, L., Boehlecke, B., Brown, T., Coleman, J., Kapur, V., Lee-Chiong, T., Owens, J., Pancer, J., and Swick, T. (2006). Practice parameters for the psychological and behavioral treatment of insomnia: An update. An american academy of sleep medicine report. Sleep 29, 1415–1419. Morin, C. M. (1993). Insomnia: Psychological Assessment and Management. Guilford Press, New York, NY. Morin, C. M., and Espie, C. A. (2003). Insomnia: A Clinical Guide to Assessment and Treatment. Kluwer Academic/Plenum Publishers, New York, NY.



Moul, D. E., Germain, A., Cashmere, J. D., Quigley, M., Miewald, J. M., and Buysse, D. J. (2007a). Examining initial sleep onset in primary insomnia: A case-control study using 4-second epochs. J. Clin. Sleep Med. 3, 479–488. Moul, D. E., Mai, E. F., Miewald, J., Shablesky, M., Pilkonis, P. A., and Buysse, D. J. (2007b). Psychometric study of the Pittsburgh Insomnia Rating Scale (PIRS) in an initial calibration sample. Sleep 30 (Abstract Suppl.), A343. Nakamura, M., Uchida, S., Maehara, T., Kawai, K., Hirai, N., Nakabayashi, T., Arakaki, H., Okubo, Y., Nishikawa, T., and Shimizu, H. (2003). Sleep spindles in human prefrontal cortex: An electrocorticographic study. Neurosci. Res. 45, 419–427. Nofzinger, E. A., Buysse, D. J., Germain, A., Price, J. C., Miewald, J. M., and Kupfer, D. J. (2004). Functional neuroimaging evidence for hyperarousal in insomnia. Am. J. Psychiatry 161, 2126–2128. Nofzinger, E. A., Nissen, C., Germain, A., Moul, D., Hall, M., Price, J. C., Miewald, J. M., and Buysse, D. J. (2006). Regional cerebral metabolic correlates of WASO during NREM sleep in insomnia. J. Clin. Sleep Med. 2, 316–322. Ohayon, M. M. (2002). Epidemiology of insomnia: What we know and what we still need to learn. Sleep Med. Rev. 6, 97–111. O’Neill, J., Pleydell-Bouverie, B., Dupret, D., and Csicsvari, J. (2010). Play it again: Reactivation of waking experience and memory. Trends Neurosci. 33, 220–229. Paulesu, E., Sambugaro, E., Torti, T., Danelli, L., Ferri, F., Scialfa, G., Sberna, M., Ruggiero, G. M., Bottini, G., and Sassaroli, S. (2010). Neural correlates of worry in generalized anxiety disorder and in normal controls: A functional MRI study. Psychol. Med. 40, 117–124. Pearlmutter, B. A., and Houghton, C. J. (2009). A new hypothesis for sleep: Tuning for criticality. Neural. Comput. 21, 1622–1641. Pellow, S., and File, S. E. (1987). Lack of cross-tolerance in mice between the stimulatory and depressant actions of novel anxiolytics in the holeboard. Behav. Brain. Res. 23, 159–166. Perlis, M. L., Giles, D. E., Mendelson, W. B., Bootzin, R. R., and Wyatt, J. K. (1997). Psychophy­ siological insomnia: The behavioural model and a neurocognitive perspective. J. Sleep Res. 6, 179–188. Perlis, M. L., Smith, M. T., Andrews, P. J., Orff, H., and Giles, D. E. (2001). Beta/Gamma EEG activity in patients with primary and secondary insomnia and good sleeper controls. Sleep 24, 110–117. Perlis, M. L., Smith, M. T., and Pigeon, W. R. (2005). Etiopathology and pathophysiology of insomnia. In: Principles and Practice of Sleep Medicine ( M. H. Kryger, T. Roth, and W. C. Dement, eds.), Elsevier, Philadelphia, PA, pp. 714–725. Price, J. L. (2003). Comparative aspects of amygdala connectivity. Ann. N. Y. Acad. Sci. 985, 50–58. Rechtschaffen, A., and Kales, A. (1968). A Manual of Standardized Terminology, Techniques, and Scoring Systems of Sleep Stages in Human Subjects. UCLA Brain Information Service/Brain Research Institute, Los Angeles, CA. Ricœur, P. (1984). Time and Narrative. University of Chicago Press, Chicago, IL. Riemann, D., Spiegelhalder, K., Feige, B., Voderholzer, U., Berger, M., Perlis, M., and Nissen, C. (2010). The hyperarousal model of insomnia: A review of the concept and its evidence. Sleep Med. Rev. 14, 19–31. Robins, L. N., and Regier, D. A. (1991). Psychiatric Disorders in America: The Epidemiologic Catchment Area Study. The Free Press, New York, NY. Saper, C. B., Chou, T. C., and Scammell, T. E. (2001). The sleep switch: Hypothalamic control of sleep and wakefulness. Trends Neurosci. 24, 726–731. Schienle, A., Schafer, A., Pignanelli, R., and Vaitl, D. (2009). Worry tendencies predict brain activation during aversive imagery. Neurosci. Lett. 461, 289–292. Searle, J. R. (1969). Speech Acts: An Essay in the Philosophy of Language. Cambridge University Press, UK.



Shin, L. M., Rauch, S. L., and Pitman, R. K. (2006). Amygdala, medial prefrontal cortex, and hippocampal function in PTSD. Ann. N. Y. Acad. Sci. 1071, 67–79. Siegel, J. M. (2005). REM sleep. In: Principles and Practice of Sleep Medicine ( M. H. Kryger, T. Roth, and W. C. Dement, eds.), W. B. Saunders, Philadelphia, PA, pp. 120–135. Soliman, F., Glatt, C. E., Bath, K. G., Levita, L., Jones, R. M., Pattwell, S. S., Jing, D., Tottenham, N., Amso, D., Somerville, L. H., Voss, H. U., Glover, G., Ballon, D. J., Liston, C., Teslovich, T., Van Kempen, T., Lee, F. S., and Casey, B. J. (2010). A genetic variant BDNF polymorphism alters extinction learning in both mouse and human. Science 327, 863–866. Spielman, A. J., Caruso, L. S., and Glovinsky, P. B. (1987a). A behavioral perspective on insomnia treatment. Psychiatr. Clin. North. Am. 10, 541–553. Spielman, A. J., Saskin, P., and Thorpy, M. J. (1987b). Treatment of chronic insomnia by restriction of time in bed. Sleep 10, 45–56. Spoormaker, V. I., Sturm, A., Andrade, K. C., Schroter, M. S., Goya-Maldonado, R., Holsboer, F., Wetter, T. C., Samann, P. G., and Czisch, M. (In Press). The neural correlates and temporal sequence of the relationship between shock exposure, disturbed sleep and impaired consolidation of fear extinction. J. Psychiatr. Res. Staner, L., Cornette, F., Maurice, D., Viardot, G., Bon, O. L., Haba, J., Staner, C., Luthringer, R., Muzet, A., and Macher, J. P. (2003). Sleep microstructure around sleep onset differentiates major depressive insomnia from primary insomnia. J. Sleep Res. 12, 319–330. Steriade, M., and McCarley, R. W. (2005). Brain Control of Wakefulness and Sleep. Springer, New York, NY. Tanaka, H., Hayashi, M., and Hori, T. (1996). Statistical features of hypnagogic EEG measured by a new scoring system. Sleep 19, 731–738. Taylor, D. J., Lichstein, K. L., Durrence, H. H., Reidel, B. W., and Bush, A. J. (2005). Epidemiology of insomnia, depression, and anxiety. Sleep 28, 1457–1464. ter Meulen, A.G.B. (1995). Representing Time in Natural Language: The Dynamic Interpretation of Tense and Aspect. MIT Press, Cambridge, MA. Terzano, M. G., Parrino, L., Smerieri, A., Carli, F., Nobili, L., Donadio, S., and Ferrillo, F. (2005). CAP and arousals are involved in the homeostatic and ultradian sleep processes. J. Sleep Res. 14, 359–368. Terzano, M. G., Parrino, L., Smerieri, A., Chervin, R., Chokroverty, S., Guilleminault, C., Hirshko­ witz, M., Mahowald, M., Moldofsky, H., Rosa, A., Thomas, R., and Walters, A. (2002). Atlas, rules, and recording techniques for the scoring of cyclic alternating pattern (CAP) in human sleep. Sleep Med. 3, 187–199. Terzano, M. G., Parrino, L., Spaggiari, M. C., Palomba, V., Rossi, M., and Smerieri, A. (2003). CAP variables and arousals as sleep electroencephalogram markers for primary insomnia. Clin. Neuro­ physiol. 114, 1715–1723. Timofeev, I., Grenier, F., and Steriade, M. (2001). Disfacilitation and active inhibition in the neocortex during the natural sleep-wake cycle: An intracellular study. Proc. Natl. Acad. Sci. U.S.A. 98, 1924–1929. Vendler, Z. (2005). Verbs and times. In: The Language of Time: A Reader ( I. Mani, J. Pustejovsky, and R. Gaizauskas, eds.), Oxford University Press, New York, NY, pp. 21–32. Walker, M. P. (2009). The role of slow wave sleep in memory processing. J. Clin. Sleep Med. 5, S20–S26. World Health Organization (2007). ICD-10: International Classification of Diseases, 10th Revision. World Health Organization, Geneva, Switzerland. Zucconi, M., Oldani, A., Ferini-Strambi, L., and Smirne, S. (1995). Arousal fluctuations in non-rapid eye movement parasomnias: The role of cyclic alternating pattern as a measure of sleep instability. J. Clin. Neurophysiol. 12, 147–154.


Seiji Nishino and Yohei Sagawa Sleep and Circadian Neurobiology Laboratory, Stanford University School of Medicine, Stanford, CA 94304-5489, USA



X. XI.

Introduction Neurobiology of Wakefulness Narcolepsy and Symptoms of Narcolepsy Discovery of Hypocretin Deficiency and Postnatal Cell Death of Hypocretin Neurons Idiopathic Hypersomnia, Hypocretin Non-deficient Primary Hypersomnia Symptomatic Narcolepsy and Hypersomnia: Hypocretin Involvements How Does Hypocretin Ligand Deficiency Cause the Narcolepsy Phenotype? A. Hypocretin/Orexin System and Sleep Regulation B. Hypocretin/Orexin Deficiency and Narcoleptic Phenotype Considerations for the Pathophysiology of Narcolepsy with Normal Hypocretin Levels Changes in Other Neurotransmitter Systems in Narcolepsy and Idiopathic Hypersomnia A. Narcolepsy in Dogs and Humans B. Idiopathic Hypersomnia Involvements of Histaminergic Neurotransmission in Human Narcolepsy and Other Hypersomnia Conclusion Acknowledgments References

Recent progress in our understanding of the pathophysiology of excessive sleepiness (EDS) is particularly indebted to the 1999 discovery of narcolepsy genes (i.e., hypocretin receptor and peptide genes) in animals and the subse­ quent discovery of hypocretin ligand deficiency in idiopathic cases of human narcolepsy-cataplexy. Hypocretin deficiency is also involved in many cases of symptomatic narcolepsy and EDS. Changes in other neurotransmitter systems (such as monoamines and acetylcholine) previously reported in these conditions are likely to be secondary to the impaired hypocretin neurotransmission; however, these may also mediate the sleep abnormalities seen in hypocretin deficient narcolepsy. The pathophysiology of hypocretin non-deficient narcolepsy is debated. Similarly, the pathophysiology of idiopathic hypersomnia, another defined primary hypersomnia, is largely unknown. INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 93 DOI: 10.1016/S0074-7742(10)93010-9


Copyright 2010, Elsevier Inc. All rights reserved. 0074-7742/10 $35.00



This chapter discusses our current understanding of the neurochemistry of EDS, a disease of awakening.

I. Introduction

In this review, we discuss our current understanding of the neurochemistry of excessive sleepiness (EDS) (i.e., disease of awakening). Our recent progress in understanding the pathophysiology of EDS is particularly indebted to the 1999 discovery of narcolepsy genes (i.e., hypocretin receptor and peptide genes) in animals and the subsequent discovery (in 2000) of hypocretin ligand deficiency in idiopathic cases of human narcolepsy-cataplexy. The discovery in human narco­ lepsy lead to (1) the establishment of a new diagnostic test (i.e., low CSF hypocretin-1 levels) and (2) development of hypocretin replacements to be used in the treatment of hypocretin deficient narcolepsy. Further refinement of this therapeutic option is the focus of current, ongoing research (see Nishino et al., 2009a). The prevalence of primary hypersomnia, such as narcolepsy and idiopathic hypersomnia, is not high (0.05 and 0.005%, respectively), but the prevalence of symptomatic (secondary) hypersomnia may be much higher. For example, sev­ eral million subjects in the USA suffer from chronic brain injury. Seventy five percent of these patients have sleep problems and about half complain of sleepi­ ness (Verma et al., 2007). By comparison, the prevalence of symptomatic narco­ lepsy is likely to be much smaller and only about 120 such cases have been reported in the literature in the past 30 years. Nevertheless, meta-analysis of these cases indicates that hypocretin deficiency may also partially explain the neuro­ chemical mechanisms of both symptomatic EDS and EDS associated with symptomatic cases of narcolepsy (Nishino and Kanbayashi, 2005). The recent discovery of hypocretin peptidergic systems in 1998, followed by the discovery of narcolepsy genes only a year later, immediately prompted and illuminated related studies, seeking specific understanding of the roles of hypocretin peptidergic systems in sleep regulation under both normal and pathological conditions. Anatomical and functional studies demonstrate that the hypocretin systems integrate and coordinate multiple wake-promoting systems (such as monoamine and acetylcholine systems) to keep subjects fully alert (Jones, 2005). Histamine is one of these wake-active monoamines, and, notably, low CSF histamine levels are also found in narcolepsy with hypocretin deficiency (Kanbayashi et al., 2009a; Nishino et al., 2009b). Since hypocretin neurons project and excite histamine neurons in the posterior hypothalamus, it is conceivable that impaired histamine neurotransmission may mediate sleep abnormalities in hypocretin deficient



narcolepsy. However, low CSF histamine levels were also observed in narcolepsy with normal hypocretin levels and in idiopathic hypersomnia, a primary hypersomnia not associated with hypocretin deficiency (nor with rapid eye movement [REM] sleep abnormalities). Thus, decreased histamine neuro­ transmission may be involved in the broader category of EDS rather than in hypocretin deficient narcolepsy (Kanbayashi et al., 2009a). Since CSF histamine levels are normalized in EDS patients treated with wake-promoting compounds, low CSF histamine levels may be a new state marker for primary hypersomnia. The functional significance of this finding requires further study (Kanbayashi et al., 2009a). A large majority of patients with diagnosed EDS are currently treated with pharmacological agents, such as amphetamine-like compounds and modafinil. These treatments are symptomatic cures, and treatments that restore the primary impairments are not yet available. In this regard, further knowledge of the neuro­ chemistry of EDS/awakening will likely lead to the development of new treatments and management strategies for patients with hypersomnia with various etiologies.

II. Neurobiology of Wakefulness

In order to help in the understanding of the neurochemistry of hypersomnia, we will discuss current understandings of the neurobiology of wakefulness. Sleep/wake is a complex physiology regulated by brain activity, and multiple neurotransmitter systems such as monoamines, acetylcholine, excitatory and inhibitory amino acids, peptides, purines, and neuronal and non-neuronal humoral modulators (i.e., cytokines and prostaglandins) ( Jones, 2005) are likely to be involved. Monoamines are perhaps the first neurotransmitters recognized to be involved in wakefulness ( Jouvet, 1972), and the monoaminergic systems have been the most common pharmacological targets for wake-promoting compounds in the past years. On the other hand, most hypnotics target the gamma­ aminobutyric acid (GABA)nergic system, a main inhibitory neurotransmitter system in the brain (Nishino et al., 2004a). Cholinergic neurons also play critical roles in cortical activation during wakefulness (and during REM sleep) ( Jones, 2005). Brainstem cholinergic neu­ rons originating from the laterodorsal and pedunculopontine tegmental nuclei activate thalamocortical signaling, and cortex activation is further reinforced by direct cholinergic projections from the basal forebrain. However, currently no cholinergic compounds are used in sleep medicine, perhaps due to the complex nature of the systems and prominent peripheral side effects. Monoamine neurons, such as norepinephrine (NE) containing locus coeruleus neurons, serotonin (5-HT) containing raphe neurons, and histamine



containing tuberomammillary neurons are wake-active and act directly on cor­ tical and subcortical regions to promote wakefulness ( Jones, 2005). In contrast to the focus on these wake-active monoaminergic systems, researchers have often underestimated the importance of dopamine (DA) in promoting wakefulness. Most likely, this is because the firing rates of midbrain DA-producing neurons (ventral tegmental area [VTA] and substantia nigra) do not have an obvious variation according to behavioral states (Steinfels et al., 1983). In addition, DA is produced by many different cell groups (Bjo¨ rklund and Lindvall, 1984), and which of these promote wakefulness remains undetermined. Nevertheless, DA release is greatest during wakefulness (Trulson, 1985), and DA neurons increase discharge and tend to fire bursts of action potentials in association with significant sensory stimulation, purposive movement, or behavioral arousal (Ljungberg et al., 1992). Lesions that include the dopaminergic neurons of the VTA reduce behavioral arousal ( Jones et al., 1973). Recent work has also identified a small wake-active population of DA-producing neurons in the ventral periaqueductal grey that project to other arousal regions (Lu et al., 2006). People with DA deficiency from Parkinson’s disease are often sleepy (Moller et al., 2000), and DA antagonists (or small doses of DA autoreceptor (D2/3) agonists) are fre­ quently sedating. These physiological and clinical findings clearly demonstrate that DA also plays a role in wakefulness. Wakefulness (and various physiologies associated with wakefulness) is essential for the survival of creatures and thus is likely to be regulated by multiple systems, each having a distinct role. Some arousal systems may have essential roles for cortical activation, attention, cognition, or neuroplasticity during wakefulness while others may only be active during specific times to promote particular aspects of wakefulness. Some of the examples may be motivated-behavioral wakefulness or wakefulness in emergency states. Wakefulness may thus likely be maintained by many systems with differential roles coordinating in line. Similarly, the wake-promoting mechanism of some drugs may not be able to be explained by a single neurotransmitter system.

III. Narcolepsy and Symptoms of Narcolepsy

As narcolepsy is a prototypical EDS disorder, and since the major pathophy­ siology of narcolepsy (i.e., deficient in hypocretin neurotransmission) has recently been revealed, a discussion of the neurochemical aspects of narcolepsy will also help establish a general understanding of the neurochemistry in EDS. Narcolepsy patients manifest symptoms specifically related to the dysregula­ tion of REM sleep (Nishino and Mignot, 1997). In the structured, cyclic process



of normal sleep, two distinct states—REM and four stages (S1, S2, S3, S4) of nonREM (NREM) sleep—alternate sequentially every 90 min in a cycle repeating 4–5 times per night (Nishino et al., 2004b). As electroencephalogram signals in humans indicate, NREM sleep, characterized by slow oscillation of thalamocor­ tical neurons (detected as cortical slow waves) and muscle tonus reduction, precedes REM sleep, when complete muscle atonia occurs. Slow wave NREM predominates during the early phase of normal sleep, followed by a predomi­ nance of REM during the later (Nishino et al., 2004b). Notably, sleep and wake are highly fragmented in narcolepsy, and affected subjects cannot maintain long bouts of either state. Normal sleep physiology is currently understood as dependent upon the coordination of the interactions of facilitating sleep centers and inhibiting arousal centers in the brain, such that stable sleep and wake states are maintained for specific durations (Nishino et al., 2004b). An ascending arousal pathway, running from the rostal pons and through the midbrain reticular formation, promotes wakefulness (Nishino et al., 2004b; Saper et al., 2005). This arousal pathway may be composed of neuro­ transmitters (acetylcholine, NE, DA, excitatory amino acids), produced by brain­ stem and hypothalamic neurons (hypocretin/orexin and histamine) and also linked to muscle tonus control during sleep (Nishino et al., 2004b; Saper et al., 2005). Whereas full alertness and cortical activation require coordination of these arousal networks, effective sleep requires suppression of arousal by the hypothalamus (Saper et al., 2005). Narcolepsy patients may experience a major neurolo­ gical malfunction of this control system. Narcoleptics exhibit a phenomenon, termed short REM sleep latency or sleep onset REM period (SOREMP), in which REM sleep is entered more immedi­ ately upon falling asleep than is normal (Nishino and Mignot, 1997). In some cases, NREM sleep is completely bypassed and the transition to REM sleep occurs instantly (Nishino and Mignot, 1997). Moreover, intrusion of REM sleep into wakefulness may explain the cata­ plexy, sleep paralysis, and hypnagogic hallucinations which are cardinal symp­ toms of narcolepsy. Significantly, however, whereas paralysis and hallucinations are manifest in other sleep disorders (sleep apnea syndromes and disturbed sleep patterns in normal population) (Aldrich et al., 1997), cataplexy is pathognomonic for narcolepsy (Nishino and Mignot, 1997). As such, identifying cataplexy’s unique pathophysiological mechanism emerged as potentially pivotal to describ­ ing the pathology underlying narcolepsy overall. More than 90% of patients diagnosed with narcolepsy receive pharmacological treatments. The pharmacological treatments of EDS include amphetamine-like central nervous system (CNS) stimulants and modafinil (and its r-enantiomer), but these are symptomatic treatments and do not cure the disease, and often unsatis­ factory for some patients due to the side effects and incomplete efficacy (see Nishino and Mignot, 2005).



IV. Discovery of Hypocretin Deficiency and Postnatal Cell Death of Hypocretin Neurons

The significant roles of, first, hypocretin deficiency and, subsequently, post­ natal cell death of hypocretin neurons as the major pathophysiological process underlying narcolepsy with cataplexy emerged from a decade of investigation, employing both animal and human models. In 1998, the simultaneous discovery by two independent research groups of a novel hypothalamic peptide neuro­ transmitter (variously named hypocretin and orexin) proved pivotal (De Lecea et al., 1998; Sakurai et al., 1998) (Fig. 1). These neurotransmitters are produced A.

signal sequence



Propro-hypocretin (Prepro-orexin)

Hypocretin-1 (Orexin A)

Hypocretin-2 (Orexin B) HcrtR2 (OX2R)

HcrtR1 (OX1R) Receptors

Gq Gi/Go



Acetylcholine Noradrenalin Serotonin Dopamine Histamine

Cortex Thalamus (1=2)





LDT PPT LC (1 only)



(1=2) Glu

Hcrt LHA


Activation Inhibition


TMN (2 only)


RF (1=2) (1<2)



Spinal cord



exclusively by thousands of neurons, which are localized in the lateral hypotha­ lamus and project broadly to specific cerebral regions and more densely to others (Peyron et al., 1998) (Fig. 1). Within a year, Stanford researchers, using positional cloning of a naturally occurring familial canine narcolepsy model, identified an autosomal recessive mutation of hypocretin receptor 2 (Hcrtr 2) responsible for canine narcolepsy, characterized by cataplexy, reduced sleep latency, and SOREMPs (Lin et al., 1999). This finding coincided with the simultaneous observation of the narco­ lepsy phenotype, characterized by cataplexic behavior and sleep fragmentation, in hypocretin ligand-deficient mice (prepro-orexin gene knockout mice) (Chemelli et al., 1999). Together, these findings confirmed hypocretins as princi­ pal sleep-modulating neurotransmitters and prompted the investigation of hypocretin system involvement in human narcolepsy. Although screening of patients with cataplexy failed to implicate hypocretin­ related gene mutations as a major cause of human narcolepsy, narcoleptic patients did exhibit low cerebrospinal fluid (CSF) levels of hypocretin-1 (Nishino et al., 2000) (Fig. 2). Postmortem brain tissue of narcoleptic patients, assessed through immunochemistry, radioimmunological peptide assays, and in situ hybridization, revealed hypocretin peptide loss and undetectable levels of hypocretin peptides or pre-hypocretin RNA (Fig. 2). Further, melanin-concentrating hormone neurons, normal to the same brain region (Peyron et al., 2000), were observed intact, thus indicating that damage to hypocretin neurons and produc­ tion is selective in narcolepsy, rather than due to generalized neuronal degeneration. As a result of these findings, a diagnostic test for narcolepsy, based on clinical measurement of CSF hypocretin-1 and detected hypocretin ligand deficiency, is now available (ICSD-2, 2005). Whereas CSF hypocretin-1 concentrations above 200 pg/ml almost always occur in controls and patients with other sleep and neurological disorders, concentrations below 110 pg/ml are 94% predictive of

FIG. 1. (A) Structures of mature hypocretin-1 (orexin-A) and hypocretin-2 (orexin-B) peptides. (B) Schematic representation of the hypocretin (orexin) system. (A) The topology of the two intrachain disulfide bonds in orexin-A is indicated in the above sequence. Amino acid identities are indicated by shaded areas. (B) The actions of hypocretins are mediated via two G protein-coupled receptors named hypocretin receptor 1 (Hcrtr 1) and hypocretin receptor 2 (Hcrtr 2), also known as orexin-1 (OX1R) and orexin-2 (OX2R) receptors, respectively. Hcrtr 1 is selective for hypocretin-1, whereas Hcrtr 2 is nonselective for both hypocretin-1 and hypocretin-2. Hcrtr 1 is coupled exclusively to the Gq subclass of heterotrimeric G proteins, whereas in vitro experiments suggest that Hcrtr 2 couples with Gi/o, and/ or Gq (adapted from Sakurai Sakurai, 2002) VTA, ventral tegmental area; SN, substantia nigra; LC, locus coeruleus; LDT, laterodorsal tegmental nucleus; PPT, pedunculopontine tegmental nucleus; RF, reticular formation; BF, basal forebrain; VLPO, ventrolateral preoptic nucleus; LHA, lateral hypothalamic area; TMN, tuberomamillary nucleus; DR, dorsal raphe; Ach, acetylcholine; Glu, glutamate; GABA, gamma-aminobutyric acid.




CSF Hypocretin 1 Levels (pg/ml)




Familial case



400 DQB1*0602 (-)



200 DQB1*0602 (-)

0 Narcolepsy Neurological (n=38) Control (n=19)

Control (n=15)



FIG. 2. Hypocretin deficiency in narcoleptic subjects. (A) CSF hypocretin-1 levels are undetectably low in most narcoleptic subjects (84.2%). Note that two HLA DqB1*0602-negative and one familial case have normal or high CSF hypocretin levels. (B) Preprohypocretin transcripts are detected in the hypothalamus of control (b) but not in narcoleptic subjects (a). Melaninconcentrating hormone (MCH) transcripts are detected in the same region in both control (d) and narcoleptic (c) sections. f and fx, fornix. Scale bar represents 10 mm (a–d), (adapted from Peyron et al., 2000).

narcolepsy with cataplexy (Mignot et al., 2002). As this represents a more specific assessment than the multiple sleep latency test (MSLT), CFS hypocretin-1 levels below 110 pg/ml are indicated in the ICSD-2 as diagnostic of narcolepsy with cataplexy (ICSD-2, 2005). Moreover, separate coding of “narcolepsy with cataplexy” and “narcolepsy without cataplexy” in the ICSD-2 underscores how the discovery of specific diagnostic criteria now informs our understanding of narcolepsy’s nosology; narcolepsy with cataplexy, as indicated by low CSF hypocretin-1, appears etio­ logically hom*ogeneous and distinct from narcolepsy without cataplexy, exhibited by normal hypocretin levels (Mignot et al., 2002). Further, the potential of hypocretin receptor agonists (or cell transplantation) in narcolepsy treatment is currently being explored, and CFS hypocretin-1 measures may be useful in identifying appropriate patients for a novel therapeutic option, namely hypocre­ tin replacement therapy. Soon after the discovery of human hypocretin deficiency, researchers identified specific substances and genes, such as dynorphin and neuronal activity-regulated pentraxin (NARP) (Crocker et al., 2005) and, most recently, insulin-like growth factor binding protein 3 (IGF BP3) (Honda et al., 2009), which colocalize in neurons containing hypocretin. These findings underscored selective hypocretin cell death



as the cause of hypocretin deficiency (as opposed to transcription/biosynthesis or hypocretin peptide processing problems) because these substances are also deficient in the postmortem brain lateral hypothalamic area (LHA) of hypocretin deficient narcoleptic patients (Crocker et al., 2005; Honda et al., 2009). Further, these findings, in view of the generally late onsets of sporadic narcolepsy compared with those of familial cases, suggest that postnatal cell death of hypocretin neurons constitutes the major pathophysiological process in human narcolepsy with cataplexy. Narcolepsy is associated with the human leukocyte antigen (HLA)­ DQB1*0602 allele (Mignot et al., 1997). Many have therefore hypothesized that narcolepsy is caused by an autoimmune process that kills the hypocretin/orexin­ producing neurons. This perspective was further reinforced recently by the observation that narcolepsy is also associated with a polymorphism in the T-cell receptor alpha gene (Hallmayer et al., 2009), but still, direct evidence for an autoimmune process has been lacking. Quite interestingly, Cvetkovic-Lopes et al. (2010) found that some patients with narcolepsy have elevated levels of antibodies against a protein known as Tribbles hom*olog 2 (TRIB2) (Fig. 3). TRIB2 is produced in hypocretin neurons, and TRIB2 is also known to be a potential autoimmune target in some patients with autoimmune uveitis. Anti­ TRIB2 titers seemed higher in the first 2 years after the onset of narcolepsy. The results were immediately replicated with two independent studies (Kawashima et al., 2010; Toyoda et al., 2010), and these exciting researches may be leading toward some of the firmest evidence yet for an autoimmune cause of narcolepsy. The possibility that TRIB2 antibodies are a consequence of hypocretin neuron loss and not a cause should further be evaluated (see Lim and Scammell, 2010). Hypocretin targeted therapy, such as hypocretin replacement therapy, is awaited for the treatments of hypocretin deficient narcolepsy/EDS, but as of yet is not available. Attempts to treat narcolepsy patients at the disease onset with immunotherapy, including plasma changes and IVIG with some positive results, is reported in small case reports (Chen et al., 2005; Dauvilliers et al., 2004; Plazzi et al., 2008). However since no control studies have been done yet, further evaluations are critical.

V. Idiopathic Hypersomnia, Hypocretin Non-deficient Primary Hypersomnia

With the clear definition of narcolepsy (cataplexy and dissociated manifesta­ tions of REM sleep), it became apparent that some patients with hypersomnia suffer from a different disorder. Bedrich Roth was the first in the late 1950s and early 1960s to describe a syndrome characterized by EDS: prolonged sleep and sleep drunkenness with the absence of “sleep attacks,” cataplexy, sleep paralysis,

2.6 P < 3 x10–9


Relative Trib2-specific antibody titer


P < 0.0001


P < 0.01


P < 0.001


P < 0.01

1.4 1.2 1 0.8 0.6 0.4 Narcolepsy Cataplexy

Narcolepsy without cataplexy


Idiopathic hypersomnia

Multiple sclerosis


FIG. 3. ELISA determination of Trib2-specific antibodies in sera. Each symbol corresponds to the serum of a single subject. Mean + 1 SD of each group is shown next to the individual values. The dotted horizontal line indicates the mean Trib2-specific antibody titer in healthy control subjects plus 2 SD. All values are relative to the optical density of a healthy control subject (which is equal to 1). P values correspond to independent t-tests between indicated groups. OIND, other inflammatory neurological diseases (from Cvetkovic-Lopes et al., 2010).



and hallucinations. Although the terms “independent sleep drunkenness” and “hypersomnia with sleep drunkenness” were initially suggested (Roth, 1962), this syndrome is now categorized as idiopathic hypersomnia with and without long sleep time (ICSD-2, 2005). Idiopathic hypersomnia should not be considered synonymous with hypersomnia of unknown origin. In the absence of systematic studies, the prevalence of idiopathic hypersomnia is unknown. Nosologic uncertainty causes difficulty in determining the epide­ miology of the disorder. Recent reports from large sleep centers reported a 1:10 ratio of idiopathic hypersomnia to narcolepsy (Bassetti and Aldrich, 1997). The age of onset of symptoms varies, but is frequently between 10 and 30 years. The condition usually develops progressively over several weeks or months. Once established, symptoms are generally stable and long lasting, but spontaneous improvement in EDS may be observed in up to one quarter of patients (Bassetti and Aldrich, 1997). The pathogenesis of idiopathic hypersomnia is unknown. Hypersomnia usually starts insidiously. Occasionally, EDS is first experienced after transient insomnia, abrupt changes in sleep–wake habits, overexertion, general anesthesia, viral illness, or mild head trauma (Bassetti and Aldrich, 1997). Despite reports of an increase in HLA DQ1, 11 DR5, Cw2, and DQ3, and of a decrease in Cw3, no consistent findings have emerged (Bassetti and Aldrich, 1997). The most recent attempts to understand the pathophysiology of idiopathic hypersomnia relate to the potential role of the hypocretins. However, most studies suggest normal CSF levels of hypocretin-1 in idiopathic hypersomnia (Bassetti et al., 2003; Mignot et al., 2002). Thus, it is now confirmed that the pathophysiology of idiopathic hypersomnia is distinct from that of narcolepsy.

VI. Symptomatic Narcolepsy and Hypersomnia: Hypocretin Involvements

Narcolepsy symptoms can also occur during the course of other neurological conditions (i.e., symptomatic narcolepsy), and the discovery of hypocretin ligand deficiency in idiopathic narcolepsy has led to new insights into the pathophysiol­ ogy of symptomatic (or secondary) narcolepsy and EDS. In a recent meta-analysis, 116 symptomatic narcolepsy cases reported in the literature were analyzed (Nishino and Kanbayashi, 2005). As several authors have previously reported, inherited disorder (n = 38), tumors (n = 33), and head trauma (n = 19) are the three most frequent causes for symptomatic narcolepsy. Of the 116 cases, 10 are associated with multiple sclerosis (MS), one with acute disseminated encephalomyelitis, and relatively few with vascular disorders (n = 6), encephalitis (n = 4), degeneration (n = 1), and heterodegenerative disorder (autosomal



dominant cerebrospinal ataxia w/deafness, three cases in one family). Although it is difficult to rule out the comorbidity of idiopathic narcolepsy in some cases, literature review reveals numerous unquestionable cases of symptomatic narco­ lepsy (Nishino and Kanbayashi, 2005). These include cases with HLA negative and/or late onset and cases where occurrence of narcoleptic symptoms parallels the rise and fall of the causative disease. Notably, the review of these cases (particularly those with brain tumors) clearly illustrates that the hypothalamus is most often involved (Nishino and Kanbayashi, 2005). Also, quite a few EDS cases without cataplexy or REM sleep abnormalities (defined as symptomatic cases) are associated with these neurological conditions (Nishino and Kanbayashi, 2005). While the same review lists about 70 sympto­ matic EDS cases, prevalence of symptomatic EDS is likely much higher. For example, several million USA subjects suffered chronic brain injury, and 75% experienced sleep problems and about 50% reported sleepiness (Verma et al., 2007). Thus, symptomatic EDS may have significant clinical relevance. CSF hypocretin-1 measurement was also conducted in these symptomatic narcolepsy and EDS cases, and reduced CSF hypocretin-1 levels were noted in most with various etiologies (Nishino and Kanbayashi, 2005). EDS in these cases is sometimes reversible with an improvement of the causative neurological dis­ order or hypocretin status, thus suggesting a functional link between hypocretin deficiency and sleep symptoms in these patients. Low CSF hypocretin-1 concentrations were also found in some immunemediated neurological conditions, namely subsets of Guillain–Barre syndrome (Nishino et al., 2003), Ma2-positive paraneoplastic syndrome (Overeem et al., 2001), and MS (Nishino and Kanbayashi, 2005), and EDS is often associated with the patients with low CSF hypocretin-1 levels. Of note, Kanbayashi et al. (2009b) recently experienced seven cases of EDS occurring in the course of MS patients initially diagnosed with symmetrical hypothalamic inflammatory lesions together with hypocretin ligand deficiency that contrasts with the characteristics of classic MS cases (Fig. 4). Symptomatic narcolepsy in MS patients has been reported for several dec­ ades. Since both MS and narcolepsy are associated with the HLA-DR2 positivity, an autoimmune target on the same brain structures has been proposed to be a common etiology for both diseases (Poirier et al., 1987). However, the discovery of the selective loss of hypothalamic hypocretin neurons in narcolepsy rather indi­ cates that narcolepsy coincidently occurs in MS patients when MS plaques appear in the hypothalamic area and secondarily damage the hypocretin/orexin neurons. In favor of this interpretation, the hypocretin systems are not impaired in MS subjects who do not exhibit narcolepsy (Ripley et al., 2001b), although MS patients frequently show other sleep problems such as insomnia, parasomnia, and sleep-related movement disorders (Tachibana et al., 1994). Nevertheless, it is also the case that a subset of MS patients predominantly show EDS and REM sleep




MRI scan gender/age hcrt-1 level (pg/mL)


FLAIR F/45* < 40



MRI scan gender/age hcrt-1 level (pg/mL) Anti-AQP4


FLAIR F/43** 190 Anti-AQP4 (+)


FLAIR F/21* < 40


T2 F/45* 106

FLAIR M/61 173

Anti-AQP4 (+)


T2 F/45* 91

FLAIR F/54** 184

Anti-AQP4 (+)

FIG. 4. Magnetic resonance imaging findings (FLAIR or T2) of MS/NMO patients with hypocretin deficiency and EDS. A typical horizontal slice including the hypothalamic periventricular area from each case is presented. The gender (male [M] and female [F]), ages (years), as well as CSF hypocretin levels are listed below the MRI image. All cases were initially diagnosed as MS. Cases 3–5 exhibited optic neuritis and/or spinal cord lesions and are seropositive for anti-AQP4 antibody and thus being diagnosed as NMO. *Met with ICSD-2 criteria for narcolepsy because of medical condition, and **met with ICSD-2 criteria for hypersomnia because of medical condition.

abnormalities, and it is likely that specific immune-mediated mechanisms may be involved in these cases. CSF hypocretin measures revealed that marked (110 pg/ml, n = 3) or moderate (110–200 pg/ml, n = 4) hypocretin deficiency was observed in all seven cases (Kanbayashi et al., 2009b). Therefore, four cases met with ICSDII criteria (ICSD-2, 2005) for narcolepsy due to a medical condition, and three cases met with the hypersomnia criteria due to a medical condi­ tion. Interestingly, four of them had either or both optic neuritis and spinal cord lesions, sharing the clinical characteristics of Neuromyelitis optica (NMO). HLA was evaluated in only two cases (case 2 and case 4) and was



negative for DQB1*0602. Repeated evaluations of the hypocretin status were carried out in six cases, and CSF hypocretin-1 levels returned to the normal levels or significantly increased with marked improvements of EDS and hypothalamic lesions in all six cases. Since four of them exhibited clinical characterization of NMO, anti-AQP4 antibody was evaluated and it was found that three out of seven cases were anti-AQP4 antibody positive, thus being diagnosed as an NMO-related disorder (Kanbayashi et al., 2009b). AQP4, a member of the AQP super-family, is an integral membrane protein that forms pores in the membrane of biological cells (Amiry-Moghaddam and Ottersen, 2003). Aquaporins selectively conduct water molecules in and out of the cell while preventing the passage of ions and other solutes and are known as water channels. AQP4 is expressed throughout the central nervous system, especially in periaqueductal and periventricular regions (Amiry-Moghaddam and Ottersen, 2003; Pittock et al., 2006) and is found in non-neuronal structures such as astrocytes and ependymocytes, but is absent from neurons. Recently, the NMO-IgG, which can be detected in the serum of patients with NMO, has been shown to selectively bind to AQP4 (Lennon et al., 2005). Since AQP4 is enriched in periventricular regions in the hypothalamus where hypocretin-containing neurons are primarily located, symmetrical hypothalamic lesions associated with reduced CSF hypocretin-1 levels in our three NMO cases with anti-AQP4 antibody might be caused by the immuno-attack to the AQP4, and this may secondarily affect the hypocretin neurons. However, another four MS cases with EDS and hypocretin deficiency were anti-AQP4 antibody negative at the time of blood testing. This leaves a possibility that other antibody-mediated mechanisms are additionally respon­ sible for the bilateral symmetric hypothalamic damage causing EDS in the MS/NMO subjects. There is a possibility that the four MS cases whose anti­ AQP4 antibody was negative could be NMO, since anti-AQP4 antibody was tested only once for each subject during the course of the disease and the assay was not standardized among the institutes (Kanbayashi et al., 2009b). It is thus essential to further determine the immunological mechanisms that cause the bilateral hypothalamic lesions with hypocretin deficiency and EDS and their association with NMO and AQP4. This effort may lead to estab­ lishment of a new clinical entity, and the knowledge is essential to prevent and treat EDS associated with MS and its related disorders. It should also be noted that none of these cases exhibited cataplexy, contrary to the 9 out of 10 symptomatic narcoleptic MS cases reported in the past (Nishino and Kanbayashi, 2005). Early therapeutic intervention with steroids and other immunosuppressants may thus prevent irreversible damage of hypocretin neurons and prevent chronic sleep-related symptoms.



VII. How Does Hypocretin Ligand Deficiency Cause the Narcolepsy Phenotype?

Because hypocretin deficiency is a major pathophysiological mechanism in narcolepsy-cataplexy, some discussion of how hypocretin ligand deficiency may cause the narcolepsy phenotype is warranted.




Hypocretins/orexins were discovered by two independent research groups in 1998. One group called the peptides “hypocretin” because of their primary hypotha­ lamic localization and similarities with the hormone “secretin” (De Lecea et al., 1998). The other group called the molecules “orexin” after observing that central administration of these peptides increased appetite in rats (Sakurai et al., 1998). Hypocretins/orexins (hypocretin-1 and hypocretin-2/Orexin-A and Orexin-B) are cleaved from a precursor preprohypocretin (prepro-orexin) peptide (De Lecea et al., 1998; Sakurai, 2002; Sakurai et al., 1998)). Hypocretin-1 with 33 residues contains four cysteine residues forming two disulfide bonds. Hypocretin-2 consists of 28 amino acids and shares similar sequence hom*ology, especially at the C-terminal side, but has no disulfide bonds (a linear peptide) (Sakurai et al., 1998). There are two G-protein-coupled hypocretin receptors—Hcrtr 1 and Hcrtr 2, also called orexin receptor 1 and 2 (OX1R and OX2R). The distinct distribution of these receptors in the brain is known: Hcrtr 1 is abundant in the locus coeruleus (LC) and Hcrtr 2 is found in the tuberomamillary nucleus (TMN) and basal forebrain. Both receptor types are found in the midbrain raphe nuclei and mesopontine reticular formation (Marcus et al., 2001). Hypocretins-1 and -2 are produced exclusively by a well-defined group of neurons localized in the lateral hypothalamus. The neurons project to the olfactory bulb, cerebral cortex, thalamus, hypothalamus, and brainstem, parti­ cularly the LC, raphe nucleus, as well as to the cholinergic nuclei (the laterodorsal tegmental and pedunculopontine tegmental nuclei) and cholinoceptive sites (such as pontine reticular formation), which are thought to be important for sleep regulation (Peyron et al., 1998; Sakurai, 2002). A series of recent studies have now shown that the hypocretin system is a major excitatory system, which affects the activity of monoaminergic (dopamine [DA], norepinephrine [NE], serotonin [5-HT] and histamine) and cholinergic systems, significantly affecting vigilance states (Sakurai, 2002; Willie et al., 2001). Thus, it is likely that a deficiency in hypocretin neurotransmission induces an imbalance between these classic neurotransmitter systems, with primary effects on sleep-state organization and vigilance.



Many measurable activities (brain and body) and compounds manifest rhyth­ mic fluctuations over a 24-h period. Whether or not hypocretin tone changes with Zeitgeber time was assessed by measuring extracellular hypocretin-1 levels in the rat brain CSF across 24-h periods, using in vivo dialysis (Yoshida et al., 2001). The results demonstrate the involvement of a slow diurnal pattern of hypocretin neurotransmission regulation (as in the homeostatic and/or circadian regulation of sleep). Hypocretin levels increase during the active periods and are highest at the end of the active period, with the levels declining at sleep onset. Furthermore, sleep deprivation increases hypocretin levels (Yoshida et al., 2001). Electrophysiological studies have shown that hypocretin neurons are active during wakefulness and reduce the activity during slow wave (Lee et al., 2005). The neuronal activity during REM sleep is the lowest, but intermittent increases in the activity, associated with body movements or phasic REM activity, are observed (Lee et al., 2005). In addition to this short-term change, the results of microdialysis experiments also suggest that basic hypocretin neurotransmission fluctuates across the 24-h period and slowly builds up toward the end of the active period. Adrener­ gic LC neurons are typical wake-active neurons, involved in vigilance control, and it has been demonstrated that basic firing activity of wake-active LC neurons also significantly fluctuates across various circadian times (Aston-Jones et al., 2001).




Human studies have demonstrated that the occurrence of cataplexy is closely associated with hypocretin deficiency (Mignot et al., 2002). Furthermore, the hypocretin deficiency was already observed at very early stages of the disease ( just after the onset of EDS), even before the occurrences of clear cataplexy. Occurrences of cataplexy are rare in acute symptomatic cases of EDS, associated with a significant hypocretin deficiency (see Nishino and Kanbayashi, 2005); therefore, it appears that a chronic and selective deficit of hypocretin neuro­ transmission may be required for the occurrence of cataplexy. The possibility of an involvement of a secondary neurochemical change, related to the occurrence of cataplexy, cannot be ruled out. If some of these changes are irreversible, hypocretin supplement therapy may only have limited effects on cataplexy. Sleepiness in narcolepsy is most likely due to the patients’ difficulty in main­ taining wakefulness as normal subjects do. The sleep pattern of narcoleptic subjects is also fragmented; they exhibit insomnia (frequent wakening) at night. This fragmentation occurs across 24 h, and, thus, the loss of hypocretin signaling likely plays a role in this vigilance stage stability (see Saper et al., 2001), but other mechanism may also be involved in EDS in narcoleptic subjects. One of the most



important characteristics of EDS in narcolepsy is that sleepiness is reduced, and patients feel refreshed after a short nap; however, but this does not last long and patients become sleepy within a short period of time. Hypocretin-1 levels in the extracellular space and in the CSF of rats fluctuate significantly across 24 h and build up toward the end of the active periods (Yoshida et al., 2001). Several manipulations (such as sleep deprivation, exercise, and long-term food depriva­ tion) are also known to increase hypocretin tonus (Fujiki et al., 2001; Yoshida et al., 2001). Thus, the lack of this hypocretin build-up (or increase), caused by circadian time and by various alerting stimulations, may also play a role in EDS associated with hypocretin deficient narcolepsy. Mechanisms for cataplexy and REM sleep abnormalities, associated with impaired hypocretin neurotransmission, have been studied. Hypocretin signifi­ cantly inhibits REM sleep in vivo, but could activate all brainstem REM-off LC neurons, REM-off raphe neurons, and REM-on cholinergic neurons as well as local GABAnergic neurons in vitro preparations. It is proposed that disinhibition (rather than disfacillitation) of REM-on cholinergic neurons, which are mediated through disfacillitation of inhibitory GABAnergic interneurons together with disfacillitation of REM-off monoaminergic neurons are responsible for the occurrences of abnormal manifestations of REM sleep in hypocretin deficient narcolepsy (Koyama, a personal communication).

VIII. Considerations for the Pathophysiology of Narcolepsy with Normal Hypocretin Levels

The pathophysiology of narcolepsy with normal hypocretin levels is currently debated. Over 90% patients with narcolepsy without cataplexy exhibit normal CSF hypocretin levels, yet they also present REM sleep abnormalities (i.e., SOREMS). Moreover, even when strict criteria for narcolepsy-cataplexy are applied, up to 10% of patients with narcolepsy-cataplexy show normal CSF hypocretin levels. Considering the fact that occurrence of cataplexy is tightly associated with hypocretin deficiency, impaired hypocretin neurotransmission is still likely involved in narcolepsy with normal CSF hypocretin levels. Concep­ tually, there are two potential explanations for these mechanisms: (1) specific impairment of hypocretin receptor and their downstream pathway and (2) partial/localized loss of hypocretin ligand (yet exhibition of normal CSF levels). A good example for the first explanation is provided by Hcrtr 2-mutated narco­ leptic dogs, which exhibit normal CSF hypocretin-1 levels (Ripley et al., 2001a), while having full blown narcolepsy. Thannickal et al. (2009) recently reported one narcolepsy without cataplexy patient, who had an overall loss of 33% of hypocretin cells (compared to normal) with maximal cell loss in the posterior



hypothalamus. This result is more supportive of the second hypothesis, but further case studies are needed.

IX. Changes in Other Neurotransmitter Systems in Narcolepsy and Idiopathic







Studies in humans with narcolepsy have shown a decrease in DA concentration in the CSF (Montplaisir et al., 1982). Studies on Hcrtr 2-mutated narcoleptic dogs, performed before and after probenecid administration, demonstrated an altered monoamine turnover with significantly less free hom*ovanillic acid (HVA), dihy­ droxyphenylacetic acid (DOPAC), 3-methoxy-4-hydroxyphenylglycol (MHPG), and 5-hydroxyindoleacetic acid (5-HIAA) (Faull et al., 1986). The lower concentration of 5-HIAA in the CSF of narcoleptic dogs suggests a decreased concentration of the parent amine 5-HT, a decreased turnover of 5-HT in the brain, or both. Similarly, the lower steady-state CSF of HVA and DOPAC, as well as the reduced accumulation of DOPAC and HVA after probenecid, suggests decreased DA concentration, decreased turnover, or both. Finally, the lower concentration of MHPG after probenecid administration suggests decreased NE activity. Analyses of both human and animal narcoleptic brain tissue also suggest dopaminergic dysfunction. In postmortem human autoradiographic studies, striatal DA D2 receptor binding was increased in narcolepsy, more so than D1 receptors. (Aldrich et al., 1992) However, most in vivo studies with single-photon emission computed tomography (Hublin et al., 1994) and positron emission tomography (Rinne et al., 1995) found no increase in striatal D2 receptor binding in narcolepsy. Pharmacological studies demonstrated that narcoleptic canines are very sensitive to alpha-1b blockade and alpha-2 stimulation (as well as DA D2/D3 stimulation) and exhibit cataplexy (Nishino and Mignot, 1997). Also, they are sensitive to cholinergic M2/3 stimulation and exhibit cataplexy, and upregula­ tion of muscarinic receptors in the pons was reported (see Nishino and Mignot, 1997). Three independent studies reported altered catecholamine contents in the brains of narcoleptic dogs (Faull et al., 1986; Mefford et al., 1983). These studies found increases in DA and NE in many brain structures, especially DA in the amygdala and NE in the pontis reticularis oralis (Faull et al., 1986; Mefford et al., 1983). These changes are not due to the reduction in the turnover of these monoamines in the brain, since the turnover of these monoamines is either rather



high or not altered (Nishino et al., 2001). Considering the fact that the drugs, which enhance dopaminergic neurotransmission (such as amphetamine-like sti­ mulants and modafinil [for EDS]) and NE neurotransmission (such as noradrena­ line uptake blockers [for cataplexy]), are needed to treat the symptoms in these animals (Nishino and Mignot, 1997), increases in DA and NE contents in the brain may be compensatory—mediated either by Hcrtr 1 or by other neuro­ transmitter systems; however, these findings are not consistent with the CSF findings. Most of these abnormalities are likely secondary to the deficiency in hypocretin neurotransmission, but alterations in these systems may actively mediate some of sleep-related symptoms of narcolepsy. The most recent neurochemical studies in canine narcolepsy specifically pointed to the involvement of histamine in narcolepsy. Histamine content in the brain was measured in genetically narcoleptic (n = 9) and control Dobermans (n = 9). As a reference, contents of DA, NE, and 5HT and their metabolites were also measured (Nishino et al., 2001). The histamine content in the cortex and thalamus (the areas important in the control of wakefulness via histami­ nergic input) was significantly lower in narcoleptic Dobermans compared to controls (Fig. 4). Considering the fact that hypocretins strongly excite TMN histaminergic neurons in vitro through Hcrtr2 stimulation (Eriksson et al., 2001; Yamanaka et al., 2002), the decrease in histaminergic content, found in narcoleptic dogs, may be due to the lack of excitatory input of hypocretin on TMN histaminergic neurons. Uncompensated low histamine levels in narcolepsy may suggest that the hypocretin system may be the major excitatory input to histaminergic neurons (through Hcrtr2). Histamine in the brains was also measured in three sporadic (ligand-deficient) narcoleptic dogs, and it was found that the histamine content in these animals was also as low as the Hcrtr2-mutated narcoleptic Dobermans (Nishino et al., 2001), thus suggesting that a decrease in histamine neurotransmission may also exist in ligand-deficient human narcolepsy.

B. IDIOPATHIC HYPERSOMNIA CSF analyses in idiopathic hypersomnia have shown normal cell counts, cytology, and protein content. Montplaisir and coworkers found a decrease in DA and indoleacetic acid in both patients with idiopathic hypersomnia and those with narcolepsy (Montplaisir et al., 1982). Faull and colleagues found similar mean concentrations of monoamine metabolites in subjects with narcolepsy or idiopathic hypersomnia and with controls; however, using a principal component



analysis, they also found a dysregulation of the DA system in narcolepsy and of the NE system in idiopathic hypersomnia (Faull et al., 1983). These metabolic data may support the hypothesis of a primary deficient arousal system in patients with idiopathic hypersomnia.

X. Involvements of Histaminergic Neurotransmission in Human Narcolepsy and Other


Research evidence suggests that central histaminergic neurotransmission is involved in the control of vigilance (see Lin, 2000 for review). Clinically, it is widely known that histaminergic H1 blockers, such as promethazine or diphen­ hydramine, produce sedation, sleep, and temporal disruptions of attention and cognition. These effects are less prominent with the 2nd generation of H1 blockers with low central penetration. The 1st generation H1 blockers, such as diphenhydramine and doxylamine, are available as over-the-counter hypnotics. Histamine neurons are located exclusively in the TMN of the posterior hypothalamus, from where they project to practically all brain regions, including areas important for vigilance control, such as the hypothalamus, basal forebrain, thalamus, cortex, and brainstem structures (see Haas and Panula, 2003 for review). A series of experimental evidence had suggested that Hcrtr 2-mediated function plays more critical roles (over hcrtr1-mediated function) in generating narcoleptic symptoms in animals (Lin et al., 1999; Ripley et al., 2001a). The TMN exclusively expresses Hcrtr 2 (Marcus et al., 2001), and a series of electrophysio­ logical studies consistently demonstrated that hypocretin potently excites TMN histaminergic neurons through Hcrtr 2 (Eriksson et al., 2001; Yamanaka et al., 2002). Furthermore, it has been demonstrated that the wake-promoting effects of hypocretins were totally abolished in histamine H1 receptor KO mice, suggesting that the wake-promoting effects of hypocretin are dependent on the histaminergic neurotransmission (Huang et al., 2001). Extracellular histamine levels in the hypothalamus of rats show a clear diurnal variation: high during the active period and low during the resting period (Mochizuki et al., 1992). Histamine levels in the preoptic anterior hypothalamus in cats were also high during sleep deprivation and became lower during recovery sleep (Strecker et al., 2002), the findings similar to those of extracellular levels of hypocretin-1 (Yoshida et al., 2001). The animal experiment demonstrated that the changes in the brain extracellular histamine levels associated with diurnal and sleep/wake changes are also reflected in the CSF histamine levels (Soya et al., 2008), suggesting that CSF histamine levels at least partially reflect the central histamine neurotransmission and vigilance state changes. There were two clinical studies that evaluated the CSF histamine in



human narcolepsy. The first study included narcolepsy with low CSF hypocretin-1 (£110 pg/ml, n = 34, 100% with cataplexy), narcolepsy without low CSF hypocretin-1 (n = 24, 75% with cataplexy), and normal controls (n = 23) (Nishino et al., 2009b). Narcoleptic subjects with and without hypocretin deficiency were included in order to determine if histamine neurotransmission is dependent on the hypocretin status of each subject. A significant reduction of CSF histamine levels was found in the cases with low CSF hypocretin-1, and levels were intermediate in other narcolepsy cases: Mean CSF histamine levels were 133.2 + 20.1 pg/ml in narcoleptic subjects with low CSF hypocretin­ 1, 233.3 + 46.5 pg/ml in patients with normal CSF hypocretin-1, and 300.5 + 49.7 pg/ml in controls. The results suggest the impaired histaminergic neurotransmission in human narcolepsy, but this is not entirely dependant on the hypocretin deficient status. We also examined CSF histamine levels in narcolepsy and other sleep disorders in a Japanese population. This second clinical study included 67 narcolepsy subjects, 26 idiopathic hypersomnia (IHS) subjects, 16 obstructive sleep apnea syndrome (OSAS) subjects, and 73 neurological controls (Kanbayashi et al., 2009a). We found significant reductions in CSF histamine levels in hypocretin deficient narcolepsy with cataplexy (mean + SEM; 176.0 +25.8 pg/ml), hypocretin non-deficient narcolepsy with cataplexy (97.8 + 38.4 pg/ml), hypocretin non-deficient narcolepsy without cataplexy (113.6 + 16.4 pg/ml), and idiopathic hypersomnia (161.0 + 29.3 pg/ml), while the levels in OSAS (259.3 + 46.6 pg/ ml) did not statistically differ from those in the controls (333.8 +22.0 pg/ml) (Fig. 5). Low CSF histamine levels were mostly observed in non-medicated patients, and significant reductions in histamine levels were evident in nonmedicated patients with hypocretin deficient narcolepsy with cataplexy (112.1 + 16.3 pg/ml) and idiopathic hypersomnia (143.3 + 28.8 pg/ml), while the levels in the medicated patients were in the normal range. Similar degrees of reduction, as seen in hypocretin deficient narcolepsy with cataplexy, were also observed in hypocretin non-deficient narcolepsy and in idiopathic hypersomnia, while those in OSAS (non-central nervous system hypersomnia) were not altered. These results confirmed the result of the first study, but further suggest that an impaired histaminergic system may be involved in mediating sleepiness in a much broader category of patients with EDS than hypocretin deficient narcolepsy cases. The decrease in histamine in these subjects was more specifically observed in non-medicated subjects, suggesting CSF histamine is a biomarker, reflecting the degree of hypersomnia of central origin. It is not known if decreased hista­ mine could either passively reflect or partially mediate daytime sleepiness in these pathologies. Further studies are essential, since central histaminomimetic com­ pounds, such as H3 antagonists, may be developed as a new class of wakepromoting compounds for EDS with various etiologies.


NISHINO AND SAGAWA CSF histamine levels (pg/ml)

CSF Hcrt-1 levels (pg/ml) 0












(A)Neurological controls (B1)Hcrt- / N / C / med­


(B2)Hcrt- / N / C / med+ (C)Hcrt+ / N / C / med­


(D1)Hcrt- / N / woC / med­ (D2)Hcrt- / N / woC / med+

(F1)IHS / med­

** **

(E)Hcrt+ / N / woC / med­

(F2)IHS / med+ (G)OSAS

Medicated patient group

** p<0.01 ANOVA with post-hoc, vs. N. Controls

FIG. 5. CSF Hcrt-1 and histamine values for each individual with sleep disorders. CSF Hcrt-1 (i: left panel) and histamine (ii: right panel) values for each individual are plotted. The patient groups are indicated as Group A to Group G from above. The results of the subjects with CNS stimulants (shadowed) and without CNS stimulants medication are presented separately in the figure. The vertical lines show mean values. The cutoff value of CSF hypocretin-1 level (less than or equal to 110 pg/ml) clearly segregated hypocretin deficiency from non-deficiency. None of the patients with idiopathic hypersomnia and OSAS showed hypocretin deficiency. We found significant reductions in CSF histamine levels in hypocretin deficient (B: 176 + 25.8 pg/ml) and non-deficient narcolepsy with cataplexy (C: 97.8 + 38.4 pg/ml), hypocretin non-deficient narcolepsy without cataplexy (E: 113.6 + 16.4 pg/ml) and idiopathic hypersomnia (F: 161.0 + 29.3 pg/ml), while those in hypocretin deficient narcolepsy without cataplexy (D: 273.6 + 105 pg/ml) and OSAS (G: 259.3 + 46.6 pg/ml) were not statistically different from those in the control range (A: 333.8 + 22.0 pg/ml). The low CSF histamine levels were mostly observed in nonmedicated patients, and significant reductions in histamine levels were observed only in non-medicated patients with hypocretin deficient narcolepsy with cataplexy (B1: 112.1 + 16.3 pg/ml) and idiopathic hypersomnia (F1: 143.3 + 28.8 pg/ml). The levels in the medicated subjects are in the normal range (B2: 256.6 + 51.7 pg/ml and F2: 259.5 + 94.9 pg/ml). Non-medicated subjects had a tendency for low CSF histamine levels in hypocretin deficient narcolepsy without cataplexy (D1: 77.5 + 11.5 pg/ml) (adapted from Kanbayashi et al., 2009a). XI. Conclusion

This review described the current understanding of the neurochemistry for EDS with various etiologies. Although prevalence of primary hypersomnia, such as narcolepsy and idiopathic hypersomnia, is not high, prevalence of sympto­ matic EDS is considerably high, and the pathophysiology of symptomatic EDS likely overlaps with that of primary hypersomnia. Although much progress has been made regarding the pathophysiology and neurochemistry of EDS, this new knowledge, such as hypocretin replacement or



histaminomimetic treatments, is not yet incorporated in the development of new treatments, rendering further research absolutely critical. Acknowledgments The authors thank Carl-Francis A. Deguzman for editing the manuscript.


Aldrich, M. S., Chervin, R. D., and Malow, B. A. (1997). Value of the multiple sleep latency test (MSLT) for the diagnosis of narcolepsy. Sleep 20, 620–629. Aldrich, M. S., Hollingsworth, Z., and Penney, J. B. (1992). Dopamine-receptor autoradiography of human narcoleptic brain. Neurology 42, 410–415. Amiry-Moghaddam, M., and Ottersen, O. P. (2003). The molecular basis of water transport in the brain. Nat. Rev. Neurosci. 4, 991–1001. Aston-Jones, G., Chen, S., Zhu, Y., and Oshinsky, M. L. (2001). A neural circuit for circadian regulation of arousal. Nat. Neurosci. 4, 732–738. Bassetti, C., and Aldrich, M. S. (1997). Idiopathic hypersomnia. A series of 42 patients. Brain 120, 1423–1435. Bassetti, C., Gugger, M., Bischof, M., Mathis, J., Sturzenegger, C., Werth, E., Radanov, B., Ripley, B., Nishino, S., and Mignot, E. (2003). The narcoleptic borderland: A multimodal diag­ nostic approach including cerebrospinal fluid levels of hypocretin-1 (orexin A). Sleep Med. 4, 7–12. Bjo¨rklund, A., and Lindvall, O. (1984). Dopamine-containing systems in the CNS. In: Handbook of Chemical Neuroanatomy, Vol. 2, Classical Transmitter in the CNS, Part I ( A. Bjo¨ rklund, and T. Ho¨kfelt, eds.), Elsevier, Amsterdam, The Netherlands, pp. 55–121. Chemelli, R. M., Willie, J. T., Sinton, C. M., Elmquist, J. K., Scammell, T., Lee, C., Richardson, J. A., Williams, S. C., Xiong, Y., Kisanuki, Y., Fitch, T. E., Nakazato, M., Hammer, R. E., Saper, C. B., and Yanagisawa, M. (1999). Narcolepsy in orexin knockout mice: Molecular genetics of sleep regulation. Cell 98, 437–451. Chen, W., Black, J., Call, P., Mignot, E. (2005). Late-onset narcolepsy presenting as rapidly progres­ sing muscle weakness: response to plasmapheresis. Ann Neurol. 58, 489–90. Crocker, A., Espana, R. A., Papadopoulou, M., Saper, C. B., Faraco, J., Sakurai, T., Honda, M., Mignot, E., and Scammell, T. E. (2005). Concomitant loss of dynorphin, NARP, and orexin in narcolepsy. Neurology 65, 1184–1188. Cvetkovic-Lopes, V., Bayer, L., Dorsaz, S., Maret, S., Pradervand, S., Dauvilliers, Y., Lecendreux, M., Lammers, G. J., Donjacour, C. E., Du Pasquier, R. A., Pfister, C., Petit, B., Hor, H., Muhlethaler, M., and Tafti, M. (2010). Elevated Tribbles hom*olog 2-specific antibody levels in narcolepsy patients. J. Clin. Invest. 120, 713–719. Dauvilliers, Y., Carlander, B., River, F., Touchon, J., Tafti, M. (2004). IVIG treatment in narcolepsy: Report on two new cases. Journal of Sleep Research. 13 (Suppl. 1), 167. De Lecea, L., Kilduff, T. S., Peyron, C., Gao, X.-B., Foye, P. E., Danielson, P. E., f*ckuhara, C., Battenberg, E.L.F., Gautvik, V. T., Barlett, F. S., Frankel, W. N., Van Den Pol, A. N., Bloom, F. E., Gautvik, K. M., and Sutcliffe, J. G. (1998). The hypocretins: Hypothalamus-specific peptides with neuroexcitatory activity. Proc. Natl. Acad. Sci. U.S.A. 95, 322–327. Eriksson, K. S., Sergeeva, O., Brown, R. E., and Haas, H. L. (2001). Orexin/hypocretin excites the histaminergic neurons of the tuberomammillary nucleus. J. Neurosci. 21, 9273–9279.



Faull, K. F., Guilleminault, C., Berger, P. S., and Barchas, J. D. (1983). Cerebrospinal fluid mono­ amine metabolites in narcolepsy and hypersomnia. Ann. Neurol. 13, 258–263. Faull, K. F., Zeller-DeAmicis, L. C., Radde, L., Bowersox, S. S., Baker, T. L., Kilduff, T. S., and Dement, W. C. (1986). Biogenic amine concentrations in the brains of normal and narcoleptic canines: Current status. Sleep 9, 107–110. Fujiki, N., Yoshida, Y., Ripley, B., Honda, K., Mignot, E., and Nishino, S. (2001). Changes in CSF hypocretin-1 (orexin A) levels in rats across 24 hours and in response to food deprivation. NeuroReport 12, 993–997. Haas, H., and Panula, P. (2003). The role of histamine and the tuberomamillary nucleus in the nervous system. Nat. Rev. Neurosci. 4, 121–130. Hallmayer, J., Faraco, J., Lin, L., Hesselson, S., Winkelmann, J., Kawashima, M., Mayer, G., Plazzi, G., Nevsimalova, S., Bourgin, P., Hong, S. C., Honda, Y., Honda, M., Hogl, B., Longstreth, W. T. Jr., Montplaisir, J., Kemlink, D., Einen, M., Chen, J., Musone, S. L., Akana, M., Miyagawa, T., Duan, J., Desautels, A., Erhardt, C., Hesla, P. E., Poli, F., Frauscher, B., Jeong, J. H., Lee, S. P., Ton, T. G., Kvale, M., Kolesar, L., Dobrovolna, M., Nepom, G. T., Salomon, D., Wichmann, H. E., Rouleau, G. A., Gieger, C., Levinson, D. F., Gejman, P. V., Meitinger, T., Young, T., Peppard, P., Tokunaga, K., Kwok, P. Y., Risch, N., and Mignot, E. (2009). Narcolepsy is strongly associated with the T-cell receptor alpha locus. Nat. Genet. 41, 708–711. Honda, M., Eriksson, K. S., Zhang, S., Tanaka, S., Lin, L., Salehi, A., Hesla, P. E., Maehlen, J., Gaus, S. E., Yanagisawa, M., Sakurai, T., Taheri, S., Tsuchiya, K., Honda, Y., and Mignot, E. (2009). IGFBP3 colocalizes with and regulates hypocretin (orexin). PLoS ONE 4, e4254. Huang, Z. L., Qu, W. M., Li, W. D., Mochizuki, T., Eguchi, N., Watanabe, T., Urade, Y., and Hayaishi, O. (2001). Arousal effect of orexin A depends on activation of the histaminergic system. Proc. Natl. Acad. Sci. U.S.A. 98, 9965–9970. Hublin, C., Launes, J., Nikkinen, P., and Partinen, M. (1994). Dopamine D2-receptors in human narcolepsy: A SPECT study with 123I-IBZM. Acta Neurol. Scand. 90, 186–189. ICSD-2 (ed.) (2005). ICSD-2-International classification of sleep disorders, Diagnostic and coding manual, (2nd ed.), American Academy of Sleep Medicine Westchester, Illinois, USA. Jones, B. E. (2005). Basic mechanism of sleep-wake states. In: Principles and Practice of Sleep Medicine, 4th ed. ( M. H. Kryger, T. Roth, and W. C. Dement, eds.), Elsevier Saunders, Philadelphia, PA, pp. 136–153. Jones, B. E., Bobillier, P., Pin, C., and Jouvet, M. (1973). The effect of lesions of catecholaminecontaining neurons upon monoamine content of the brain and EEG and behavioral waking in the cat. Brain Res. 58, 157–177. Jouvet, M. (1972). The role of monoamines and acetylcholine-containing neurons in the regulation of the sleep-waking cycle. Ergeb. Physiol. 64, 166–307. Kanbayashi, T., Kodama, T., Kondo, H., Satoh, S., Inoue, Y., Chiba, S., Shimizu, T., and Nishino, S. (2009a). CSF histamine contents in narcolepsy, idiopathic hypersomnia and obstruc­ tive sleep apnea syndrome. Sleep 32, 181–187. Kanbayashi, T., Shimohata, T., Nakashima, I., Yaguchi, H., Yabe, I., Shimizu, T., and Nishino, S. (2009b). Symptomatic narcolepsy in MS and NMO patients; new neurochemical and immuno­ logical implications. Arch. Neurol. 66(12), 1563–1566. Kawashima, M., Lin, L., Tanaka, S., Jennum, P., Knudsen, S., Nevsimalova, S., Plazzi, G., and Mignot, E. (2010). Anti-Tribbles hom*olog 2 (TRIB2) autoantibodies in narcolepsy are associated with recent onset of cataplexy. Sleep 33, 869–874. Lee, M. G., Hassani, O. K., and Jones, B. E. (2005). Discharge of identified orexin/hypocretin neurons across the sleep-waking cycle. J. Neurosci. 25, 6716–6720. Lennon, V. A., Kryzer, T. J., Pittock, S. J., Verkman, A. S., and Hinson, S. R. (2005). IgG marker of optic-spinal multiple sclerosis binds to the aquaporin-4 water channel. J. Exp. Med. 202, 473–477.



Lim, A. S., and Scammell, T. E. (2010). The trouble with Tribbles: Do antibodies against TRIB2 cause narcolepsy? Sleep 33, 857–858. Lin, J. S. (2000). Brain structures and mechanisms involved in the control of cortical activation and wakefulness, with emphasis on the posterior hypothalamus and histaminergic neurons. Sleep Med. Rev. 4, 471–503. Lin, L., Faraco, J., Li, R., Kadotani, H., Rogers, W., Lin, X., Qiu, X., de Jong, P. J., Nishino, S., and Mignot, E. (1999). The sleep disorder canine narcolepsy is caused by a mutation in the hypocretin (orexin) receptor 2 gene. Cell 98, 365–376. Ljungberg, T., Apicella, P., and Schultz, W. (1992). Responses of monkey dopamine neurons during learning of behavioral reactions. J. Neurophysiol. 67, 145–163. Lu, J., Jhou, T. C., and Saper, C. B. (2006). Identification of wake-active dopaminergic neurons in the ventral periaqueductal gray matter. J. Neurosci. 26, 193–202. Marcus, J. N., Aschkenasi, C. J., Lee, C. E., Chemelli, R. M., Saper, C. B., Yanagisawa, M., and Elmquist, J. K. (2001). Differential expression of orexin receptors 1 and 2 in the rat brain. J. Comp. Neurol. 435, 6–25. Mefford, I. N., Baker, T. L., Boehme, R., Foutz, A. S., Ciaranello, R. D., Barchas, J. D., and Dement, W. C. (1983). Narcolepsy: Biogenic amine deficits in an animal model. Science 220, 629–632. Mignot, E., Hayduk, R., Grumet, F. C., Black, J., Guilleminault, C. (1997). HLA DQB1�0602 is associated with cataplexy in 509 narcoleptic patients. Sleep. 20, 1012–1020. Mignot, E., Lammers, G. J., Ripley, B., Okun, M., Nevsimalova, S., Overeem, S., Vankova, J., Black, J., Harsh, J., Bassetti, C., Schrader, H., and Nishino, S. (2002). The role of cerebrospinal fluid hypocretin measurement in the diagnosis of narcolepsy and other hypersomnias. Arch. Neurol. 59, 1553–1562. Mochizuki, T., Yamatodani, A., Okakura, K., Horii, A., Inagaki, N., and Wada, H. (1992). Circadian rhythm of histamine release from the hypothalamus of freely moving rats. Physiol. Behav. 51, 391–394. Moller, J. C., Stiasny, K., Cassel, W., Peter, J. H., Kruger, H. P., and Oertel, W. H. (2000). “Sleep attacks” in Parkinson patients. A side effect of nonergoline dopamine agonists or a class effect of dopamine agonists? Nervenarzt 71, 670–676. Montplaisir, J., de Champlain, J., Young, S. N., Missala, K., Sourkes, T. L., Walsh, J., and Remillard, G. (1982). Narcolepsy and idiopathic hypersomnia: Biogenic amines and related compounds in CSF. Neurology 32, 1299–1302. Nishino, S., Fujiki, N., Ripley, B., Sakurai, E., Kato, M., Watanabe, T., Mignot, E., and Yanai, K. (2001). Decreased brain histamine contents in hypocretin/orexin receptor-2 mutated narcoleptic dogs. Neurosci. Lett. 313, 125–128. Nishino, S., and Kanbayashi, T. (2005). Symptomatic narcolepsy, cataplexy and hypersomnia, and their implications in the hypothalamic hypocretin/orexin system. Sleep Med. Rev. 9, 269–310. Nishino, S., Kanbayashi, T., Fujiki, N., Uchino, M., Ripley, B., Watanabe, M., Lammers, G. J., Ishiguro, H., Shoji, S., Nishida, Y., Overeem, S., Toyoshima, I., Yoshida, Y., Shimizu, T., Taheri, S., and Mignot, E. (2003). CSF hypocretin levels in Guillain-Barre syndrome and other inflammatory neuropathies. Neurology 61, 823–825. Nishino, S., and Mignot, E. (1997). Pharmacological aspects of human and canine narcolepsy. Prog. Neurobiol. 52, 27–78. Nishino, S., Mignot, E. (2005). CNS stimulants in Sleep Medicine: Basic Mechanisms and Pharma­ cology. In: Principles and Practice of Sleep Medicine. 4th ed. (M. H. Kryger, T. Roth, W. C. Dement, Eds.), Elsevier Saunders, Philadelphia, pp. 468–498. Nishino, S., Mignot, E., and Dement, W. C. (2004a). Sedative-hypnotics. In: Textbook of Psycho­ pharmacology (A. F. Schatzberg, and C. B. Nemeroff, eds.), American Psychiatric Press, Washington, DC, pp. 651–684.



Nishino, S., Okuro, M., Kotorii, N., Anegawa, E., Ishimaru, Y., Matsumura, M., and Kanbayashi, T. (2009a). Hypocretin/orexin and narcolepsy: New basic and clinical insights. Acta Physiol. (Oxf). 198(3), 209–222. Nishino, S., Ripley, B., Overeem, S., Lammers, G. J., and Mignot, E. (2000). Hypocretin (orexin) deficiency in human narcolepsy. Lancet 355, 39–40. Nishino, S., Sakurai, E., Nevsimalova, S., Yoshida, Y., Watanabe, T., Yanai, K., and Mignot, E. (2009b). Decreased CSF histamine in narcolepsy with and without low CSF hypocretin-1 in comparison to healthy controls. Sleep 32, 175–180. Nishino, S., Taheri, S., Black, J., Nofzinger, E., and Mignot, E. (2004b). The neurobiology of sleep in relation to mental illness. In: Neurobiology of Mental Illness (E. J. Nestler D. S. Charney, eds.), Oxford University Press, New York, NY, pp. 1160–1179. Overeem, S., Dalmau, J., Bataller, L., Nishino, S., Mignot, E., Vershuuren, J., and Lammers, G. J. (2001). Secondary narcolepsy in patients with paraneoplastic anti-Ma2 antibodies is associated with hypocretin deficiency. J. Sleep Res. 11(Suppl. 1), 166–167. Peyron, C., Faraco, J., Rogers, W., Ripley, B., Overeem, S., Charnay, Y., Nevsimalova, S., Aldrich, M., Reynolds, D., Albin, R., Li, R., Hungs, M., Pedrazzoli, M., Padigaru, M., Kucherlapati, M., Fan, J., Maki, R., Lammers, G. J., Bouras, C., Kucherlapati, R., Nishino, S., and Mignot, E. (2000). A mutation in a case of early onset narcolepsy and a generalized absence of hypocretin peptides in human narcoleptic brains. Nat. Med. 6, 991–997. Peyron, C., Tighe, D. K., van den Pol, A. N., de Lecea, L., Heller, H. C., Sutcliffe, J. G., and Kilduff, T. S. (1998). Neurons containing hypocretin (orexin) project to multiple neuronal systems. J. Neurosci. 18, 9996–10015. Pittock, S. J., Weinshenker, B. G., Lucchinetti, C. F., Wingerchuk, D. M., Corboy, J. R., and Lennon, V. A. (2006). Neuromyelitis optica brain lesions localized at sites of high aquaporin 4 expression. Arch. Neurol. 63, 964–968. Plazzi, G., Poli, F., Franceschini, C., Parmeggiani, A., Pirazzoli, P., Bernardi, F., Mignot, E., Cicognani, A., Montagna, P. (2008). Intravenous high-dose immunoglobulin treatment in recent onset childhood narcolepsy with cataplexy. J Neurol. 255, 1549–54. Poirier, G., Montplaisir, J., Dumont, M., Duquette, P., Decary, F., Pleines, J., and Lamoureux, G. (1987). Clinical and sleep laboratory study of narcoleptic symptoms in multiple sclerosis. Neurology 37, 693–695. Rinne, J., Hublin, C., Partinen, M., Ruottinen, H., Na˚ gren, K., Lehikoinen, P., Ruosalainen, U., and Laihinen, A. (1995). PET study of human narcolepsy: No increase in striatal dopamine D2-receptors. Neurology 45, 1735–1738. Ripley, B., Fujiki, N., Okura, M., Mignot, E., and Nishino, S. (2001a). Hypocretin levels in sporadic and familial cases of canine narcolepsy. Neurobiol. Dis. 8, 525–534. Ripley, B., Overeem, S., Fujiki, N., Nevsimalova, S., Uchino, M., Yesavage, J., Di Monte, D., Dohi, K., Melberg, A., Lammers, G. J., Nishida, Y., Roelandse, F. W., Hungs, M., Mignot, E., and Nishino, S. (2001b). CSF hypocretin/orexin levels in narcolepsy and other neurological conditions. Neurology 57, 2253–2258. Roth, B. (1962). Narkolepsie und hypersomnie. VEB Verlag Volk und Gesundheit, Berlin, Germany. Sakurai, T. (2002). Roles of orexins in regulation of feeding and wakefulness. NeuroReport 13, 987–995. Sakurai, T., Amemiya, A., Ishii, M., Matsuzaki, I., Chemelli, R. M., Tanaka, H., Williams, S. C., Richardson, J. A., Kozlowski, G. P., Wilson, S., Arch, J.R.S., Buckingham, R. E., Haynes, A. C., Carr, S. A., Annan, R. S., McNulty, D. E., Liu, W.-S., Terrett, J. A., Elshourbagy, N. A., Bergsma, D. J., and Yanagisawa, M. (1998). Orexins and orexin receptors: A family of hypotha­ lamic neuropeptides and G protein-coupled receptors that regulate feeding behavior. Cell 92, 573–585. Saper, C. B., Chou, T. C., and Scammell, T. E. (2001). The sleep switch: Hypothalamic control of sleep and wakefulness. Trends Neurosci. 24, 726–731.



Saper, C. B., Scammell, T. E., and Lu, J. (2005). Hypothalamic regulation of sleep and circadian rhythms. Nature 437, 1257–1263. Soya, S., Song, Y. H., Kodama, T., Honda, Y., Fujiki, N., and Nishino, S. (2008). CSF histamine levels in rats reflect the central histamine neurotransmission. Neurosci. Lett. 430, 224–229. Steinfels, G. F., Heym, J., Streckjer, R. E., and Jacobs, B. J. (1983). Behavioral correlates of dopaminergic activity in freely moving cats. Brain Res. 258, 217–228. Strecker, R. E., Nalwalk, J., Dauphin, L. J., Thakkar, M. M., Chen, Y., Ramesh, V., Hough, L. B., and McCarley, R. W. (2002). Extracellular histamine levels in the feline preoptic/anterior hypothalamic area during natural sleep-wakefulness and prolonged wakefulness: An in vivo microdialysis study. Neuroscience 113, 663–670. Tachibana, N., Howard, R. S., Hirsch, N. P., Miller, D. H., Moseley, I. F., and Fish, D. (1994). Sleep problems in multiple sclerosis. Eur. Neurol. 34, 320–323. Thannickal, T. C., Nienhuis, R., and Siegel, J. M. (2009). Localized loss of hypocretin (orexin) cells in narcolepsy without cataplexy. Sleep 32, 993–998. Toyoda, H., Tanaka, S., Miyagawa, T., Honda, Y., Tokunaga, K., and Honda, M. (2010). AntiTribbles hom*olog 2 autoantibodies in Japanese patients with narcolepsy. Sleep 33, 875–878. Trulson, M. E. (1985). Simultaneous recording of substantia nigra neurons and voltammetric release of dopamine in the caudate of behaving cats. Brain Res. Bull. 15, 221–223. Verma, A., Anand, V., and Verma, N. P. (2007). Sleep disorders in chronic traumatic brain injury. J. Clin. Sleep Med. 3, 357–362. Willie, J. T., Chemelli, R. M., Sinton, C. M., and Yanagisawa, M. (2001). To eat or to sleep? Orexin in the regulation of feeding and wakefulness. Annu. Rev. Neurosci. 24, 429–458. Yamanaka, A., Tsujino, N., Funahashi, H., Honda, K., Guan, J. L., Wang, Q. P., Tominaga, M., Goto, K., Shioda, S., and Sakurai, T. (2002). Orexins activate histaminergic neurons via the orexin 2 receptor. Biochem. Biophys. Res. Commun. 290, 1237–1245. Yoshida, Y., Fujiki, N., Nakajima, T., Ripley, B., Matsumura, H., Yoneda, H., Mignot, E., and Nishino, S. (2001). Fluctuation of extracellular hypocretin-1 (orexin A) levels in the rat in relation to the light-dark cycle and sleep-wake activities. Eur. J. Neurosci. 14, 1075–1081.


A A2a receptor agonist, 12 Adenosine, 12, 65, 66, 67 sleep-generating effects of, 12 Adrenal steroids, 92 Adrenocorticotropic hormone (ACTH), 44, 113 dissociation of, 97 producing cells, 94 Alerting effects of light, 69 Alertness and cognitive performance, 73–74 AQP4, 242 AQP super-family, 242 Arcuate nucleus (ARC), 98 Arginine vasopressin (AVP), inhibitory effect of, 95 Aristotelian method of review, pathology of awakenings

correlation with Spielman factors, 210

efficient causes, 216–221

formal causes, 211–216

nuclear structures, 211–213 relevant network and neuron structures, 214–216 thalamocortical circuit elements, 214 relating theories from different conceptual levels, 210–211

substantial causes, 211

telic causes, 221–223

Arousal(s) awakenings, distinguished from, 25 defining, 26–27 states, homeostatic regulation of, 8–11 Arousability on attention in sleep, 41–42

40-Hz response, 42

N350, 42–44

P3, 42

behavioral reactivity, 28–29

individual differences in, 36–41

from sleep, factors influencing, 30

sleep-stage-specific effects, 29–31

NREM stages, 31 stage REM sleep, 31–33 Ascending arousal system, 3 “Ascending reticular activating system,” 3

Auditory-evoked potentials (AEP), 41 Auditory stimuli in waking, 39 Autonomic nervous system, 113–114 Awake, reason for being, 57–59 circadian and homeostatic impetus on wakefulness, 59–60 brain circuitry underlying circadian and homeostatic influences, 63–67 human sleep–wake cycle, 60–63 light on human wakefulness, 67–68 alerting effects of light, 69 dose- and wavelength, 69–72 light switches on clock and hourglass, 68–69 neuroanatomical underpinnings, 73–74 non-clinical applications of light, 74–77 melatonin on human sleep and wakefulness, 77 effects of exogenous melatonin, 79–80 endogenous melatonin and human circadian sleep–wake cycle, 77–79 treatment of insomnia and circadian rhythm disorders, 81–82 Awakenings, 23 ambiguity of, 200–201 of cardiovascular system, 100–102 defining, 26–27 distinguished from arousals, 25 lack of clear definition, 27 from NREM sleep, 137 process, CAR as, 160–161 shifts in attention, 26 Awakening, neurochemistry of, 229–251 changes in other neurotransmitter systems in narcolepsy, 246–248 histaminergic neurotransmission in human narcolepsy, 248–250 hypocretin deficiency and postnatal cell death of hypocretin neurons, 234–237 hypocretin ligand deficiency cause narcolepsy phenotype, 243 hypocretin/orexin deficiency and narcoleptic phenotype, 244–245 hypocretin/orexin system and sleep regulation, 243–244 pathophysiology of narcolepsy with normal hypocretin levels, 245–246 257



Awakening, neurochemistry of (Continued) hypocretin non-deficient primary hypersomnia, 237–239 idiopathic hypersomnia, 247–248 narcolepsy in dogs and humans, 246–247 narcolepsy and symptoms of narcolepsy, 232–233 neurobiology of wakefulness, 231–232 symptomatic narcolepsy and hypersomnia, 239–242 Awakening onset process (AOP) researchers, 197 Awakening (pre and post), EEG changes, 23–25 critical remarks, 25–26 defining arousals and awakenings, 26–27 EEG changes following awakening partial awakenings, 46–48 state-related effects on cognition and behavior, 44–46 EEG changes preceding awakening activity in sleep and behavioral arousal thresholds, 33–35 on attention in sleep, 41–44 behavioral reactivity, 28–29 behavioral responsiveness and PGO waves, 35–36 individual differences in arousability, 36–41 sleep-stage-specific effects, 29–33 waking up to external stimuli, 27–28 B Bedtime settling routines, 179–80 Behavioral arousal thresholds, 33–35 Behavioral awakening, and CAR, 165–166 Behavioral responsiveness, 26, 49 and PGO waves, 35–36 “Behavioral sleep state,” 202 Breastfeeding, night awakenings in childhood, 181–182 C c-Fos, expression of, 6, 7 c-Fos immunoreactive neurons (IRN), 6–7 Fos-immunoreactivity in MnPN GABAergic neurons, 9 c-Fos-immunoreactivity, patterns of, 8 Cardiovascular system, 100 awakenings of, 100–102 Cataplexy and REM sleep abnormalities, 245 Childhood, night awakenings in, 177–188

developmental problems and diagnoses, 187 parent–child interactions and attachment, 186–187 temperament, 186 Cholinergic neurons, 5, 231 Chronic insomnia, 194 classification of “pure” insomnias, 195–196 clinical context, 194 defined syndromes of chronic insomnia, 196–200 DSM-AU7 IV generic definition of, 195 Circadian and homeostatic impetus on wakefulness, 59–60 circadian and homeostatic influences on human cognition, 63–67

diagrammatic representation of, 131

human sleep–wake cycle, 60–63

Circadian and sleep episode duration influences, 130–131 different measures of cognitive functioning, 142–145 length of sleep episode and SI, 137–141 time-of-day and cognition, 130–133 time-of-day effects and waking up, 133–137 Circadian aspects of sleepiness, 135 Circadian clock, 60 circadian modulation, 61 circadian regulation of alertness, 63 Circadian factors, 138 Circadian rhythm of core body temperature (CBT), 68 and homeostatic process self-awakening, factors of successful, 122–123 Clocks and hourglasses, light, and melatonin, role of, 57–59 circadian and homeostatic impetus on wakefulness, 59–60 from basic arousal states to controlled cognitive behavior, 60–63 homeostatic influences on human cognition, 63–67 effects of light on human wakefulness, 67–68 alerting effects of light, 69 effect of light on alertness and cognitive performance, 73–74 of light exposure and alertness, 69–72 light switches on clock and hourglass, 68–69 non-clinical applications of light, 74–77 melatonin on human sleep and wakefulness, 77 effects of exogenous melatonin, 79–80


endogenous melatonin and human circadian sleep–wake cycle, 77–79 treatment of insomnia and circadian rhythm disorders, 81–82 Co-sleeping, night awakenings in childhood, 180–181

Cognition, time-of-day and, 130–133

Cognitive ability, 129

Cognitive awakening, and CAR, 161–163

Cognitive functioning, different measures of,


Colonic motility, 44

Conscious awareness, 40

Corticotropin-releasing hormone (CRH), 94

Cortisol awakening response (CAR), 153

average citations per year for papers published on, 157

as awakening process, 160–161

and behavioral awakening, 165–166

and cognitive awakening, 161–163

in context, 153–154

history of investigation of, 154–158

and HPA activity, 156

and immunological awakening, 164–165

measurement of, 166–169

peer-reviewed publications about, 156

regulation of CAR and SCN, 158–160

sensitive to non-psychological factors, 158

Cortisol/corticosterone awakening rise, 94–97

CSF Hcrt-1 and histamine values, 250

Cued reaction time task (CRTT), 144

Culture, 183

Cyclic alternating pattern (CAP), 217

grades of, 220

“microarousals,” 220

D Daytime naps, 115

Daytime sleepiness, 115

Decision-making performance after arousal, 46

Dehydroepiandrosterone (DHEA), 168

Delayed sleep phase syndrome (DSPS), 81

Descending subtraction task (DST), 136

Digit Symbol Substitution Test (DSST), 133

Dim light melatonin onset (DLMO), 75

“Disorder of awakenings,” 195

Distal vasoconstriction, 35

Dorsomedial hypothalamic nucleus (DMH), 63

“Dynamic state,” 201–202


E EEG changes pre and post awakening, 23–25 critical remarks, 25–26 defining arousals and awakenings, 26–27 following awakening partial awakenings, 46–48 sleep inertia or state-related effects, 44–46 preceding awakening activity in sleep and behavioral arousal thresholds, 33–35 behavioral reactivity, 28–29 behavioral responsiveness and PGO waves, 35–36 event-related potential studies on attention in sleep, 41–44 individual differences in arousability, 36–41 sleep-stage-specific effects, 29–33 waking up to external stimuli, 27–28 ELISA determination of Trib2-specific antibodies in sera, 238

Endocrine, anticipatory changes of, 113

Endogenous “melatonin cycle,” 59

Environmental factors

in control of sleep/wakefulness and intensity/

quality, 58

self-awakening, factors of successful, 122

Event-related potential (ERP), 28

Excessive sleepiness (EDS), 229

Exogenous melatonin, 79

on human sleep and wakefulness, 79–80 F “Failure-of-anticipation” theory, 101

Family context, night awakenings in childhood,


parental psychopathology, 184–185

socioeconomics, 183–184

“Forced awakening” (FA), 110

“Forced desynchronization (FD) protocols,” 132

Forced-desynchrony protocol, 80

G Gamma-aminobutyric acid (GABA), 1

Glucocorticoids, 154

Glucose homeostasis, 98

Gonadotropin-releasing hormone (GnRH)

neurons, 93

GABAergic neurons, 7, 15



H Histaminergic neurotransmission, 248–250

Homeostatic impetus on wakefulness, 59–67

Homeostatic process, 60

diagrammatic representation of, 131

Homeostatic regulation of arousal states, 8–11

Homeostatic sleep pressure, 11, 66

Human sleep–wake cycle, 60–63

Hybrid CR/FDprocedure, 135

“Hyperarousal,” 208–209


idiopathic, 247–248

hypocretin non-deficient primary

hypersomnia, 237–239

narcolepsy in dogs and humans, 246–247

with sleep drunkenness, 239

symptomatic narcolepsy and, 239–243

Hypocretin deficiency, 229, 234–237

with cataplexy, 236

and narcoleptic phenotype, 244–245

in narcoleptic subjects, 236

Hypocretin ligand deficiency and narcolepsy phenotype, 243

hypocretin/orexin deficiency, 244–245

hypocretin/orexin system, 243–244

pathophysiology of narcolepsy, 245–246

Hypocretin neurons, 4–5 structures of mature hypocretin-1 and hypocretin-2 peptides, 235

Hypocretin non-deficient narcolepsy, 229

Hypocretin/orexin system and sleep regulation,


Hypocretin targeted therapy, 237

Hypothalamic SCN, 92, 155, 159

Hypothalamo-pituitary-adrenal (HPA) axis, 94,


I ICD-10, 196

Idiopathic hypersomnia, 247–248

hypocretin non-deficient primary

hypersomnia, 237–239

narcolepsy in dogs and humans, 246–247

Illuminance and subjective alertness, 70

Immunological awakening, and CAR, 164–165

“Independent sleep drunkenness,” 239

Insomnia, 81

and circadian rhythm disorders, 81–82

from multiple theory levels, 193–224

primary, 198–199

therapies, mid-level therapeutic theories of,


Intrinsic photosensitive retinal ganglion cell

(ipRGC), 67

K Karolinska Sleepiness Scale (KSS), dynamics of

subjective sleepiness on, 62

L Laterodorsal (LDT), 3


exposure/alertness, dose/wavelength response

relationship of, 69–72

on human wakefulness, effects of, 67–68

alerting effects of light, 69

light switches on clock and hourglass, 68–69

neuroanatomical underpinnings, 73–74

non-clinical applications of light, 74–77

non-clinical applications of, 74–77

switches on clock and hourglass, 68–69

wavelength of, and its alerting response, 71

Lucid dreaming

40 Hz activity in, 48

coherences in, 49

M Median preoptic nucleus (MnPN), 1, 5

activation of GABAergic neurons, 5

expression of c-Fos, 9

Melanopsin-containing ipRGC, 67

Melatonin, 77

endogenous melatonin and human circadian

sleep–wake cycle, 77–79

on human sleep and wakefulness, 77, 79–80

increase in secretion in evening, 78

in insomniacs, 81

role in regulation human sleep–wake

behavior, 77

secretion, 134

treatment of insomnia and circadian rhythm

disorders, 81–82

Metaphysics (Aristotle), 210

“Micro-awakenings” , gamma-band, 204

Mid-level therapeutic theories of insomnia

therapies, 205–209

Miller Behavioral Style Scale (MBSS), 37


MnPN GABAergic neurons, 9 nonREM and REM sleep, strong response, 10 Monitoring and blunting, 37 finger-lift response for, 38 Monoamine neurons, 231 Monoaminergic cell groups, 4 Morningness, sleep habit and, 117–118 Motivation and self-efficacy, 121–122 N Narcolepsy, 232–233, 237 changes in neurotransmitter systems in, 246–248 in dogs and humans, 246–247 with normal hypocretin levels, pathophysiology of, 245–246

sleepiness in, 244

symptoms, 232–233, 239, 240

“Natural awakening” (NA), 110 Nature Neuroscience, 157 Neuroanatomical underpinnings, 73–74 Neurobiology of wakefulness, 231–232 Neurochemistry of awakening, 229–231 changes in other neurotransmitter systems in narcolepsy, 246–248 histaminergic neurotransmission in human narcolepsy, 248–250 hypocretin deficiency and postnatal cell death, 234–237 hypocretin ligand deficiency cause narcolepsy phenotype, 243 hypocretin/orexin deficiency and narcoleptic phenotype, 244–245 hypocretin/orexin system and sleep regulation, 243–244 narcolepsy with normal hypocretin levels, 245–246 idiopathic hypersomnia, 247–248 narcolepsy in dogs and humans, 246–247 idiopathic hypersomnia, hypocretin nondeficient primary hypersomnia, 237–239 narcolepsy and symptoms of narcolepsy, 232–233 neurobiology of wakefulness, 231–232 symptomatic narcolepsy and hypersomnia, 239–242 Neuronal processes, theory level of, 209 Neuropeptide-Y (NPY)-containing neurons, 98 Newtonian conception, 203 Night awakenings, 177


child characteristics, 185 developmental problems and diagnoses, 187 parent–child interactions and attachment, 186–187 temperament, 186

in early childhood, 177–179

family context, 183

parental psychopathology, 184–185 socioeconomics, 183–184 parenting practices, 179

bedtime settling routines, 179–180

breastfeeding, 181–182

co-sleeping, 180–181

culture, 183

sleep aid use, 182

Non-visual (or non-image forming (NIF)) effects, 67 Nonignorable psychologically based mid-level theories, 206–209 discriminate stimuli as leading to awakenings, 206–207 limit-cycling cognitions affecting sleep, 207 mid-level theory dependencies on notion of “hyperarousal,” 208–209 sleep behaviors and cognitions follow operant principles of reinforcement, 207–208 NonREM sleep/NREM sleep, 3 awakenings from, 137 neurons during, 5 stages, 31 NREM–REM cycles, 29, 39, 112, 122, 123 O On Sleep and Sleeplessness (Aristotle), 59 Orexin deficiency. See Hypocretin deficiency P Parasomnias, 200 Paraventricular nucleus (PVN), 94 Parental psychopathology, 184–185 Parent–child interactions and attachment, 186–187 Parenting practices, 179 developmental progression of factors, 179 night awakenings in childhood, 179

bedtime settling routines, 179–180

breastfeeding, 181–182

co-sleeping, 180–181

culture, 183

sleep aid use, 182



Partial awakenings, 46–48

frequency-specific activity, 47

Pathology of awakenings, 193–194

Aristotelian method of review

correlation with Spielman factors, 210

efficient causes, 216–221

formal causes, 211–216

relating theories from different conceptual

levels, 210–211

substantial causes, 211

telic causes, 221–223

chronic insomnia

classification of “pure” insomnias, 195–196

clinical context, 194

limitation of explanatory ambitions for

defined syndromes of chronic insomnia, 196–200 mid-level therapeutic theories of insomnia therapies, 205–209 realities about sleep “awakening” and “sleep,” ambiguity of, 200–201 metrological ambiguities of “sleep state,” 201–202 mnemonic and integrative duties of sleep, 204–205 process S and process C, 202–203 temporalizations relevant to understanding chronic insomnia patients, 204

theoretical vaguenesses and

incommensurate temporalizations, 203

Spielman 3-factor high-level model of


implications for cognitive-behavioral

therapists, 205–206

nonignorable psychologically based mid-

level theories, 206–209

theory level of neuronal processes, 209

Pedunculopontine (PPT), 3

Perifornical region of lateral hypothalamus

(PFLH), 14

PGO waves, 32

behavioral responsiveness and, 35–36

Pineal-hormone melatonin, 59

Post-traumatic stress disorder (PTSD), 206

Postnatal cell death of hypocretin neurons, 234–237

Preoptic sleep regulatory systems, 8–11

Preparation for awakening, 109–110

definitions, 110–111

effects of attempt to self-awaken on sleep, 111

anticipatory changes of autonomic nervous system, 113–114

anticipatory changes of endocrine, 113

changes of sleep, 111–113

factors of successful self-awakening circadian rhythm and homeostatic process, 122–123

environmental factors, 122

motivation and self-efficacy, 121–122

psychological stress, 120–121

success rate of self-awakening, 119–120

time perception, 123

habit and ability of self-awakening

ability to self-awake, 118

habit of self-awakening, 115–117

sleep habit and morningness, 117–118

schematic model of self-awakening, 123–125 self-awakening and daytime functions

daytime naps, 115

daytime sleepiness, 115

sleep inertia, 114

Preparatory changes in pre-awakening period,


Primary insomnia, 194

DSM-IV definition of, 222

Psychological stress, 120–121

Q Quasi-Newtonian conception, 203

R Rapid eye movement (REM) sleep, 3

Reaction time (RT) task, 134

RT and SEM, 139

Realities about sleep ambiguity of “awakening” and “sleep,” 200–201 metrological ambiguities of “sleep state,” 201–202 mnemonic and integrative duties of sleep, 204–205 process S and process C, 202–203 theoretical vaguenesses and incommensurate temporalizations, 203

understanding chronic insomnia patients, 204

“REM-off,” 4, 13

REM sleep

40 Hz activity in, 48

coherences in, 49

cortical activation during waking and, 4


mismatch negativity (MMN) during, 43

neurons during, 5

PGO waves, 32

relationship between SA and, 112

secondary consciousness, 24

stage, 31–33

Reticular formation, 2

S SCN. See Suprachiasmatic nuclei (SCN)

Secondary consciousness, 24

Self-awaken on sleep, effects of attempt to, 111

autonomic nervous system, changes in, 113–114

changes of sleep, 111–113

endocrine changes, 113

Self-awakening, 109

ability to, 118

and daytime functions

daytime naps, 115

daytime sleepiness, 115

sleep inertia, 114

with different age groups, 116

factors of successful

circadian rhythm and homeostatic process,


environmental factors, 122

motivation and self-efficacy, 121–122

psychological stress, 120–121

success rate of self-awakening, 119–120

time perception, 123

habit and ability of

ability to self-awake, 118

habit of self-awakening, 115–117

sleep habit and morningness, 117

morningness score and ratio of, 117

relationship between REM sleep and, 112

schema of, 124

schematic model of, 123–125

sleep–wake habit of university students, 118

vs. forced awakening, 109–125

Self-efficacy, 121–122

Sensory gating, 25

Simple RT, 135–136, 140

from neutral-flanker trials, 139

“Sleep,” ambiguity of, 200

Sleep aid use, 182

“Sleep atonia,” 165

Sleep disorders

international classification of, 196

narcolepsy, findings from, 229–251


“Sleep drunkenness,” 130

Sleep EEG, 8

Sleep endstate, 201

Sleep episode

duration influences, circadian and, 130–131 of cognitive functioning, 142–145 length of sleep episode and SI, 137–141 time-of-day and cognition, 130–133 time-of-day effects and waking up, 133–137 and SI, length of, 137–141

Sleep homeostasis, 8

Sleep inertia, 26, 45, 114, 130, 162

diagrammatic representation of, 131

or state-related effects on cognition and

behavior, 44–48

Sleep onset process (SOP), 196

Sleep-promoting circuitry, 6

Sleep regulation, hypocretin/orexin system

and, 243–244 Sleep-regulatory neurons neuronal activity in preoptic area, 11–13 in preoptic area, 13–15 in preoptic hypothalamus, 5–8 Sleep-regulatory regions, 6

Sleep stages (SS)

40-Hz response, 42

changes, 30

effects of stimulus probability/task relevance/

stimulus salience, 41

mean behavioral arousal thresholds across,

33, 34

N350, 42

P3, 42

specific effects, 29–31

ultradian rhythm of NREM and REM, 30

Sleep states, 165

metrological ambiguities of term, 201–202

Sleep-wakefulness cycles, 1–2

arousal states and preoptic sleep regulatory

systems, 8–11

integration of sleep-regulatory neuronal

activity, 11–13

rest phases in, 28

sleep-regulating neurons in preoptic

hypothalamus, 5–8 by sleep-regulatory neurons in preoptic area, 13–15 wakefulness-regulating systems, 2–5

Sleep–wake regulation, two-process model of, 122

Slow wave activity (SWA), 28



Slow wave sleep (SWS), 26, 138

Socioeconomics, night awakenings in childhood,


Spielman 3-factor high-level model of insomnia

implications for cognitive-behavioral

therapists, 205–206

nonignorable psychologically based mid-level

theories, 206–209

“Spontaneous awakening,” 110

Stimulation (react to) and not wake up, 29

Stimulus processing, during sleep, 44

Suprachiasmatic GABAergic/glutamatergic

neurons, 99

Suprachiasmatic nuclei (SCN), 60

and autonomic nervous system, 91–93

awakening of cardiovascular system,

100–102 cortisol/corticosterone awakening rise, 94–97 dawn phenomenon, 97–100 SCN output rhythms, 93–94 circadian control of corticosterone release, 95

circadian oscillations in, 63

demonstrated and putative connections of, 96

distinct regulation of CAR and relationship

with, 158–160

neuropeptides, 101

promoting sleep, 61

Symptomatic narcolepsy and hypersomnia, 239–242 T “Temporal chimeras,” 93


and cognition, 130–133 effects and waking up, 133–137

Time perception, 123

TMN neurons, 13

U Ultradian rhythm of NREM and REM sleep

stage (SS), 30

Unihemispheric sleep, 24


Vasoactive intestinal polypeptide (VIP), 92–93 Ventral lateral preoptic area (VLPO), 1, 5

activation of GABAergic neurons, 5

expression of c-Fos, 9

GABAergic neurons, 14

Visual evoked potentials (VEP), 162

VLPO GABAergic neurons, 9

nonREM and REM sleep, moderate

response, 10

W Wakefulness, 232

regulating systems, 2–5


40 Hz activity in, 48

coherences in, 49

to external stimuli, EEG, 27–28

time-of-day effects and, 133–137

Waking after sleep onset (WASO), 111


Volume 37

Implicit Knowledge: New Perspectives on Unconscious Processes Daniel L. Schacter

Section I: Selectionist Ideas and Neurobiology Selectionist and Instructionist Ideas in Neuroscience Olaf Sp*rns

Section V: Psychophysics, Psychoanalysis, and Neuropsychology

Population Thinking and Neuronal Selection: Metaphors or Concepts? Ernst Mayr

Phantom Limbs, Neglect Syndromes, Repressed Memories, and Freudian Psychology V. S. Ramachandran

Selection and the Origin of Information Manfred Eigen

Neural Darwinism and a Conceptual Crisis in Psychoanalysis Arnold H. Modell

Section II: Development and Neuronal Populations

A New Vision of the Mind Oliver Sacks

Morphoregulatory Molecules and Selectional Dynamics during Development Kathryn L. Crossin


Exploration and Selection in the Early Acquisi­ tion of Skill Esther Thelen and Daniela Corbetta Population Activity in the Control of Movement Apostolos P. Georgopoulos Section III: Functional Segregation and Integra­ tion in the Brain Reentry and the Problem of Cortical Integration Giulio Tononi Coherence as an Organizing Principle of Corti­ cal Functions Wolf Singerl Temporal Mechanisms in Perception Ernst Po¨ppel Section IV: Memory and Models Selection versus Instruction: Use of Computer Models to Compare Brain Theories George N. Reeke, Jr. Memory and Forgetting: Long-Term and Gradual Changes in Memory Storage Larry R. Squire

Volume 38 Regulation of GABAA Receptor Function and Gene Expression in the Central Nervous System A. Leslie Morrow Genetics and the Organization of the Basal Ganglia Robert Hitzemann, Yeang Olan, Stephen Kanes, Katherine Dains, and Barbara Hitzemann Structure and Pharmacology of Vertebrate GABAA Receptor Subtypes Paul J. Whiting, Ruth M. McKeman, and Keith A. Wafford Neurotransmitter Transporters: Molecular Biol­ ogy, Function, and Regulation Beth Borowsky and Beth J. Hoffman Presynaptic Excitability Meyer B. Jackson Monoamine Neurotransmitters in Invertebrates and Vertebrates: An Examination of the Diverse




Enzymatic Pathways Utilized to Synthesize and Inactivate Biogenic Amines B. D. Sloley and A. V. Juorio

Changes in Ionic Fluxes during Cerebral Ischemia Tibor Kristian and Bo K. Siesjo

Neurotransmitter Systems in Schizophrenia Gavin P. Reynolds

Techniques for Examining Neuroprotective Drugs in Vitro A. Richard Green and Alan J. Cross

Physiology of Bergmann Glial Cells Thomas Mu¨ ller and Helmut Kettenmann INDEX

Volume 39 Modulation of Amino Acid-Gated Ion Channels by Protein Phosphorylation Stephen J. Moss and Trevor G. Smart Use-Dependent Regulation of GABAA Receptors Eugene M. Barnes, Jr. Synaptic Transmission and Modulation in the Neostriatum David M. Lovinger and Elizabeth Tyler The Cytoskeleton and Neurotransmitter Receptors Valerie J. Whatley and R. Adron Harris Endogenous Opioid Regulation of Hippocampal Function Michele L. Simmons and Charles Chavkin Molecular Neurobiology of the Cannabinoid Receptor Mary E. Abood and Billy R. Martin Genetic Models in the Study of Anesthetic Drug Action Victoria J. Simpson and Thomas E. Johnson Neurochemical Bases of Locomotion and Etha­ nol Stimulant Effects Tamara J. Phillips and Elaine H. Shen Effects of Ethanol on Ion Channels Fulton T. Crews, A. Leslie Morrow, Hugh Criswell, and George Breese INDEX

Volume 40 Mechanisms of Nerve Cell Death: Apoptosis or Necrosis after Cerebral Ischemia R. M. E. Chalmers-Redman, A. D. Fraser, W. Y. H. Ju, J. Wadia, N. A. Tatton, and W. G. Tatton

Techniques for Examining Neuroprotective Drugs in Vivo Mark P. Goldberg, Uta Strasser, and Laura L. Dugan Calcium Antagonists: Their Role in Neuro­ protection A. Jacqueline Hunter Sodium and Potassium Channel Modulators: Their Role in Neuroprotection Tihomir P. Obrenovich NMDA Antagonists: Their Role in Neuroprotection Danial L. Small Development of the NMDA Ion-Channel Blocker, Aptiganel Hydrochloride, as a Neuro­ protective Agent for Acute CNS Injury Robert N. McBurney The Pharmacology of AMPA Antagonists and Their Role in Neuroprotection Rammy Gill and David Lodge GABA and Neuroprotection Patrick D. Lyden Adenosine and Neuroprotection Bertil B. Fredholm Interleukins and Cerebral Ischemia Nancy J. Rothwell, Sarah A. Loddick, and Paul Stroemer Nitrone-Based Free Radical Traps as Neuropro­ tective Agents in Cerebral Ischemia and Other Pathologies Kenneth Hensley, John M. Carney, Charles A. Stewart, Tahera Tabatabaie, Quentin Pye, and Robert A. Floyd Neurotoxic and Neuroprotective Roles of Nitric Oxide in Cerebral Ischemia Turgay Dalkara and Michael A. Moskowitz A Review of Earlier Clinical Studies on Neuroprotective Agents and Current Approaches Nils-Gunnar Wahlgren INDEX


Volume 41 Section I: Historical Overview

Verbal Fluency and Agrammatism Marco Molinari, Maria G. Leggio, and Maria C. Silveri

Rediscovery of an Early Concept Jeremy D. Schmahmann

Classical Conditioning Diana S. Woodruff-Pak

Section II: Anatomic Substrates

Early Infantile Autism Margaret L. Bauman, Pauline A. Filipek, and

Thomas L. Kemper

The Cerebrocerebellar System Jeremy D. Schmahmann and Deepak N. Pandya Cerebellar Output Channels Frank A. Middletan and Peter L. Strick Cerebellar-Hypothalamic Axis: Basic Circuits and Clinical Observations Duane E. Haines, Espen Dietrichs,

Gregory A. Mihaileff, and

E. Frank McDonald Section III. Physiological Observations Amelioration of Aggression: Response to Selec­ tive Cerebellar Lesions in the Rhesus Monkey Aaron J. Berman Autonomic and Vasomotor Regulation Donald J. Reis and Eugene V. Golanov Associative Learning Richard F. Thompson, Shaowen Bao, Lu Chen,

Benjamin D. Cipriano, Jeffrey S. Grethe, Jeansok

J. Kim, Judith K. Thompson, Jo Anne Tracy, Martha S. Weninger, and David J. Krupa


Olivopontocerebellar Atrophy and Fried-reich’s Ataxia: Neuropsychological Consequences of Bilateral versus Unilateral Cerebellar Lesions Th�e r�e se Botez-Marquard and Mihai I. Botez Posterior Fossa Syndrome Ian F. Pollack Cerebellar Cognitive Affective Syndrome Jeremy D. Schmahmann and Janet C. Sherman Inherited Cerebellar Diseases Claus W. Wallesch and Claudius Bartels Neuropsychological Abnormalities in Cerebellar Syndromes—Fact or Fiction? Irene Daum and Hermann Ackermann Section VI: Theoretical Considerations Cerebellar Microcomplexes Masao Ito Control of Sensory Data Acquisition James M. Bower

Visuospatial Abilities Robert Lalonde

Neural Representations of Moving Systems Michael Paulin

Spatial Event Processing Marco Molinari, Laura Petrosini, and Liliana G. Grammaldo Section IV: Functional Neuroimaging Studies

How Fibers Subserve Computing Capabilities: Similarities between Brains and Machines Henrietta C. Leiner and

Alan L. Leiner

Linguistic Processing Julie A. Fiez and Marcus E. Raichle

Cerebellar Timing Systems Richard Ivry

Sensory and Cognitive Functions Lawrence M. Parsons and Peter T. Fox

Attention Coordination and Anticipatory Control Natacha A. Akshoomoff, Eric Courchesne, and

Jeanne Townsend

Skill Learning Julien Doyon Section V: Clinical and Neuropsychological Observations Executive Function and Motor Skill Learning Mark Hallett and Jordon Grafman

Context-Response Linkage W. Thomas Thach Duality of Cerebellar Motor and Cognitive Functions James R. Bloedel and Vlastislav Bracha



Section VII: Future Directions Therapeutic and Research Implications Jeremy D. Schmahmann Volume 42 Alzheimer Disease Mark A. Smith Neurobiology of Stroke W. Dalton Dietrich Free Radicals, Calcium, and the Synaptic Plasticity-Cell Death Continuum: Emerging Roles of the Trascription Factor NF�B Mark P. Mattson AP-I Transcription Factors: Short- and LongTerm Modulators of Gene Expression in the Brain Keith Pennypacker Ion Channels in Epilepsy Istvan Mody Posttranslational Regulation of Ionotropic Glu­ tamate Receptors and Synaptic Plasticity Xiaoning Bi, Steve Standley, and Michel Baudry Heritable Mutations in the Glycine, GABAA, and Nicotinic Acetylcholine Receptors Provide New Insights into the Ligand-Gated Ion Chan­ nel Receptor Superfamily Behnaz Vafa and Peter R. Schofield INDEX

Volume 43 Early Development of the Drosophila Neuromus­ cular Junction: A Model for Studying Neuronal Networks in Development Akira Chiba Development of Larval Body Wall Muscles Michael Bate, Matthias Landgraf, and Mar Ruiz Gmez Bate Development of Electrical Properties and Synap­ tic Transmission at the Embryonic Neuro-mus­ cular Junction Kendal S. Broadie

Ultrastructural Correlates of Neuromuscular Junction Development Mary B. Rheuben, Motojiro Yoshihara, and Yoshiaki Kidokoro Assembly and Maturation of the Drosophila Lar­ val Neuromuscular Junction L. Sian Gramates and Vivian Budnik Second Messenger Systems Underlying Plasticity at the Neuromuscular Junction Frances Hannan and Ti Zhong Mechanisms of Neurotransmitter Release J. Troy Littleton, Leo Pallanck, and Barry Ganetzky Vesicle Recycling at the Drosophila Neuromuscu­ lar Junction Daniel T. Stimson and Mani Ramaswami Ionic Currents in Larval Muscles of Drosophila Satpal Singh and Chun-Fang Wu Development of the Adult Neuromuscular System Joyce J. Femandes and Haig Keshishian Controlling the Motor Neuron James R. Trimarchi, Ping Jin, and Rodney K. Murphey Volume 44 Human Ego-Motion Perception A. V. van den Berg Optic Flow and Eye Movements M. Lappe and K.-P. Hoffman The Role of MST Neurons during Ocular Tracking in 3D Space K. Kawano, U. Inoue, A. Takemura, Y. Kodaka, and F. A. Miles Visual Navigation in Flying Insects M. V. Srinivasan and S.-W. Zhang Neuronal Matched Filters for Optic Flow Proces­ sing in Flying Insects H. G. Krapp A Common Frame of Reference for the Analysis of Optic Flow and Vestibular Information B. J. Frost and D. R. W. Wylie Optic Flow and the Visual Guidance of Locomo­ tion in the Gat H. Sherk and G. A. Fowler



Stages of Self-Motion Processing in Primate Pos­ terior Parietal Cortex F. Bremmer, J.-R. Duhamel, S. B. Hamed,

and W. Graf

Cortical Reorganization and Seizure Generation in Dysplastic Cortex G. Avanzini, R. Preafico, S. Franceschetti, G. Sancini, G. Battaglia, and V. Scaioli

Optic Flow Analysis for Self-Movement Perception C. J. Duffy

Rasmussen’s Syndrome with Particular Refer­ ence to Cerebral Plasticity: A Tribute to Frank Morrell Fredrick Andermann and Yuonne Hart

Neural Mechanisms for Self-Motion Perception in Area MST R. A. Andersen, K. V. Shenoy, J. A. Crowell,

and D. C. Bradley

Computational Mechanisms for Optic Flow Analysis in Primate Cortex M. Lappe Human Cortical Areas Underlying the Percep­ tion of Optic Flow: Brain Imaging Studies M. W. Greenlee What Neurological Patients Tell Us about the Use of Optic Flow L. M. Vaina and S. K. Rushton INDEX

Volume 45

Structural Reorganization of Hippocampal Net­ works Caused by Seizure Activity Daniel H. Lowenstein Epilepsy-Associated Plasticity in gamma-Amnio­ butyric Acid Receptor Expression, Function and Inhibitory Synaptic Properties Douglas A. Coulter Synaptic Plasticity and Secondary Epilepto­ genesis Timothy J. Teyler, Steven L. Morgan, Rebecca N. Russell, and Brian L. Woodside Synaptic Plasticity in Epileptogenesis: Cellular Mechanisms Underlying Long-Lasting Synaptic Modifications that Require New Gene Expression Oswald Steward, Christopher S. Wallace, and Paul F Worley

Mechanisms of Brain Plasticity: From Normal Brain Function to Pathology Philip. A. Schwartzkroin

Cellular Correlates of Behavior Emma R. Wood, Paul A. Dudchenko, and Howard Eichenbaum

Brain Development and Generation of Brain Pathologies Gregory L. Holmes and Bridget McCabe

Mechanisms of Neuronal Conditioning Dcwid A. T King, David J. Krupa, Michael R. Foy, and Richard F. Thompson

Maturation of Channels and Receptors: Conse­ quences for Excitability David F Owens and Arnold R. Kriegstein

Plasticity in the Aging Central Nervous System C. A. Barnes

Neuronal Activity and the Establishment of Nor­ mal and Epileptic Circuits during Brain Development John W. Swann, Karen L. Smith, and Chong L. Lee The Effects of Seizures of the Hippocampus of the Immature Brain Ellen F Sperber and Solomon L. Moshe Abnormal Development and Catastrophic Epi­ lepsies: The Clinical Picture and Relation to Neuroimaging Harry T. Chugani and Diane C. Chugani

Secondary Epileptogenesis, Kindling, and Intractable Epilepsy: A Reappraisal from the Perspective of Neuronal Plasticity Thomas P. Sutula Kindling and the Mirror Focus Dan C. Mclntyre and Michael 0. Poulter Partial Kindling and Behavioral Pathologies Robert E. Adamec The Mirror Epileptogenesis B. J. Wilder






Hippocampal Lesions in Epilepsy: A Historical RobertNaquet Robert Naquet Clinical Evidence for Secondary Epileptogensis Hans 0. Luders Epilepsy as a Progressive (or Nonprogressive "Benign") Disorder John A. Wada Pathophysiological Aspects of Landau-Kleffher Syndrome: From the Active Epileptic Phase to Recovery Marie-Noelle Metz-Lutz, Pierre Maquet, Annd De Saint Martin, Gabrielle Rudolf, Norma Wioland, Edouard Hirsch, and Chriatian Marescaux Local Pathways of Seizure Propagation in Neocortex Barry W. Connors, David J. Pinto, and

Albert E. Telefeian

Multiple Subpial Assessment C. E. Polkey




The Legacy of Frank Morrell Jerome Engel, Jr. Volume 46 Neurosteroids: Beginning of the Story Etienne E. Baulieu, P. Robel, and M. Schumacher Biosynthesis of Neurosteroids and Regulation of Their Synthesis Synthia H. Mellon and Hubert Vaudry Neurosteroid 7-Hydroxylation Products in the Brain Robert Morfin and Luboslav St�arka Neurosteroid Analysis Ahmed A. Alomary, Robert L. Fitzgerald, and Robert H. Purdy Role of the Peripheral-Type Benzodiazepine Receptor in Adrenal and Brain Steroidogenesis Rachel C. Brown and Vassilios Papadopoulos Formation and Effects of Neuroactive Steroids in the Central and Peripheral Nervous System Roberto Cosimo Melcangi, Valeria Magnaghi,

Mariarita Galbiati, and Luciano Martini

Neurosteroid Modulation of Recombinant and Synaptic GABAA Receptors Jeremy J. Lambert, Sarah C. Homey, Delia Belelli, and John A. Peters GABAA-Receptor Plasticity during Long-Term Exposure to and Withdrawal from Progesterone Giovanni Biggio, Paolo Follesa, Enrico Sanna, Robert H. Purdy, and Alessandra Concas Stress and Neuroactive Steroids Maria Luisa Barbaccia, Mariangela Sena,

Robert H. Purdy, and Giovanni Biggio

Neurosteroids in Learning and Memory Processes Monique Vall�ee, Willy Mayo, George F. Koob, and Michel Le Moal Neurosteroids and Behavior Sharon R. Engel and Kathleen A. Grant Ethanol and Neurosteroid Interactions in the Brain A. Leslie Morrow, Margaret J. VanDoren, Rebekah Fleming, and Shannon Penland Preclinical Development of Neurosteroids as Neuroprotective Agents for the Treatment of Neurodegenerative Diseases Paul A. Lapchak and Dalia M. Araujo Clinical Implications of Circulating Neuroster­ oids Andrea R. Genazzani, Patrizia Monteleone,

Massimo Stomati, Francesca Bernardi,

Luigi Cobellis, Elena Casarosa, Michele Luisi,

Stefano Luisi, and Felice Petraglia

Neuroactive Steroids and Central Nervous Sys­ tem Disorders Mingde Wang, Torbjorn Ba¨ckstro¨m,

Inger Sundstrom, Go¨ran Wahlstro¨m,

Tommy Olsson, Di Zhu, Inga-Maj Johansson,

Inger Bjo¨rn, and Marie Bixo

Neuroactive Steroids in Neuropsychopharma­ cology Rainer Rupprecht and Florian Holsboer Current Perspectives on the Role of Neuroster­ oids in PMS and Depression Lisa D. Griffin, Susan C. Conrad, and Synthia H. Mellon INDEX


Volume 47 Introduction: Studying Gene Expression in Neural Tissues by in Situ Hybridization W. Wisden and B. J. Morris Part I: In Situ Hybridization with Radiolabelled Oligonucleotides In Situ Hybridization with Oligonucleotide Probes Wl. Wisden and B. J. Morris


Nonradioactive in Situ Hybridization: Simplified Procedures for Use in Whole Mounts of Mouse and Chick Embryos Linda Ariza-McNaughton and Robb Krumlauf INDEX

Volume 48

Cryostat Sectioning of Brains Victoria Revilla and Alison Jones

Assembly and Intracellular GABAA Receptors Eugene Barnes

Processing Rodent Embryonic and Early Post­ natal Tissue for in Situ Hybridization with Radi­ olabelled Oligonucleotides David J. Laurie, Petra C. U. Schrotz, Hannah Monyer, and Ulla Amtmann

Subcellular Localization and Regulation of GABAA Receptors and Associated Proteins Bernhard Liischer and Jean-Marc Fritschy D1 Dopamine Receptors Richard Mailman

Processing of Retinal Tissue for in Situ Hybridization Frank Miiller

Molecular Modeling of Ligand-Gated Ion Chan­ nels: Progress and Challenges Ed Bertaccini and James R. Trudel

Processing the Spinal Cord for in Situ Hybridiza­ tion with Radiolabelled Oligonucleotides A. Berthele and T. R. Tolle

Alzheimer’s Disease: Its Diagnosis and Patho­ genesis Jillian J. Kril and Glentla M. Halliday

Processing Human Brain Tissue for in Situ Hybri­ dization with Radiolabelled Oligonucleotides Louise F B. Nicholson

DNA Arrays and Functional Genomics in Neurobiology Christelle Thibault, Long Wang, Li Zhiang, and Michael F Miles

In Situ Hybridization of Astrocytes and Neurons Cultured in Vitro L. A. Arizza-McNaughton, C. De Felipe,

and S. P. Hunt

In Situ Hybridization on Organotypic Slice Cultures A. Gerfin-Moser and H. Monyer Quantitative Analysis of in Situ Hybridization Histochemistry Andrew L. Gundlach and Ross D. O’Shea Part II: Nonradioactive in Situ Hybridization Nonradioactive in Situ Hybridization Using Alkaline Phosphatase-Labelled Oligonucleotides S. J. Augood, E. M. McGowan, B. R. Finsen, B. Heppelmann, and P. C. Emson Combining Nonradioactive in Situ Hybridization with Immunohistological and Anatomical Techniques Petra Wahle




Volume 49 What Is West Syndrome? Olivier Dulac, Christine Soujflet, Catherine Chiron, and Anna Kaminski The Relationship between encephalopathy and Abnormal Neuronal Activity in the Developing Brain Frances E. Jensen Hypotheses from Functional Neuroimaging Studies Csaba Juh�asz, Harry T. Chugani, Ouo Muzik, and Diane C Chugani Infantile Spasms: Unique Sydrome or General Age-Dependent Manifestation of a Diffuse Encephalopathy? M. A. Koehn and M. Duchowny



Histopathology of Brain Tissue from Patients with Infantile Spasms Harry V. Vinters

Brain Malformation, Epilepsy, and Infantile Spasms M. Elizabeth Ross

Generators of Ictal and Interictal Electroence­ phalograms Associated with Infantile Spasms: Intracellular Studies of Cortical and Thalamic Neurons M. Steriade and L Timofeeu

Brain Maturational Aspects Relevant to Patho­ physiology of Infantile Spasms G. Auanzini, F. Panzica, and S. Franceschetti

Cortical and Subcortical Generators of Normal and Abnormal Rhythmicity David A. McCormick Role of Subcortical Structures in the Patho-gen­ esis of Infantile Spasms: What Are Possible Sub­ cortical Mediators? F. A. Lado and S. L. Mosh�e

Gene Expression Analysis as a Strategy to Understand the Molecular Pathogenesis of Infantile Spasms Peter B. Crino Infantile Spasms: Criteria for an Animal Model Carl E. Stafstrom and Gregory L. Holmes INDEX

What Must We Know to Develop Better Therapies? Jean Aicardi

Volume 50

The Treatment of Infantile Spasms: An Evidence-Based Approach Mark Mackay, Shelly Weiss, and 0. Carter Snead III

Part I: Primary Mechanisms

ACTH Treatment of Infantile Spasms: Mechan­ isms of Its Effects in Modulation of Neuronal Excitability K. L. Brunson, S. Avishai-Eliner, and T. Z. Baram Neurosteroids and Infantile Spasms: The Deox­ ycorticosterone Hypothesis Michael A. Rogawski and Doodipala S. Reddy Are there Specific Anatomical and/or Transmit­ ter Systems (Cortical or Subcortical) That Should Be Targeted? Phillip C. Jobe Medical versus Surgical Treatment: Which Treatment When W. Donald Shields Developmental Outcome with and without Suc­ cessful Intervention Rochelle Caplan, Prabha Siddarth, Gary Mathem, Harry Vinters, Susan Curtiss, Jennifer Levitt, Robert Asarnow, and W. Donald Shields Infantile Spasms versus Myoclonus: Is There a Connection? Michael R. Pranzatelli Tuberous Sclerosis as an Underlying Basis for Infantile Spasm Raymond S. Yeung

How Does Glucose Generate Oxidative Stress In Peripheral Nerve? Irina G. Obrosova Glycation in Diabetic Neuropathy: Characteris­ tics, Consequences, Causes, and Therapeutic Options Paul J. Thomalley Part II: Secondary Changes Protein Kinase C Changes in Diabetes: Is the Concept Relevant to Neuropathy? Joseph Eichberg Are Mitogen-Activated Protein Kinases Glucose Transducers for Diabetic Neuropathies? Tertia D. Purves and David R. Tomlinson Neurofilaments in Diabetic Neuropathy Paul Fernyhough and Robert E. Schmidt Apoptosis in Diabetic Neuropathy Aviva Tolkovsky Nerve and Ganglion Blood Flow in Diabetes: An Appraisal Douglas W. Zochodne Part III: Manifestations Potential Mechanisms of Neuropathic Pain in Diabetes Nigel A. Calcutt



Electrophysiologic Measures of Diabetic Neuro­ pathy: Mechanism and Meaning Joseph C. Arezzo and Elena Zotova Neuropathology and Pathogenesis of Diabetic Autonomic Neuropathy Robert E. Schmidt Role of the Neuropathy Luke Eckersky







Glucose Transporter Protein Syndromes Darryl C. De Vivo, Dong Wang, Juan M. Pascual, and Yuan Yuan Ho Glucose, Stress, and Hippocampal Neuronal Vulnerability Lawrence P. Reagan

Part IV: Potential Treatment Polyol Pathway Neuropathy Peter J. Oates

CNS Sensing and Regulation of Peripheral Glu­ cose Levels Barry E. Levin, Ambrose A. Dunn-Meynell, and Vanessa H. Routh


Nerve Growth Factor for the Treatment of Dia­ betic Neuropathy: What Went Wrong, What Went Right, and What Does the Future Hold? Stuart C. Apfel Angiotensin-Converting Enzyme Inhibitors: Are there Credible Mechanisms for Beneficial Effects in Diabetic Neuropathy: Rayaz A. Malik and David R. Tomlinson Clinical Trials for Drugs Against Diabetic Neu­ ropathy: Can We Combine Scientific Needs With Clinical Practicalities? Dan Ziegler and Dieter Luft INDEX

Glucose/Mitochondria in Neurological Conditions John P. Blass Energy Utilization in the Ischemic/Reperfused Brain John W. Phillis and Michael H. O’Regan Diabetes Mellitus and the Central Nervous System Anthony L. McCall Diabetes, the Brain, and Behavior: Is There a Biological Mechanism Underlying the Associa­ tion between Diabetes and Depression? A. M. Jacobson, J. A. Samson, K. Weinger, and C. M. Ryan Schizophrenia and Diabetes David C. Henderson and Elissa R. Ettinger Psychoactive Drugs Affect Glucose Transport and the Regulation of Glucose Metabolism Donard S. Dwyer, Timothy D. Ardizzone, and Ronald J. Bradley

Volume 51


Energy Metabolism in the Brain Leif Hertz and Gerald A. Dienel

Volume 52

The Cerebral Glucose-Fatty Acid Cycle: Evolu­ tionary Roots, Regulation, and (Patho) physiolo­ gical Importance Kurt Heininger

Neuroimmune Relationships in Perspective Frank Huckkbridge and Angela Clow

Expression, Regulation, and Functional Role of Glucose Transporters (GLUTs) in Brain Donard S. Dwyer, Susan J. Vannucci, and Ian A. Simpson Insulin-Like Growth Factor-1 Promotes Neu­ ronal Glucose Utilization During Brain Develop­ ment and Repair Processes Carolyn A. Bondy and Clara M. Cheng

Sympathetic Nervous System Interaction with the Immune System Virginia M. Sanders and Adam P. Kohm Mechanisms by Which Cytokines Signal the Brain Adrian J. Dunn Neuropeptides: Modulators of Responses in Health and Disease David S. Jessop




Brain—Immune Interactions in Sleep Lisa Marshall and Jan Born Neuroendocrinology of Autoimmunity Michael Harbuz Systemic Stress-Induced Th2 Shift and Its Clin­ ical Implications IbiaJ. Elenkov

Section II: Primary Respiratory Chain Disorders Mitochondrial Disorders of the Nervous System: Clinical, Biochemical, and Molecular Genetic Features Dominic Thyagarqjan and Edward Byrne Section III: Secondary Respiratory Chain Disorders

Neural Control of Salivary S-IgA Secretion Gordon B. Proctor and Guy H. Carpenter

Friedreich’s Ataxia J. M. Cooper andj. L. Bradley

Stress and Secretory Immunity Jos A. Bosch, Christopher Ring Eco J. C. de Geus, Enno C. I. Veerman, and Arie V. Nieuw Amerongen

Wilson Disease C. A. Davie and A. H. V. Schapira

Cytokines and Depression Angela Clow Immunity and Schizophrenia: Autoimmunity, Cytokines, and Immune Responses Fiona Gaughran Cerebral Lateralization and the Immune System Pierre J. Neveu Behavioral Conditioning of the Immune System Frank Huckkbridge Psychological and Neuroendocrine Correlates of Disease Progression Julie M. Turner-Cobb The Role of Psychological Intervention in Mod­ ulating Aspects of Immune Function in Relation to Health and Well-Being J. H. Gruzelier INDEX

Volume 53 Section I: Mitochondrial Structure and Function Mitochondrial DNA Structure and Function Carlos T. Moraes, Sarika Srivastava, Ilias Krkinezos, Jose Oca-Cossio, Corina van Waveren, Markus Woischnick, and Francisca Diaz Oxidative Phosphorylation: Structure, Function, and Intermediary Metabolism Simon J. R. Heales, Matthew E. Gegg, and John B. Clark Import of Mitochondrial Proteins Matthias F. Bauer, Sabine Hofmann, and Walter Neupert

Hereditary Spastic Paraplegia Christopher J. McDerrmott and Pamela J. Shaw Cytochrome c Oxidase Deficiency Giacomo P. Comi, Sandra Strazzer, Sara Galbiati, and Nereo Bresolin Section IV: Toxin Induced Mitochondrial Dysfunction Toxin-Induced Mitochondrial Dysfunction Susan E. Browne and M. Flint Beal Section V: Neurodegenerative Disorders Parkinson’s Disease L.V.P. Korlipara and A. H. V. Schapira Huntington’s Disease: The Mystery Unfolds? ˚ sa Peters�en and Patrik Brundin A Mitochondria in Alzheimer’s Disease Russell H. Swerdlow and Stephen J. Kish Contributions of Mitochondrial Alterations, Resulting from Bad Genes and a Hostile Envir­ onment, to the Pathogenesis of Alzheimer’s Disease Mark P. Mattson Mitochondria and Amyotrophic Lateral Sclerosis Richard W. Orrell and Anthony H. V. Schapira Section VI: Models of Mitochondrial Disease Models of Mitochondrial Disease Danae Liolitsa and Michael G. Hanna Section VII: Defects of � Oxidation Including Carnitine Deficiency Defects of � Oxidation Including Carnitine Deficiency K. Bartlett and M. Pourfarzam


Section VIII: Mitochondrial Involvement in Aging The Mitochondrial Theory of Aging: Involve­ ment of Mitochondrial DNA Damage and Repair Nadja C. de Souza-Pinto and Vilhelm A. Bohr INDEX

Volume 54 Unique General Anesthetic Binding Sites Within Distinct Gonformational States of the Nicotinic Acetylcholine Receptor Hugo R. Ariaas, William, R. Kem, James R. Truddell, and Michael P. Blanton Signaling Molecules and Receptor Transduction Cascades That Regulate NMDA ReceptorMediated Synaptic Transmission Suhas. A. Kotecha and John F. MacDonald Behavioral Measures of Alcohol Self-Administra­ tion and Intake Control: Rodent Models Herman H. Samson and Cristine L. Czachowski Dopaminergic Mouse Mutants: Investigating the Roles of the Different Dopamine Receptor Sub­ types and the Dopamine Transporter Shirlee Tan, Bettina Hermann, and Emiliana Borrelli Drosophila melanogaster, A Genetic Model System for Alcohol Research Douglas J. Guarnieri and Ulrike Heberlein


Problems in the Use of Herpes Simplex Virus as a Vector L. T. Feldman Lentiviral Vectors J. Jakobsson, C. Ericson, JV. Rosenquist, and C. Lundberg Retroviral Vectors for Gene Delivery to Neural Precursor Cells K. Kageyama, H. Hirata, andj. Hatakeyama Section II: Gene Therapy with Virus Vectors for Specific Disease of the Nervous System The Principles of Molecular Therapies for Glioblastoma G. Karpati and J. Nalbatonglu Oncolytic Herpes Simplex Virus J. C. C. Hu and R. S. Coffin Recombinant Retrovirus Vectors for Treatment of Brain Tumors N. G. Rainov and C. M. Kramm Adeno-Associated Viral Vectors for Parkinson’s Disease I. Muramatsu, L. Wang K. Ikeguchi, K-i Fujimoto, T. Okada, H. Mizukami, T. Hanazono, A. Kume, I. J. Vakano, and K. Ozawa HSV Vectors for Parkinson’s Disease D. S. Latchman Gene Therapy for Stroke K. Abe and W. R. Zhang Gene Therapy for Mucopolysaccharidosis A. Bosch and J. M. Heard



Volume 55

Volume 56

Section I: Virsu Vectors For Use in the Nervous System

Behavioral Mechanisms and the Neurobiology of Conditioned Sexual Responding Mark Krause

Non-Neurotropic Adenovirus: a Vector for Gene Transfer to the Brain and Gene Therapy of Neurological Disorders P. R. Lowenstein, D. Suwelack, J. Hu, X. Yuan, M. Jimenez-Dalmaroni, S. Goverdhama, and M.G. Castro Adeno-Associated Virus Vectors E. Lehtonen and L. Tenenbaum

NMDA Receptors in Alcoholism Paula L. Hoffman Processing and Representation of Species-Specific Communication Calls in the Auditory System of Bats George D. Pollak, Achim Klug, and Erie E. Bauer



Central Nervous System Control of Micturition Gert Holstege and Leonora J. Mouton The Structure and Physiology of the Rat Audi­ tory System: An Overview Manuel Malmierca

Postsynaptic Density Scaffolding Proteins at Excitatory Synapse and Disorders of Synaptic Plasticity: Implications for Human Behavior Pathologies Andrea de Bartolomeis and Germane Fiore

Neurobiology of Cat and Human Sexual Behavior Gert Holstege and J. R. Georgiadis

Prostaglandin-Mediated Signaling in Schizo­ phrenia S. Smesny


Volume 57

Mitochondria, Synaptic Plasticity, and Schizo­ phrenia Dorit Ben-Shachar and Daphna Laifenfeld

Cumulative Subject Index of Volumes 1–25

Membrane Phospholipids and Cytokine Interac­ tion in Schizophrenia Jeffrey K. Yao and Daniel P. van Kammen

Volume 58

Neurotensin, Schizophrenia, and Antipsychotic Drug Action Becky Kinkead and Charles B. Nemeroff

Cumulative Subject Index of Volumes 26–50

Volume 59 Loss of Spines and Neuropil Liesl B. Jones Schizophrenia as a Disorder of Neuroplasticity Robert E. McCullumsmith, Sarah M. Clinton, and James H. Meador-Woodruff The Synaptic Pathology of Schizophrenia: Is Aberrant Neurodevelopment and Plasticity to Blame? Sharon L. Eastwood Neurochemical Basis for an Epigenetic Vision of Synaptic Organization E. Costa, D. R. Grayson, M. Veldic,

and A. Guidotti

Muscarinic Receptors in Schizophrenia: Is There a Role for Synaptic Plasticity? Thomas J. Raedler

Schizophrenia, Vitamin D, and Brain Development Alan Mackay-Sim, Franc¸ois Feron, Dartyl Eyles, Thomas Bume, and John McGrath Possible Contributions of Myelin and Oligo­ dendrocyte Dysfunction to Schizophrenia Daniel G. Stewart and Kenneth L. Davis Brain-Derived Neurotrophic Factor and the Plasticity of the Mesolimbic Dopamine Pathway Oliver Guillin, Nathalie Griffon, Jorge Diaz, Bernard Le Foil, Erwan Bezard, Christian Gross, Chris Lammers, Holger Stark, Patrick Carroll, Jean-Charles Schwartz, and Pierre Sokoloff S100B in Schizophrenic Psychosis Matthias Rothermundt, Gerald Ponath, and Volker Arolt Oct-6 Transcription Factor Maria Ilia NMDA Receptor Function, Neuroplasticity, and the Pathophysiology of Schizophrenia Joseph T. Coyle and Guochuan Tsai INDEX

Serotonin and Brain Development Monsheel S. K Sodhi and Elaine Sanders-Bush

Volume 60

Presynaptic Proteins and Schizophrenia William G. Honer and Clint E. Young

Microarray Platforms: Introduction and Appli­ cation to Neurobiology Stanislav L. Karsten, Lili C. Kudo, and

Daniel H. Geschwind

Mitogen-Activated Protein Kinase Signaling Svetlana V. Kyosseva



Experimental Design and Low-Level Analysis of Microarray Data B. M. Bolstad, F. Collin, K M. Simpson, R. A. Irizarry, and T. P. Speed Brain Gene Expression: Genomics and Genetics ElissaJ. Chester and Robert W. Williams

Proteomics Analysis in Alzheimer’s Disease: New Insights into Mechanisms of Neurodegeneration D. Allan Butterfield and Debra Boyd-Kimball Proteomics and Alcoholism Frank A. Witzmann and Wendy N. Strother

DNA Microarrays and Animal Models of Learn­ ing and Memory Sebastiano Cavallaro

Proteomics Studies of Traumatic Brain Injury Kevin K. W. Wang, Andrew Ottens, William Haskins, Ming Cheng Liu, Firas Kobeissy, Nancy Denslow, SuShing Chen, and Ronald L. Hayes

Microarray Analysis of Human Nervous System Gene Expression in Neurological Disease Steven A. Greenberg

Influence of Huntington’s Disease on the Human and Mouse Proteome Claus Zabel and Joachim Klose

DNA Microarray Analysis of Postmortem Brain Tissue K�aroly Mirnics, Pat Levitt, and David A. Lewis

Section V: Overview of the Neuroproteome


Proteomics—Application to the Brain Katrin Marcus, Oliver Schmidt, Heike Schaefer, Michael ˚ van Hall, and Helmut E. Meyer Hamacher, AndrA INDEX

Volume 61 Section I: High-Throughput Technologies Biomarker Discovery Using Molecular Profiling Approaches Stephen J. Walker and Arron Xu Proteomic Analysis of Mitochondrial Proteins Mary F. Lopez, Simon Melov, Felicity Johnson, Nicole Nagulko, Eva Golenko, Scott Kuzdzal, Suzanne Ackloo, and Alvydas Mikulskis Section II: Proteomic Applications NMDA Receptors, Neural Pathways, and Pro­ tein Interaction Databases Holger Husi Dopamine Transporter Network and Pathways Rajani Maiya and R. Dayne Mayjield

Volume 62 GABAA Receptor Structure–Function Studies: A Reexamination in Light of New Acetylcholine Receptor Structures Myles H. Akabas Dopamine Mechanisms and Cocaine Reward Aiko Ikegami and Christine L. Duvauchelle Proteolytic Dysfunction in Neurodegenerative Disorders Kevin St. P. McNaught Neuroimaging Studies in Bipolar Children and Adolescents Rene L. Olvera, David C. Glahn, Sheila C. Caetano, Steven R. Pliszka, andjair C. Soares

Proteomic Approaches in Drug Discovery and Development Holly D. Soares, Stephen A. Williams, Peter J. Snyder, Feng Gao, Tom Stiger, Christian Rohljf, Athula Herath, Trey Sunderland, Karen Putnam, and W. Frost White

Chemosensory G-Protein-Coupled Signaling in the Brain Geoffrey E. Woodard


Section III: Informatics Proteomic Informatics Steven Russell, William Old, Katheryn Resing, and Lawrence Hunter

The Use of Caenorhabditis elegans in Molecular Neuropharmacology Jill C. Bettinger, Lucinda Carnell, Andrew G. Davies, and Steven L. McIntire

Section IV: Changes in the Proteome by Disease


Disturbances of Emotion Regulation after Focal Brain Lesions Antoine Bechara



Volume 63

Volume 65

Mapping Neuroreceptors at work: On the Defi­ nition and Interpretation of Binding Potentials after 20 years of Progress Albert Gjedde, Dean F. Wong, Pedro Rosa-Neto, and Paul Cumming

Insulin Resistance: Causes and Consequences Zachary T. Bloomgarden

Mitochondrial Dysfunction in Bipolar Disorder: From 31P-Magnetic Resonance Spectroscopic Findings to Their Molecular Mechanisms Tadafumi Kato Large-Scale Microarray Studies of Gene Expres­ sion in Multiple Regions of the Brain in Schizo­ phrenia and Alzeimer’s Disease Pavel L. Katsel, Kenneth L. Davis, and Vahram Haroutunian Regulation of Serotonin 2C Receptor PRE­ mRNA Editing By Serotonin Claudia Schmauss The Dopamine Hypothesis of Drug Addiction: Hypodopaminergic State Miriam Melis, Saturnino Spiga, and Marco Diana Human and Animal Spongiform Encephalopa­ thies are Autoimmune Diseases: A Novel Theory and Its supporting Evidence Bao Ting Zhu Adenosine and Brain Function Bertil B. Fredholm, Jiang-Fan Chen, Rodrigo A. Cunha, Per Svenningsson, and Jean-Marie Vaugeois INDEX

Volume 64 Section I. The Cholinergic System John Smythies Section II. The Dopamine System John Symythies

Antidepressant-Induced Manic Conversion: A Developmentally Informed Synthesis of the Literature Christine J. Lim, James F. Leckman, Christopher Young, and Andr�e s Martin Sites of Alcohol and Volatile Anesthetic Action on Glycine Receptors Ingrid A. Lobo and R. Adron Harris Role of the Orbitofrontal Cortex in Reinforce­ ment Processing and Inhibitory Control: Evi­ dence from Functional Magnetic Resonance Imaging Studies in Healthy Human Subjects Rebecca Elliott and Bill Deakin Common Substrates of Dysphoria in Stimulant Drug Abuse and Primary Depression: Therapeu­ tic Targets Kate Baicy, Carrie E. Bearden, John Monterosso, Arthur L. Brody, Andrew J. Isaacson, and Edythe D. London The Role of cAMP Response Element–Binding Proteins in Mediating Stress-Induced Vulner­ ability to Drug Abuse Arati Sadalge Kreibich and Julie A. Blendy G-Protein–Coupled Receptor Deorphanizations Yumiko Saito and Olivier Civelli Mechanistic Connections Between Glucose/ Lipid Disturbances and Weight Gain Induced by Antipsychotic Drugs Donard S. Dwyer, Dallas Donohoe, Xiao-Hong Lu, and Eric J. Aamodt Serotonin Firing Activity as a Marker for Mood Disorders: Lessons from Knockout Mice Gabriella Gobbi INDEX

Section III. The Norepinephrine System John Smythies Section IV. The Adrenaline System John Smythies

Volume 66

Section V. Serotonin System John Smythies

Brain Atlases of Normal and Diseased Populations Arthur W. Toga and Paul M. Thompson



Neuroimaging Databases as a Resource for Scientific Discovery John Darrell Van Horn, John Wolfe,

Autumn Agnoli, Jeffrey Woodward,

Michael Schmitt, James Dobson,

Sarene Schumacher, and Bennet Vance

Modeling Brain Responses Karl J. Friston, William Penny, and Olivier David Voxel-Based Morphometric Analysis Using Shape Transformations Christos Davatzikos


Neuroimaging in Functional Somatic Syndromes Patrick B. Wood Neuroimaging in Multiple Sclerosis Alireza Minagar, Eduardo Gonzalez-Toledo, James Pinkston, and Stephen L. Jaffe Stroke Roger E. Kelley and Eduardo Gonzalez-Toledo Functional MRI in Pediatric Neurobehavioral Disorders Michael Seyffert and F. Xavier Castellanos

Quantification of White Matter Using DiffusionTensor Imaging Hae-Jeong Park

Structural MRI and Brain Development Paul M. Thompson, Elizabeth R. Sowell,

Nitin Gogtay, Jay N. Giedd, Christine

N. Vidal, Kiralee M. Hayashi, Alex Leow,

Rob Nicolson, Judith L. Rapoport, and

Arthur W. Toga

Perfusion fMRI for Functional Neuroimaging Geoffrey K. Aguirre, John A. Detre, and Jiongjiong Wang

Neuroimaging and Human Genetics Georg Winterer, Ahmad R. Hariri, David Goldman, and Daniel R. Weinberger

Functional Near-Infrared Spectroscopy: Poten­ tial and Limitations in Neuroimaging Studies Toko Hoshi

Neuroreceptor Imaging in Psychiatry: Theory and Applications W. Gordon Frankle, Mark Slifstein, Peter S. Talbot, and Marc Laruelle

The Cutting Edge of fMRI and High-Field fMRI Dae-Shik Kim

Neural Modeling and Functional Brain Imaging: The Interplay Between the Data-Fitting and Simulation Approaches Barry Horwitz and Michael F. Glabus Combined EEG and fMRI Studies of Human Brain Function V. Menon and S. Crottaz-Herbette INDEX

Volume 67 Distinguishing Neural Substrates of Heterogene­ ity Among Anxiety Disorders Jack B. Nitschke and Wendy Heller Neuroimaging in Dementia K. P. Ebmeier, C. Donaghey, and N. J. Dougall Prefrontal and Anterior Cingulate Contributions to Volition in Depression Jack B. Nitschke and Kristen L. Mackiewicz Functional Imaging Research in Schizophrenia H. Tost, G. Ende, M. Ruf, F. A. Henn, and A. Meyer-Lindenberg


Volume 68 Fetal Magnetoencephalography: Viewing the Developing Brain In Utero Hubert Preissl, Curtis L. Lowery, and Hari Eswaran Magnetoencephalography in Studies of Infants and Children Minna Huotilainen Let’s Talk Together: Memory Traces Revealed by Cooperative Activation in the Cerebral Cortex Jochen Kaiser, Susanne Leiberg, and Werner


Human Communication Investigated With Magnetoencephalography: Speech, Music, and Gestures Thomas R. Kno¨sche, Burkhard Maess, Akinori

Nakamura, and Angela D. Friederici



Combining Magnetoencephalography Functional Magnetic Resonance Imaging Klaus Mathiak and Andreas J. Fallgatter


Across-Channel Spectral Processing John H. Grose, Joseph W. Hall III, and Emily Buss

Beamformer Analysis of MEG Data Arjan Hillebrand and Gareth R. Barnes Functional Connectivity Analysis Magnetoencephalography Alfons Schnitzler and Joachim Gross

Basic Psychophysics of Human Spectral Processing Brian C. J. Moore


Human Visual Processing as Revealed by Mag­ netoencephalographys Yoshiki Kaneoke, Shoko Watanabe, and Ryusuke Kakigi A Review of Clinical Applications of Magnetoencephalography Andrew C. Papanicolaou, Eduardo M. Castillo, Rebecca Billingsley-Marshall, Ekaterina Pataraia, and Panagiotis G. Simos INDEX

Volume 69 Nematode Neurons: Anatomy and Anatomical Methods in Caenorhabditis elegans David H Hall, Robyn Lints, and Zeynep Altun Investigations of Learning and Memory in Cae­ norhabditis elegans Andrew C. Giles, Jacqueline K. Rose, and Catharine H. Rankin Neural Specification and Differentiation Eric Aamodt and Stephanie Aamodt Sexual Behavior of the Caenorhabditis elegans Male Scott W. Emmons The Motor Circuit Stephen E. Von Stetina, Millet Treinin, and David M. Miller III Mechanosensation in Caenorhabditis elegans Robert O’Hagan and Martin Chalfie Volume 70 Spectral Processing by the Peripheral Auditory System Facts and Models Enrique A. Lopez-Poveda

Speech and Music Have Different Requirements for Spectral Resolution Robert V. Shannon Non-Linearities and the Representation of Audi­ tory Spectra Eric D. Young, Jane J. Yu, and Lina A. J. Reiss Spectral Processing in the Inferior Colliculus Kevin A. Davis Neural Mechanisms for Spectral Analysis in the Auditory Midbrain, Thalamus, and Cortex Monty A. Escabi and Heather L. Read Spectral Processing in the Auditory Cortex Mitchell L. Sutter Processing of Dynamic Spectral Properties of Sounds Adrian Rees and Manuel S. Malmierca Representations of Spectral Coding in the Human Brain Deborah A. Hall, PhD Spectral Processing Determination Donal G. Sinex




Spectral Information in Sound Localization Simon Carlile, Russell Martin, and Ken McAnally Plasticity of Spectral Processing Dexter R. F. Irvine and Beverly A. Wright Spectral Processing In Cochlear Implants Colette M. McKay INDEX

Volume 71 Autism: Neuropathology, Alterations of the GA-BAergic System, and Animal Models Christoph Schmitz, Imke A. J. van Kooten, Patrick R. Hof, Herman van Engeland, Paul H. Patterson, and Harry W. M. Steinbusch The Role of GABA in the Early Neuronal Development Marta Jelitai and Emi ’lia Madarasz


GABAergic Signaling Cerebellum Chitoshi Takayama




Shared Chromosomal Susceptibility Regions Between Autism and Other Mental Disorders Yvon C. Chagnon index

Insights into GABA Functions in the Developing Cerebellum Mo 0 nica L. Fiszman


Role of GABA in the Mechanism of the Onset of Puberty in Non-Human Primates Ei Terasawa

Volume 72

Rett Syndrome: A Rosetta Stone for Understanding the Molecular Pathogenesis of Autism Janine M. LaSalle, Amber Hogart, and Karen N. Thatcher GABAergic Cerebellar System in Autism: A Neu-ropathological and Developmental Perspec­ tive Gene J. Blatt Reelin Glycoprotein Schizophrenia S. Hossein Fatemi




Is There A Connection Between Autism, PraderWilli Syndrome, Catatonia, and GABA? Dirk M. Dhossche, Yaru Song, and Yiming Liu Alcohol, GABA Receptors, and Neurodevelop­ mental Disorders Ujjwal K. Rout Effects of Secretin on Extracellular GABA and Other Amino Acid Concentrations in the Rat Hippocampus Hans-Willi Clement, Alexander Pschibul, and Eberhard Schulz Predicted Role of Secretin and Oxytocin in the Treatment of Behavioral and Developmental Disorders: Implications for Autism Martha G. Welch and David A. Ruggiero Immunological Findings in Autism Hari Har Parshad Cohly and Asit Panja Correlates of Psychom*otor Symptoms in Autism Laura Stoppelbein, Sara Sytsma-Jordan, and Leilani Greening GABRB3 Gene Deficient Mice: A Potential Model of Autism Spectrum Disorder Timothy M. DeLorey The Reeler Mouse: Anatomy of a Mutant Gabriella D’Arcangelo


Classification Matters for Catatonia and Autism in Children Klaus-Ju¨ rgen Neuma¨rker A Systematic Examination of Catatonia-Like Clinical Pictures in Autism Spectrum Disorders Lorna Wing and Amitta Shah Catatonia in Individuals with Autism Spectrum Disorders in Adolescence and Early Adulthood: A Long-Term Prospective Study Masataka Ohta, Yukiko Kano, and Yoko Nagai Are Autistic and Catatonic Regression Related? A Few Working Hypotheses Involving GABA, Purkinje Cell Survival, Neurogenesis, and ECT Dirk Marcel Dhossche and Ujjwal Rout Psychom*otor Development and Psychopath­ ology in Childhood Dirk M. J. De Raeymaecker The Importance of Catatonia and Stereotypies in Autistic Spectrum Disorders Laura Stoppelbein, Leilani Greening, and Angelina Kakooza Prader–Willi Syndrome: Atypical Psychoses and Motor Dysfunctions Willem M. A. Verhoeven and Siegfried Tuinier Towards a Valid Nosography and Psychopath­ ology of Catatonia in Children and Adolescents David Cohen Is There a Common Neuronal Basis for Autism and Catatonia? Dirk Marcel Dhossche, Brendan T. Carroll, and Tressa D. Carroll Shared Susceptibility Region on Chromosome 15 Between Autism and Catatonia Yvon C. Chagnon Current Trends in Behavioral Interventions for Children with Autism Dorothy Scattone and Kimberly R. Knight



Case Reports with a Child Psychiatric Explora­ tion of Catatonia, Autism, and Delirium Jan N. M. Schieveld ECT and the Youth: Catatonia in Context Frank K. M. Zaw Catatonia in Autistic Spectrum Disorders: A Medical Treatment Algorithm Max Fink, Michael A. Taylor, and Neera Ghaziuddin Psychological Approaches to Chronic CatatoniaLike Deterioration in Autism Spectrum Disorders Amitta Shah and Lorna Wing Section V: Blueprints Blueprints for the Assessment, Treatment, and Future Study of Catatonia in Autism Spectrum Disorders Dirk Marcel, Dhossche, Amitta Shah, and Lorna Wing INDEX

Volume 73 Chromosome 22 Deletion Syndrome and Schizophrenia Nigel M. Williams, Michael C. O’Donovan, and Michael J. Owen Characterization of Proteome of Human Cere­ brospinal Fluid Jing Xu, Jinzhi Chen, Elaine R. Peskind, Jinghua Jin, Jimmy Eng, Catherine Pan, Thomas J. Montine, David R. Goodlett, and Jing Zhang Hormonal Pathways Regulating Intermale and Interfemale Aggression Neal G. Simon, Qianxing Mo, Shan Hu,

Carrie Garippa, and Shi-Fang Lu

Neuronal GAP Junctions: Expression, Function, and Implications for Behavior Clinton B. McCracken and David C. S. Roberts Effects of Genes and Stress on the Neurobiology of Depression J. John Mann and Dianne Currier Quantitative Imaging with the Micropet SmallAnimal Pet Tomograph Paul Vaska, Daniel J. Rubins, David L. Alexoff, and Wynne K. Schiffer

Understanding Myelination through Studying its Evolution Ru¨ diger Schweigreiter, Betty I. Roots, Christine Bandtlow, and Robert M. Gould INDEX

Volume 74 Evolutionary Neurobiology and Art C. U. M. Smith Section I: Visual Aspects Perceptual Portraits Nicholas Wade The Neuropsychology of Visual Art: Conferring Capacity Anjan Chatterjee Vision, Illusions, and Reality Christopher Kennard Localization in the Visual Brain George K. York Section II: Episodic Disorders Neurology, Synaesthesia, and Painting Amy Ione Fainting in Classical Art Philip Smith Migraine Art in the Internet: A Study of 450 Contemporary Artists Klaus Podoll Sarah Raphael’s Migraine with Aura as Inspira­ tion for the Foray of Her Work into Abstraction Klaus Podoll and Debbie Ayles The Visual Art of Contemporary Artists with Epilepsy Steven C. Schachter Section III: Brain Damage Creativity in Painting and Style in BrainDamaged Artists Julien Bogousslavsky Artistic Changes in Alzheimer’s Disease Sebastian J. Crutch and Martin N. Rossor Section IV: Cerebrovascular Disease Stroke in Painters H. Ba¨zner and M. Hennerici



Visuospatial Neglect in Lovis Corinth’s SelfPortraits Olaf Blanke

Transmitter Release at the Neuromuscular Junction Thomas L. Schwarz

Art, Constructional Apraxia, and the Brain Louis Caplan

Vesicle Trafficking and Recycling at the Neuro­ muscular Junction: Two Pathways for Endocytosis Yoshiaki Kidokoro

Section V: Genetic Diseases Neurogenetics in Art Alan E. H. Emery A Naı¨ ve Artist of St Ives F. Clifford Rose Van Gogh’s Madness F. Clifford Rose Absinthe, The Nervous System and Painting Tiina Rekand Section VI: Neurologists as Artists Sir Charles Bell, KGH, FRS, FRSE (1774–1842) Christopher Gardner-Thorpe Section VII: Miscellaneous Peg Leg Frieda Espen Dietrichs The Deafness of Goya (1746–1828) F. Clifford Rose INDEX

Volume 75 Introduction on the Use of the Drosophila Embryonic/Larval Neuromuscular Junction as a Model System to Study Synapse Development and Function, and a Brief Summary of Pathfind­ ing and Target Recognition Catalina Ruiz-Can˜ada and Vivian Budnik

Glutamate Receptors at the Drosophila Neuro­ muscular Junction Aaron DiAntonio Scaffolding Proteins at the Drosophila Neuromus­ cular Junction Bulent Ataman, Vivian Budnik, and Ulrich Thomas Synaptic Cytoskeleton at the Neuromuscular Junction Catalina Ruiz-Can˜ada and Vivian Budnik Plasticity and Second Messengers During Synapse Development Leslie C. Griffith and Vivian Budnik Retrograde Signaling that Regulates Synaptic Development and Function at the Drosophila Neuromuscular Junction Guillermo Marqu�e s and Bing Zhang Activity-Dependent Regulation of Transcription During Development of Synapses Subhabrata Sanyal and Mani Ramaswami Experience-Dependent Potentiation of Larval Neuromuscular Synapses Christoph M. Schuster Selected Methods for the Anatomical Study of Drosophila Embryonic and Larval Neuromuscular Junctions Vivian Budnik, Michael Gorczyca, and Andreas Prokop INDEX

Development and Structure of Motoneurons Matthias Landgraf and Stefan Thor The Development of the Drosophila Larval Body Wall Muscles Karen Beckett and Mary K. Baylies Organization of the Efferent System and Struc­ ture of Neuromuscular Junctions in Drosophila Andreas Prokop Development of Motoneuron Electrical Proper­ ties and Motor Output Richard A. Baines

Volume 76 Section I: Physiological Correlates of Freud’s Theories The ID, the Ego, and the Temporal Lobe Shirley M. Ferguson and Mark Rayport ID, Ego, and Temporal Lobe Revisited Shirley M. Ferguson and Mark Rayport



Section II: Stereotaxic Studies Olfactory Gustatory Responses Evoked by Elec­ trical Stimulation of Amygdalar Region in Man Are Qualitatively Modifiable by Interview Con­ tent: Case Report and Review Mark Rayport, Sepehr Sani, and Shirley M. Ferguson Section III: Controversy in Definition of Beha­ vioral Disturbance Pathogenesis of Psychosis in Epilepsy. The "Seesaw" Theory: Myth or Reality? Shirley M. Ferguson and Mark Rayport Section IV: Outcome of Temporal Lobectomy Memory Function After Temporal Lobectomy for Seizure Control: A Comparative Neuropsy chiatric and Neuropsychological Study Shirley M. Ferguson, A. John McSweeny, and Mark Rayport Life After Surgery for Temporolimbic Seizures Shirley M. Ferguson, Mark Rayport, and Carolyn A. Schell

Neurogenesis and Neuroenhancement in the Pathophysiology and Treatment of Bipolar Disorder Robert J. Schloesser, Guang Chen, and Husseini K. Manji Neuroreplacement, Growth Factor, and Small Molecule Neurotrophic Approaches for Treating Parkinson’s Disease Michael J. O’Neill, Marcus J. Messenger, Viktor Lakics, Tracey K. Murray, Eric H. Karran, Philip G. Szekeres, Eric S. Nisenbaum, and Kalpana M. Merchant Using Caenorhabditis elegans Models of Neuro­ degenerative Disease to Identify Neuroprotective Strategies Brian Kraemer and Gerard D. Schellenberg Neuroprotection and Enhancement of Neurite Outgrowth With Small Molecular Weight Com­ pounds From Screens of Chemical Libraries Donard S. Dwyer and Addie Dickson INDEX

Appendix I Mark Rayport Appendix II: Conceptual Foundations of Studies of Patients Undergoing Temporal Lobe Surgery for Seizure Control Mark Rayport

Volume 78


Neurobiology of Dopamine in Schizophrenia Olivier Guillin, Anissa Abi-Dargham, and Marc Laruelle

Volume 77

The Dopamine System and the Pathophysiology of Schizophrenia: A Basic Science Perspective Yukiori Goto and Anthony A. Grace

Regenerating the Brain David A. Greenberg and Kunlin Jin Serotonin and Brain: Evolution, Neuroplasticity, and Homeostasis Efrain C. Azmitia

Glutamate and Schizophrenia: Phencyclidine, N-methyl-D-aspartate Receptors, and Dopamine–Glutamate Interactions Daniel C. Javitt Deciphering the Disease Process of Schizo­ phrenia: The Contribution of Cortical GABA Neurons David A. Lewis and Takanori Hashimoto

Therapeutic Approaches to Promoting Axonal Regeneration in the Adult Mammalian Spinal Cord Sari S. Hannila, Mustafa M. Siddiq, and Marie T. Filbin

Alterations of Serotonin Schizophrenia Anissa Abi-Dargham

Evidence for Neuroprotective Effects of Antipsy­ chotic Drugs: Implications for the Pathophysiol­ ogy and Treatment of Schizophrenia Xin-Min Li and Haiyun Xu

Serotonin and Dopamine Interactions in Rodents and Primates: Implications for Psychosis and Antipsychotic Drug Development Gerard J. Marek




Cholinergic Circuits and Signaling in the Patho­ physiology of Schizophrenia Joshua A. Berman, David A. Talmage, and

Lorna W. Role

Schizophrenia and the �7 Nicotinic Acetylchol­ ine Receptor Laura F. Martin and Robert Freedman Histamine and Schizophrenia Jean-Michel Arrang Gannabinoids and Psychosis Deepak Cyril D’Souza Involvement of Neuropeptide Systems in Schizo­ phrenia: Human Studies Ricardo C�aceda, Becky Kinkead, and

Charles B. Nemeroff

Brain-Derived Neurotrophic Factor in Schizo­ phrenia and Its Relation with Dopamine Olivier Guillin, Caroline Demily, and

Florence Thibaut

Schizophrenia Susceptibility Genes: In Search of a Molecular Logic and Novel Drug Targets for a Devastating Disorder Joseph A. Gogos INDEX

Volume 79 The Destructive Alliance: Interactions of Leuko­ cytes, Cerebral Endothelial Cells, and the Immune Cascade in Pathogenesis of Multiple Sclerosis Alireza Minagar, April Carpenter, and J. Steven Alexander Role of B Cells in Pathogenesis of Multiple Sclerosis Behrouz Nikbin, Mandana Mohyeddin Bonab,

Farideh Khosravi, and Fatemeh Talebian

The Role of CD4 T Cells in the Pathogenesis of Multiple Sclerosis Tanuja Chitnis The CD8 T Cell in Multiple Sclerosis: Suppres­ sor Cell or Mediator of Neuropathology? Aaron J. Johnson, Georgette L. Suidan,

Jeremiah McDole, and Istvan Pirko


Immunopathogenesis of Multiple Sclerosis Smriti M. Agrawal and V. Wee Yong Molecular Mimicry in Multiple Sclerosis Jane E. Libbey, Lori L. McCoy, and

Robert S. Fujinami

Molecular “Negativity” May Underlie Multiple Sclerosis: Role of the Myelin Basic Protein Family in the Pathogenesis of MS Abdiwahab A. Musse and George Harauz Microchimerism and Stem Cell Transplantation in Multiple Sclerosis Behrouz Nikbin, Mandana Mohyeddin Bonab, and Fatemeh Talebian The Insulin-Like Growth Factor System in Mul­ tiple Sclerosis Daniel Chesik, Nadine Wilczak, and

Jacques De Keyser

Cell-Derived Microparticles and Exosomes in Neuroinflammatory Disorders Lawrence L. Horstman, Wenche Jy, Alireza Minagar, Carlos J. Bidot, Joaquin J. Jimenez, J. Steven Alexander, and Yeon S. Ahn Multiple Sclerosis in Children: Clinical, Diag­ nostic, and Therapeutic Aspects Kevin Rost�asy Migraine in Multiple Sclerosis Debra G. Elliott Multiple Sclerosis as a Painful Disease Meghan Kenner, Uma Menon, and Debra Elliott Multiple Sclerosis and Behavior James B. Pinkston, Anita Kablinger, and Nadejda Akkseeva Cerebrospinal Fluid Analysis in Multiple Sclerosis Francisco A. Luque and Stephen L. Jaffe Multiple Sclerosis in Isfahan, Iran Mohammad Saadatnia, Masoud Etemadifar, and Amir Hadi Maghzi Gender Issues in Multiple Sclerosis Robert N. Schwendimann and Nadejda Alekseeva Differential Diagnosis of Multiple Sclerosis Halim Fadil, Roger E. Kelley, and Eduardo


Prognostic Factors in Multiple Sclerosis Roberto Bergamaschi



Neuroimaging in Multiple Sclerosis Robert Zivadinov and Jennifer L. Cox

Volume 80

Detection of Cortical Lesions Is Dependent on Choice of Slice Thickness in Patients with Multi­ ple Sclerosis Ondrej Dolezal, Michael G. Dwyer, Dana Horakova,

Eva Havrdova, Alireza Minagar,

Srivats Balachandran, Niels Bergsland, Zdenek Seidl,

Manuela Vaneckova, David Fritz, Jan Krasensky,

and Robert Zjvadinov

Epilepsy in the Elderly: Scope of the Problem Ilo E. Leppik

The Role of Quantitative Neuroimaging Indices in the Differentiation of Ischemia from Demyelina­ tion: An Analytical Study with Case Presentation Romy Hoque, Christina Ledbetter, Eduardo GonzalezToledo, Vivek Misra, Uma Menon, Meghan Kenner, Alejandro A. Rabinstein, Roger E. Kelley, Robert Zjvadinov, and Alireza Minagar

Life and Death of Neurons in the Aging Cerebral Cortex John H. Morrison and Patrick R. Hof

HLA-DRB1*1501, -DQB1*0301, -DQB l*0302, -DQB1*0602, and -DQB1*0603 Alleles Are Associated with More Severe Disease Outcome on MRI in Patients with Multiple Sclerosis Robert Zivadinov, Laura Uxa, Alessio Bratina, Antonio Bosco, Bhooma Srinivasaraghavan, Alireza Minagar, Maja Ukmar, Su yen Benedetto, and Marino Zorzon Glatiramer Acetate: Mechanisms of Action in Multiple Sclerosis Tjalf Ziemssen and Wiebke Schrempf Evolving Therapies for Multiple Sclerosis Elena Korniychuk, John M. Dempster, Eileen O’Connor, J. Steven Alexander, Roger E. Kelley, Meghan Kenner, Uma Menon, Vivek Misra, Romy Hoque, Eduardo C. Gonzalez-Toledo, Robert N. Schwendimann, Stacy Smith, and Alireza Minagar Remyelination in Multiple Sclerosis Divya M. Chari Trigeminal Neuralgia: A Modern-Day Review Kelly Hunt and Ravish Patwardhan Optic Neuritis and the Neuro-Ophthalmology of Multiple Sclerosis Paramjit Kaur and Jeffrey L. Bennett Neuromyelitis Optica: Pathogenesis Dean M. Wingerchuk INDEX




Animal Models in Gerontology Research Nancy L. Nadon Animal Models of Geriatric Epilepsy Lauren J. Murphree, Lynn M. Rundhaugen, and Kevin M. Kelly

An In Vitro Model of Stroke-Induced Epilepsy: Elucidation of the Roles of Glutamate and Cal­ cium in the Induction and Maintenance of Stroke-Induced Epileptogenesis Robert J. DeLorenzo, David A. Sun, Robert E. Blair, and Sompong Sambati Mechanisms of Action of Antiepileptic Drugs H. Steve White, Misty D. Smith, and Karen S. Wilcox Epidemiology and Outcomes of Status Epilepti­ cus in the Elderly Alan R. Towne Diagnosing Epilepsy in the Elderly R. Eugene Ramsay, Flavia M. Macias, and A. James Rowan Pharmacoepidemiology in Community-Dwelling Elderly Taking Antiepileptic Drugs Dan R. Berlowitz and Mary Jo V. Pugh Use of Antiepileptic Medications in Nursing Homes Judith Garrard, Susan L. Harms, Lynn E. Eberly, and Ilo E. Leppik Differential Diagnosis of Multiple Sclerosis Halim Fadil, Roger E. Kelley, and Eduardo


Prognostic Factors in Multiple Sclerosis Roberto Bergamaschi Neuroimaging in Multiple Sclerosis Robert Zivadinov and Jennifer L. Cox Detection of Cortical Lesions Is Dependent on Choice of Slice Thickness in Patients with Multi­ ple Sclerosis Ondrej Dolezal, Michael G. Dwyer, Dana Horakova, Eva Havrdova, Alireza Minagar, Srivats


Balachandran, Niels Bergsland, Zdenek Seidl, Manuela Vaneckova, David Fritz, Jan Krasensky, and Robert Zivadinov The Role of Quantitative Neuroimaging Indices in the Differentiation of Ischemia from Demyelination: An Analytical Study with Case Presentation Romy Hoque, Christina Ledbetter, Eduardo GonzalezToledo, Vivek Misra, Uma Menon, Meghan Kenner, Alejandro A. Rabinstein, Roger E. Kelley, Robert Zivadinov, and Alireza Minagar HLA-DRB l*1501,-DQB l*0301,-DQB l*0302, -DQB 1*0602, and -DQB 1*0603 Alleles Are Associated with More Severe Disease Outcome on MRI in Patients with Multiple Sclerosis Robert Zivadinov, Laura Uxa, Alessio Bratina, Antonio Bosco, Bhooma Srinivasaraghavan, Alireza Minagar, Maja Ukmar, Su yen Benedetto, and Marino Zorzon


Animal Models of Geriatric Epilepsy Lauren J. Murphree, Lynn M. Rundhaugen, and Kevin M. Kelly Life and Death of Neurons in the Aging Cerebral Cortex John H. Morrison and Patrick R. Hof An In Vitro Model of Stroke-Induced Epilepsy: Elucidation of the Roles of Glutamate and Cal­ cium in the Induction and Maintenance of Stroke-Induced Epileptogenesis Robert J. DeLorenzo, David A. Sun, Robert E. Blair, and Sompong Sambati Mechanisms of Action of Antiepileptic Drugs H. Steve White, Misty D. Smith, and Karen S. Wilcox Epidemiology and Outcomes of Status Epilepti­ cus in the Elderly Alan R. Towne

Glatiramer Acetate: Mechanisms of Action in Multiple Sclerosis Tjalf Ziemssen and Wiebke Schrempf

Diagnosing Epilepsy in the Elderly R. Eugene Ramsay, Flavia M. Macias, and A. James Rowan

Evolving Therapies for Multiple Sclerosis Elena Komiychuk, John M. Dempster, Eileen O’Connor, J. Steven Alexander, Roger E. Kelley, Meghan Kenner, Uma Menon, Vivek Misra, Romy Hoque, Eduardo C. Gonzalez-Toledo, Robert N. Schwendimann, Stacy Smith, and Alireza Minagar

Pharmacoepidemiology in Community-Dwelling Elderly Taking Antiepileptic Drugs Dan R. Berlowitz and Mary Jo V. Pugh

Remyelination in Multiple Sclerosis Divya M. Chari

Age-Related Changes in Pharmaco*kinetics: Pre­ dictability and Assessment Methods Emilio Perucca

Trigeminal Neuralgia: A Modern-Day Review Kelly Hunt and Ravish Patwardhan

Use of Antiepileptic Medications in Nursing Homes Judith Garrard, Susan L. Harms, Lynn E. Eberly, and Ilo E. Leppik

Optic Neuritis and the Neuro-Ophthalmology of Multiple Sclerosis Paramjit Kaur and Jeffrey L. Bennett

Factors Affecting Antiepileptic Drug Pharmaco­ kinetics in Community-Dwelling Elderly James C. Cloyd, Susan Marino,

and Angela K. Bimbaum

Neuromyelitis Optica: Pathogenesis Dean M. Wingerchuk

Pharmaco*kinetics of Antiepileptic Drugs in Elderly Nursing Home Residents Angela K. Bimbaum





Volume 81 Epilepsy in the Elderly: Scope of the Problem Ilo E. Leppik Animal Models in Gerontology Research Nancy L. Nadon

The Impact of Epilepsy on Older Veterans Maty Jo V. Pugh, Dan R. Berlowitz, and Lewis Kazis Risk and Predictability of Drug Interactions in the Elderly Rene H. Levy and Carol Collins Outcomes in Elderly Patients With Newly Diag­ nosed and Treated Epilepsy Martin J. Brodie and Linda J. Stephen



Recruitment and Retention in Clinical Trials of the Elderly Flavia M. Macias, R. Eugene Ramsay, and A. James Rowan Treatment of Convulsive Status Epilepticus David M. Treiman Treatment of Nonconvulsive Status Epilepticus Matthew C. Walker Antiepileptic Drug Formulation and Treatment in the Elderly: Biopharmaceutical Considerations Barry E. Gidal INDEX

Volume 82 Inflammatory Mediators Leading to Protein Misfolding and Uncompetitive/Fast Off-Rate Drug Therapy for Neurodegenerative Disorders Stuart A. Lipton, Zezong Gu, and Tomohiro


Innate Immunity and Protective Neuroinflam­ mation: New Emphasis on the Role of Neuroim­ mune Regulatory Proteins M. Griffiths, J. W. Nead, and P. Gasque Glutamate Release from Astrocytes in Physiolo­ gical Conditions and in Neurodegenerative Dis­ orders Characterized by Neuroinflammation Sabino Vesce, Daniela Rossi, Liliana Brambilla, and Andrea Volterra The High-Mobility Group Box 1 Cytokine Induces Transporter-Mediated Release of Gluta­ mate from Glial Subcellular Particles (Gliosomes) Prepared from In Situ-Matured Astrocytes Giambattista Bonanno, Luca Raiteri, Marco Milanese, Simona Zappettini, Edon Melloni, Marco Pedrazzi, Mario Passalacqua, Carlo Tacchetti, Cesare Usai, and Bianca Sparatore The Role of Astrocytes and Complement System in Neural Plasticity Milos Pekny, Ulrika Wilhelmsson, Yalda Rahpeymai Bogestal, and Marcela Pekna New Insights into the Roles of Metalloprotei-nases in Neurodegeneration and Neuroprotection A. J. Turner and N. N. Nalivaeva

Relevance of High-Mobility Group Protein Box 1 to Neurodegeneration Silvia Fossati and Alberto Chiarugi Early Upregulation of Matrix Metalloproteinases Following Reperfusion Triggers Neuroinflam­ matory Mediators in Brain Ischemia in Rat Diana Amantea, Rossella Russo, Micaela Gliozzi, Vincenza Fratto, Laura Berliocchi, G. Bagetta, G. Bemardi, and M. Tiziana Corasaniti The (Endo)Cannabinoid System in Multiple Sclerosis and Amyotrophic Lateral Sclerosis Diego Centonze, Silvia Rossi, Alessandro

Finazzi-Agro, Giorgio Bemardi, and Mauro


Chemokines and Chemokine Receptors: Multi­ purpose Players in Neuroinflammation Richard M. Ransohoff, LiPing Liu, and

Astrid E. Cardona

Systemic and Acquired Immune Responses in Alzheimer’s Disease Markus Britschgi and Tony Wyss-Coray Neuroinflammation in Alzheimer’s Disease and Parkinson’s Disease: Are Microglia Pathogenic in Either Disorder? Joseph Rogers, Diego Mastroeni, Brian Leonard, Jeffrey Joyce, and Andrew Grover Gytokines and Neuronal Ion Channels in Health and Disease Barbara Viviani, Fabrizio Gardoni, and Marina Marinovch Cyclooxygenase-2, Prostaglandin E2, and Micro­ glial Activation in Prion Diseases Luisa Minghetti and Maurizio Pocchiari Glia Proinflammatory Cytokine Upregulation as a Therapeutic Target for Neurodegenerative Diseases: Function-Based and Target-Based Discovery Approaches Linda J. Van Eldik, Wendy L. Thompson, Hantamalala Ralay Ranaivo, Heather A. Behanna, and D. Martin Watterson Oxidative Stress and the Pathogenesis of Neuro­ degenerative Disorders Ashley Reynolds, Chad Laurie, R. Lee Mosley, and Howard E. Gendelman



Differential Modulation of Type 1 and Type 2 Gannabinoid Receptors Along the Neuro­ immune Axis Sergio Oddi, Paola Spagnuolo, Monica Bari,

Antonella D’Agostino, and Mauro Maccarrone

Effects of the HIV-1 Viral Protein Tat on Central Neurotransmission: Role of Group I Meta-botropic Glutamate Receptors Elisa Neri, Veronica Musante, and Anna Pittaluga Evidence to Implicate Early Modulation of Inter­ leukin-1/� Expression in the Neuroprotectdon Afforded by 17/�-Estradiol in Male Rats Under­ gone Transient Middle Cerebral Artery Occlusion Olga Chiappetta, Micaela Gliozzi, Elisa Siviglia, Diana Amantea, Luigi A. Morrone, Laura Berliocchi, G. Bagetta, and M. Tiziana Corasaniti ARoleforBrainCyclooxygenase-2andProstaglandin­ E2 in Migraine: Effects of Nitroglycerin Cristina Tassorelli, Rosaria Greco, Marie Ther�e se Armentero, Fabio Blandini, Giorgio Sandrini, and Giuseppe Nappi The Blockade of K+-ATP Channels has Neuro­ protective Effects in an In Vitro Model of Brain Ischemia Robert Nistic�o, Silvia Piccirilli, L. Sebastianelli, Giuseppe Nistic�o, G. Bernardi, and N. B. Mercuri Retinal Damage Caused by High Intraocular Pressure-Induced Transient Ischemia is Pre­ vented by Coenzyme Q10 in Rat Carlo Nucci, Rosanna Tartaglione, Angelica Cerulli, R. Mancino, A. Spano, Federica Cavaliere, Laura Rombol, G. Bagetta, M. Tiziana Corasaniti, and Luigi A. Morrone Evidence Implicating Matrix Metalloproteinases in the Mechanism Underlying Accumulation of IL-1 � and Neuronal Apoptosis in the Neocortex of HIV/gpl20-Exposed Rats Rossella Russo, Elisa Siviglia, Micaela Gliozzi, Diana Amantea, Annamaria Paoletti, Laura Berliocchi, G. Bagetta, and M. Tiziana Corasaniti Neuroprotective Effect of Nitroglycerin in a Rodent Model of Ischemic Stroke: Evaluation of Bcl-2 Expression Rosaria Greco, Diana Amantea, Fabio Blandini, Giuseppe Nappi, Giacinto Bagetta, M. Tiziana Corasaniti, and Cristina Tassorelli INDEX

Volume 83 Gender Differences in Pharmacological Response Gail D. Anderson Epidemiology and Classification of Epilepsy: Gender Comparisons John C. McHugh and Norman Delanty Hormonal Influences Neurobiology Cheryl A. Frye




Catamenial Epilepsy Patricia E. Penovich and Sandra Helmers Epilepsy in Women: Special Considerations for Adolescents Mary L. Zupanc and Sheryl Haut Contraception in Women with Epilepsy: Phar­ maco*kinetic Interactions, Contraceptive Options, and Management Caryn Dutton and Nancy Foldvary-Schaefer Reproductive Dysfunction in Women with Epi­ lepsy: Menstrual Cycle Abnormalities, Fertility, and Polycystic Ovary Syndrome Ju¨ rgen Bauer and Deirdre Cooper-Mahkorn Sexual Dysfunction in Women with Epilepsy: Role of Antiepileptic Drugs and Psychotropic Medications Mary A. Gutierrez, Romila Mushtaq, and Glen Stimmel Pregnancy in Epilepsy: Issues of Concern John DeToledo Teratogenicity and Antiepileptic Drugs: Poten­ tial Mechanisms Mark S. Yerby Antiepileptic Drug Teratogenesis: What are the Risks for Congenital Malformations and Adverse Cognitive Outcomes? Cynthia L. Harden Teratogenicity of Antiepileptic Drugs: Role of Pharmacogenomics Raman Sankar and Jason T. Lerner Antiepileptic Drug Therapy in Pregnancy I: Gesta­ tion-Induced Effects on AED Pharmaco*kinetics Page B. Pennell and Collin A. Hovinga Antiepileptic Drug Therapy in Pregnancy II: Fetal and Neonatal Exposure Collin A. Hovinga and Page B. Pennell



Seizures in Pregnancy: Diagnosis Management Robert L. Beach and Peter W. Kaplan


Management of Epilepsy and Pregnancy: An Obstetrical Perspective Julian N. Robinson and Jane Cleary-Goldman Pregnancy Registries: Strengths, Weaknesses, and Bias Interpretation of Pregnancy Registry Data Marianne Cunnington and John Messenheimer Bone Health in Women With Epilepsy: Clinical Features and Potential Mechanisms Alison M. Pack and Thaddeus S. Walczak Metabolic Effects of AEDs: Impact on Body Weight, Lipids and Glucose Metabolism Raj D. Sheth and Georgia Montouris Psychiatric Gomorbidities in Epilepsy W. Curt Lafrance, Jr., Andres M. Kanner, and Bruce Hermann Issues for Mature Women with Epilepsy Cynthia L. Harden Pharmacodynamic and Pharmaco*kinetic Interac­ tions of Psychotropic Drugs with Antiepileptic Drugs Andres M. Kanner and Barry E. Gidal Health Disparities in Epilepsy: How PatientOriented Outcomes in Women Differ from Men Frank Gilliam INDEX

Volume 84 Normal Brain Aging: Clinical, Immunological, Neuropsychological, and Neuroimaging Features Maria T. Caserta, Yvonne Bannon, Francisco Fernandez, Brian Giunta, Mike R. Schoenberg, and Jun Tan

Contributions of Neuropsychology and Neuroi­ maging to Understanding Clinical Subtypes of Mild Cognitive Impairment Amy J. Jak, Katherine J. Bangen, Christina E. Wierenga, Lisa Delano-Wood,

Jody Corey-Bloom, and Mark W. Bondi

Proton Magnetic Resonance Spectroscopy in Dementias and Mild Cognitive Impairment H. Randall Griffith, Christopher C. Stewart, and Jan A. den Hollander Application of PET Imaging to Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment James M. Noble and Nikolaos Scarmeas The Molecular and Cellular Pathogenesis of Dementia of the Alzheimer’s Type: An Overview Francisco A. Luque and Stephen L. Jaffe Alzheimer’s Disease Genetics: Current Status and Future Perspectives Lars Bertram Frontotemporal Lobar Degeneration: Insights from Neuropsychology and Neuroimaging Andrea C. Bozoki and Muhammad U. Farooq Lewy Body Dementia Jennifer C. Hanson and Carol F. Lippa Dementia in Parkinson’s Disease Bradley J. Robottom and William J. Weiner Early Onset Dementia Halim Fadil, Aimee Borazanci, Elhachmia Ait Ben Haddou, Mohamed Yahyaoui, Elena Korniychuk, Stephen L. Jaffe, and Alireza Minagar Normal Pressure Hydrocephalus Glen R. Finney Reversible Dementias Anahid Kabasakalian and Glen R. Finney INDEX

Subcortical Ischemic Gerebrovascular Dementia Uma Menon and Roger E. Kelley Cerebrovascular and Cardiovascular Pathology in Alzheimer’s Disease Jack C. de la Torre

Volume 85

Neuroimaging of Cognitive Impairments in Vas­ cular Disease Carol Di Perri, Turi 0. Dalaker, Mona K. Beyer, and Robert Zivadinov

Solving Hajime Mushiake, Kazuhiro Sakamoto, Naohiro Saito, Toshiro Inui, Kazuyuki Aihara, and Jun Tanji

Involvement of the Prefrontal Cortex in Problem


GluK l Receptor Antagonists and Hippocampal Mossy Fiber Function Robert Nistico, Sheila Dargan, Stephen M. Fitzjohn, David Lodge, David E. Jane, Graham L. Collingridge, and Zuner A. Bortolotto Monoamine Transporter as a Target Molecule for Psychostimulants Ichiro Sora, Bing Jin Li, Setsu Fumushima, Asami f*ckui, Yosefu Arime, Yoshiyuki Kasahara, Hiroaki Tomita, and Kazutaka Ikeda Targeted Lipidomics as a Tool to Investigate Endocannabinoid Function Giuseppe Astarita, Jennifer Geaga, Faizy Ahmed, and Daniele Piomelli The Endocannabinoid System as a Target for Novel Anxiolytic and Antidepressant Drugs Silvana Gaetani, Pasqua Dipasquale, Adele Romano, Laura Righetti, Tommaso Cassano, Daniele Piomelli, and Vincenzo Cuomo GABAA Receptor Function and Gene Expres­ sion During Pregnancy and Postpartum Giovanni Biggio, Maria Cristina Mostallino, Paolo Follesa, Alessandra Concas, and Enrico Sanna Early Postnatal Stress and Neural Circuit Under­ lying Emotional Regulation Machiko Matsumoto, Mitsuhiro Yoshioka, and

Hiroko Togashi

Roles of the Histaminergic Neurotransmission on Methamphetamine-Induced Locomotor Sen­ sitization and Reward: A Study of Receptors Gene Knockout Mice Naoko Takino, Eiko Sakurai, Atsuo Kuramasu,

Nobuyuki Okamura, and Kazuhiko Yanai

Developmental Exposure to Cannabinoids Causes Subtle and Enduring Neurofunctional Alterations Patrizia Campolongo, Viviana Trezza, Maura

Palmery, Luigia Trabace, and Vincenzo Cuomo

Neuronal Mechanisms for Pain-Induced Aver­ sion: Behavioral Studies Using a Conditioned Place Aversion Test Masabumi Minami Bv8/Prokineticins and their Receptors: A New Pronociceptive System Lucia Negri, Roberta Lattanzi, Elisa Giannini, Michela Canestrelli, Annalisa Nicotra, and Pietro Melchiorri


P2Y6-Evoked Microglial Phagocytosis Kazuhide Inoue, Schuichi Koizumi, Ayako Kataoka, Hidetoshi Tozaki-Saitoh, and Makoto Tsuda PPAR and Pain Takehiko Maeda and Shiroh Kishioka Involvement of Inflammatory Mediators in Neu­ ropathic Pain Caused by Vincristine Norikazu Kiguchi, Takehiko Maeda, Yuka Kobayashi, Fumihiro Saika, and Shiroh Kishioka Nociceptive Behavior Induced by the Endogen­ ous Opioid Peptides Dynorphins in Uninjured Mice: Evidence with Intrathecal N-ethylmaleimide Inhibiting Dynorphin Degradation Kbichi Tan-No, Hiroaki Takahashi, Osamu Nakagawasai, f*ckie Niijima, Shinobu Sakurada, Georgy Bakalkin, Lars Terenius, and Takeshi Tadano Mechanism of Allodynia Evoked by Intrathecal Morphine-3-Glucuronide in Mice Takaaki Komatsu, Shinobu Sakurada,

Sou Katsuyama, Kengo Sanai, and Tsukasa Sakurada

(–)-Linalool Attenuates Allodynia in Neuropathic Pain Induced by Spinal Nerve Ligation in C57/B16 Mice Laura Berliocchi, Rossella Russo, Alessandra Levato, Vincenza Fratto, Giacinto Bagetta, Shinobu Sakurada, Tsukasa Sakurada, Nicola Biagio Mercuri, and Maria Tiziana Corasaniti Intraplantar Injection of Bergamot Essential Oil into the Mouse Hindpaw: Effects on CapsaicinInduced Nociceptive Behaviors Tsukasa Sakurada, Hikari Kuwahata, Soh Katsuyama, Takaaki Komatsu, Luigi A. Morrone, M. Tiziana Corasaniti, Giacinto Bagetta, and Shi­ nobu Sakurada New Therapy for Neuropathic Pain Hirokazu Mizoguchi, Chizuko Watanabe, Akihiko Yonezawa, and Shinobu Sakurada Regulated Exocytosis from Astrocytes: Physiolo­ gical and Pathological Related Aspects Corrado Calii, Julie Marchaland, Paola Spagnuolo, Julien Gremion, and Paola Bezzi Glutamate Release from Astrocytic Gliosomes Under Physiological and Pathological Conditions Marco Milanese, Tiziana Bonifacino, Sitmona Zappettini, Cesare Usai, Carlo Tacchetti, Mario Nobile, and Giambattista Bonanno



Neurotrophic and Neuroprotective Actions of an Enhancer of Ganglioside Biosynthesis Jin-ichi Inokuchi

Bidirectional Interfaces with the Peripheral Nervous System Silvestro Micera and Xavier Navarro

Involvement of Endocannabinoid Signaling in the Neuroprotective Effects of Subtype 1 Meta­ botropic Glutamate Receptor Antagonists in Models of Cerebral Ischemia Elisa Landucci, Francesca Boscia, Elisabetta Gerace, Tania Scartabelli, Andrea Cozzi, Flavio Moroni, Guido Mannaioni, and Domenico E. Pellegrini-Giampietro

Interfacing Insect Brain for Space Applications Giovanni Di Pino, Tobias Seidl, Antonella Benvenuto, Fabrizio Sergi, Domenico Campolo, Dino Accoto, Paolo Maria Rossini, and Eugenio Guglielmelli

NF-kappaB Dimers in the Regulation of Neuro­ nal Survival Ilenia Sarnico, Annamaria Lanzillotta, Marina Benarese, Manuela Alghisi, Cristina Baiguera, Leontino Battistin, PierFranco Spano, and Marina Pizzi Oxidative Stress in Stroke Pathophysiology: Vali­ dation of Hydrogen Peroxide Metabolism as a Pharmacological Target to Afford Neuroprotection Diana Amantea, Maria Cristina Marrone, Robert Nistic�o, Mauro Federici, Giacinto Bagetta, Giorgio Bernardi, and Nicola Biagio Mercuri Role of Akt and ERK Signaling in the Neuro­ genesis following Brain Ischemia Norifumi Shioda, Feng Han, and Kohji f*ckunaga Prevention of Glutamate Accumulation and Upregulation of Phospho-Akt may Account for Neuroprotection Afforded by Bergamot Essential Oil against Brain Injury Induced by Focal Cere­ bral Ischemia in Rat Diana Amantea, Vincenza Fratto, Simona Maida, Domenicantonio Rotiroti, Salvatore Ragusa, Giuseppe Nappi, Giacinto Bagetta, and Maria Tiziana Corasaniti Identification of Novel Pharmacological Targets to Minimize Excitotoxic Retinal Damage Rossella Russo, Domenicantonio Rotiroti, Cristina Tassorelli, Carlo Nucci, Giacinto Bagetta, Massimo Gilberto Bucci, Maria Tiziana Corasaniti, and Luigi Antonio Morrone INDEX

Volume 86 Section One: Hybrid Bionic Systems EMG-Based and Gaze-Tracking-Based Man–Machine Interfaces Federico Carpi and Danilo De Rossi

Section Two: Meet the Brain Meet the Brain: Neurophysiology John Rothwell Fundamentals of Electroencefalography, Magne­ toencefalography, and Functional Magnetic Resonance Imaging Claudio Babiloni, Vittorio Pizzella, Cosimo Del

Gratta, Antonio Ferretti, and Gian Luca Romani

Implications of Brain Plasticity to Brain–Machine Interfaces Operation: A Potential Paradox? Paolo Maria Rossini Section Three: Brain Machine Interfaces, A New Brain-to-Environment Communication Channel An Overview of BMIs Francisco Sepulveda Neurofeedback and Brain–Computer Interface: Clinical Applications Niels Birbaumer, Ander Ramos Murguialday, Cornelia Weber, and Pedro Montoya Flexibility and Practicality: Graz Brain– Computer Interface Approach Reinhold Scherer, Gernot R. Mulkr-Putz, and

Gert Pfurtscheller

On the Use of Brain–Computer Interfaces Out­ side Scientific Laboratories: Toward an Applica­ tion in Domotic Environments F. Babiloni, F. Cincotti, M. Marciani, S. Salinari, L. Astolfi, F. Aloise, F. De Vico Fallani, and D. Mattia Brain–Computer Interface Research at the Wadsworth Center: Developments in Noninva­ sive Communication and Control Dean J. Krusienski and Jonathan R. Wolpaw Watching Brain TV and Playing Brain Ball: Exploring Novel BCL Strategies Using Real–Time Analysis of Human Intercranial Data Karim Jerbi, Samson Freyermuth, Lorella Minotti, Philippe Kahane, Alain Berthoz, and Jean-Philippe Lachaux


Section Four: Brain-Machine Interfaces and Space Adaptive Changes of Rhythmic EEG Oscilla­ tions in Space: Implications for Brain–Machine Interface Applications G. Cheron, A. M. Cebolla, M. Petieau, A. Bengoetxea, E. Paknero-Soter, A. Leroy, and B. Dan Validation of Brain–Machine Interfaces During Parabolic Flight Jos�e del R. Mill�an, Pierre W. Ferrez, and Tobias Seidl Matching Brain–Machine Interface Perfor­ mance to Space Applications Luca Citi, Oliver Tonet, and Martina Marinelli Brain–Machine Interfaces for Space Applications —Research, Technological Development, and Opportunities Leopold Summerer, Dario Izzo, and Luca Rossini INDEX

Volume 87 Peripheral Nerve Repair and Regeneration Research: A Historical Note Bruno Battiston, Igor Papalia, Pierluigi Tos, and Stefano Geuna Development of the Peripheral Nerve Suleyman Kaplan, Ersan Odaci, Bunyami Unal, Bunyamin Sahin, and Michele Fornaro Histology of the Peripheral Nerve and Changes Occurring During Nerve Regeneration Stefano Geuna, Stefania Raimondo, Giulia Ronchi, Federka Di Scipio, Pierluigi Tos, Krzysztof Czaja, and Michete Fornaro Methods and Protocols in Peripheral Nerve Regeneration Experimental Research: Part I— Experimental Models Pierluigi Tos, Giulia Ronchi, Igor Papalia, Vera Sallen, Josette Legagneux, Stefano Geuna, and Maria G. Giacobini-Robecchi Methods and Protocols in Peripheral Nerve Regeneration Experimental Research: Part II— Morphological Techniques Stefania Raimondo, Michele Fornaro, Federica Di Scipio, Giulia Ronchi, Maria G. Giacobini-Robecchi, and Stefano Geuna


Methods and Protocols in Peripheral Nerve Regeneration Experimental Research: Part III— Electrophysiological Evaluation Xavier Navarro and Esther Udina Methods and Protocols in Peripheral Nerve Regeneration Experimental Research: Part IV— Kinematic Gait Analysis to Quantify Per­ ipheral Nerve Regeneration in the Rat Luis M. Costa, Maria J. Simes, Ana C. Mauricio and Artur S. P. Varejo Current Techniques and Concepts in Peripheral Nerve Repair Maria Siemionow and Grzegorz Brzezicki Artificial Scaffolds for Peripheral Reconstruction Valeria Chiono, Chiara Tonda-Turo, and

Gianluca Ciardelli


Conduit Luminal Additives for Peripheral Nerve Repair Hede Yan, Feng Zhang, Michael B. Chen, and

William C. Lineaweaver

Tissue Engineering of Peripheral Nerves Bruno Battiston, Stefania Raimondo, Pierluigi Tos, Valentina Gaidano, Chiara Audisio, Anna Scevola, Isabelle Perroteau, and Stefano Geuna Mechanisms Underlying The End-to-Side Nerve Regeneration Eleana Bontioti and Lars B. Dahlin Experimental Results in End-To-Side Neurorrhaphy Alexandras E. Beris and Marios G. Lykissas End-to-Side Nerve Regeneration: From the Laboratory Bench to Clinical Applications Pierluigi Tos, Stefano Artiaco, Igor Papalia, Ignazio Marcoccio, Stefano Geuna, and Bruno Battiston Novel Pharmacological Approaches to Schwann Cells as Neuroprotective Agents for Peripheral Nerve Regeneration Valeria Magnaghi, Patrizia Procacci, and

Ada Maria Tata

Melatonin and Nerve Regeneration Ersan Odaci and Suleyman Kaplan Transthyretin: An Enhancer of Nerve Regeneration Carolina E. Fleming, Fernando Milhazes Mar, Filipa Franquinho, and Mnica M. Sousa



Enhancement of Nerve Regeneration and Recovery by Immunosuppressive Agents Damien P. Kuffler

Dosing Time-Dependent Psychostimulants H. Manev and T. Uz

The Role of Collagen in Peripheral Nerve Repair Guide Koopmans, Birgit Hasse, and Nektarios Sinis

Dopamine-Induced Behavioral Changes and Oxidative Stress in Methamphetamine-Induced Neurotoxicity Taizo kita, Ikuko Miyazaki, Masato Asanuma, Mika Takeshima, and George C. Wagner

Gene Therapy Perspectives for Nerve Repair Serena Zacchigna and Mauro Giacca Use of Stem Cells for Improving Nerve Regeneration Giorgio Terenghi, Mikael Wiberg, and Paul J. Kingham Transplantation of Olfactory Ensheathing Cells for Peripheral Nerve Regeneration Christine Radtke, Jeffery D. Kocsis, and Peter M. Vogt Manual Stimulation of Target Muscles has Dif­ ferent Impact on Functional Recovery after Injury of Pure Motor or Mixed Nerves Nektarios Sinis, Thodora Manoli, Frank Werdin, Armin Kraus, Hans E. Schaller, Orlando GuntinasLichius, Maria Grosheva, Andrey Irintchev, Emanouil Skouras, Sarah Dunlop, and Doychin N. Angelov Electrical Stimulation for Improving Nerve Regeneration: Where do we Stand? Tessa Gordon, Olewale A. R. Sulaiman, and Adil Ladak Phototherapy in Peripheral Nerve Injury: Effects on Muscle Preservation and Nerve Regeneration Shimon Rochkind, Stefano Geuna, and Asher Shainberg Age-Related Differences in the Reinnervation after Peripheral Nerve Injury Uro Kovai, Janez Sketelj, and Fajko F. Bajrovi Neural Plasticity After Nerve Injury and Regeneration Xavier Navarro Future Perspective in Peripheral Nerve Reconstruction Lars Dahlin, Fredrik Johansson, Charlotta Lindwall, and Martin Kanje INDEX

Volume 88 Effects Of Psychostimulants On Neurotrophins: Implications For Psychostimulant-Induced Neurotoxicity Francesco Angelucci, Valerio Ricci, Gianfranco Spalletta, Carlo Caltagirone, Aleksander A. Math�e , and Pietro Bria



Acute Methamphetamine Intoxication: Brain Hyperthermia, Blood–Brain Barrier, Brain Edema, and morphological cell abnormalities Eugene A. Kiyatkin and Hari S. Sharma Molecular Bases of Methamphetamine-Induced Neurodegeneration Jean Lud Cadet and Irina N. Krasnova Involvement of Nicotinic Receptors in Metham­ phetamine- and MDMA-Induced Neurotoxicity: Pharmacological Implications E. Escubedo, J. Camarasa, C. Chipana, S. Garcia-Rates, and D.Pubill Ethanol Alters the Physiology of Neuron–Glia Communication Antonio Gonzalez and Gines M. Salido Therapeutic Targeting of “DARPP-32”: A Key Signaling Molecule in the Dopiminergic Pathway for the Treatment of Opiate Addiction Supriya D. Mahajan, Ravikumar Aalinkeel, Jessica L. Reynolds, Bindukumar B. Nair, Donald E. Sykes, Zihua Hu, Adela Bonoiu, Hong Ding, Paras N. Prasad, and Stanley A. Schwartz Pharmacological and Neurotoxicological Actions Mediated By Bupropion and Diethylpropion Hugo R. Arias, Abel Santamaria, and Syed F. Ali Neural and Cardiac Toxicities Associated With 3,4-Methylenedioxymethamphetamine (MDMA) Michael H. Baumann and Richard B. Rothman Cocaine-Induced Breakdown of the Blood–Brain Barrier and Neurotoxicity Hari S. Sharma, Dafin Muresanu, Aruna Sharma, and Ranjana Patnaik Cannabinoid Receptors in Brain: Pharmacoge­ netics, Neuropharmacology, Neurotoxicology, and Potential Therapeutic Applications Emmanuel S. Onaivi



Intermittent Dopaminergic Stimulation causes Behavioral Sensitization in the Addicted Brain and Parkinsonism Francesco Fornai, Francesca Biagioni, Federica Fulceri, Luigi Muni, Stefano Ruggieri, Antonio Paparelli

Method and Validity of Transcranial Sonogra­ phy in Movement Disorders ˇ David Skoloud� ı k and Uwe Walter

The Role of the Somatotrophic Axis in Neuro­ protection and Neuroregeneration of the Addic­ tive Brain Fred Nyberg

Part II: Transcranial Sonography in Parkinsons Disease


Volume 89 Molecular Profiling of Striatonigral and Striato­ pallidal Medium Spiny Neurons: Past, Present, and Future Mary Kay Lobo BAC to Degeneration: Bacterial Artificial Chro­ mosome (Bac)-Mediated Transgenesis for Model­ ing Basal Ganglia Neurodegenerative Disorders Xiao-Hong Lu Behavioral Outcome Measures for the Assess­ ment of Sensorimotor Function in Animal Mod­ els of Movement Disorders Sheila M. Fleming The Role of DNA Methylation in the Central Nervous System and Neuropsychiatric Disorders Jian Feng and Guoping Fan

Transcranial Sonography—Anatomy Heiko Huber

Transcranial Sonography in Relation to SPECT and MIBG Yoshinori Kajimoto, Hideto Miwa and Tomoyoshi Kondo Diagnosis of Parkinson’s Disease—Transcranial Sonography in Relation to MRI Ludwig Niehaus and Kai Boelmans Early Diagnosis of Parkinson’s Disease Alexandra Gaenslen and Daniela Berg Transcranial Sonography in the Premotor Diag­ nosis of Parkinson’s Disease Stefanie Behnke, Ute Schro¨der and Daniela Berg Pathophysiology of Transcranial Sonography Signal Changes in the Human Substantia Nigra K. L. Double, G. Todd and S. R. Duma Transcranial Sonography for the Discrimination of Idiopathic Parkinson’s Disease from the Aty­ pical Parkinsonian Syndromes A. E. P. Bouwmans, A. M. M. Vlaar, K. Srulijes, W. H. Mess AND W. E. J. Weber

Heritability of Structural Brain Traits: An Endo­ phenotype Approach to Deconstruct Schizophrenia Nil Kaymaz and J. Van Os

Transcranial Sonography in the Discrimination of Parkinson’s Disease Versus Vascular Parkinsonism Pablo Venegas-Francke

The Role of Striatal NMDA Receptors in Drug Addiction Yao-Ying Ma, Carlos Cepeda, and Cai-Lian Cui

TCS in Monogenic Forms of Parkinson’s Disease Kathrin Brockmann and Johann Hagenah

Deciphering Rett Syndrome With Mouse Genet­ ics, Epigenomics, and Human Neurons Jifang Tao, Hao Wu, and Yi Eve Sun INDEX

Part III—Transcranial Sonography in other Movement Disorders and Depression Transcranial Sonography in Brain Disorders with Trace Metal Accumulation Uwe Walter

Volume 90

Transcranial Sonography in Dystonia Alexandra Gaenslen

Part I: Introduction

Transcranial Sonography in Essential Tremor Heike Stockner and Isabel Wurster

Introductory Remarks on the History and Cur­ rent Applications of TCS Matthew B. Stern

VII—Transcranial Sonography in Restless Legs Syndrome Jana Godau and Martin Sojer



Transcranial Sonography in Ataxia Christos Krogias, Thomas Postert and Jens Eyding Transcranial Sonography in Huntington’s Disease Christos Krogias, Jens Eyding and Thomas Postert Transcranial Sonography in Depression Milija D. Mijajlovic Part IV: Future Applications and Conclusion Transcranial Sonography-Assisted Stereotaxy and Follow-Up of Deep Brain Implants in Patients with Movement Disorders Uwe Walter

Intrinsic Ion Channels and Neurotransmitter Inputs Hitoshi Morikawa and Richard A. Morrisett Alcohol and the Prefrontal Cortex Kenneth Abernathy, L. Judson Chandler

and John J. Woodward

BK Channel and Alcohol, A Complicated Affair Gilles Erwan Martin

Conclusions Daniela Berg

A Review of Synaptic Plasticity at Purkinje Neurons with a Focus on Ethanol-Induced Cerebellar Dysfunction C. Fernando Valenzuela, Britta Lindquist

and Paula A. Zamudio-Bulco*ck



Volume 91

Volume 92

The Role of microRNAs in Drug Addiction: A Big Lesson from Tiny Molecules Andrzej Zbigniew Pietrzykowski

The Development of the Science of Dreaming Claude Gottesmann

The Genetics of Behavioral Alcohol Responses in Drosophila Aylin R. Rodan and Adrian Rothenfluh

Dreaming as Inspiration: Evidence from Religion, Philosophy, Literature, and Film Kelly Bulkeley

Neural Plasticity, Human Genetics, and Risk for Alcohol Dependence Shirley Y. Hill

Developmental Perspective: Dreaming Across the Lifespan and What This Tells Us Melissa M. Burnham and Christian Conte

Using Expression Genetics to Study the Neurobiology of Ethanol and Alcoholism Sean P. Farris, Aaron R. Wolen and Michael F. Miles

REM and NREM Sleep Mentation Patrick Mcnamara, Patricia Johnson, Deirdre McLaren, Erica Harris,Catherine Beauharnais and Sanford Auerbach

Genetic Variation and Brain Gene Expression in Rodent Models of Alcoholism: Implications for Medication Development Karl Bjo¨rk, Anita C. Hansson and Wolfgang H. Sommer

Neuroimaging of Dreaming: State of the Art and Limitations Caroline Kuss�e, Vincenzo Muto, Laura Mascetti, Luca Matarazzo, Ariane Foret, Anahita Shaffii-Le Bourdiec and Pierre Maquet

Identifying Quantitative Trait Loci (QTLs) and Genes (QTGs) for Alcohol-Related Phenotypes in Mice Lauren C. Milner and Kari J. Buck

Memory Consolidation, The Diurnal Rhythm of Cortisol, and The Nature of Dreams: A New Hypothesis Jessica D. Payne

Glutamate Plasticity in the Drunken Amygdala: The Making of an Anxious Synapse Brian A. Mccool, Daniel T. Christian, Marvin R. Diaz and Anna K. La¨ck

Characteristics and Contents of Dreams Michael Schredl

Ethanol Action on Dopaminergic Neurons in the Ventral Tegmental Area: Interaction with

Trait and Neurobiological Correlates of Indivi­ dual Differences in Dream Recall and Dream Content Mark Blagrove and Edward F. Pace-Schott


Consciousness in Dreams David Kahn and Tzivia Gover The Underlying Emotion and the Dream: Relating Dream Imagery to the Dreamer‘s Underlying Emo­ tion can Help Elucidate the Nature of Dreaming Ernest Hartmann Dreaming, Handedness, and Sleep Architecture: Interhemispheric Mechanisms Stephen D. Christman and Ruth E. Propper


To What Extent Do Neurobiological Sleep-Wak­ ing Processes Support Psychoanalysis? Claude Gottesmann The Use of Dreams in Modern Psychotherapy Clara E. Hill and Sarah Knox INDEX

Science of awakening, Volume 93 (International Review of Neurobiology.) - PDF Free Download (2024)


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