Sleep Extension in Humans: Sleep Stages, EEG Power Spectra and Body Temperature

Transcription

1 Sleep, 14(4): Association of Professional Sleep Societies Sleep Extension in Humans: Sleep Stages, EEG Poer Spectra and Body Temperature Derk-Jan Dijk, Christian Cajochen, Irene Tobler and Alexander A. BorbeIy Institute of Pharmacology, University of Zurich, Sitzerland Summary: In eight male subjects the electroencephalogram (EEG) and core body temperature (Teore) ere recorded during long sleep episodes from to 15 hr. EEGs ere visuallv scored and subjected to spectral analysis by fast Fourier transform. Slo-ave sleep [SWS, i.e. stages of non-rapid eye movement (NREM) sleep and slo-ave activity (SWA, mean EEG poer density in the range of Hz)} in NREM sleep attained highest values in the first 3 hr of sleep and loest values in the morning hours hen rapid eye movement (REM) sleep as at its maximum. Wakefulness as significantly enhanced in the last 3 hr of the recording period. Occasional NREM episodes containing SWS ere observed in the late morning and early afternoon. Hoever, no significant increase in SWS or SWAin the last 3 hr of the sleep episode over any of the preceding 3-hr intervals as present and SWAin this interval as significantly belo the values observed at the beginning of sleep. The duration of NREM episodes varied significantly over the sleep episode. Analysis of the dynamics of SW A ithin NREM episodes revealed that SW A gradually rose during the episode. Consequently, SW A averaged per episode as positively correlated ith episode duration. T core dropped in the initial part of sleep, rose during the morning hours and reached values in the afternoon that ere highlr than at the beginning of sleep. Thus the time course of Teore dissociated from the time course of SW A. This indlicates that SWAin NREM sleep is not directly related to the variation in core body temperature. Key Words: Sleep extension-slo-ave sleep-slo-ave activity-rapid eye movement sleep-body temperature-circadian rhythms. Among the most conspicuous characteristics of human sleep is the marked variation of electroencephalographic (EEG) slo-ave activity (SW A) ithin nonrapid eye movement (NREM) sleep. As early as 1937 Blake and Gerard (1) reported that slo aves are abundant in the first hours of nocturnal sleep and decline thereafter. These observations have been replicated and expanded in numerous studies in hich an estimate of SW A as obtained by means of visual scoring of sleep EEGs (2). Visual scoring classifies epochs that are dominated by slo aves in the -2-Hz range as slo-ave sleep (SWS). In more recent years SWAin the EEG has been quantified ith spectral analysis based on fast Fourier transforms (3), and ith period-amplitude analysis (4,5). All methods revealed that SW A is high in the first NREM episodes of nocturnal sleep and then declines in subsequent NR1EM episodes. When one night of sleep is skipped and re- Accepted for publication April Address correspondence and reprint requests to Dr. D.-J. Dijk, Laboratory for Circadian and Sleep Disorders Medicine, Harvard Medical School, Brigham and Women's Hospital, 221 Longood Avenue, Boston, MA 2115, U.S.A. 294 covery sleep is initiated at habitual bedtime, SW A is enhanced (3,6). The physiological basis of these variations in SW A is largely unknon. They have been conceptualized by postulating that SW A is regulated by a process that depends on the prior history of akefulness and sleep. This process as formalized in the to-process model of sleep regulation (7,8) as process S, hich can be regarded as an hourglass process maintaining sleep homeostasis (9). The variable S increases during akefulness and decreases during sleep independent of the circadian phase at hich akefulness or sleep occurs. In keeping ith this hypothesis, SW A in the first 3 min of naps increased as a function of the duration of prior aking, hich ranged from 2 to 2 hr (1). The decrease ofswa over the sleep episode as preserved hen sleep as initiated at 7 hr after 24 hr of aking, and recovery sleep thus occurred on the rising limb of the endogenous body temperature rhythm (11). Further support for the hypothesis that the time course of SW A is determined by an hourglass process as derived from selective SW A deprivation studies. When SW A in the first part of sleep as reduced by acoustic stimulation, hich did not induce

2 SLEEP EXTENSION IN HUMANS 295 akefulness, an intrasleep rebound of SW A as observed (12,13). Evidence for the involvement of clock-like processes has been collected in so-called extended sleep studies. When sleep is initiated at habitual bedtimes or at 4 hr and is extended into the day, visually scored SWS has been reported not to decrease monotonically. Approximately hr after the beginning of sleep, SWS as reported to resurge (14-16). Because this recurrence of SWS could be shifted by delaying bedtime, the data ere interpreted as evidence for a sleep-dependent 12.5-hr rhythm of SWS (15,17). We studied the time course ofsw A during prolonged sleep in sleep episodes that ere initiated at 19 hr, i.e. on the falling limb of the core body temperature (T core) rhythm, after either 12 or 36 hr of aking (18, 19). During these long (12 hr) sleep episodes no resurgence of SW A as observed. SW A declined over the first three or four NREMepisodes and thereafter remained at a constant level. Thus the reported resurgence of SWS is unlikely to be related to sleep duration per se but, alternatively, may be related to circadian phase. Until no, the resurgence ofswa in extended sleep has been documented by visual scoring only. Hoever, visual scoring of the EEG merely give a rough estimate of SW A, and dissociations beteen the time course of SWS and SW A have been reported repeatedly (2-22). In the present report e analyze the time course of EEG SW A, as quantified by spectral analysis, sleep stages and T eore during long sleep episodes that ere initiated at midnight. Subjects and study design METHODS Male subjects (age range 2-24 yr) ithout sleep complaints ere selected on the basis of a questionnaire in hich they ere asked about their health, medical history, sleep habits, caffeine, nicotine, drug intake, etc. None of the empaneled subjects had a significant medical history or used prescription or nonprescription drugs. They reported habitual sleep durations in the range of 7 to 8 hr. Visual inspection of the poer spectra plots of the second night in the laboratory did not reveal abnormal patterning in any of the subjects. Ten subjects ere scheduled but to had to be excluded from the analysis because they became ill during the experiment. Subjects slept during three consecutive nights in the sound-attenuated and darkened bedroom of the sleep laboratory. On the first to nights, time in bed as restricted from till 7 hr. Subjects ere instructed not to sleep during the day. This as verified by ambulatory monitoring of motor activity (23). On the third evening, hich as a Saturday evening in all cases, subjects ent to bed at midnight and ere instructed to stay in bed till 15 hr Sunday afternoon and to sleep as long as possible. Body temperature recording Body temperature as recorded during all three nights by a battery-poered ambulatory thermolog (Minilog TA V2). The temperature probe (diameter 5 mm) as inserted approximately 1 cm into the rectum. The thermistor (LM 335, National Semiconductor) had a resolution of.2 C. Temperature data ere digitized (National Semiconductor ADC 84; 8 bit, accuracy ± I least significant bit, temperature range 35-4 C) and stored every 8 sec. Room temperature during the long sleep episodes as on average 17.8 C ±.12 (SEM). EEG recording and analysis On the second and third night, EEGs, the submental electromyogram (EMG) and the electrooculogram (EOG) ere recorded ith gold disc electrodes (Grass Instruments Type E5GH) that ere filled ith EC2 (Grass) electrode cream and affixed ith collodium. The EEGs ere derived from C3-A2 and C4-Al. Signals ere amplified by the preamplifiers of a Grass 78D polygraph. The time constant of the EEG amplifiers as set to.6 sec. Signals ere recorded on analog tape (Helett Packard 3968A) and on paper (paper speed 1 mm/sec). The EEG, EMG and EOG signals ere on-line digitized (sampling rate 128 Hz, input range ± 1 V, 12 bit) by a signal processor board (Texas Instruments TMS 32-1) installed on a personal computer (PC, Oliv,etti M24). The EEG signals ere lo pass filtered (25 Hz, 24 db/octave) before AD conversion and then subjected to a fast Fourier transform, hich as implemented on the signal processor board. Poer spectra ere calculated over 512 data points (4 sec) ith a rectangular indo. This procedure results in one poer value per.25 Hz over the range from.25 to 64. Hz. Data above 25. Hz ere omitted from the analysis and further data reduction as achieved by collapsing poer values into.5-hz (in the range of Hz) or 1.-Hz ( Hz) bins. Off-line, the average spectrum as calculated over five 4-sec spectra, resulting in one spectrum per 2 sec. The PC generated a marker signal that as ritten on paper every 2 sec. This facilitated the synchronization beteen spectra and sleep scores. The EEG records of the third night ere scored visually per 2-sec epoch according to established rules (24). The scores obtained ere entered into the PC and matched ith the poer spectra. This alloed the cal- Sleep. Vol, 14. No,

3 296 D.-J. DIJK ET AL. TABLE 1. Sleep stages and SWA in NREM sleep during extended sleep per 3-hr intervals Interval -3 hr 3-6 hr 6-9 hr 9-12 hr hr F p< W 1.9 (2.9) 1.6 (1.)** 5.3 (2.1) 38. (19.) 82.6 (21. 7)* (1.2) 12.2 (1.5) 17. (2.6) 19.3 (3.3) 17.9 (4.3) 1.65 NS (6.1) 85.2 (6.2)* 73.5 (3.7) 74. (1.9) 4.8 (1.8)** (2.1) 18.1 (4.5)* 9.4 (2.) 6.8 (2.6) 4.1(1.4) (6.9) 1.3 (3.1 )** 2.6 (1.)* 1.5 (1.) 2.8 (1.6) SWS 67.4 (7.8) 28.4 (5.4)** 12. (2.6)* 8.4 (3.4) 6.8 (2.7) REM 16.8(2.1) 48.6 (4.7)** 69. (4.1)** 37. (8.1)** 24.9 (6.7) MT 3.5 (.7) 4. (.2) 3.11 (.3) 3.4 (.5) 2. (.5) 2.92 NS TST (2.6) (1.)** (2.1) (19.) 9.5 (2.2)* % 6.6 (.8) 7. (.9) 1. (1.6) 16.7 (4.1) 19. (2.5) % 43. (4.3) 49. (3.9) 42.8 (2.) 54. (2.7) 45.8 (5.8).98 NS 3% 17.2 (1.1) 1.3 (2.5)* 5.5 (1.2) 5.5 (1.9) 6.3 (2.6) % 23.2 (4.) 5.9 (1.7)** 1.5 (.6)* 1. (.6) 3.2 (1.9) SWS% 4.4 (4.4) 16.2 (3.1 )** 7. (1.5)* 6.6 (2.3) 9.5 (3.3) REM% 1.1 (1.2) 27.8 (2.6)** 4.11 (2.)** 22.8 (4.5)** 25.8 (5.8) SWAnrem% (4.8) 78.7 (6.)** 61.2 (6.9) 51.3 (6.1) 59.7 (7.9) SWAss% 18.4 (3.1) 87.6 (7.1) 71.5 (8.2) 49.7 (lo.4)** 62.7 (8.6) Values are in minutes or in percentage of total sleep time (TST = I REM); n = 8 for all variables in all intervals except for values expressed as percentage oftst in interval hi' for hich n = 7. W = akefulness; MT = movement time; SWS = sloave sleep: stage 3 + 4; REM = Rapid eye movement sleep. SWAnrem% = slo ave activity ( Hz) in NREM sleep (stages 2, 3,4) expressed as percentage of the mean value ofswa in NREM sleep during the first 8 hr of the recording period. SWAss% = SWA in SWS expressed as percentage of the mean value of SWA in SWS during the first 8 hr of the recording period. Note that in interval 12-15, stages W, 1,2, 3, 4, REM and MT do not add up to 18 min. This is due to small deviations from the protocol in to subjects. F values ere derived from a one-factor (interval) repeated measures ANOVA; p values are based on Greenhouse-Geiser adjusted degrees of freedom but the original degrees of freedom are given. Values that are significantly different from the value in the preceding interval are indicated by *p <.5 or **p <.1 (paired t test). Pairise comparisons ere only made if the effect of interval as significant (p <.5); NS, not significant. culation of poer spectra per sleep stage and the exclusion of movement time epochs. NREM episodes ere defined as the succession of sleep stages 2, 3 or 4 ith less than 5 min interruption by other stages except REM, of hich any occurrence terminated an NREM episode. The minimum duration for an NREM episode as set to 5 min. REM episodes ere defined by the succession of any number of REM epochs not interrupted by more than 5 consecutive minutes of any other stage. Because in some subjects sleep as quite fragmented toard the end of the sleep episode, NREM-REM cycles could not alays unambiguously be identified. Therefore, some of the analyses ere based on 1.5-hr or 3-hr intervals. Changes of variables over these intervals ere first analyzed ith ANOVAs. If the effect ofinterval as significant, selected intervals ere compared ith a t test. We calculated significances ith and ithout correction for multiple comparisons. We chose to present the results of the simple t test because based on the literature a priori predictions ere available. RESULTS Sleep stages, SWA (poer density Hz) and T eore of all eight individuals are depicted per I-min interval in Fig. 1. All subjects fell asleep readily (latency to stage 2: 13.6 min ± 9.9 SEM). One subject (#3) did not sleep after 1 hr hereas subjects 4 and 8 slept through the entire 15-hr period ithout major episodes of intermittent akefulness. In others (e.g. #2 and #7), a major aking episode folloed by sleep as present around noon. Average per 3-hr interval akefulness (W) as significantly higher in the first interval than in the second and, in the last interval, W as significantly highr than in the preceding interval (Table 1). In all subjects SWS and SW A attained high values in the initial 3 hr of sleep. SW A and SWS decreased in the next 4.5-hr period (Fig. 1). Hoever, a strict progressive decline of SW A per NREM-REM cycle as not observed in all subjects during the first 8 hr of sleep. For instance, in subject #1, SWA in NREM REM cycle 5 as higher than in cycle 4 and in the fourth cycle of subject #5, SW A as higher than in the preceding cycle. In the remaining 7 hr of the recording period, a large interindividual variability in sleep patterns as observed. In subject #4, an NREM episode that contained stages 3 and 4 occurred after approximately 11.5 hr of sleep. SWAin this NREM episode as also higher than in the preceding NREM episodes although considerably loer than SWAin the first to NREM episodes. In subject #8, some SWS as scored in the 14th hr of sleep. SWAin this episode as slightly higher than in the preceding 5 hr but much loer than in the first 4 hr. Analyzed over all subjects, SW A ithin SWS varied significantly over the five 3-hr intervals ith loest values being present in intervals 4 and 5. Average per 3-hr interval SWS decreased significantly Sleep. Vol. 14. No.4, 1991

4 SLEEP EXTENSION IN HUMANS 297 Cl LL W It)... C') '*I: '*I: jl L <t: - "'C')N_: ob (:)) 31:ln.lVl:J3dV13.l \i: VMS Sleep. Vol. 14. No

5 til 1 :-. Fig. IB N '... -' p ::>!;{ n. ::; I-- #5 #6,. 1.,lr :.:."T1.,Nr! A "'rr!r ':pi_rr-,i.,y.r.it"" l, ,U.j 'F,L, ' "...,' 4 1t, kd 1.I;,.Ljlh. 11] ''dj.hlj!.1 #7 #8 ::.. t:::l t:: tl'l ""-3 r- o o TIME OF DAY FIG. 1. A, B Sleep stages, slo-ave activity (SWA, mean poer density in the hz band) and core body temperature during extended sleep in eight subjects. Data are plotted per I-min episode. SW A is not plotted after final aakening as many artifacts ere present. Calibration marks on the right represent 5 J.L y2/hz.

6 SLEEP EXTENSION IN HUMANS 299 P #. I- (J) I- U. #. z c( :E.r:: a) I- (J) u. u. "if. 37. i a ',",.. EXTENDED SLEEP CORE TEMPERATURE "'...,..,...,..., ,.",... SWS / // /Y 1'/ WAKING +/\\I! A\REMS /,..' \... _ ,..' SWA IN nonrems a TIME OF DAY FIG. 2. Wakefulness, core body temperature (T,o,,), SWS, REM and SWA in NREM during extended sleep. All data (except Te) are plotted per 9-min intervals. SWS and REM are expressed as percentage of TST; aking as a percentage of recording time. SW A is expressed as percentage of mean SWAin NREM sleep in the first 8 hr of the recording period. For T,",e and aking n = 8 in au intervals. For SWS, REM and SWA n = 8 except in the last to intervals here n = 7 and 6 for the next to last and the last interval, respectively. Vertical bars represent ±2 SEM. over the first three intervals hereas for SW A a significant decrease as present only over the first to intervals. In hours 12-lS, %SWS and SWA in NREM ere slightly higher than in the preceding interval. This increase as, hoever, not significant. SW A ithin SWS also varied significantly over the five 3-hr intervals (Table 1). Highest values ere observed in the first 3-hr interval and loest values ere present in hours REM% increased over the first three 3-hr intervals to approximately 4%, hereafter a sharp drop to 23% occurred in the next 3-hr interval. To visualize the average time course of REM, SWS, Wand SW A in NREM sleep in more detail, data ere plotted per 9-min interval (starting at lights-off). In addition, the average Teore as calculated per I-min interval (Fig. 2). Teore dropped at the beginning of the recording period. In some subjects a clear minimum as located in the first 2 hr of sleep (e.g. subjects #3, #8, see Fig. 1) folloed by a rise of Teore throughout the remaining recording period. In other subjects the minimum as not reached until after 6 hr of sleep (e.g. #2) or could not be easily identified (#7). On average (Fig. 2 top panel) Teore started to rise at approximately 6: a.m. In all subjects Teore rose in the morning and early afternoon to values that ere higher than those observed at the beginning of the recording period. Except for the first interval in hich because of the latency to sleep onset some aking as present, aking attained levels close to zero throughout the first 7.S hr of the recording period. Thereafter a rise to SO% of the recording period in the last interval occurred. REM sleep expressed as a percentage of TST reached its maximum in the sixth interval, i.e. 7.S-9 hr after lightsoff. This interval coincided ith the interval in hich minimum levels of SWS and SWAin NREM sleep ere observed. Although a small but increasing trend could be observed from intervals 6 through 9, SWS, %SWS and SW A ere not significantly higher in any of the intervals after 9: a.m. than in any of the preceding intervals (p > O.OS in all cases, Student's t test). Time course of EEG poer density To document the changes in the various frequency components of the EEG, all spectra ere analyzed per 3-hr interval in NREM and REM sleep (Fig. 3). In NREM sleep, poer density over a broad frequency range varied significantly over the five 3-hr intervals. In the delta and theta frequencies up to 9 Hz, values decreased monotonically over the first four intervals. The largest drop as observed in the.7s-l.-hz bin. In the fifth interval, values in the delta and theta frequencies ere slightly higher than in preceding intervals. Hoever, for none of the frequency bins as a significant difference beteen intervals Sand 4 observed (Student's t test, p > O.OS). In the frequency range from 13 to IS, Hz trends opposite to those observed in the delta and theta frequencies ere present. Prominent enhancements in the 14.2S-lS.-Hz range ere present, especially in the last to 3-hr blocks. Sleep. Vol. 14. No

7 3 D.-J. DIJK ET AL. In REM sleep significant variations over the five intervals occurred in the Hz range only, and in some delta and theta/alpha frequencies a p value <.1 as observed. Dynamics of SW A and temperature ithin NREM episodes SW A averaged per 3 hr or any comparable time interval can only give a crude description of the relevant changes of the dynamics of SW A. A lo valm: in a certain interval may be the result of either a slo evolution of SWAin NREM episodes but unchanged NREM episode duration, or of an unchanged rise rate of SW A but a reduced NREM episode duration. To distinguish beteen these possibilities e analyzed the dynamics ofsw A and, in addition, temperature, ithin NREM episodes. NREM and REM episode durations ere calculated per 1.5-hr interval (Table 2). Both for NREM and REM sleep, episode duration varied significantly over the 1 intervals (NREM F 9,79 = 5.62, p <.1; REM F 9,66 = 6.24, P <.1). Longest NREM episodes ere present in the beginning of skep and minimum durations in the 7th and lath intervals. In intervals 8 and 9, i.e hr after lights-off, NREM episodes ere slightly longer than in adjacent intervals. In these intervals SW A as also somehat higher, although in neither interval 8 nor 9 ere the values significantly higher than in the preceding in1tervals (in all cases, p >.5, Student's t test). To analyze the interrelation beteen the mean SWAin an NREM episode and the duration of this episode, the correlation beteen the to variables as calculated. In several intervals a positive correlation as observed (see Table 2). To obtain a sufficient number of episodes, data ere analyzed per 3-hr interval (Fig. 4). In all intervals the correlation beteen SW A and the duration of an episode as positive, and in all but the first interval, statistically significant. The dynamics of SW A and Teore ithin NREM episodes are illustrated in Fig. 5. NREM episodes ere assigned to 1.5-hr intervals according to the tim{: at hich the episode started and only NREM episodes ith a duration of 2 min or longer ere included. These NREM episodes ere subdivided into 2 5-percentiles and SW A as averaged over these percentiles. In addition, SWAin to 5-percentiles before and to 5-percentiles after an NREM episode as calculated. The temperature data ere analyzed in a similar ay. Note that in order not to obscure the dynamics of temperature ithin NREM episodes by the interindividual variation in the absolute level of Teore, all temperature data ere expressed as deviation from Teore at the beginning of an NREM episode and averaged over subjects. Then the mean absolute va1u(: of Sleep, Vol. 14, No.4, 1991 en :::i: 15 g 125 >- 1 z , ,,I I' ", ' I I I ' ' ' i " J\\ \,1 175, , en 15 :::i: 125 >- I _ p<o.5 p<o.1 25r o Hz FIG. 3. Poer density per ISO-min interval in NREM (top) and REM sleep (bottom). Data ere expressed as a percentage of the value in the first 3 hr and log transformed. After averaging over subjects data ere retransformed to a linear scale. Lines beneath the abscissa indicate frequencies for hich a one-ay ANOV A on the log-transformed values yielded a significant effect. NREM sleep: intervals 1-4: n = 8; interval 5: n = 7. REM sleep: intervals 1-3: n = 8; interval 4: n = 7; interval 5: n = 6. Teore at the beginning of the NREM episodes as added to all values. Figure 5 illustrates that SWA increases gradually during the larger part ofnrem e'pisodes and decreases rapidly in the last part. SW A in the selected episodes varied significantly over the recording period (F 9,57 = 15.93; p <.1). Highest values ere present the first to 9-min intervals. SWAin all subsequent intervals as significantly belo SWAin the first to intervals (p <.5, Student's t test). Loest values ere located in intervals 6 and 7. In the intervals thereafter, average SW A as somehat higher again, although not significantly (p >.5, Student's t test). Because also in the present analysis the duration of NREM episodes influences the SW A values, SW A as averaged over the first 2 min of these episodes (SW Azo Table 3a). SW Azo varied significantly over the lain tervals (F 9,57 = 1.65, p <.5). Highest values ere observed in the initial part of the recording period and the loest values ere located in interval 6. In intervals 7-9, val-

8 SLEEP EXTENSION IN HUMANS , n=2 r=.195 ns 2 15 \ e. 2 n=16 r=.592 p< CJ) c c CJ) z « n=18 r=.732 p<.1 / 5 n=13 r=.626 p<.5 4 n=22 r=.63 p< o o nonrems EPISODE DURATION (min) FIG. 4. Mean SW A per NREM episode plotted against episode duration for five 3-hr intervals. The solid line as derived from the linear regression ofswa on NREM episode duration. The slopes (s) and intercepts (i) of the regression lines ere: intervall: s =.35 SWA%/ min, i = 17.3 SWA%; interval 2: s =.58, i = 33.; interval 3: s =.89, i = 13.8; interval 4: s =.48, i = 27.3; interval 5: s =.72, i = ues ere somehat higher again (p >.5, Student's t test) although still significantly (p <.5, Student's t test) belo the values in the first interval. Finally, e calculated the maximal SW A in each of the selected episodes (SW Asmax) using a moving 5-min indo. SW Asmax varied significantly over the 1 intervals (F 9,S7 = 11.7, p <.1), and its time course as basically identical to that of the other SW A parameters. Thus maximum values ere found at the beginning of sleep; the values in the late morning/early afternoon (intervals 8, 9) ere not significantly higher than in preceding intervals and significantly loer than the values in the first to intervals (p <.5, Student's t test). T eore at the beginning of NREM episodes varied significantly over the recording period (F 9,S7 = 8.17, P <.1). The values in intervals 8 and 9, i.e. in the late morning/ early afternoon, ere significantly higher than those in the first interval (p <.5, Student's t test) (Table 3b). Sleep, Vol. 14. No

9 32 D.-J. DIJK ET AL. 37. Ul :;)!;{ 36.5 Ul a. ::;; Ul f- Ul 36. () >- f- 2 :;: i= () c( 15 Ul 5: 5: 1...J en TIME (% OF nona EMS EPISODE) FIG. S. Dynamics ofswa and T<ore ithin NREM episodes. Vertical bars in SWA plot represent ±2 SEM. For the T,are data the solid line represents the mean and the dashed lines ± I SEM. For number of subjects contributing to the mean and statistics, see Table 3. Details on the procedure for calculating the time course of SWA and T<ore are given in the text. The change of T core ithin NREM episodes also varied significantly over the recording period (F 9 57 = 4.1S, p < O.OOOS). At the begining of sleep, T oore decreased during NREM episodes, but increased during NREM episodes in the morning. In intervals 8 and 9 no significantchanges ere observed. In the interval in hich T core reached highest values (interval 8), SW A as significantly belo the values at the beginning of sleep, but somehat (not significantly) higher than in adjacent intervals. Correlations beteen SW A and temperature parameters in NREM episodes ere calculated per l.s-hr intervals (see Table 3b). Only in interval S as a significant correlation beteen mean temperature and TABLE 2. NREM and REM episode durations, SWA per NREM episodes and Pearson's correlation beteen SWA and NREM episode duration a Duration of Duration of SWAinNREM NREM episode REM episode SWAin NREM VS. duration INT!.>.," n Mean SEM n Mean SEM n Mean SEM r p NS NS NS NS NS lo- S NS a Episodes ere assigned to 1.5-hr intervals on the basis of the beginning of an episode. For definition of episodes see Methods section. Values are in minutes. b INT 1.5., = 1.5-hr interval. For this table, SW A values are slightly different from those in Fig. 2 because values ere first averaged per NREM episode and then averaged per interval. Furthermore, NREM episodes < 5 min ere excluded from the analysis. SWA is expressed as percentage of mean SWAin NREM during the first 8 hr of the recording period. NS, not significant. Sleep. Vol. 14. No

10 SLEEP EXTENSION IN HUMANS 33 TABLE 3a. SWA and core body temperature parameters for the NREM episodes that are included in Fig. 5, and their duration Duration a SW A.,P;'od,b SWA 2 ' SWA5ma/ T besine Tchang/ INTl.5h, n Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM * Q ** ** * a Duration of NREM episodes in minutes. b SW A averaged over the entire NREM episode., SW A averaged over the first 2 min of the NREM episode. d SWAin 5 min period in hich SWA as maximal. e T core ("C) 1 min before the beginning of the NREM episode. J Average change in T,m, (1-3 C/min-') over the entire NREM episode. SWA parameters are expressed as percentage of mea Ii SWA in NREM sleep in the first 8 hr of the recording period. Intervals in hich temperature changed significantly over the NREM episodes are indicated by * (p <.5) and ** (p <.1) to-sided t test. SW A observed. Significant positive correlations beteen the change in temperature and SW A ere obtained only in one interval hen the analysis as restricted to the first 2 min of the NREM episode. When the data ere analyzed per 3-hr intervals in a similar ay, significant correlations ere obtained only for T change and SWAin the first 2 min of the NREM episodes in intervals I (n = 19, r = -.461, p <.5) and 2 (n = 15, r =.583, p <.5). At the end of the recording period no significant correlations beteen SW A and temperature parameters ere observed. DISCUSSION Although the subjects had to stay in bed for 15 hr and ere instructed to sleep as long as possible, akefulness increased in the last to 3-hr intervals of the recording period. This finding is in accordance ith previous extended sleep studies, although in the present study the values of aking ere somehat higher. This is likely to be due to the subject selection and data analysis procedure. In one previous study (15) one of the inclusion criteria as that subjects occasionally ere capable of sleeping 12 hr or more hereas in our study this as not a prerequisite. In the to other studies records ith too much intermittent aking in the last part of extended sleep ere excluded from the analysis (14,16) or no information on intermittent akefulness as presented (25). In the present study the increase in akefulness as preceded by an increase in REM that as maximal at 8-9 hr. Visually scored SWS and SW A ere maximal at the beginning TABLE 3b. Pearson's correlation beteen SWA and core body temperature parameters in NREM episodes that ere included in Fig. 5 Entire episode First 2 min SWA vs. SWA vs. SWA vs. SWAvs. SWA vs. SWA vs. INT1.5h, n Tbeg;n r Tmean r T'h""", r Tbeg;n r Tmean r TChange r *.716* ** NREM episodes ere assigned to 1.5-hr intervals, according to the time at hich the NREM episode started. No correlation in the 1th INTl.5h' as n = 1. SWA as averaged over either the entire episode or the first 2 min and expressed as a percentage of mean SWAin NREM sleep during the first 8 hr. Tbeg;n = Toore 1 min before the beginning of the NREM episode. Tmean = average T,ore during either the entire episode or the first 2 min of the episode. T,han" = average change oft,ore during either the entire episode or the first 2 min of the episode. *p <.5; **p <.1. Sleep, Vol. 14, No.4, 1991

11 34 D.-f. D/JK ET AL. of sleep and then declined. After 6 hr no significant further decrease of SW A as observed. The absence of a progressive decrease of computer-detected SW A has been observed before in long sleep episodes (19,26). In the late morning and early afternoon hours, SWS% and SWA increased slightly but not significantly. In the study of Gagnon et a1. (15), SWS expressed a.s a percentage of TST in hours of sleep episodes that ere initiated at midnight amounted to 14.2%. This does not dramatically differ from the 9.5% observed in the present study. Gagnon et ai., hoever, concluded that after hr of sleep, a significant resurgence or reappearance of visually scored SWS occurred (14,15). This conclusion as based on the presence of a significant quadratic in a polynomial trend analysis. When our data ere analyzed in a similar ay, a significant quadratic term emerged. Hoever, because at quadratic term in a polynomial trend analysis as described by Gagnon et a1. (15) is also present hen the data exhibit a decline folloed by a positive horizontal asymptote, it cannot be concluded from this analysis that there is a systematic increase of SWs. or SW A. The analysis of SW A demonstrated that although in the late morning and early afternoon occasional NREM episodes ith SWS occurred, and SW A in these episodes as somehat higher than in preceding hours, it never reached levels similar to those at the beginning of the sleep period. In accordance ith previous findings (3,22), the parallel analysis of the s1<eep EEG by visual scoring and spectral analysis demonstrated that ithin visually scored SWS, SW A varied considerably. Thus, in the present data ithin SWS that occurred at the end of the recording period, SW A as on average 1.7 times loer than in SWS in the first 3 hr of the recording period. These findings sho that visual scoring cannot be used to quantitatively describe the changes that occur in the sleep EEG in the course of sleep. Therefore e conclude that previous analyses oflong sleep, hich only applied visual scoring, overestimated the resurgence of SW A. In agreement ith previous results (3,19), in NREM, poer values in the delta and theta frequencies varied significantly over the sleep episode. These variations ere also present ithin REM although not as pronounced as previously reported (19). Quantitative differences beteen frequencies existed. For instance, in NREM, the largest reduction of poer density over the first 12 hr as present in the hz bin. This frequency bin has been shon to be very sensitivt to changes in the duration of aking prior to s1<eep (3,1,13). In none of the delta and theta frequencies as a significant resurgence of high poer values at the end of the recording period observed. As reported before (19), poer values in the frequency range from to 15. Hz increased in the course of sleep and Sleep, Vol. 14, No.4, 1991 the increase shifted progressively to higher frequencies. Whether these changes reflect variations in amplitude, incidence and frequency of sleep spindles remains to be clarified. The purpose of the present analysis as to identify correlates of variations in SW A. The duration of prior aking and of sleep have been shon to be major determinants of SW A ithin NREM sleep. Because during long sleep episodes that ere initiated at 19 hr, NREM episodes ith high SW A ere only observed during the initial part of sleep (19), the occasional high SW A values in the later part of the sleep episode in the present study are unlikely to be caused by a sleep-dependent rhythm ofsws. Because no statistically significant increase as observed, e cannot exclude the possibility that it reflects random variation in SW A. Alternatively, it may reflect a circadian influence on SW A. Several mechanisms by hich this circadian effect on slo aves is mediated have been proposed. Horne (27) suggested that the "reappearance" of SWS is caused by the large amounts of intermittent aking and REM sleep that are present in the last part (i.e. in the morning hours) of long sleep episodes hen they are initiated at habitual bedtimes (14,15 and present data). In his vie, both aking and REM sleep contribute to "pressure" for SW A. The influence of prior aking on SW A is ell established and in vie of the electrophysiological and metabolic similarities beteen REM sleep and aking (see 27 for references), it is likely that REM sleep also leads to an increase of SW A. The present data partially support this vie as the small increase of SW A occurred after the intervals in hich on average the maximum amounts of REM sleep ere observed. This latter finding is, hoever, also in accordance ith the hypothesis advanced by Webb (16). He suggested that the reappearance of SWS is related to a release of this sleep state from the inhibitory influence of REM sleep. The present data indeed sho that the interval ith maximum REM values coincided ith minimum SWAin NREM sleep. Experimental manipulation of the need for REM sleep by selective REM sleep deprivation (28) or by a partial sleep deprivation in the second part of the night (29) hich is essentially a REM sleep deprivation, indeed tended to inhibit SW A. It should be noted that hen sleep is initiated in the early morning after one night ithout sleep, SW A is high at the beginning of sleep (11,22). Obviously, the inhibitory influence of REM sleep on SW A is not so strong that it can change the time course ofsw A substantially hen the pressure for SW A is enhanced by total sleep deprivation. These interactions beteen SWAin NREM and REM sleep remain to be quantified and incorporated in the extended version of the to-process model (3). Another correlate of the variation of SWAin

12 SLEEP EXTENSION IN HUMANS 35 NREM sleep is the duration of NREM episodes. It should be kept in mind that because SW A is a density measure, the positive correlation beteen the duration of NREM episodes and SW A ithin these episodes is not entirely trivial. This correlation is related to the gradual buildup of SW A ithin an NREM episode, as illustrated in Fig. 5 and previously analyzed for baseline sleep episodes of normal duration (31,32), and recovery sleep after sleep deprivation (19). It has been suggested that the pressure for NREM sleep is a major determinant (7,33) ofnrem episode duration. Hoever, because NREM episode duration during recovery sleep in the morning as shorter than during nocturnal baseline sleep (11), circadian factors in the regulation of NREM episode duration have to be taken into account. On the other hand, SW A averaged over the first 2 min of NREM episodes exhibited a time course similar to SW A averaged over the entire NREM episode. This indicates that the variation in NREM episode duration cannot be the only cause of variation in SW A although its contribution may be substantial hen NREM sleep becomes fragmented. SWS and temperature regulation are thought to be closely related (34,35). In accordance ith this vie, T eore decreased during NREM sleep at the beginning of sleep, and the rate of decrease of T eore ithin NREM episodes as positively correlated ith SW A. Hoever, in the second part of sleep, no consistent relation beteen the rate of change in T eore and SWA as observed, and T eore even increased during NREM sleep. In the early afternoon T eore as significantly higher than at sleep onset. This underscores the strong influence of circadian processes on T eore and is in agreement ith the results of Gill berg and Akerstedt (36) ho analyzed the time course of T eore in sleep initiated at various circadian phases. Because our temperature data ere collected in the presence of the masking effects of sleep on temperature, the temperature data cannot be taken to accurately reflect circadian phase. Consequently, e cannot exclude the possibility that if the sleep episodes ere synchronized ith respect to circadian phase instead of clock time a significant circadian influence on SW A ould have emerged. Nevertheless, in the late morning/early afternoon no consistent correlations beteen core body temperature parameters and SW A ere observed. Therefore the present data do not support the hypothesis that the rise of body temperature in the morning is directly related to the high SW A values in the late morning/early afternoon hours, as has been hypothesized (35). CONCLUDING REMARKS The present data demonstrate that the time course of SW A is primarily sleep dependent and differs from the time course of body temperature, hich is to a large extent under circadian control. 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