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Ultradian rhythms in alertness — A pupillometric study
Biological Psychology 9 (1979) 49-62 © North-Holland Publishing Company
ULTRADIAN RHYTHMS IN
ALERTNESS
49
-
A PUPILLOMETRIC STUDY
PERETZ LAVIE Faculty of Medicine, Technion, Haifa, Israel Accepted for publication 4 June 1979
PupiUary size, pupillary light reflex and pupiUary motility were measured every 15 min, for 10 continuous hours, in eight young adults. Time series constructed from the range of pupillary motility revealed 75 to 125 min rhythms; these were significantly out of phase with rhythms of similar periodicity in pupillary diameter and in the magnitude of the pupillary light reflex. There was no consistent correspondence between Stanford Sleepiness Scores and pupillary activity. It is suggested that the rhythms in pupiUary activity reflect underlying rhythms in CNS arousal that also modulate perceptual, cognitive and electroencephalographic processes, a conclusion which supports Kleitman's BRAC model.
1. Introduction The existence of short term rhythms in alterness during the awake state was first suggested by Kleitman (1961) who viewed these rhythms as part of an ongoing 24 h rhythm which appears in sleep as the REM-NONREM cycle. Kleitman speculated that this Basic Rest-Activity Cycle (BRAC) originated from a primitive sleep and wakefulness rhythm, adjusted to the nutritional needs of the organism. Several studies have provided support for Kleitman's hypothesis by demonstrating rhythms in different indices of alterness or arousal, with periodicities approximating the 90 min periodicity of the sleep REM-NONREM cycles. Such rhythms were shown in perception of visual illusions (Lavie, Lord and Frank, 1974; Lavie, Levy and Coolidge, 1974; Lavie, 1976), vigilance performance (Orr, Hoffman and Hegge, 1976), accuracy of motor performance (Lavie and Gopher, paper submitted for publication), and in daydreams and electroencephalographic activity (Kripke 1972; Kripke and Sonnenschein, 1978). The present study investigated the possible existence of ultradian rhythms in pupillary activity, a well established, sensitive index of alterness (Yoss, Mayer and Ogle, 1969; Yoss, Mayer and Hollenhorst, 1970; Lowenstein, Feinberg and Lowenfeld, 1963). The pupils are large and stable in alert humans and contract when alertness declines. Contraction is associated with reduction in pupillary reactivity to light and with spontaneous pupillary oscillations, consisting of recurrent waves of pupillary constriction and dilation (Lowenstein and Lowenfeld, 1964).
50
P. Lavie /Rhythms in pupillometric activity
Establishment of ultradian rhythms in either pupillary diameter and/or pupillary stability would provide further support for the notion that the fluctuations previously observed in behavioral and physiological processes reflect a common underlying alertness rhythm. 2. Methods and materials Subjects were five men and three women aged 2 1 - 2 5 years. Testing began at 07:30-09:30 am and continued for 10 h. Two tests were terminated after 8 h 30 min because of excessive tearing. Three subjects were re-examined one week after the original test, and each test was considered as a separate time series. Through the tests, measurement trials lasting 1 - 2 min were administered every 15 rain. During each trial, the diameter of the left pupil was measured continuously to the nearest 0.1 mm using an infrared pupillograph (Whittaker Corp., CCTV Camera model LLSA-15, Eye view monitor, model 19845), and data were recorded on a plotter at a paper speed of 2.5 cm/s. To measure pupillary light reflex, the subject was given three 100 msec stroboscopic flashes at intervals of 8 - 2 0 sec from a 15 W lamp (Knott Elektronik) located 50 cm from the eye. The length of the interflash interval was varied to avoid eye movement and blinking artifacts within the interval. Subject fixated on a point above the lamp and 50 cm from the eye. Before each session the subject filled out the Stanford Sleepiness Scale (SSS) (Hoddes, Zarcone, Smyth, Phillips and Dement, 1973). Testing was conducted in an air conditioned soudproof chamber, lighted between trials to a level of 3 0 - 4 0 lx. During trials, illumination around the subject's eye was maintained at below 5 Ix. Subjects and experimenter communicated via intercom. During the test, the subject was perm!tted to read or write, to order soft drinks and sandwiches at will, and to leave the chamber for short trips to a nearby toilet. After such absences, they were reaccustomed to lighting conditions in the chamber pior to resumption of testing. 2.1. Pupillary measurements
Data obtained at each trial were analyzed for three variables: pupillary diameter (PD), pupillary movement (PM) and pupillary light reflex (PR). Pupillary diameter (PD) was averaged for 500 msec before the three stroboscopic flashes. To measure spontaneous oscillations (PM) eight consecutive 500 msec segments, free of eye movements and blink artifacts, were measured following each flash. In each segment, the absolute range of pupillary movement (in mm) was determined, and the average range was calculated for all 24 segments. The pupillary light reflex (PR) was taken a s the mean amplitude of the three pupillary reflex responses. These were measured as the difference between the baseline pupillary diameter during the 500 msec before the flash and the peak of the light reflex.
P. Lavie / Rhythms in pupillometric activity
51
2.2. Statistical analysis
Four 36-point time series were constructed for each subject from PD, PM, PR and SSS. The first hour was considered as adaptation to the experiment and was not included in the final analysis. The mean was subtracted from each time series and linear trends were removed. Then, 10 lag autocorrelation functions were calculated and spectra estimates computed for 10 spectral frequencies (Jenkins and Watts, 1968). Spectra were individually hanned, normalized to yield spectral density functions and separately averaged for each variable. Since we were particularly interested in the temporal structure of the covariations in pupillary diameter and pupillary stability, cross-correlation functions, hanned cross-spectra, coherence spectra and cross-spectral phase-angle differences, were calculated at each spectral frequency, between PM and PD. A coherence spectrum varies between 0 and 1 is analogous to a linear correlation coefficient between two variables. Coherence close to 1, at a particular frequency, at a phase angle close to 0 °, is analogous to high positive correlation between the two time series, at that particular frequency. The same at phase angle of 180 ° means a high negative correlation between the time series (Orr and Naitoh, 1976;Walter, 1963). Pearson product moment (PPM) correlations between PD and PM and between each of these variables and SSS were calculated as well. Since orthogonal variance spectrum gives rather crude estimate of the dominant periodicity in the data, the least square spectrum technique, which gives a finer estimation of the dominant periodicity, was also utilized (Lubin, Nute, Naitoh and Martin, 1973).
3. Results Samples of pupillary records of one subject taken at different times, are presented in fig. 1, with the corresponding PM scores. In the upper three traces pupillary light reflex was followed by persistent pupillary oscillations, which resulted in high PM scores: the uppermost trace is an example of pupillary hippus which is rhythmic and rapid dilation and contraction of the pupils. In the other two traces the pupils gradually resumed a stable diameter without apparent oscillations; consequently PM scores were low. It should be emphasized that periods of intense pupillary oscillations occurred spontaneously before the photic stimulation, and that photic stimulation did not induce pupillary oscillations when the pupils were stable. The frequency of the oscillations greatly varied within and between subjects for no apparent reason, but no attempt was made in this work to analyze this aspect of pupillary motility. When the average range of oscillations was plotted against time, stationary ultradian rhythms emerged (fig. 2). Variance spectra revealed that eight of the 11 PM time series (72%) peaked at either 14.4 cycles/day (n = 5), corresponding to periodicity of 100 min/cycle, or at 19.2 cycles/day (n = 3), corresponding to
52
P. Lavie / Rhythms in pupillometric activity
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SECONDS Fig. 1. Samples of pupillary records o f one subject, following one stroboscopic flash (indicated b y an arrow) t a k e n at different times, w i t h the c o r r e s p o n d i n g PM scores.
periodicity of approximately 75 min/cycle (fig. 3). Average spectra peaked at 14.4 cycles/day. To test the possibility that the occurrence of five of the 11 spectral peaks at one out of 10 frequencies (14.4 cycles/day) was a chance event, nine 36-point random data time series were generated within the range of the raw data of each PM time series, at simulated 15 min intervals. Then, the 99 simulated time series (nine per experimental time series) were subjected to spectral analysis in a way similar to the analysis of the original data. The average spectra for the simulated time series was fiat, and only 12% of the time series had a spectral peak at 14.4 cycles/day as compared to 45% of the PM time series. Furthermore, at 14.4 cycles/
P. Lavie /Rhythms in pupillometric activity
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19oo 20oo 1~oo 15oo I~°° i'oo i',oo 1'oo i~,oo ,'oo 18oo ' ' ' TIME
Fig. 2. Time series constructed from the raw data of PM scores for five subjects. The percentages of variance at 14.4 cycles/day calculated by orthogonal variance spectra are also presented, 10% are expected in random data.
day the average spectra intensity of the PM data was significantly higher than that of the simulated time series (t = 3.23, df = 108, p < 0.001, one-tailed). In contrast to pupillary motility records, data of pupiUary diameter and light reflex were non-stationary with marked linear and quadratic trends. Figs. 4 and 5 exemplified these trends in pupiUary diameter. Since identical trends were seen in the amplitude of the light reflex they are not presented. Consequently only five of the PD and PR time series peaked at ultradian frequencies, three at 14.4 cycles/day and two at 19.2 cycles/day. The other six time series peaked at frequencies slower than 14.4 cycles/day, which might suggest the existence of circadian rhythms in the data. However, since only 10 hr of data were available, circadian rhythms could not be derived. Sleepiness scores generally exhibited less variability than did the other measures, sometimes remaining unchanged for 3 - 4 hr despite obvious fluctuations in pupillary diameter or motility. For this reason no attempt was made to search for rhythmicity in SSS. Least square spectral analysis performed on the PM and PD records confirmed the results of the orthogonal variance spectrum and provided accurate estimation of
P. Lavie / Rhythms in pupillometric activity
54
PUPILLARY DIAMETER PUPILLARY AeOTILITY --day1 aay 2
I2
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<
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FREQUENCY (in cycles/day) Fig. 3. Ten frequency orthogonal variance spectra for each subject for PM and PD. Spectral peaks are indicated by heavy dots.
P. Lavie /Rhythms in pupillometric activity
55
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Fig. 4. PupiUary diameter (PD) and pupiUary motility (PM) indices of one subject. Although increases in PM coincided with decreases in PD, the linear increase in PD suggests circadian effects on pupillary diameter. the periodicities in the two variables. Table 1 presents the 'primary periods' (the period which gave the highest squared correlation, r 2, of the associated sinusoid with the PD and PM time series) and the corresponding squared correlations. On the average, pure sinusoids accounted for 17% of the total variance in the PD time series and 19% of the PM variance. The average periods for PM and PD were close, 109.4-+27.2 min and 116-+25.5 min, respectively. Approximately identical periods in PM and PD were obtained for six of the 11 time series. In three other cases secondary period in one of the variables was close to the primary period in the other variable. For instance, subject 4 who had primary periods of 141 min for PD and 85 min for PM, demonstrated also a secondary period of 81 min for PD. Fig. 6 presentes the average cross spectral phase angle differences (-+SD) between
P. Lavie /Rhythms in pupillometric activity
56 5.4
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Fig. 5. Time series constructed from PD data of one subject; hourly means are indicated by the heavy line. Note that the obvious approximately 1.5 hr ultradian variations are superimposed on prominent quadratic trend.
Table 1 Primary periodicities and corresponding r 2 values for PD and PM time series Subject
Pupillary diameter (PD)
PupiUary motility (PM)
Period in mins
r2
Period in mins
r2
1 2 3 4 5 6a 6b 7a 7b 8a 8b
89 134
0.20 0.12
141 156 92 92 142 110 88 116
0.15 0.19 0.20 0.12 0.11 0.23 0.23 0.13
87 126 80 85 99 113 160 143 112 75 124
0.19 0.19 0.23 0.16 0.25 0.13 0.16 0.15 0.13 0.28 0.19
Mean sd
116.0 25.6
0.17 0.04
109.4 27.2
0.19 0.04
P. Lavie / Rhythms in pupillometric activity
57
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,5
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(in cycles/day) Fig. 6. Average cross spectra phase angle difference (-+SD) and coherence spectra at each spectral frequency between PD and PM. FREQUENCY
PD and PM, calculated according to Batschelet (1965), and the corresponding average coherence values, at each spectral frequency. As can be se.en from the figure, though pupillary diameter and stability measures were generally out of phase at all frequencies, the average phase angle differences were closest to 180 ° , and standard deviations were smallest, at the ultradian frequencies of 14.4. cycles/day and 19.2 cycles/day. Furthermore, coherence values were largest at these frequencies. Thus, it can be concluded that the out-of-phase relationship between the stability of the pupils and the diameter of the pupils were more stable at the ultradian frequencies than at any other spectral frequency. The Rayleigh Test, introduced by Batschelet (1965) to determine phase consistency was utilized to test the significance of the average phase angle differences between PM and PD, PD and SSS and PM and SSS at the ultradian frequency of 14.4 cycles/day. Fig. 7 displays the cross spectral phase angles among these variables for each subject. Significant relationships were obtained only between PD and PM (p < 0,01). The mean angular differences at 14.4. cycles/day between PD and SSS and PM and SSS were 172 ° + 60 ° and 12 ° -+ 67 °, respectively, but they
P. Lavie / Rhythms in pupillometric activity
58 0°
oo
PO.c P M * p-
0°
PD,~SSS
PM,tSSS
.01
Fig. 7. Cross-spectral phase angle differences, calculated at 14.4 cycles/day between PD and PM, PD and SSS, and PM and SSS. The arrows indicate the angular differences calculated according to Batschelet (1965), rs are the length of the mean vectors. Note that, except for one, all phase angle differences between PD and PM were within the range of 225°-135 ° and between PD and SSS, except for three, all phase angles were between 225 ° and 135 °, while between PM and SSS, except for three, all phase angle differences were between 90 ° - 3 1 5 °, of which six were within 0 ° - 4 5 ° .
were n o t significant. Since P R was clearly in-phase w i t h PD, its p h a s e r e l a t i o n s h i p s w i t h t h e o t h e r variables were n o t calculated. C o r r e l a t i o n a l analyses c o n f i r m e d t h e cross-spectral p h a s e angle analyses. P e a r s o n p r o d u c t m o m e n t c o r r e l a t i o n c o e f f i c i e n t s b e t w e e n P D a n d PM, P D a n d SSS, a n d
Table 2 Pearson product moment correlation coefficients between PD/PM, PD/SSS and PM/SSS Subject
PD/PM
PD/SSS
1 2 3 4 5 6a 6b 7a 7b 8a 8b
-0.51 -0.63 -0.74 -0.69 0.18 -0.78 -0.72 -0.37 -0.49 -0.31 -0.41
-0.57 c) -0.19 -0.15 0.11 0.08 0.I0 0.00 0.21 -0.48 b) -0.21 -0.17
Mean
-0.53
a) p < 0.05.
b) p < 0.01. c) p < 0.001.
b) c) e) c) c) c) a) b) a)
-0.14
PM/SSS 0.2 0.32 0.12 -0.39 0.19 -0.14 -0.17 0.25 0.48 b) 0.20 -0.13 0.09
1". Lavie / Rhythms in pupillometric activity
59
PM and SSS, calculated after linear trends were removed from all time series, are presented in table 2. Ten of the 11 correlations between PD and PM were negative, nine significant with at least p < 0.05. Six of the 11 correlations between PD and SSS were negative but only two significant; on the other hand seven of the 11 correlations between PM and SSS were positive, one significant at p < 0.01. Since three subjects were tested twice, the day-to-day variability of the ultradian rhythmicities in PM and PD could be assessed. One subject demonstrated ultradian rhythms in PM on both days, but in PD on the first day only; a second demonstrated ultradian rhtyhms in PM and PD on the first day only and a third subject did not demonstrate ultradian rhythms in PM but demonstrated such rhythmicity in PD on the first day. 4. Discussion Present results demonstrate the presence of ultradian rhythms in pupillary activity that were most prominent in the range of pupillary motility and less clear in pupillary diameter and in the magnitude of pupillary reactivity to light. As was exemplified in figs. 3 and 4, ultradian rhythms in pupillary diameter were masked by linear and quadratic trends, which might reflect circadian rhythmicity in these variables. Circadian rhythms in these variables were demonstrated by Doring and Schaefers (1950) and Tiedt (1963), previously. There is a second explanation for the masking of ultradian rhythmicities in pupillary diameter and light reflex. Lowenstein and Lowenfeld (1952a, b) reported that though pupillary size is small and pupillary light reflex declines from response to response in tired subjects, upon arousal by brief emotional, or sensory stimuli, the pupils immediately dilate and normal light reflex reappears. We observed this phenomena in several subjects after they were given food, regardless of the time of testing or the phase of the ultradian rhythms in pupillary stability. Such events had much less effect on pupillary stability. Nevertheless, the close similarity in periodicity between the ultradian rhythms in diameter and stability, as revealed by least square spectrum, and the significant out-of-phase relationship between the two variables at the ultradian frequencies, which was more stable than at any other frequency, suggest that both ultradian rhythms reflect the activity of a common oscillator. According to Lowenstein and Lowenfeld (1964) spontaneous pupillary oscillations are of central origin, and their amplitude and shape depends on the dynamic equilibrium of the sympatheticparasympathetic tonus. The existence of rhythmic variations in the autonomic balance closely agree with Kelitman's proposed BRAC in alertness. Rhythmic variations in perceptual processes, vigilance and motor performance, daydreams and electroencephalographic activities, can all be seen as linked to these underlying variations in autonomic nervous system activity. It cannot be determined at this point if the neural oscillator that regulates the rhythms ha arousal is actually located at neural substrate that control autonomic activity, or is located elsewhere in the
60
P. Lavie /Rhythms in pupillometric activity
central nervous system and modulates autonomic activity as part of a more general cortical and subcortical activation. Undoubtedly the generating mechanism is rather'noisy'. Ultradian rhythms were not seen in all testing periods, and sometimes their amplitude greatly varied during the course of a test period. Similar non-stationarities were observed with respect to the rhythms in the perception of the spiral afteraffect (Lavie, 1977), and by Orr, Hoffman and Hegge (1976) in ultradian rhythms in vigilance performance. One may speculate that this instability might be due to variables such as circadian sleep-wake cycles, overall motivational and arousal levels and personality characteristics. The present results do not add new information regarding the relationship between the sleep REM-NONREM rhythms and the BRAC. Kleitman's proposal that the BRAC and the sleep rhythms are fragments of an ongoing 24 hr rhythm has been supported by three types of evidence so far: (1) the similar periodicity of the waking and the REM-NONREM rhythms, (2) the fact that both reflect rhythmic variations in cortical arousal and autonomic activity, and (3) the apparent phase relationship between some of the waking rhythms and the sleep REMNONREM rhythms (Lavie and Sutter, 1973). However, the facts that humans retiring at habitual bedtime reach the first REM period after approximately 90 rain of NONREM sleep, and that humans deprived of REM sleep compensate for the loss of REM when sleep is uninterrupted in spite of the existence of a waking counterpart to the REM-NONREM cycle, suggest that the relationships between the sleep and waking rhythms are by no means simple. Furthermore, recent results have suggested the existence of more than one 90 min oscillator. Nocturnal ultradian rhythms in gastric motility were found unrelated to the sleep REM-NONREM rhythms (Lavie, Kripke, Hiatt and Morrison, 1978), and similar grastric motility rhythms in awake humans were unrelated to ultradian rhythms in daydreams and electronencaphalographic activity (Hiatt, Kripke and Lavie, 1975). Similarly 90 rain ultradian rhythms in urine flow were found unrelated to rhythms in motor performance (Lavie and Gopher, paper submitted for publication). Thus, it can be concluded that the proposed BRAC is only one out of a population of ultradian rhythms, all sharing, for as yet unknown reason, the same dominant periodicity approximating 90 min. In light of the previously established association between pupillary movements and subjective feelings of fatigue (Yoss, Mayer and Hollenhorst, 1970; Lowenstein, Feinberg and Lowenfeld, 1963), the failure to demonstrate significant phase relarelationship between SSS and PM was unexpected. Lack of correlation between PM and SSS could be due to the insensitivity of the SSS to detect subtle changes in subject's arousal. This explanation is supported by the fact that subjects exhibited few changes in sleepiness scores, and in some instances reported the same sleeepiness score for 3 - 4 hr.
P. Lavie / Rhythms in pupillometric activity
61
Acknowledgements This study was done while P. Lavie was a guest scientist at the Max Planck Institute o f Psychiatry, Munich, W. Germany. This study would not have been possible without the constant help of Dr. H. Schulz. Ms. R. Benz provided excellent technical assistance.
References Batschelet, E. (1965). Statistical Methods for the Analysis of Problems in Animal Orientation and Certain Biological Rhythms. American Institute of Biological Sciences: Washington, DC. Doting, G.K. and Schaefers, E. (1950). Uber die Tagesrhythmik der pupillenweite beim Menschen. Pfluegers Archly; European Journal of Physiology, 252, 537-541. Friedman, S and Fisher, D. (1967). On the presence of a rhythmic diurnal, oral instinctual drive cycle in man. Journal of the American Psychoanalytic Association, 15, 317- 343. Haitt, J.F. and Kripke, D.F. (1975). Ultradian rhythms in waking gastric activity. Psychosomatic Medicine, 37,320-325. Hiatt, J.F., Kripke, D.F. and Lavie, P. (1975). Relationships among psychophysiological ultradian rhythms. Chronobiologia Suppl., 1, 43. Hoddes, E., Zarcone, U., Smythe, H., Phillips, R and Dement, W.C. (1973). Quantification of sleepiness: A new approach. Psychophysiology, 10,431-436. Jenkins, G.M. and Watts, D.G. (1968). Spectral Analysis and its Applications. Holden Day: New York. Kleitman, N. (1961). The nature of dreaming. In: Wolstenholm, G.E.W. and O'Connor, M. (Eds.). Ciba Foundation Symposium on the Nature of Sleep. Churchill: London. Kripke, D.F. (1972). An ultradian biological rhythm associated with perceptual deprivation and REM sleep. Psychosomatic Medicine, 34, 221-234. Kripke, D.F. and Sonnenschein, D. (1978). A biologic rhythm in waking fantasy. In: Pope, D.S. and Singer, J.L. (Eds.). The Stream of Consciousness. Plenum: New York 321-332. Lavie, P. (1976). Ultradian rhythms in the perception of two apparent motions. Chronobiologia, 3,214-218. Lavie, P. (1977) Nonstationarity in human perceptual ultradian rhythms. Chronobiologia, 4, 38-48. Lavie, P. and Sutter, D. (1973). Differential respondings to the beta movement following awakenings from REM and NONREM sleep. American Journal of Psychology, 88, 595-604. Lavie, P., Lord, J. and Frank, A. (1974). Basic rest-activity cycles in the perception of the spiral aftereffect: A sensitive detector of a basic biologic rhythm. Behavioral Biology, 11, 373-379. Lavie, P., Levy, C.M. and Coolidge, F. (1975). Ultradian rhythms in the perception of the spiral aftereffect. Physiological Psychology, 3,144-146. Lavie, P., Kripke, D.F., Hiatt, J.F. and Morrison, J. (1978). Gastric rhythms during sleep. Behavioral Biology, 23, 526-530. Lavie, P. and Gopher, D. (paper submitted for publication). Lowenstein, O., Feinberg, R. and Lowenfeld, I.E. (1963). Pupillary movements during acute and chronic fatigue: A new test for the objective evaluation of tiredness. Investigative Ophthalmology, 2, 138-157. Lowenstein, O. and Lowenfeld, I.E. (1952a). Disintegration of central autonomic regulation
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during fatigue and its reintegration by psychosensory controlling mechanisms. I. Disintegration: Pupillographic studies. Journal of Nervous and Mental Disease, 115, 1-21. Lowenstein, O. and Lowenfeld, I.E. (1964). The sleep-waking cycle and pupillary activity. during fatigue and its reintegration by psychosensory controlling mechanisms. II. Reintegration: PupiUographic studies. Journal of Nervous and Mental Disease, 115,121-145. Lowenstein, O. and Lowenfeld, I.E. (1964). The sleep-waking cycle and pupiUary activity. Annals of the New York Academy of Sciences, 117, 142-156. Lubin, A., Nute, C., Naitoh, P. and Martin, W.B. (1973). EEG delta activity during human sleep as a damped ultradian rhythm. Psychophysiology, 10(3), 27-35. Orr, W.C., Hoffman, H.J. and Hegge, F.W. (1976). The assessment of time-dependent changes in human performance. Chronobiologia, 3,293-309. Orr, W.C. and Naitoh, P. (1976). The coherence spectrum: An extension of correlation analysis with applications to chronobiology. International Journal of Chronobiology, 3, 171. Tiedt, N. (1963). Die 24-stunden-rhythmik der kinetik des lichtreflexes der menschlichen pupille. Pfluegers Archiv; European Journal of Physiology, 277,458-472. Walter, D.O. (1963). Spectral analysis of neurophysiological relationships from records of limited duration. Experimental Neurology, 8,155-183. Yoss, R.E., Mayer, N.J. and Ogle, N.K. (1969). The pupiUogram and narcolepsy. Neurology, 19, 921-927. Yoss, R.E. Mayer, N.J. and HoUenhorst, R.W. (1970). Pupil size and spontaneous pupillary waves associated with alterness, drowiness and sleep. Neurology, 20, 545-554.
ULTRADIAN RHYTHMS IN
ALERTNESS
49
-
A PUPILLOMETRIC STUDY
PERETZ LAVIE Faculty of Medicine, Technion, Haifa, Israel Accepted for publication 4 June 1979
PupiUary size, pupillary light reflex and pupiUary motility were measured every 15 min, for 10 continuous hours, in eight young adults. Time series constructed from the range of pupillary motility revealed 75 to 125 min rhythms; these were significantly out of phase with rhythms of similar periodicity in pupillary diameter and in the magnitude of the pupillary light reflex. There was no consistent correspondence between Stanford Sleepiness Scores and pupillary activity. It is suggested that the rhythms in pupiUary activity reflect underlying rhythms in CNS arousal that also modulate perceptual, cognitive and electroencephalographic processes, a conclusion which supports Kleitman's BRAC model.
1. Introduction The existence of short term rhythms in alterness during the awake state was first suggested by Kleitman (1961) who viewed these rhythms as part of an ongoing 24 h rhythm which appears in sleep as the REM-NONREM cycle. Kleitman speculated that this Basic Rest-Activity Cycle (BRAC) originated from a primitive sleep and wakefulness rhythm, adjusted to the nutritional needs of the organism. Several studies have provided support for Kleitman's hypothesis by demonstrating rhythms in different indices of alterness or arousal, with periodicities approximating the 90 min periodicity of the sleep REM-NONREM cycles. Such rhythms were shown in perception of visual illusions (Lavie, Lord and Frank, 1974; Lavie, Levy and Coolidge, 1974; Lavie, 1976), vigilance performance (Orr, Hoffman and Hegge, 1976), accuracy of motor performance (Lavie and Gopher, paper submitted for publication), and in daydreams and electroencephalographic activity (Kripke 1972; Kripke and Sonnenschein, 1978). The present study investigated the possible existence of ultradian rhythms in pupillary activity, a well established, sensitive index of alterness (Yoss, Mayer and Ogle, 1969; Yoss, Mayer and Hollenhorst, 1970; Lowenstein, Feinberg and Lowenfeld, 1963). The pupils are large and stable in alert humans and contract when alertness declines. Contraction is associated with reduction in pupillary reactivity to light and with spontaneous pupillary oscillations, consisting of recurrent waves of pupillary constriction and dilation (Lowenstein and Lowenfeld, 1964).
50
P. Lavie /Rhythms in pupillometric activity
Establishment of ultradian rhythms in either pupillary diameter and/or pupillary stability would provide further support for the notion that the fluctuations previously observed in behavioral and physiological processes reflect a common underlying alertness rhythm. 2. Methods and materials Subjects were five men and three women aged 2 1 - 2 5 years. Testing began at 07:30-09:30 am and continued for 10 h. Two tests were terminated after 8 h 30 min because of excessive tearing. Three subjects were re-examined one week after the original test, and each test was considered as a separate time series. Through the tests, measurement trials lasting 1 - 2 min were administered every 15 rain. During each trial, the diameter of the left pupil was measured continuously to the nearest 0.1 mm using an infrared pupillograph (Whittaker Corp., CCTV Camera model LLSA-15, Eye view monitor, model 19845), and data were recorded on a plotter at a paper speed of 2.5 cm/s. To measure pupillary light reflex, the subject was given three 100 msec stroboscopic flashes at intervals of 8 - 2 0 sec from a 15 W lamp (Knott Elektronik) located 50 cm from the eye. The length of the interflash interval was varied to avoid eye movement and blinking artifacts within the interval. Subject fixated on a point above the lamp and 50 cm from the eye. Before each session the subject filled out the Stanford Sleepiness Scale (SSS) (Hoddes, Zarcone, Smyth, Phillips and Dement, 1973). Testing was conducted in an air conditioned soudproof chamber, lighted between trials to a level of 3 0 - 4 0 lx. During trials, illumination around the subject's eye was maintained at below 5 Ix. Subjects and experimenter communicated via intercom. During the test, the subject was perm!tted to read or write, to order soft drinks and sandwiches at will, and to leave the chamber for short trips to a nearby toilet. After such absences, they were reaccustomed to lighting conditions in the chamber pior to resumption of testing. 2.1. Pupillary measurements
Data obtained at each trial were analyzed for three variables: pupillary diameter (PD), pupillary movement (PM) and pupillary light reflex (PR). Pupillary diameter (PD) was averaged for 500 msec before the three stroboscopic flashes. To measure spontaneous oscillations (PM) eight consecutive 500 msec segments, free of eye movements and blink artifacts, were measured following each flash. In each segment, the absolute range of pupillary movement (in mm) was determined, and the average range was calculated for all 24 segments. The pupillary light reflex (PR) was taken a s the mean amplitude of the three pupillary reflex responses. These were measured as the difference between the baseline pupillary diameter during the 500 msec before the flash and the peak of the light reflex.
P. Lavie / Rhythms in pupillometric activity
51
2.2. Statistical analysis
Four 36-point time series were constructed for each subject from PD, PM, PR and SSS. The first hour was considered as adaptation to the experiment and was not included in the final analysis. The mean was subtracted from each time series and linear trends were removed. Then, 10 lag autocorrelation functions were calculated and spectra estimates computed for 10 spectral frequencies (Jenkins and Watts, 1968). Spectra were individually hanned, normalized to yield spectral density functions and separately averaged for each variable. Since we were particularly interested in the temporal structure of the covariations in pupillary diameter and pupillary stability, cross-correlation functions, hanned cross-spectra, coherence spectra and cross-spectral phase-angle differences, were calculated at each spectral frequency, between PM and PD. A coherence spectrum varies between 0 and 1 is analogous to a linear correlation coefficient between two variables. Coherence close to 1, at a particular frequency, at a phase angle close to 0 °, is analogous to high positive correlation between the two time series, at that particular frequency. The same at phase angle of 180 ° means a high negative correlation between the time series (Orr and Naitoh, 1976;Walter, 1963). Pearson product moment (PPM) correlations between PD and PM and between each of these variables and SSS were calculated as well. Since orthogonal variance spectrum gives rather crude estimate of the dominant periodicity in the data, the least square spectrum technique, which gives a finer estimation of the dominant periodicity, was also utilized (Lubin, Nute, Naitoh and Martin, 1973).
3. Results Samples of pupillary records of one subject taken at different times, are presented in fig. 1, with the corresponding PM scores. In the upper three traces pupillary light reflex was followed by persistent pupillary oscillations, which resulted in high PM scores: the uppermost trace is an example of pupillary hippus which is rhythmic and rapid dilation and contraction of the pupils. In the other two traces the pupils gradually resumed a stable diameter without apparent oscillations; consequently PM scores were low. It should be emphasized that periods of intense pupillary oscillations occurred spontaneously before the photic stimulation, and that photic stimulation did not induce pupillary oscillations when the pupils were stable. The frequency of the oscillations greatly varied within and between subjects for no apparent reason, but no attempt was made in this work to analyze this aspect of pupillary motility. When the average range of oscillations was plotted against time, stationary ultradian rhythms emerged (fig. 2). Variance spectra revealed that eight of the 11 PM time series (72%) peaked at either 14.4 cycles/day (n = 5), corresponding to periodicity of 100 min/cycle, or at 19.2 cycles/day (n = 3), corresponding to
52
P. Lavie / Rhythms in pupillometric activity
4.0L
~
PMI40.2
5.5 6.0 4.0-
PM1=7.75
4.5 5.0 5.5 6.0
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7.5H .
8.0
_
P M , = o . T s
I
I
i
I
I
I --'-""W
I
2
3
4
5
6
7
SECONDS Fig. 1. Samples of pupillary records o f one subject, following one stroboscopic flash (indicated b y an arrow) t a k e n at different times, w i t h the c o r r e s p o n d i n g PM scores.
periodicity of approximately 75 min/cycle (fig. 3). Average spectra peaked at 14.4 cycles/day. To test the possibility that the occurrence of five of the 11 spectral peaks at one out of 10 frequencies (14.4 cycles/day) was a chance event, nine 36-point random data time series were generated within the range of the raw data of each PM time series, at simulated 15 min intervals. Then, the 99 simulated time series (nine per experimental time series) were subjected to spectral analysis in a way similar to the analysis of the original data. The average spectra for the simulated time series was fiat, and only 12% of the time series had a spectral peak at 14.4 cycles/day as compared to 45% of the PM time series. Furthermore, at 14.4 cycles/
P. Lavie /Rhythms in pupillometric activity
53 S-WA (14.5 ~ )
~J ¢ ~ o
S - N I l (16.5 ~) _
a. E
_
3 Z
<
S-ST1 ( 21 ~4)
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~ K , . . ( 2 4 s ~ ) ' 0800
'o 09o
. Oo
19oo 20oo 1~oo 15oo I~°° i'oo i',oo 1'oo i~,oo ,'oo 18oo ' ' ' TIME
Fig. 2. Time series constructed from the raw data of PM scores for five subjects. The percentages of variance at 14.4 cycles/day calculated by orthogonal variance spectra are also presented, 10% are expected in random data.
day the average spectra intensity of the PM data was significantly higher than that of the simulated time series (t = 3.23, df = 108, p < 0.001, one-tailed). In contrast to pupillary motility records, data of pupiUary diameter and light reflex were non-stationary with marked linear and quadratic trends. Figs. 4 and 5 exemplified these trends in pupiUary diameter. Since identical trends were seen in the amplitude of the light reflex they are not presented. Consequently only five of the PD and PR time series peaked at ultradian frequencies, three at 14.4 cycles/day and two at 19.2 cycles/day. The other six time series peaked at frequencies slower than 14.4 cycles/day, which might suggest the existence of circadian rhythms in the data. However, since only 10 hr of data were available, circadian rhythms could not be derived. Sleepiness scores generally exhibited less variability than did the other measures, sometimes remaining unchanged for 3 - 4 hr despite obvious fluctuations in pupillary diameter or motility. For this reason no attempt was made to search for rhythmicity in SSS. Least square spectral analysis performed on the PM and PD records confirmed the results of the orthogonal variance spectrum and provided accurate estimation of
P. Lavie / Rhythms in pupillometric activity
54
PUPILLARY DIAMETER PUPILLARY AeOTILITY --day1 aay 2
I2
Jl
Q'.
<
E
J
/ 18 1 S
FREQUENCY (in cycles/day) Fig. 3. Ten frequency orthogonal variance spectra for each subject for PM and PD. Spectral peaks are indicated by heavy dots.
P. Lavie /Rhythms in pupillometric activity
55
a.
7.~ E 6.| E 6.6 '~' 6.4 I,-,-
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1 10°°
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I 12 ° 0
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I 14oo
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I 19° o
TIME
Fig. 4. PupiUary diameter (PD) and pupiUary motility (PM) indices of one subject. Although increases in PM coincided with decreases in PD, the linear increase in PD suggests circadian effects on pupillary diameter. the periodicities in the two variables. Table 1 presents the 'primary periods' (the period which gave the highest squared correlation, r 2, of the associated sinusoid with the PD and PM time series) and the corresponding squared correlations. On the average, pure sinusoids accounted for 17% of the total variance in the PD time series and 19% of the PM variance. The average periods for PM and PD were close, 109.4-+27.2 min and 116-+25.5 min, respectively. Approximately identical periods in PM and PD were obtained for six of the 11 time series. In three other cases secondary period in one of the variables was close to the primary period in the other variable. For instance, subject 4 who had primary periods of 141 min for PD and 85 min for PM, demonstrated also a secondary period of 81 min for PD. Fig. 6 presentes the average cross spectral phase angle differences (-+SD) between
P. Lavie /Rhythms in pupillometric activity
56 5.4
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Fig. 5. Time series constructed from PD data of one subject; hourly means are indicated by the heavy line. Note that the obvious approximately 1.5 hr ultradian variations are superimposed on prominent quadratic trend.
Table 1 Primary periodicities and corresponding r 2 values for PD and PM time series Subject
Pupillary diameter (PD)
PupiUary motility (PM)
Period in mins
r2
Period in mins
r2
1 2 3 4 5 6a 6b 7a 7b 8a 8b
89 134
0.20 0.12
141 156 92 92 142 110 88 116
0.15 0.19 0.20 0.12 0.11 0.23 0.23 0.13
87 126 80 85 99 113 160 143 112 75 124
0.19 0.19 0.23 0.16 0.25 0.13 0.16 0.15 0.13 0.28 0.19
Mean sd
116.0 25.6
0.17 0.04
109.4 27.2
0.19 0.04
P. Lavie / Rhythms in pupillometric activity
57
\\'q
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uJ
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,5
o u
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o
,.,
.
,4., ,+.2 ,4. ,,+.+ 3~., 38.+ ,d.+
(in cycles/day) Fig. 6. Average cross spectra phase angle difference (-+SD) and coherence spectra at each spectral frequency between PD and PM. FREQUENCY
PD and PM, calculated according to Batschelet (1965), and the corresponding average coherence values, at each spectral frequency. As can be se.en from the figure, though pupillary diameter and stability measures were generally out of phase at all frequencies, the average phase angle differences were closest to 180 ° , and standard deviations were smallest, at the ultradian frequencies of 14.4. cycles/day and 19.2 cycles/day. Furthermore, coherence values were largest at these frequencies. Thus, it can be concluded that the out-of-phase relationship between the stability of the pupils and the diameter of the pupils were more stable at the ultradian frequencies than at any other spectral frequency. The Rayleigh Test, introduced by Batschelet (1965) to determine phase consistency was utilized to test the significance of the average phase angle differences between PM and PD, PD and SSS and PM and SSS at the ultradian frequency of 14.4 cycles/day. Fig. 7 displays the cross spectral phase angles among these variables for each subject. Significant relationships were obtained only between PD and PM (p < 0,01). The mean angular differences at 14.4. cycles/day between PD and SSS and PM and SSS were 172 ° + 60 ° and 12 ° -+ 67 °, respectively, but they
P. Lavie / Rhythms in pupillometric activity
58 0°
oo
PO.c P M * p-
0°
PD,~SSS
PM,tSSS
.01
Fig. 7. Cross-spectral phase angle differences, calculated at 14.4 cycles/day between PD and PM, PD and SSS, and PM and SSS. The arrows indicate the angular differences calculated according to Batschelet (1965), rs are the length of the mean vectors. Note that, except for one, all phase angle differences between PD and PM were within the range of 225°-135 ° and between PD and SSS, except for three, all phase angles were between 225 ° and 135 °, while between PM and SSS, except for three, all phase angle differences were between 90 ° - 3 1 5 °, of which six were within 0 ° - 4 5 ° .
were n o t significant. Since P R was clearly in-phase w i t h PD, its p h a s e r e l a t i o n s h i p s w i t h t h e o t h e r variables were n o t calculated. C o r r e l a t i o n a l analyses c o n f i r m e d t h e cross-spectral p h a s e angle analyses. P e a r s o n p r o d u c t m o m e n t c o r r e l a t i o n c o e f f i c i e n t s b e t w e e n P D a n d PM, P D a n d SSS, a n d
Table 2 Pearson product moment correlation coefficients between PD/PM, PD/SSS and PM/SSS Subject
PD/PM
PD/SSS
1 2 3 4 5 6a 6b 7a 7b 8a 8b
-0.51 -0.63 -0.74 -0.69 0.18 -0.78 -0.72 -0.37 -0.49 -0.31 -0.41
-0.57 c) -0.19 -0.15 0.11 0.08 0.I0 0.00 0.21 -0.48 b) -0.21 -0.17
Mean
-0.53
a) p < 0.05.
b) p < 0.01. c) p < 0.001.
b) c) e) c) c) c) a) b) a)
-0.14
PM/SSS 0.2 0.32 0.12 -0.39 0.19 -0.14 -0.17 0.25 0.48 b) 0.20 -0.13 0.09
1". Lavie / Rhythms in pupillometric activity
59
PM and SSS, calculated after linear trends were removed from all time series, are presented in table 2. Ten of the 11 correlations between PD and PM were negative, nine significant with at least p < 0.05. Six of the 11 correlations between PD and SSS were negative but only two significant; on the other hand seven of the 11 correlations between PM and SSS were positive, one significant at p < 0.01. Since three subjects were tested twice, the day-to-day variability of the ultradian rhythmicities in PM and PD could be assessed. One subject demonstrated ultradian rhythms in PM on both days, but in PD on the first day only; a second demonstrated ultradian rhtyhms in PM and PD on the first day only and a third subject did not demonstrate ultradian rhythms in PM but demonstrated such rhythmicity in PD on the first day. 4. Discussion Present results demonstrate the presence of ultradian rhythms in pupillary activity that were most prominent in the range of pupillary motility and less clear in pupillary diameter and in the magnitude of pupillary reactivity to light. As was exemplified in figs. 3 and 4, ultradian rhythms in pupillary diameter were masked by linear and quadratic trends, which might reflect circadian rhythmicity in these variables. Circadian rhythms in these variables were demonstrated by Doring and Schaefers (1950) and Tiedt (1963), previously. There is a second explanation for the masking of ultradian rhythmicities in pupillary diameter and light reflex. Lowenstein and Lowenfeld (1952a, b) reported that though pupillary size is small and pupillary light reflex declines from response to response in tired subjects, upon arousal by brief emotional, or sensory stimuli, the pupils immediately dilate and normal light reflex reappears. We observed this phenomena in several subjects after they were given food, regardless of the time of testing or the phase of the ultradian rhythms in pupillary stability. Such events had much less effect on pupillary stability. Nevertheless, the close similarity in periodicity between the ultradian rhythms in diameter and stability, as revealed by least square spectrum, and the significant out-of-phase relationship between the two variables at the ultradian frequencies, which was more stable than at any other frequency, suggest that both ultradian rhythms reflect the activity of a common oscillator. According to Lowenstein and Lowenfeld (1964) spontaneous pupillary oscillations are of central origin, and their amplitude and shape depends on the dynamic equilibrium of the sympatheticparasympathetic tonus. The existence of rhythmic variations in the autonomic balance closely agree with Kelitman's proposed BRAC in alertness. Rhythmic variations in perceptual processes, vigilance and motor performance, daydreams and electroencephalographic activities, can all be seen as linked to these underlying variations in autonomic nervous system activity. It cannot be determined at this point if the neural oscillator that regulates the rhythms ha arousal is actually located at neural substrate that control autonomic activity, or is located elsewhere in the
60
P. Lavie /Rhythms in pupillometric activity
central nervous system and modulates autonomic activity as part of a more general cortical and subcortical activation. Undoubtedly the generating mechanism is rather'noisy'. Ultradian rhythms were not seen in all testing periods, and sometimes their amplitude greatly varied during the course of a test period. Similar non-stationarities were observed with respect to the rhythms in the perception of the spiral afteraffect (Lavie, 1977), and by Orr, Hoffman and Hegge (1976) in ultradian rhythms in vigilance performance. One may speculate that this instability might be due to variables such as circadian sleep-wake cycles, overall motivational and arousal levels and personality characteristics. The present results do not add new information regarding the relationship between the sleep REM-NONREM rhythms and the BRAC. Kleitman's proposal that the BRAC and the sleep rhythms are fragments of an ongoing 24 hr rhythm has been supported by three types of evidence so far: (1) the similar periodicity of the waking and the REM-NONREM rhythms, (2) the fact that both reflect rhythmic variations in cortical arousal and autonomic activity, and (3) the apparent phase relationship between some of the waking rhythms and the sleep REMNONREM rhythms (Lavie and Sutter, 1973). However, the facts that humans retiring at habitual bedtime reach the first REM period after approximately 90 rain of NONREM sleep, and that humans deprived of REM sleep compensate for the loss of REM when sleep is uninterrupted in spite of the existence of a waking counterpart to the REM-NONREM cycle, suggest that the relationships between the sleep and waking rhythms are by no means simple. Furthermore, recent results have suggested the existence of more than one 90 min oscillator. Nocturnal ultradian rhythms in gastric motility were found unrelated to the sleep REM-NONREM rhythms (Lavie, Kripke, Hiatt and Morrison, 1978), and similar grastric motility rhythms in awake humans were unrelated to ultradian rhythms in daydreams and electronencaphalographic activity (Hiatt, Kripke and Lavie, 1975). Similarly 90 rain ultradian rhythms in urine flow were found unrelated to rhythms in motor performance (Lavie and Gopher, paper submitted for publication). Thus, it can be concluded that the proposed BRAC is only one out of a population of ultradian rhythms, all sharing, for as yet unknown reason, the same dominant periodicity approximating 90 min. In light of the previously established association between pupillary movements and subjective feelings of fatigue (Yoss, Mayer and Hollenhorst, 1970; Lowenstein, Feinberg and Lowenfeld, 1963), the failure to demonstrate significant phase relarelationship between SSS and PM was unexpected. Lack of correlation between PM and SSS could be due to the insensitivity of the SSS to detect subtle changes in subject's arousal. This explanation is supported by the fact that subjects exhibited few changes in sleepiness scores, and in some instances reported the same sleeepiness score for 3 - 4 hr.
P. Lavie / Rhythms in pupillometric activity
61
Acknowledgements This study was done while P. Lavie was a guest scientist at the Max Planck Institute o f Psychiatry, Munich, W. Germany. This study would not have been possible without the constant help of Dr. H. Schulz. Ms. R. Benz provided excellent technical assistance.
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during fatigue and its reintegration by psychosensory controlling mechanisms. I. Disintegration: Pupillographic studies. Journal of Nervous and Mental Disease, 115, 1-21. Lowenstein, O. and Lowenfeld, I.E. (1964). The sleep-waking cycle and pupillary activity. during fatigue and its reintegration by psychosensory controlling mechanisms. II. Reintegration: PupiUographic studies. Journal of Nervous and Mental Disease, 115,121-145. Lowenstein, O. and Lowenfeld, I.E. (1964). The sleep-waking cycle and pupiUary activity. Annals of the New York Academy of Sciences, 117, 142-156. Lubin, A., Nute, C., Naitoh, P. and Martin, W.B. (1973). EEG delta activity during human sleep as a damped ultradian rhythm. Psychophysiology, 10(3), 27-35. Orr, W.C., Hoffman, H.J. and Hegge, F.W. (1976). The assessment of time-dependent changes in human performance. Chronobiologia, 3,293-309. Orr, W.C. and Naitoh, P. (1976). The coherence spectrum: An extension of correlation analysis with applications to chronobiology. International Journal of Chronobiology, 3, 171. Tiedt, N. (1963). Die 24-stunden-rhythmik der kinetik des lichtreflexes der menschlichen pupille. Pfluegers Archiv; European Journal of Physiology, 277,458-472. Walter, D.O. (1963). Spectral analysis of neurophysiological relationships from records of limited duration. Experimental Neurology, 8,155-183. Yoss, R.E., Mayer, N.J. and Ogle, N.K. (1969). The pupiUogram and narcolepsy. Neurology, 19, 921-927. Yoss, R.E. Mayer, N.J. and HoUenhorst, R.W. (1970). Pupil size and spontaneous pupillary waves associated with alterness, drowiness and sleep. Neurology, 20, 545-554.