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  • Ultradian Rhythms in EEG Literature


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    1. Aeschbach D, Matthews JR, Postolache TT, Jackson MA, Giesen HA, Wehr TA (1999). Two circadian rhythms in the human electroencephalogram during wakefulness. American Journal of Physiology, 277, R1771-9

    2. Meneses Ortega S, Corsi Cabrera M (1990). Ultradian rhythms in the EEG and task performance. Chronobiologia, 17, 183-94.

    3. Hayashi M, Sato K, Hori T (1994). Ultradian rhythms in task performance, self-evaluation, and EEG activity. Perceptual & Motor Skills, 29, 791-800

    4. Lavie P (1989). Ultradian rhythms in arousal--the problem of masking. Chronobiology International, 6, 21-8.

    5. Tsuji Y, Kobayashi T (1988). Short and long ultradian EEG components in daytime arousal. EEG & Clinical Neurophysiology, 70, 110-7.

    Am J Physiol 1999 Dec;277(6 Pt 2):R1771-9

    Two circadian rhythms in the human electroencephalogram during wakefulness.

    Aeschbach D, Matthews JR, Postolache TT, Jackson MA, Giesen HA, Wehr TA

    The influence of the circadian pacemaker and of the duration of time awake on the electroencephalogram (EEG) was investigated in 19 humans during approximately 40 h of sustained wakefulness. Two circadian rhythms in spectral power density were educed. The first rhythm was centered in the theta band (4.25-8.0 Hz) and exhibited a minimum approximately 1 h after the onset of melatonin secretion. The second rhythm was centered in the high-frequency alpha band (10.25-13.0 Hz) and exhibited a minimum close to the body temperature minimum. The latter rhythm showed a close temporal association with the rhythms in subjective alertness, plasma melatonin, and body temperature. In addition, increasing time awake was associated with an increase of power density in the 0.25- to 9.0-Hz and 13.25- to 20. 0-Hz ranges. It is concluded that the waking EEG undergoes changes that can be attributed to circadian and homeostatic (i.e., sleep-wake dependent) processes. The distinct circadian variations of EEG activity in the theta band and in the high-frequency alpha band may represent electrophysiological correlates of different aspects of the circadian rhythm in arousal.


    Percept Mot Skills 1994 Oct;79(2):791-800

    Ultradian rhythms in task performance, self-evaluation, and EEG activity.

    Hayashi M, Sato K, Hori T

    Many studies have shown the existence of cycles of approximately 90 to 100 minutes (corresponding to Kleitman's basic rest-activity cycle) and several hours ('slow ultradian rhythm' cycles). EEG power spectra, mood, performance, and self-evaluation of performance were measured every 15 minutes for 9 hours for 10 male university students. Principal component analysis was applied to extracted ultradian fluctuations in EEG activity, task performance, and the subjective variables. The analysis indicated that two common temporal fluctuations were present, one in the behavioral and subjective variables, and the other in EEG activity. Spectral analysis indicated that the former fluctuated at a rate of 12 cycles per day (corresponding to basic rest-activity cycle), and the latter was comprised of both a slower (6 cycles per day) and a faster (10 to 18 cycles per day) cycle, thereby supporting the multioscillator hypothesis of ultradian rhythm.


    Chronobiologia 1990 Jul-Sep;17(3):183-94

    Ultradian rhythms in the EEG and task performance.

    Meneses Ortega S, Corsi Cabrera M

    The purpose of this work was to investigate the presence of ultradian rhythms in: 1. levels of electroencephalographic activation; 2. interhemispheric correlation and 3. the performance of two cognitive tasks, and the correlation between these variables. Eight volunteers, aged 20 to 30, participated in the experiment. Two sessions were carried out: one from 0800 to 1400 on one day and the other from 1400 to 2000 another day. Samples of EEG activity were taken every 15 min at rest with eyes open in left and right temporal, central, parietal and occipital derivations referred to the ipsilateral earlobe the performance on two tasks, one logico-analytical (left hemisphere functions) and one spatial test (right hemisphere functions) was assessed. As control, body and environmental temperature were recorded. To test for the presence of ultradian rhythms, the data were subjected to a Fourier analysis. Different EEG variables showed rhythmicity throughout the sessions, principally with slow oscillation periods (3 and 6h); ultradian rhythms with 3h periods were also found in body temperature, while task performance showed no significant rhythmic patterns during sessions. Finally, no significant correlations were found between physiological variables evaluated and task performance.


    Chronobiol Int 1989;6(1):21-8

    Ultradian rhythms in arousal--the problem of masking.

    Lavie P

    Studies utilizing widely different experimental techniques provided evidence that there are spontaneous ultradian cycles in arousal during the waking state. These comprised of cyclic fluctuations between increased and decreased sleep propensity with a periodicity of about 1.5 hr. Being of relatively low amplitude, these cycles are vulnerable to masking effects by a variety of experimental conditions. Masking can be exerted by varying the tonic level of arousal, by coexisting slow ultradian components which are particularly prominent during the second half of the day, or by some specific experimental conditions. Furthermore, increased sleepiness was shown to enhance the slow ultradian components and suppress the 1.5-hr cycles in EEG indices of arousal on the one hand, and to emphasize the 1.5-hr cycles in motor activity and reaction time performance on the other hand. Much more attention should be paid to the problem of masking of ultradian cycles in arousal. Recognizing the sources and reasons for masking will advance our knowledge of the characteristics of these cycles and their function.


    Electroencephalogr Clin Neurophysiol 1988 Aug;70(2):110-7

    Short and long ultradian EEG components in daytime arousal.

    Tsuji Y, Kobayashi T

    In order to investigate the spatio-temporal organization of the daytime arousal state, polygraphic recordings were obtained on 9 subjects, during the period from 11.00 a.m. to 19.30 p.m. Multiple sleep latency tests (MSLTs) administered every 20 min were used as an objective index of sleepiness. Long-duration, wide-band EEG was analyzed by principal components analysis (PCA) to extract the features of ultradian rhythmicities. The data matrix for PCA was constructed from the percentage-power values of 16 frequency bands (2-18 Hz). The diurnal rhythm of the arousal EEG was made up of 2 ultradian components with periods of about 100 min and 3-8 h. The shorter component is thought to represent the oscillation of vigilance level between mental 'rest' and 'activity' states in the basic rest-activity cycle (BRAC). The longer component is thought to represent variations in levels of consciousness between 'wakefulness' and 'drowsiness' states. Our interpretation of the data suggests that the shorter component is superimposed upon the longer one, and that the specific arousal state involved in the shorter ultradian rhythmicity changes to another state at around the 'breaking point' in mid-afternoon.

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