Spectral Power Time-courses of Human Sleep EEG Reveal a Striking Discontinuity at ∼18 Hz Marking the Division between NREM-specific and Wake/REM-specific Fast Frequency Activity

Spectral power time-courses over the ultradian cycle of the sleep electroencephalogram (EEG) provide a useful window for exploring the temporal correlation between cortical EEG and sub-cortical neuronal activities. Precision in the measurement of these time-courses is thus important, but it is hampered by lacunae in the definition of the frequency band limits that are in the main based on wake EEG conventions. A frequently seen discordance between the shape of the beta power time-course across the ultradian cycle and that reported for the sequential mean firing rate of brainstem-thalamic activating neurons invites a closer examination of these band limits, especially since the sleep EEG literature indicates in several studies an intriguing non-uniformity of time-course comportment across the traditional beta band frequencies. We ascribe this tentatively to the sharp reversal of slope we have seen at ∼18 Hz in our data and that of others. Here, therefore, using data for the first four ultradian cycles from 18 healthy subjects, we apply several criteria based on changes in time-course comportment in order to examine this non-uniformity as we move in 1 Hz bins through the frequency range 14-30 Hz. The results confirm and describe in detail the striking discontinuity of shape at around 18 Hz, with only the upper range (18-30 Hz) displaying a time-course similar to that of the firing-rate changes measured in brainstem activating neurons and acknowledged to engender states of brain activation. Fast frequencies in the lower range (15-18 Hz), on the other hand, are shown to be specific to non-rapid-eye-movement sleep. Splitting the beta band at ∼18 Hz therefore permits a significant improvement in EEG measurement and a more precise correlation with cellular activit

A Unique Pattern of Sleep Structure is Found to be Identical at all Cortical Sites: a Neurobiological Interpretation

There is substantial evidence both at the cellular and at the electroencephalogram (EEG) level to support the view that the brainstem activating systems control the sleep-state (stage) progression over time that constitutes the overall sleep structure as seen at the EEG. We argue here that the brainstem therefore modulates the time-courses of spectral power in the different EEG frequency bands. These show during non-rapid eye movement (NREM) sleep a very particular interrelationship the origin of which has received little attention and for which the neuronal transition probability model for sleep structure has proposed a physiological explanation. We advance the hypothesis that if the brainstem is modulating these time-courses then they should show a marked similarity in shape and timing at all sites. Using data from 10 healthy subjects, we measure the degree of similarity of the time-courses over each of the first four NREM episodes at the frontal, central and parietal sites, for each of the frequency bands beta, sigma and delta, and also the cortically generated slow oscillation. All the cross- correlation coefficients are high and statistically significant, indicating that the shape and timing of these time-courses are practically identical at different sites despite regional differences in their average power levels. These results tend to suggest that two processes may operate concurrently: the brainstem controls the shape and timing of the power time-courses while cortical-thalamic interaction controls their site-dependent average powe

The Neuronal Transition Probability (NTP) Model for the Dynamic Progression of Non-REM Sleep EEG: The Role of the Suprachiasmatic Nucleus

Little attention has gone into linking to its neuronal substrates the dynamic structure of non-rapid-eye-movement (NREM) sleep, defined as the pattern of time-course power in all frequency bands across an entire episode. Using the spectral power time-courses in the sleep electroencephalogram (EEG), we showed in the typical first episode, several moves towards-and-away from deep sleep, each having an identical pattern linking the major frequency bands beta, sigma and delta. The neuronal transition probability model (NTP) – in fitting the data well – successfully explained the pattern as resulting from stochastic transitions of the firing-rates of the thalamically-projecting brainstem-activating neurons, alternating between two steady dynamic-states (towards-and-away from deep sleep) each initiated by a so-far unidentified flip-flop. The aims here are to identify this flip-flop and to demonstrate that the model fits well all NREM episodes, not just the first. Using published data on suprachiasmatic nucleus (SCN) activity we show that the SCN has the information required to provide a threshold-triggered flip-flop for timing the towards-and-away alternations, information provided by sleep-relevant feedback to the SCN. NTP then determines the pattern of spectral power within each dynamic-state. NTP was fitted to individual NREM episodes 1–4, using data from 30 healthy subjects aged 20–30 years, and the quality of fit for each NREM measured. We show that the model fits well all NREM episodes and the best-fit probability-set is found to be effectively the same in fitting all subject data. The significant model-data agreement, the constant probability parameter and the proposed role of the SCN add considerable strength to the model. With it we link for the first time findings at cellular level and detailed time-course data at EEG level, to give a coherent picture of NREM dynamics over the entire night and over hierarchic brain levels all the way from the SCN to the EEG

Spectral power time-course of human sleep EEG reveal a striking discontinuity at ~ 18 Hz marking the division between NREM-specific and Wake/REM-specific fast frequency activity. Cerebral cortex 2005

Spectral power time-courses over the ultradian cycle of the sleep electroencephalogram (EEG) provide a useful window for exploring the temporal correlation between cortical EEG and sub-cortical neuronal activities. Precision in the measurement of these timecourses is thus important, but it is hampered by lacunae in the definition of the frequency band limits that are in the main based on wake EEG conventions. A frequently seen discordance between the shape of the beta power time-course across the ultradian cycle and that reported for the sequential mean firing rate of brainstem--thalamic activating neurons invites a closer examination of these band limits, especially since the sleep EEG literature indicates in several studies an intriguing non-uniformity of time-course comportment across the traditional beta band frequencies. We ascribe this tentatively to the sharp reversal of slope we have seen at~18 Hz in our data and that of others. Here, therefore, using data for the first four ultradian cycles from 18 healthy subjects, we apply several criteria based on changes in time-course comportment in order to examine this non-uniformity as we move in 1 Hz bins through the frequency range 14--30 Hz. The results confirm and describe in detail the striking discontinuity of shape at around 18 Hz, with only the upper range (18--30 Hz) displaying a time-course similar to that of the firing-rate changes measured in brainstem activating neurons and acknowledged to engender states of brain activation. Fast frequencies in the lower range (15--18 Hz), on the other hand, are shown to be specific to non-rapid-eye-movement sleep. Splitting the beta band at~18 Hz therefore permits a significant improvement in EEG measurement and a more precise correlation with cellular activity

Spectral analysis of the sleep onset period in primary insomnia

To compare the EEG power spectra characteristics of the sleep onset period (SOP) in patients with sleep onset insomnia (SOI), sleep maintenance insomnia (SMI) and good sleepers (GS)