PhD Scientific Days 2022

Mental Health Sciences I. (Poster discussion will take place in the Aula during the Coffee Break)

Sleep EEG Spectral Exponents and Maximal Peak Frequencies in Consecutive NREM Periods: Possible Markers for Sleep Regulation

Text of the abstract

Introduction:
Sleep is indispensable for normal human functioning thus the reliable measurement of the processes of sleep regulation is particularly important. However, it is hard to give a definition of “good sleep” as there is a lack of standardisable polysomnography markers.

Aims:
Here we aim to provide potential polysomnography indicators for the two-process model of sleep regulation with the appropriate separation of the rhythmic and aperiodic non-rapid eye movement sleep electroencephalogram activity. We hypothesize that the slope of the Fourier spectrum and the frequency of the largest peak in the spindle frequency range can be feasible indicators for process S and C, respectively.

Methods:
Artefact-free NREM sleep periods of successive cycles in sleep records (N = 251 healthy subjects, 122 females, age range: 4–69 years) were analysed by FFT routine and power spectrum obtained for selected EEG derivations. Furthermore, the log-log power was fitted with a linear, and a peak detection was applied in the 9–18 Hz range. Statistical analysis was based on general linear models.

Results:
The NREM sleep EEG spectral slope significantly flattened in consecutive sleep cycles. The frequency of the largest peak was significantly modulated by age and there was a significant cycle effect in the frontopolar region (U-shaped curve).

Conclusions:
Our results indicate that the spectral slope is a potent and more standardizable marker of the homeostatic process of sleep regulation which supports earlier findings about the associations between the slope and sleep depth. Furthermore, the maximum spectral peak frequencies in the frontopolar region could reflect the circadian modulation of sleep. The latter index could be a useful measure in future studies, potentially substituting complicated protocols like melatonin or core body temperature measurements, with assumed applicability in retrospective investigations.

Funding:
Support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-EGA-25 funding scheme.