Recently, the sleep-wake states have been analysed using novel complexity measures, complementing the classical analysis of EEGs by frequency bands. This new approach consistently shows a decrease in EEG’s complexity during slow-wave sleep, yet it is unclear how cortical oscillations shape these complexity variations. In this work, we analyse how the frequency content of brain signals affects the complexity estimates in freely moving rats. We find that the low-frequency spectrum – including the Delta, Theta, and Sigma frequency bands – drives the complexity changes during the sleep-wake states. This happens because low-frequency oscillations emerge from neuronal population patterns, as we show by recovering the complexity variations during the sleep-wake cycle from micro, meso, and macroscopic recordings. Moreover, we find that the lower frequencies reveal synchronisation patterns across the neocortex, such as a sensory-motor decoupling that happens during REM sleep. Overall, our works shows that EEG’s low frequencies are critical in shaping the sleep-wake states’ complexity across cortical scales.
|Number of pages||11|
|Early online date||6 May 2022|
|Publication status||Published - 1 Jul 2022|
J.G. acknowledges the support of Comisio´n Acade´mica
de Posgrado (CAP), CSIC Iniciacio´n and PEDECIBA. P.
T. and N.R. also acknowledges the support of
- low frequency oscillations
- sleep-wake cycle