Decreased electrocortical temporal complexity distinguishes sleep from wakefulness

Joaquín González, Matias Cavelli, Alejandra Mondino, Claudia Pascovich, Santiago Castro-Zaballa, Pablo Torterolo, Nicolás Rubido

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23 Citations (Scopus)
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Abstract

In most mammals, the sleep-wake cycle is constituted by three behavioral states: wakefulness (W), non-REM (NREM) sleep, and REM sleep. These states are associated with drastic changes in cognitive capacities, mostly determined by the function of the thalamo-cortical system. The intra-cranial electroencephalogram or electocorticogram (ECoG), is an important tool for measuring the changes in the thalamo-cortical activity during W and sleep. In the present study we analyzed broad-band ECoG recordings of the rat by means of a time-series complexity measure that is easy to implement and robust to noise: the Permutation Entropy (PeEn). We found that PeEn is maximal during W and decreases during sleep. These results bring to light the different thalamo-cortical dynamics emerging during sleep-wake states, which are associated with the well-known spectral changes that occur when passing from W to sleep. Moreover, the PeEn analysis allows us to determine behavioral states independently of the electrodes’ cortical location, which points to an underlying global pattern in the signal that differs among the cycle states that is missed by classical methods. Consequently, our data suggest that PeEn analysis of a single EEG channel could allow for cheap, easy, and efficient sleep monitoring.
Original languageEnglish
Article number18457
Number of pages9
JournalScientific Reports
Volume9
DOIs
Publication statusPublished - 5 Dec 2019

Bibliographical note

This study was supported by the “Programa de Desarrollo de Ciencias Básicas”, PEDECIBA; Agencia Nacional de investigación e innovación (ANII), (FCE_1_2017_1_136550) and the “Comisión Sectorial de Investigación Científica” (CSIC) I + D - 2016 - 589 grant from Uruguay. N.R. acknowledges the CSIC group grant “CSIC2018 - FID 13 - Grupo ID 722”.

Keywords

  • sleep
  • wakefulness

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