Alterations in EEG connectivity in healthy young adults provide an indicator of sleep depth

Abstract

Current sleep analyses have used electroencephalography (EEG) to establish sleep intensity through linear and nonlinear measures. Slow wave activity (SWA) and entropy are the most commonly used markers of sleep depth. The purpose of this study is to evaluate changes in brain EEG connectivity during sleep in healthy subjects and compare them with SWA and entropy. Four different connectivity metrics: coherence (MSC), synchronization likelihood (SL), cross mutual information function (CMIF), and phase locking value (PLV), were computed focusing on their correlation with sleep depth. These measures provide different information and perspectives about functional connectivity. All connectivity measures revealed to have functional changes between the different sleep stages. The averaged CMIF seemed to be a more robust connectivity metric to measure sleep depth (correlations of 0.78 and 0.84 with SWA and entropy, respectively), translating greater linear and nonlinear interdependences between brain regions especially during slow wave sleep. Potential changes of brain connectivity were also assessed throughout the night. Connectivity measures indicated a reduction of functional connectivity in N2 as sleep progresses. The validation of connectivity indexes is necessary because they can reveal the interaction between different brain regions in physiological and pathological conditions and help understand the different functions of deep sleep in humans.

Characterizing pupil dynamics coupling to brain state fluctuation based on lateral hypothalamic activity

“…Besides the frequency-specific coupling features of neural firing in the ACC and LH, the magnitude-squared coherence and phase locking analyses also showed distinct values between LFP-Group 1 and 2, which is similar to previous reports of brain state switches from conscious wakefulness to unconsciousness (e.g. anesthetized or deep sleep state) [45][46][47] . Since previous studies report that phase-amplitude coupling appears stronger in deeper anesthetized or sleep states [26][27][28] ; our work strongly suggests that the trials in LFP-Group 1 are at a lower arousal level than those in LFP-Group 2.…”

Glutamatergic Neurons in the Preoptic Hypothalamus Promote Wakefulness, Destabilize NREM Sleep, Suppress REM Sleep, and Regulate Cortical Dynamics

“…These are electrophysiologic traits of more activated states. Indeed, EEG theta and gamma coherence, directed connectivity and complexity are typically highest during wakefulness (Abasolo et al, 2015;Pal et al, 2016;Brito et al, 2020;Mondino et al, 2020;Pal et al, 2020) and progressively decline as sleep deepens (Abasolo et al, 2015;Pal et al, 2016;Bandt, 2017;Gonzalez et al, 2019;Migliorelli et al, 2019;Gonzalez et al, 2020).…”

“…These are electrophysiologic traits of more activated states. Indeed, EEG theta and γ coherence, directed connectivity, and complexity are typically highest during wakefulness ( Abasolo et al, 2015 ; Pal et al, 2016 , 2020 ; Brito et al, 2020 ; Mondino et al, 2020 ) and progressively decline as sleep deepens ( Abasolo et al, 2015 ; Pal et al, 2016 ; Bandt, 2017 ; Gonzalez et al, 2019 , 2020 ; Migliorelli et al, 2019 ). Together, these EEG changes and the reduction of the spectral power of slow oscillations after CNO injection provide evidence for a “lighter” NREM sleep state.…”

Glutamatergic neurons in the preoptic hypothalamus promote wakefulness, destabilize NREM sleep, suppress REM sleep, and regulate cortical dynamics

“…These are electrophysiologic traits of more activated states. Indeed, EEG theta and gamma coherence, directed connectivity and complexity are typically highest during wakefulness (Abasolo et al, 2015;Pal et al, 2016;Brito et al, 2020;Mondino et al, 2020;Pal et al, 2020) and progressively decline as sleep deepens (Abasolo et al, 2015;Pal et al, 2016;Bandt, 2017;Gonzalez et al, 2019;Migliorelli et al, 2019;Gonzalez et al, 2020).…”