How the Human Brain Sleeps: Direct Cortical Recordings of Normal Brain Activity
- PMID: 31777112
- DOI: 10.1002/ana.25651
How the Human Brain Sleeps: Direct Cortical Recordings of Normal Brain Activity
Abstract
Objective: Regional variations in oscillatory activity during human sleep remain unknown. Using the unique ability of intracranial electroencephalography to study in situ brain physiology, this study assesses regional variations of electroencephalographic sleep activity and creates the first atlas of human sleep using recordings from the first sleep cycle.
Methods: Intracerebral electroencephalographic recordings with channels displaying physiological activity from nonlesional tissue were selected from 91 patients of 3 tertiary epilepsy centers. Sections during non-rapid eye movement sleep (stages N2 and N3) and rapid eye movement sleep (stage R) were selected from the first sleep cycle for oscillatory and nonoscillatory signal analysis. Results of 1,468 channels were grouped into 38 regions covering all cortical areas.
Results: We found regional differences in the distribution of sleep transients and spectral content during all sleep stages. There was a caudorostral gradient, with more slow frequencies and fewer spindles in temporoparieto-occipital than in frontal cortex. Moreover, deep-seated structures showed spectral peaks differing from the baseline electroencephalogram. The regions with >60% of channels presenting significant rhythmic activity were either mesial or temporal basal structures that contribute minimally to the scalp electroencephalogram. Finally, during deeper sleep stages, electroencephalographic analysis revealed a more homogeneous spatial distribution, with increased coupling between high and low frequencies.
Interpretation: This study provides a better understanding of the regional variability of sleep, and establishes a baseline for human sleep in all cortical regions during the first sleep cycle. Furthermore, the open-access atlas will be a unique resource for research (https://mni-open-ieegatlas.
Research: mcgill.ca). ANN NEUROL 2020;87:289-301.
© 2019 American Neurological Association.
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