Intracranial high-γ connectivity distinguishes wakefulness from sleep.
Ezequiel Mikulan, Eugenia Hesse, Lucas Sedeño, Tristan A Bekinschtein, Mariano Sigman, María del Carmen Garcia, Walter Silva, Carlos Ciraolo, Adolfo M García, Agustin Ibanez
Neuroimage April 1, 2018 DOI: 10.1016/j.neuroimage.2017.12.015 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 3 |
| Population | Three subjects with surgically implanted electrodes |
| Key findings | High-gamma connectivity (90-120 Hz) and related graph-theory properties were higher during wakefulness than during non-REM sleep and discriminated between conditions better than other frequency bands. |
Abstract
Neural synchrony in the γ-band is considered a fundamental process in cortical computation and communication and it has also been proposed as a crucial correlate of consciousness. However, the latter claim remains inconclusive, mainly due to methodological limitations, such as the spectral constraints of scalp-level electroencephalographic recordings or volume-conduction confounds. Here, we circumvented these caveats by comparing γ-band connectivity between two global states of consciousness via intracranial electroencephalography (iEEG), which provides the most reliable measurements of high-frequency activity in the human brain. Non-REM Sleep recordings were compared to passive-wakefulness recordings of the same duration in three subjects with surgically implanted electrodes. Signals were analyzed through the weighted Phase Lag Index connectivity measure and relevant graph theory metrics. We found that connectivity in the high-γ range (90-120 Hz), as well as relevant graph theory properties, were higher during wakefulness than during sleep and discriminated between conditions better than any other canonical frequency band. Our results constitute the first report of iEEG differences between wakefulness and sleep in the high-γ range at both local and distant sites, highlighting the utility of this technique in the search for the neural correlates of global states of consciousness.