Congratulations to Dr. Giridhar Kalamangalam on the publication of “Gradients in signal complexity of sleep-wake intracerebral EEG,” which appears in the March issue of PLOS One.
Abstract
Spatial variation in the morphology of the electroencephalogram (EEG) over the head is classically described. Ultimately, location-dependent variation in EEG must arise from the cytoarchitectural and network structure of the portion of cortex sensed. In previous work, we demonstrated that over the lateral frontal lobe, sample entropy (SE) of intracerebral EEG (iEEG) over a subdural recording contact was predictive of that contact’s connectivity to other contacts. In this work, we used a publicly available repository (the Montreal Neurological Institute Atlas; MNIA) of whole-brain normative iEEG to calculate SE over the entire cortical surface. SE was averaged region-wise and classified by the state of arousal (awake, N2, N3 and REM). SE averages were transformed to a linear scale between zero and unity, mapped to continuous color scale and overlaid on segmented cortical surface models, one for each sleep-wake state. Wake SE followed a rostro-caudal gradient (RCG), with high values anteriorly and a global minimum in the posterior cortex. Superimposed on the RCG were other gradients radiating away from primary somatic sensorimotor, visual and auditory regions to their association areas. All gradients were attenuated in deep (N3) sleep. In REM, the majority of the cortex exhibited wake-like SE, with the prominent exception of primary cortical sensory and motor areas. Normative human intracerebral EEG exhibits rich spatial structure – cortical gradients – in the distribution of SE. SE in the wake state tracks temporal processing hierarchies in cerebral cortex, concordant to the distribution of several other cortical attributes of structure (e.g., cortical thickness, myelin content). Sleep disrupts these gradients, with REM sleep bringing out unusual discordances between primary sensory and their association areas. Our results deepen the interpretation of EEG from conventional descriptors such as Berger bands to a spatial perspective related to cortical biology.