A Neurophysiological Brain Map: Spectral Parameterization of the Human Intracranial Electroencephalogram.

Objective: A library of intracranial electroencephalography (iEEG) from the normal human brain has recently been made publicly available (Frauscher et al., 2018). The library - which we term the Montreal Neurological Institute Atlas (MNIA) - comprises 30 hours of iEEG from over a hundred epilepsy patients. We present a Fourier spectrum-based model of low dimension that summarizes all of MNIA into a neurophysiological 'brain map'. Methods: Normalized amplitude spectra of the MNIA data were modelled as log-normal distributions around individual canonical Berger frequencies. The latter were concatenated to yield the composite spectrum with high accuracy. Key model parameters were color-coded into a visual representation on cortical surface models. Results: Each brain region has its own spectral characteristics that together yield a novel composite intracranial EEG brain map. Conclusions: iEEG from normal brain regions can be accurately modelled with a small number of independent parameters. Our model is based in the canonical Berger bands and naturally suits clinical electroencephalography. Significance: Due to its applicability to iEEG from all sampled regions, the model suggests a certain universality to brain rhythm generation that is independent of precise cortical location. More generally, our results are a novel abstraction of resting cortical dynamics that may help diagnostics in epileptology, in addition to informing structure-function relationships in the field of human brain mapping. (C) 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.