Subcortical electrophysiological activity is detectable with high-density EEG source imaging

Subcortical neuronal activity is highly relevant for mediating communication in large-scale brain networks. While electroencephalographic (EEG) recordings provide appropriate temporal resolution and coverage to study whole brain dynamics, the feasibility to detect subcortical signals is a matter of debate. Here, we investigate if scalp EEG can detect and correctly localize signals recorded with intracranial electrodes placed in the centromedial thalamus, and in the nucleus accumbens. Externalization of deep brain stimulation (DBS) electrodes, placed in these regions, provides the unique opportunity to record subcortical activity simultaneously with high-density (256 channel) scalp EEG. In three patients during rest with eyes closed, we found significant correlation between alpha envelopes derived from intracranial and EEG source reconstructed signals. Highest correlation was found for source signals in close proximity to the actual recording sites, given by the DBS electrode locations. Therefore, we present direct evidence that scalp EEG indeed can sense subcortical signals.

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Policy information about availability of computer code Data collection Electrical Geodesics Inc (Philips Healthcare) recording system for scalp EEG; Medtronic for intracranial electrodes Data analysis Cartool 3.7, MATLAB R2018a, freesurfer 6.0.0, FSL 5.0, MRIcron 12 For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers upon request. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

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Sample size N=4; Externalization of deep brain stimulation (DBS) intracranial electrodes provides the unique opportunity to record subcortical activity simultaneously with high-density (256 channel) scalp EEG.
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nature research | reporting summary
April 2018

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