Recursive dynamic functional connectivity reveals a characteristic correlation structure in human scalp EEG.

ABSTRACT: Time-varying neurophysiological activity has been classically explored using correlation based sliding window analysis. However, this method employs only lower order statistics to track dynamic functional connectivity of the brain. We introduce recursive dynamic functional connectivity (rdFC) that incorporates higher order statistics to generate a multi-order connectivity pattern by analyzing neurophysiological data at multiple time scales. The technique builds a hierarchical graph between various temporal scales as opposed to traditional approaches that analyze each scale independently. We examined more than a million rdFC patterns obtained from morphologically diverse EEGs of 2378 subjects of varied age and neurological health. Spatiotemporal evaluation of these patterns revealed three d

SUBMITTER: Panwar S 

PROVIDER: S-EPMC7854737 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature