Generating dynamical neuroimaging spatiotemporal representations (DyNeuSR) using topological data analysis.

ABSTRACT: In this article, we present an open source neuroinformatics platform for exploring, analyzing, and validating distilled graphical representations of high-dimensional neuroimaging data extracted using topological data analysis (TDA). TDA techniques like Mapper have been recently applied to examine the brain's dynamical organization during ongoing cognition without averaging data in space, in time, or across participants at the outset. Such TDA-based approaches mark an important deviation from standard neuroimaging analyses by distilling complex high-dimensional neuroimaging data into simple-yet neurophysiologically valid and behaviorally relevant-representations that can be interactively explored at the single-participant level. To facilitate wider use of such techniques within neuroimaging

SUBMITTER: Geniesse C 

PROVIDER: S-EPMC6663215 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature