Validating dynamicity in resting state fMRI with activation-informed temporal segmentation.

ABSTRACT: Confirming the presence (or absence) of dynamic functional connectivity (dFC) states during rest is an important open question in the field of cognitive neuroscience. The prevailing dFC framework aims to identify dynamics directly from connectivity estimates with a sliding window approach, however this method suffers from several drawbacks including sensitivity to window size and poor test-retest reliability. We hypothesize that time-varying changes in functional connectivity are mirrored by significant temporal changes in functional activation, and that this coupling can be leveraged to study dFC without the need for a predefined sliding window. Here, we introduce a data-driven dFC framework, which involves informed segmentation of fMRI time series at candidate FC state transition points

SUBMITTER: Duda M 

PROVIDER: S-EPMC8559473 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature