A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder.

ABSTRACT: To reconcile the inconsistency of the association between the resting-state functional connectivity (RSFC) and cognitive performance in healthy and depressed groups due to high variance of both measures, we proposed a Bayesian spatio-temporal model to precisely and accurately estimate the RSFC in depressed and nondepressed participants. This model was employed to estimate spatially-adjusted functional connectivity (saFC) in the extended default mode network (DMN) that was hypothesized to correlate with cognitive performance in both depressed and nondepressed. Multiple linear regression models were used to study the relationship between DMN saFC and cognitive performance scores measured in the following four cognitive domains while adjusting for age, sex, and education. In ROI pairs includi

SUBMITTER: Wang R 

PROVIDER: S-EPMC7369149 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature