Impact of sample size and regression of tissue-specific signals on effective connectivity within the core default mode network.

ABSTRACT: Interactions within brain networks are inherently directional, which are inaccessible to classical functional connectivity estimates from resting-state functional magnetic resonance imaging (fMRI) but can be detected using spectral dynamic causal modeling (DCM). The sample size and unavoidable presence of nuisance signals during fMRI measurement are the two important factors influencing the stability of group estimates of connectivity parameters. However, most recent studies exploring effective connectivity (EC) have been conducted with small sample sizes and minimally pre-processed datasets. We explore the impact of these two factors by analyzing clean resting-state fMRI data from 330 unrelated subjects from the Human Connectome Project database. We demonstrate that both the stability of

SUBMITTER: Silchenko AN 

PROVIDER: S-EPMC10619387 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature