Depression links to unstable resting-state brain dynamics: insights from hidden markov models and functional network variability.

ABSTRACT:

Background

Depression is closely associated with abnormalities in brain function. Traditional static functional connectivity analyses offer limited insight into the temporal variability of brain activity. Recent advances in dynamic analyses enable a deeper understanding of how depression relates to temporal fluctuations in brain activity.

Methods

This study utilized a large resting-state functional magnetic resonance imaging dataset (N = 696) to examine the association between brain dynamics and depression. Two complementary approaches were employed. Hidden Markov modeling (HMM) was used to identify discrete brain states and quantify their temporal switching patterns; temporal variability was computed within and between large-scale functional networks to capture time-

SUBMITTER: Geng L 

PROVIDER: S-EPMC12315643 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature