On the variability of dynamic functional connectivity assessment methods.

ABSTRACT:

Background

Dynamic functional connectivity (dFC) has become an important measure for understanding brain function and as a potential biomarker. However, various methodologies have been developed for assessing dFC, and it is unclear how the choice of method affects the results. In this work, we aimed to study the results variability of commonly used dFC methods.

Methods

We implemented 7 dFC assessment methods in Python and used them to analyze the functional magnetic resonance imaging data of 395 subjects from the Human Connectome Project. We measured the similarity of dFC results yielded by different methods using several metrics to quantify overall, temporal, spatial, and intersubject similarity.

Results

Our results showed a range of weak to strong similarity between

SUBMITTER: Torabi M 

PROVIDER: S-EPMC11000510 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature