A Wavelet-Based Approach for Estimating Time-Varying Connectivity in Resting-State Functional Magnetic Resonance Imaging.

ABSTRACT: Introduction: The selection of an appropriate window size, window function, and functional connectivity (FC) metric in the sliding window method is not straightforward due to the absence of ground truth. Methods: A previously proposed wavelet-based method was accordingly adjusted for estimating time-varying FC (TVFC) and was applied to a large high-quality, low-motion dataset of 400 resting-state functional magnetic resonance imaging data. Specifically, the wavelet coherence magnitude and relative phase were averaged across wavelet (frequency) scales to yield TVFC and synchronization patterns. To assess whether the observed fluctuations in TVFC were statistically significant (dynamic FC [dFC]; the distinction between TVFC and dFC is intentional), surrogate data

SUBMITTER: Savva AD 

PROVIDER: S-EPMC9271336 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature