Reproducibility of graph measures derived from resting-state MEG functional connectivity metrics in sensor and source spaces.

ABSTRACT: Prior studies have used graph analysis of resting-state magnetoencephalography (MEG) to characterize abnormal brain networks in neurological disorders. However, a present challenge for researchers is the lack of guidance on which network construction strategies to employ. The reproducibility of graph measures is important for their use as clinical biomarkers. Furthermore, global graph measures should ideally not depend on whether the analysis was performed in the sensor or source space. Therefore, MEG data of the 89 healthy subjects of the Human Connectome Project were used to investigate test-retest reliability and sensor versus source association of global graph measures. Atlas-based beamforming was used for source reconstruction, and functional connectivity (FC) was estimated for both s

SUBMITTER: Pourmotabbed H 

PROVIDER: S-EPMC8837594 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature