Mohammad S.E. Sendi

Apr 25, 2024 | biorxiv.org | Masoud Seraji |Charles Ellis |Mohammad S.E. Sendi |Robyn Miller

AbstractA common analysis approach for resting state functional magnetic resonance imaging (rs-fMRI) dynamic functional network connectivity (dFNC) data involves clustering windowed correlation time-series and assigning time windows to clusters (i.e., states) that can be quantified to summarize aspects of the dFNC dynamics. However, those methods can be dominated by a select few features and obscure key dynamics related to less dominant features.