Iterative consensus spectral clustering improves detection of subject and group level brain functional modules.

ABSTRACT: Specialized processing in the brain is performed by multiple groups of brain regions organized as functional modules. Although, in vivo studies of brain functional modules involve multiple functional Magnetic Resonance Imaging (fMRI) scans, the methods used to derive functional modules from functional networks of the brain ignore individual differences in the functional architecture and use incomplete functional connectivity information. To correct this, we propose an Iterative Consensus Spectral Clustering (ICSC) algorithm that detects the most representative modules from individual dense weighted connectivity matrices derived from multiple scans. The ICSC algorithm derives group-level modules from modules of multiple individuals by iteratively minimizing the consensus-cost between the tw

SUBMITTER: Gupta S 

PROVIDER: S-EPMC7200822 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature