A principled framework to assess the information-theoretic fitness of brain functional sub-circuits.

ABSTRACT: In systems and network neuroscience, many common practices in brain connectomic analysis are often not properly scrutinized. One such practice is mapping a predetermined set of sub-circuits, like functional networks (FNs), onto subjects' functional connectomes (FCs) without adequately assessing the information-theoretic appropriateness of the partition. Another practice that goes unchallenged is thresholding weighted FCs to remove spurious connections without justifying the chosen threshold. This paper leverages recent theoretical advances in Stochastic Block Models (SBMs) to formally define and quantify the information-theoretic fitness (e.g., prominence) of a predetermined set of FNs when mapped to individual FCs under different fMRI task conditions. Our framework allows for evaluating a

SUBMITTER: Duong-Tran D 

PROVIDER: S-EPMC11230349 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature