Heterogeneous fractionation profiles of meta-analytic coactivation networks.

ABSTRACT: Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "c

SUBMITTER: Laird AR 

PROVIDER: S-EPMC5408583 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature