October 20, 2020

Probabilistic mapping of human functional brain networks identifies regions of high group consensus

Many recent developments surrounding the functional network organization of the human brain have focused on data that have been averaged across groups of individuals. While such group-level approaches have shed considerable light on the brain’s large-scale distributed systems, they conceal individual differences in network organization, which recent work has demonstrated to be common and widespread. Here our goal was to leverage information about individual-level brain organization to identify locations of high inter-subject consensus. We probabilistically mapped 14 functional networks in multiple datasets with relatively high amounts of data. All networks show "core" (high-probability) regions, but differ from one another in the extent of their higher-variability components. These patterns replicate well across datasets with different scanning parameters. We produced a set of high-probability regions of interest (ROIs) from these probabilistic maps; these and the probabilistic maps are made publicly available, allowing researchers to apply information about group consistency to their own work in rest- or task-based studies.

 bioRxiv Subject Collection: Neuroscience

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