RT Journal Article
SR Electronic
T1 State-specific individualized functional networks form a predictive signature of brain state
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 372110
DO 10.1101/372110
A1 Mehraveh Salehi
A1 Amin Karbasi
A1 Daniel S. Barron
A1 Dustin Scheinost
A1 R. Todd Constable
YR 2018
UL http://biorxiv.org/content/early/2018/07/19/372110.abstract
AB There is extensive evidence that human brain functional organization is dynamic, varying within a subject as the brain switches between tasks demands. This functional organization also varies across subjects, even when they are all engaged in similar tasks. Currently, we lack a comprehensive model that unifies the two dimensions of variation (brain state and subject). Using fMRI data obtained across multiple task-evoked and rest conditions (which we operationally define as brain states) and across multiple subjects, we develop a state-and subject-specific functional network parcellation (the assignment of nodes to networks). Our parcellation approach provides a measure of how node-to-network assignment (NNA) changes across states and across subjects. We demonstrate that the brain’s functional networks are not spatially fixed, but reconfigure with brain state. This reconfiguration is robust and reliable to such an extent that it can be used to predict brain state with accuracies up to 97%.