Action-mode subnetworks for decision-making, action control, and feedback
Carolina Badke D’Andrea, Timothy O. Laumann, Dillan J. Newbold, Charles J. Lynch, Mohammad Hadji, Steven M. Nelson, Ashley N. Nielsen, Roselyne J. Chauvin, Samuel R. Krimmel, Abraham Z. Snyder, Scott Marek, Deanna J. Greene, Marcus E. Raichle, Nico U.F. Dosenbach, Evan M. Gordon
Abstract
The action-mode network (AMN) is a canonical functional brain network first identified using resting-state functional connectivity (RSFC). Based on animal and human data, we have proposed that AMN supports the brain's action mode by controlling functions required for successful goal-directed behavior. However, task fMRI averaged across groups has associated AMN regions with a variety of behaviors, contributing to uncertainty about AMN function. Here, we investigated the AMN using an inside-out approach, in which the network architecture of the AMN is first precisely mapped within individuals and then associated with behavioral functions. Individual-specific precision functional mapping with >5 h of RSFC and task functional magnetic resonance imaging (fMRI) data revealed a replicable AMN subnetwork structure. AMN subnetworks were characterized and annotated by combining a meta-analytic network association method with RSFC, intrinsic timing, and task activation profiling. We demonstrate the existence of AMN-Decision, -Action, and -Feedback subnetworks that are distributed across lobes, forming a temporally sequential within-network processing stream by which the brain adjudicates between possible goals, sets action plans, and modifies those plans in response to feedback such as pain. A subnetwork in the pars marginalis of the cingulate was distinct from the Decision, Action, and Feedback subnetworks and may be important for the construction of the bodily self.