Functional network architecture and dynamics of the somato-cognitive action network

Abstract

The somato-cognitive-action-network (SCAN) is a recently discovered brain network. SCAN interdigitates somatomotor networks and is functionally connected to the cingulo-opercular/action-mode network. SCAN is therefore thought to play a role in motor/action planning. This view of SCAN, however, is based on its "static" functional connectivity-i.e. FC estimated using data pooled over an entire scan session or dataset. However, this approach necessarily overlooks changes in network activity and connectivity that occurs over shorter timescales. In this report, we extend analyses of SCANs static architecture, demonstrating that, at the whole-brain level, SCAN vertices exhibit overlapping network membership, such that, while they form a cohesive sub-network, they may also couple transiently and dynamically with other networks. We examine these potential co-activations by focusing on SCAN dynamics and through the identification of distinct coupling modes - co-activation patterns (CAPs). We show that CAPs differentially contribute to SCANs static architecture and that their frequency varies across following limb immobilization.