Dynamic causal brain circuits during working memory and their functional controllability

Weidong Cai,Vinod Menon,Viswanath Talasila,Srikanth Ryali,Ramkrishna Pasumarthy

doi:10.1038/s41467-021-23509-x

Abstract

Control processes associated with working memory play a central role in human cognition, but their underlying dynamic brain circuit mechanisms are poorly understood. Here we use system identification, network science, stability analysis, and control theory to probe functional circuit dynamics during working memory task performance. Our results show that dynamic signaling between distributed brain areas encompassing the salience (SN), fronto-parietal (FPN), and default mode networks can distinguish between working memory load and predict performance. Network analysis of directed causal influences suggests the anterior insula node of the SN and dorsolateral prefrontal cortex node of the FPN are causal outflow and inflow hubs, respectively. Network controllability decreases with working memory load and SN nodes show the highest functional controllability. Our findings reveal dissociable roles of the SN and FPN in systems control and provide novel insights into dynamic circuit mechanisms by which cognitive control circuits operate asymmetrically during cognition.

Highlights

Control processes associated with working memory play a central role in human cognition, but their underlying dynamic brain circuit mechanisms are poorly understood
We focused our analysis of dynamic causal interactions on 11 core SN, frontoparietal networks (FPN), and default mode network (DMN) regions known to display a consistent profile of task-related activation and deactivation during the 2-back working-memory task[21] (Fig. 1A)
SN nodes consisted of the left and right anterior insula (AI) and dorsomedial prefrontal cortex (DMPFC); FPN consisted of left and right middle frontal gyrus (MFG), left and right frontal eye field (FEF), and left and right inferior parietal lobule (IPL); and the DMN consisted of the posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (VMPFC)

Summary

Introduction

Control processes associated with working memory play a central role in human cognition, but their underlying dynamic brain circuit mechanisms are poorly understood. We use system identification, network science, stability analysis, and control theory to probe functional circuit dynamics during working memory task performance. We first apply state-space models to determine dynamic causal circuits, probe dynamic brain network properties including causal outflow and inflow hubs of information flow[13,14], and determine sources of individual differences in working-memory task performance. Other related research has suggested that the DMN may encode task-relevant information during cognitively demanding tasks[38,39] While these studies point to a highly consistent pattern of working-memoryrelated neural activity in the SN, FPN, and DMN, there have been no systematic investigations of their dynamic functional interactions and network properties

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Conclusion