Dynamic causal brain circuits during working memory and their functional controllability.
Weidong Cai1,2, Srikanth Ryali3, Ramkrishna Pasumarthy4
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA. wdcai@stanford.edu.
Nature Communications
|June 30, 2021
Summary
Dynamic brain network signaling, particularly between the salience (SN) and fronto-parietal (FPN) networks, distinguishes working memory load and predicts cognitive performance. The SN and FPN exhibit distinct roles in cognitive control.
Area of Science:
- Cognitive Neuroscience
- Systems Neuroscience
- Computational Psychiatry
Background:
- Working memory is crucial for human cognition, yet its underlying brain circuit dynamics remain unclear.
- Understanding these dynamics is key to deciphering cognitive control mechanisms.
Purpose of the Study:
- To investigate the dynamic brain circuit mechanisms of working memory control.
- To identify network properties that distinguish working memory load and predict task performance.
Main Methods:
- Employed system identification, network science, stability analysis, and control theory.
- Analyzed functional circuit dynamics during working memory task performance.
- Performed network analysis of directed causal influences.
Main Results:
- Dynamic signaling between salience (SN), fronto-parietal (FPN), and default mode networks differentiates working memory load and predicts performance.
- Anterior insula (SN) and dorsolateral prefrontal cortex (FPN) act as key causal outflow and inflow hubs.
- Network controllability decreases with increased working memory load; SN nodes exhibit highest functional controllability.
Conclusions:
- Revealed dissociable roles for the SN and FPN in cognitive systems control.
- Provided novel insights into asymmetric dynamic circuit mechanisms underlying cognitive control.
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