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Abstract
Recent research has imported tools from network science control theory towards studying controllability properties of brain circuits, and investigating the possibility of restoring or enhancing brain activity using brain stimulation. However, a fundamental challenge here is that current notions of controllability based on the structural connections of the human brain may be inadequate for the study of human brain function. We use system identification, network science, stability analysis, and control theory to probe functional circuit dynamics during working memory task performance. Our main finding is that the 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.
Speaker bio
Prof. Ramkrishna Pasumarthy is currently an Associate Professor at Dynamics and Control lab, Department of Electrical Engineering, IIT Madras. He obtained his PhD in systems and control from University of Twente, Netherlands and held post doc positions at University of Melbourne and UCLA. His interests lie in the area of modeling and control of complex physical systems, identification and control of (cloud) computing systems and analysis and control of power, traffic, brain and cloud networks. He is also associated with the Robert Bosh Center for Data Sciences and Artificial Intelligence at IIT Madras.