Subgraphs of functional brain networks identify dynamical constraints of cognitive control

• Published in: PLoS computational biology Vol. 14; no. 7; p. e1006234
• Main Authors: Khambhati, Ankit N., Medaglia, John D., Karuza, Elisabeth A., Thompson-Schill, Sharon L., Bassett, Danielle S.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.07.2018; Public Library of Science (PLoS)
• Subjects: Adult; Artificial intelligence; Attention; Bioengineering; Biology and Life Sciences; Brain; Brain - anatomy & histology; Brain - physiology; Brain mapping; Brain Mapping - methods; Brain research; Cognition; Cognition & reasoning; Cognition - physiology; Cognitive ability; Cognitive tasks; Computer and Information Sciences; Computer networks; Control tasks; Cooperative control; Female; Functional magnetic resonance imaging; Gene expression; Human performance; Humans; Hypotheses; Machine Learning; Magnetic Resonance Imaging - methods; Male; Medicine and Health Sciences; Methods; Nerve Net; Neural circuitry; Neural networks; Perception; Physiological aspects; Reporting requirements; Research and Analysis Methods; Signal processing; Social Sciences; Stroop Test; Switching theory; Task Performance and Analysis; Young Adult; United States > US; Pennsylvania
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1006234

Brain anatomy and physiology support the human ability to navigate a complex space of perceptions and actions. To maneuver across an ever-changing landscape of mental states, the brain invokes cognitive control-a set of dynamic processes that engage and disengage different groups of brain regions to modulate attention, switch between tasks, and inhibit prepotent responses. Current theory posits that correlated and anticorrelated brain activity may signify cooperative and competitive interactions between brain areas that subserve adaptive behavior. In this study, we use a quantitative approach to identify distinct topological motifs of functional interactions and examine how their expression relates to cognitive control processes and behavior. In particular, we acquire fMRI BOLD signal in twenty-eight healthy subjects as they perform two cognitive control tasks-a Stroop interference task and a local-global perception switching task using Navon figures-each with low and high cognitive control demand conditions. Based on these data, we construct dynamic functional brain networks and use a parts-based, network decomposition technique called non-negative matrix factorization to identify putative cognitive control subgraphs whose temporal expression captures distributed network structures involved in different phases of cooperative and competitive control processes. Our results demonstrate that temporal expression of the subgraphs fluctuate alongside changes in cognitive demand and are associated with individual differences in task performance. These findings offer insight into how coordinated changes in the cooperative and competitive roles of cognitive systems map trajectories between cognitively demanding brain states.