Year: 2015
Type: article
Abstract: One of the most remarkable features of the human brain is its ability to adapt rapidly and efficiently to external task demands. Novel and non-routine tasks, for example, are implemented faster than structural connections can be formed. The neural underpinnings of these dynamics are far from understood. Here we develop and apply novel methods in network science to quantify how patterns of functional connectivity between brain regions reconfigure as human subjects perform 64 different tasks. By applying dynamic community detection algorithms, we identify groups of brain regions that form putative functional communities, and we uncover changes in these groups across the 64-task battery. We summarize these reconfiguration patterns by quantifying the probability that two brain regions engage in the same network community (or putative functional module) across tasks. These tools enable us to demonstrate that classically defined cognitive systems-including visual, sensorimotor, auditory, default mode, fronto-parietal, cingulo-opercular and salience systems-engage dynamically in cohesive network communities across tasks. We define the network role that a cognitive system plays in these dynamics along the following two dimensions: (i) stability vs. flexibility and (ii) connected vs. isolated. The role of each system is therefore summarized by how stably that system is recruited over the 64 tasks, and how consistently that system interacts with other systems. Using this cartography, classically defined cognitive systems can be categorized as ephemeral integrators, stable loners, and anything in between. Our results provide a new conceptual framework for understanding the dynamic integration and recruitment of cognitive systems in enabling behavioral adaptability across both task and rest conditions. This work has important implications for understanding cognitive network reconfiguration during different task sets and its relationship to cognitive effort, individual variation in cognitive performance, and fatigue.
Source: PLoS Computational Biology
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,043
Funders: National Science Foundation, John D. and Catherine T. MacArthur Foundation, Alfred P. Sloan Foundation, National Institutes of Health, National Institute of Mental Health, National Eye Institute, National Institute on Deafness and Other Communication Disorders, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Army Research Office, Army Research Laboratory
Awards: G1001159199, G1024130705, G1778482337, G2901702611, G3326146522, G3330175468, G3755125221, G3824545241, G4069802742, Object Concepts, G5259331294, Network Mechanisms of Flexible Cognitive Control, G572628577, G6409978989, CRCNS: Collaborative Research: Mapping and Control of Large-Scale Neural Dynamics, Linguistic and Nonlinguistic Functions of Frontal Cortex, G7159985717, G738160294, G7452299184, CRCNS: US-France Modeling & Predicting BCI Learning from Dynamic Networks, WORKSHOP: Quantitative Theories of Learning, Memory, and Prediction, G7747382488, Network Mechanisms of Flexible Cognitive Control, G7989609580, G8318881156, G9000248557, G9000324765
OpenAlex ID: W2181732012