Year: 2017
Type: review
Abstract: Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive "reserve," associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention.
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,860
Funders: National Science Foundation, John D. and Catherine T. MacArthur Foundation, Alfred P. Sloan Foundation, National Institutes of Health, Office of the Director, Office of Naval Research, National Institute of Mental Health, National Institute on Deafness and Other Communication Disorders, National Institute of Neurological Disorders and Stroke, National Institute of Child Health and Human Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Army Research Office, Army Research Laboratory
Awards: G1001159199, G1024130705, G1041393086, G1058535469, G1099660080, G1177916794, G1317729317, G1778482337, G1993459732, G2066955304, G2130352337, G2236980202, Virtual Resection to Treat Epilepsy, G2252567680, G235261508, G2425642435, Dynamic Network Neuroscience and Control Theory: Toward Interventions for Cognitive Control Dysfunction, G2864901048, G2887601406, G2901702611, G3137615481, G3330175468, G3424441068, G3564833335, G3611952402, G3690479056, G3755125221, G3824545241, G4069802742, G4503518981, Track-2: The Smart MATerial Design, Analysis, and Processing (SMATDAP) consortium: Building next-generation polymers and the tools to accelerate cost-effective commercial productio, G4548301804, G5172716836, G5253651465, G5259331294, G572628577, G5884259427, CAREER: Linking Graph Topology of Learned Information to Behavioral Variability via Dynamics of Functional Brain Networks, G6409978989, CRCNS: Collaborative Research: Mapping and Control of Large-Scale Neural Dynamics, G6671297155, G6689184838, G6752185412, Linguistic and Nonlinguistic Functions of Frontal Cortex, G6981911394, Evolution of the Linked Architecture of Network Control and Executive Function in Adolescence, G7159985717, G7452299184, WORKSHOP: Quantitative Theories of Learning, Memory, and Prediction, G7530591242, G7594130654, G7747382488, G793584043, G7989609580, Postdoctoral Training in Translational Neurorehabilitation Research, G8278114317, G8318881156, G8454816522, CRCNS: US-France Modeling & Predicting BCI Learning from Dynamic Networks, G8551711365, G8554419822, G9000056496, G90128336, G91481811, G916315028, G91658921
OpenAlex ID: W2336467402