期刊
ANNALS OF THE NEW YORK ACADEMY OF SCIENCES
卷 1396, 期 1, 页码 126-143出版社
WILEY
DOI: 10.1111/nyas.13338
关键词
graph theory; network neuroscience; neurofeedback; cognition; control theory
资金
- John D. and Catherine T. MacArthur Foundation
- Alfred P. Sloan Foundation
- Army Research Laboratory
- National Institute of Health [2-R01-DC-009209-11, 1R01HD086888-01, R01-MH107235, R01-MH107703, R01MH109520, 1R01NS099348, R21-M MH-106799]
- Office of Naval Research
- National Science Foundation [BCS- 1441502, CAREER PHY-1554488, BCS-1631550, CNS-1626008]
- Army Research Office [W911NF-10-2-0022, W911NF-14-1-0679]
Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition.
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