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Quantitative Biology > Neurons and Cognition
Title:The physics of brain network structure, function, and control
(Submitted on 17 Sep 2018 (v1), last revised 7 Jan 2019 (this version, v3))
Abstract: The brain is a complex organ characterized by heterogeneous patterns of structural connections supporting unparalleled feats of cognition and a wide range of behaviors. New noninvasive imaging techniques now allow these patterns to be carefully and comprehensively mapped in individual humans and animals. Yet, it remains a fundamental challenge to understand how the brain's structural wiring supports cognitive processes, with major implications for the personalized treatment of mental health disorders. Here, we review recent efforts to meet this challenge that draw on intuitions, models, and theories from physics, spanning the domains of statistical mechanics, information theory, and dynamical systems and control. We begin by considering the organizing principles of brain network architecture instantiated in structural wiring under constraints of symmetry, spatial embedding, and energy minimization. We next consider models of brain network function that stipulate how neural activity propagates along these structural connections, producing the long-range interactions and collective dynamics that support a rich repertoire of system functions. Finally, we consider perturbative experiments and models for brain network control, which leverage the physics of signal transmission along structural wires to infer intrinsic control processes that support goal-directed behavior and to inform stimulation-based therapies for neurological disease and psychiatric disorders. Throughout, we highlight several open questions in the physics of brain network structure, function, and control that will require creative efforts from physicists willing to brave the complexities of living matter.
Submission history
From: Christopher Lynn [view email][v1] Mon, 17 Sep 2018 20:55:18 UTC (7,831 KB)
[v2] Wed, 19 Sep 2018 14:26:50 UTC (7,831 KB)
[v3] Mon, 7 Jan 2019 16:30:50 UTC (5,402 KB)