认知科学
认知
计算机科学
神经科学
航程(航空)
控制(管理)
功能(生物学)
脑功能
人工智能
数据科学
人工神经网络
人机交互
复杂网络
脑解剖学
网络动力学
信号(编程语言)
网络科学
建筑
心理学
神经信息学
动力系统理论
能量(信号处理)
计算神经科学
信息传输
复杂系统
认知网络
神经影像学
作者
Christopher W. Lynn,Danielle S. Bassett
标识
DOI:10.1038/s42254-019-0040-8
摘要
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.
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