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脑状态与转变:计算神经科学的新视角。

Brain States and Transitions: Insights from Computational Neuroscience.

机构信息

Department of Psychiatry, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK.

Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany; School of Psychological Sciences, Monash University, Melbourne, Clayton, VIC 3800, Australia.

出版信息

Cell Rep. 2020 Sep 8;32(10):108128. doi: 10.1016/j.celrep.2020.108128.

Abstract

Within the field of computational neuroscience there are great expectations of finding new ways to rebalance the complex dynamic system of the human brain through controlled pharmacological or electromagnetic perturbation. Yet many obstacles remain between the ability to accurately predict how and where best to perturb to force a transition from one brain state to another. The foremost challenge is a commonly agreed definition of a given brain state. Recent progress in computational neuroscience has made it possible to robustly define brain states and force transitions between them. Here, we review the state of the art and propose a framework for determining the functional hierarchical organization describing any given brain state. We describe the latest advances in creating sophisticated whole-brain computational models with interacting neuronal and neurotransmitter systems that can be studied fully in silico to predict and design novel pharmacological and electromagnetic interventions to rebalance them in disease.

摘要

在计算神经科学领域,人们期望通过控制药理学或电磁干扰找到新的方法来重新平衡人类大脑这一复杂的动态系统。然而,要想准确预测如何以及在何处进行最佳干扰以迫使大脑状态发生转变,仍然存在许多障碍。最主要的挑战是对特定大脑状态的一个普遍认同的定义。计算神经科学的最新进展已经使得对大脑状态进行稳健定义并在它们之间进行强制转换成为可能。在这里,我们回顾了最新进展,并提出了一个用于确定描述任何给定大脑状态的功能层次结构的框架。我们描述了创建具有相互作用的神经元和神经递质系统的复杂全脑计算模型的最新进展,这些模型可以在计算机中进行全面研究,以预测和设计新型的药理学和电磁干预措施,从而在疾病中重新平衡它们。

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