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大脑信息处理的层级结构:新颖的“内在点火”框架。

Hierarchy of Information Processing in the Brain: A Novel 'Intrinsic Ignition' Framework.

机构信息

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.

Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; Center for Music in the Brain (MIB), Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark; Institut d'études avancées de Paris, 75004 Paris, France.

出版信息

Neuron. 2017 Jun 7;94(5):961-968. doi: 10.1016/j.neuron.2017.03.028.

Abstract

A general theory of brain function has to be able to explain local and non-local network computations over space and time. We propose a new framework to capture the key principles of how local activity influences global computation, i.e., describing the propagation of information and thus the broadness of communication driven by local activity. More specifically, we consider the diversity in space (nodes or brain regions) over time using the concept of intrinsic ignition, which are naturally occurring intrinsic perturbations reflecting the capability of a given brain area to propagate neuronal activity to other regions in a given brain state. Characterizing the profile of intrinsic ignition for a given brain state provides insight into the precise nature of hierarchical information processing. Combining this data-driven method with a causal whole-brain computational model can provide novel insights into the imbalance of brain states found in neuropsychiatric disorders.

摘要

一种通用的大脑功能理论必须能够解释空间和时间上的局部和非局部网络计算。我们提出了一个新的框架来捕捉局部活动如何影响全局计算的关键原则,即描述信息的传播,从而描述由局部活动驱动的广泛的通信。更具体地说,我们使用内在点火的概念来考虑随时间变化的空间(节点或脑区)的多样性,内在点火是自然发生的内在扰动,反映了给定脑区在给定脑状态下将神经元活动传播到其他区域的能力。对给定脑状态的内在点火特性进行特征化,可以深入了解层次信息处理的精确性质。将这种数据驱动的方法与因果全脑计算模型相结合,可以为神经精神障碍中发现的脑状态失衡提供新的见解。

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