Friston Karl J, Fagerholm Erik D, Zarghami Tahereh S, Parr Thomas, Hipólito Inês, Magrou Loïc, Razi Adeel
Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.
Department of Neuroimaging, King's College London, London, United Kingdom.
Netw Neurosci. 2021 Mar 1;5(1):211-251. doi: 10.1162/netn_a_00175. eCollection 2021.
At the inception of human brain mapping, two principles of functional anatomy underwrote most conceptions-and analyses-of distributed brain responses: namely, functional and . There are currently two main approaches to characterizing functional integration. The first is a mechanistic modeling of connectomics in terms of directed connectivity that mediates neuronal message passing and dynamics on neuronal circuits. The second phenomenological approach usually characterizes undirected (i.e., measurable correlations), in terms of intrinsic brain networks, self-organized criticality, dynamical instability, and so on. This paper describes a treatment of effective connectivity that speaks to the emergence of intrinsic brain networks and critical dynamics. It is predicated on the notion of that play a fundamental role in the self-organization of far from equilibrium systems. Using the apparatus of the , we show that much of the phenomenology found in network neuroscience is an emergent property of a particular partition of neuronal states, over progressively coarser scales. As such, it offers a way of linking dynamics on directed graphs to the phenomenology of intrinsic brain networks.
在人类脑图谱研究伊始,功能解剖学的两个原则支撑着大多数关于分布式脑反应的概念和分析:即功能和。目前有两种主要方法来表征功能整合。第一种是从介导神经元信息传递和神经元回路动力学的定向连接性角度对连接组学进行机制建模。第二种现象学方法通常根据内在脑网络、自组织临界性、动态不稳定性等来表征无向(即可测量的相关性)。本文描述了一种对有效连接性的处理方法,它涉及内在脑网络的出现和临界动力学。它基于在远离平衡系统的自组织中起基本作用的概念。利用[具体工具名称未给出]的工具,我们表明在网络神经科学中发现的许多现象学是神经元状态在逐渐更粗尺度上的特定划分的涌现属性。因此,它提供了一种将有向图上的动力学与内在脑网络的现象学联系起来的方法。