Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
Department of Computer Science, University of Tübingen, Tübingen, Germany.
Philos Trans A Math Phys Eng Sci. 2022 Jul 11;380(2227):20200424. doi: 10.1098/rsta.2020.0424. Epub 2022 May 23.
Many of the amazing functional capabilities of the brain are collective properties stemming from the interactions of large sets of individual neurons. In particular, the most salient collective phenomena in brain activity are oscillations, which require the synchronous activation of many neurons. Here, we analyse parsimonious dynamical models of neural synchronization running on top of synthetic networks that capture essential aspects of the actual brain anatomical connectivity such as a hierarchical-modular and core-periphery structure. These models reveal the emergence of complex collective states with intermediate and flexible levels of synchronization, halfway in the synchronous-asynchronous spectrum. These states are best described as broad Griffiths-like phases, i.e. an extension of standard critical points that emerge in structurally heterogeneous systems. We analyse different routes (bifurcations) to synchronization and stress the relevance of 'hybrid-type transitions' to generate rich dynamical patterns. Overall, our results illustrate the complex interplay between structure and dynamics, underlining key aspects leading to rich collective states needed to sustain brain functionality. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.
大脑的许多令人惊叹的功能特性都是源于大量单个神经元相互作用而产生的集体属性。特别是,大脑活动中最显著的集体现象是振荡,这需要许多神经元的同步激活。在这里,我们分析了在合成网络上运行的神经同步的简约动力模型,这些模型捕捉了实际大脑解剖连接的基本方面,如层次模块和核心-外围结构。这些模型揭示了具有中间和灵活同步水平的复杂集体状态的出现,处于同步-异步谱的中间位置。这些状态最好被描述为广泛的 Griffiths 样相位,即标准临界点在结构异质系统中出现的扩展。我们分析了不同的同步途径(分岔),并强调了“混合类型转变”的相关性,以产生丰富的动态模式。总的来说,我们的研究结果说明了结构和动力学之间的复杂相互作用,强调了导致维持大脑功能所需的丰富集体状态的关键方面。本文是“复杂物理和社会技术系统中的涌现现象:从细胞到社会”主题问题的一部分。