QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia.
Neuroimage. 2021 Apr 1;229:117738. doi: 10.1016/j.neuroimage.2021.117738. Epub 2021 Jan 14.
Synchronization is a collective mechanism by which oscillatory networks achieve their functions. Factors driving synchronization include the network's topological and dynamical properties. However, how these factors drive the emergence of synchronization in the presence of potentially disruptive external inputs like stochastic perturbations is not well understood, particularly for real-world systems such as the human brain. Here, we aim to systematically address this problem using a large-scale model of the human brain network (i.e., the human connectome). The results show that the model can produce complex synchronization patterns transitioning between incoherent and coherent states. When nodes in the network are coupled at some critical strength, a counterintuitive phenomenon emerges where the addition of noise increases the synchronization of global and local dynamics, with structural hub nodes benefiting the most. This stochastic synchronization effect is found to be driven by the intrinsic hierarchy of neural timescales of the brain and the heterogeneous complex topology of the connectome. Moreover, the effect coincides with clustering of node phases and node frequencies and strengthening of the functional connectivity of some of the connectome's subnetworks. Overall, the work provides broad theoretical insights into the emergence and mechanisms of stochastic synchronization, highlighting its putative contribution in achieving network integration underpinning brain function.
同步是振荡网络实现其功能的一种集体机制。驱动同步的因素包括网络的拓扑和动力学特性。然而，在存在随机扰动等潜在破坏性外部输入的情况下，这些因素如何驱动同步的出现，特别是对于像人脑这样的真实系统，还不是很清楚。在这里，我们旨在使用大规模的人类大脑网络模型（即人类连接组）来系统地解决这个问题。结果表明，该模型可以产生复杂的同步模式，在非相干和相干状态之间转换。当网络中的节点在某个临界强度下耦合时，会出现一个反直觉的现象，即噪声的增加会增加全局和局部动力学的同步，而结构枢纽节点受益最大。这种随机同步效应是由大脑的内在神经时间尺度层次结构和连接组的异质复杂拓扑驱动的。此外，该效应与节点相位和节点频率的聚类以及连接组的一些子网的功能连接的增强相一致。总的来说，这项工作为随机同步的出现和机制提供了广泛的理论见解，强调了其在实现大脑功能的网络整合方面的潜在贡献。
