Synchronization in Functional Networks of the Human Brain
Synchronization in Functional Networks of the Human Brain
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DOI：
10.1007/s00332-018-9505-7
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发表时间：
2020-10-01
影响因子：
3
通讯作者：
Vuksanovic, Vesna
中科院分区：
文献类型：
--
作者：
Hoevel, Philipp;Viol, Aline;Vuksanovic, Vesna
了解结构和功能组织之间的关系是神经科学中最重要的挑战之一。越来越多的研究表明，通过将大脑视为一个互动的复杂网络，可以更好地理解这种组织。这种方法激发了大量的计算模型，将实验数据与大脑相互作用的数值模拟结合起来。在这篇文章中，我们提出了一种数据驱动的计算模型，用于共享大量重叠的相邻(解剖)连接的远距离皮质区域之间的同步。这种联系来自使用弥散加权磁共振成像的大脑连通性的活体测量，并另外通过所涉及区域之间存在显著的静息状态功能相关联系而获得信息。用耦合振子系统和血流动力学响应模型相结合的方法模拟了脑区的动态过程。耦合振荡系统用Kuramoto相位振荡器表示，从而模拟了区域活动之间的相位同步。该建模方法的重点是刻画与区域神经活动同步相关的脑功能关联的拓扑特性。所提出的模型能够再现大脑区域之间的远程同步，与实验的功能连接性达到合理的一致。我们表明，对于表现出同步和同步变化的平衡的动态状态，模型和实验数据之间达到了最好的一致性，从而提供了远程大脑区域之间的活动整合。
Understanding the relationship between structural and functional organization represents one of the most important challenges in neuroscience. An increasing amount of studies show that this organization can be better understood by considering the brain as an interactive complex network. This approach has inspired a large number of computational models that combine experimental data with numerical simulations of brain interactions. In this paper, we present a summary of a data-driven computational model of synchronization between distant cortical areas that share a large number of overlapping neighboring (anatomical) connections. Such connections are derived from in vivo measures of brain connectivity using diffusion-weighted magnetic resonance imaging and are additionally informed by the presence of significant resting-state functionally correlated links between the areas involved. The dynamical processes of brain regions are simulated by a combination of coupled oscillator systems and a hemodynamic response model. The coupled oscillatory systems are represented by the Kuramoto phase oscillators, thus modeling phase synchrony between regional activities. The focus of this modeling approach is to characterize topological properties of functional brain correlation related to synchronization of the regional neural activity. The proposed model is able to reproduce remote synchronization between brain regions reaching reasonable agreement with the experimental functional connectivities. We show that the best agreement between model and experimental data is reached for dynamical states that exhibit a balance of synchrony and variations in synchrony providing the integration of activity between distant brain regions.