Nazemi Parisa Sadat, Jamali Yousef
Department of Mathematics, Tarbiat Modares University, Tehran, Iran.
Front Comput Neurosci. 2019 Jan 8;12:105. doi: 10.3389/fncom.2018.00105. eCollection 2018.
Since brain structural connectivity is the foundation of its functionality, in order to understand brain abilities, studying the relation between structural and functional connectivity is essential. Several approaches have been applied to measure the role of the structural connectivity in the emergent correlation/synchronization patterns. In this study, we investigates the cross-correlation and synchronization sensitivity to coupling strength between neural regions for different topological networks. We model the neural populations by a neural mass model that express an oscillatory dynamic. The results highlight that coupling between neural ensembles leads to various cross-correlation patterns and local synchrony even on an ordered network. Moreover, as the network departs from an ordered organization to a small-world architecture, correlation patterns, and synchronization dynamics change. Interestingly, at a certain range of the synaptic strength, by fixing the structural conditions, different organized patterns are seen at the different input signals. This variety switches to a bifurcation region by increasing the synaptic strength. We show that topological variations is a major factor of synchronization behavior and lead to alterations in correlated local clusters. We found the coupling strength (between cortical areas) to be especially important at conversions of correlation and synchronization states. Since correlation patterns generate functional connections and transitions of functional connectivity have been related to cognitive operations, these diverse correlation patterns may be considered as different dynamical states corresponding to various cognitive tasks.
由于脑结构连通性是其功能的基础，为了理解脑的能力，研究结构连通性与功能连通性之间的关系至关重要。已经应用了几种方法来测量结构连通性在涌现的相关性/同步模式中的作用。在本研究中，我们研究了不同拓扑网络中神经区域之间交叉相关性和同步对耦合强度的敏感性。我们用表达振荡动力学的神经群体模型对神经群体进行建模。结果表明，即使在有序网络上，神经集合之间的耦合也会导致各种交叉相关模式和局部同步。此外，随着网络从有序组织转变为小世界架构，相关模式和同步动态会发生变化。有趣的是，在一定范围的突触强度下，通过固定结构条件，在不同的输入信号下会出现不同的组织模式。通过增加突触强度，这种多样性会转变为一个分岔区域。我们表明，拓扑变化是同步行为的主要因素，并导致相关局部簇的改变。我们发现耦合强度（皮层区域之间）在相关性和同步状态的转换中尤为重要。由于相关模式产生功能连接，并且功能连通性的转变与认知操作有关，这些不同的相关模式可能被视为对应于各种认知任务的不同动态状态。
