通过模块化连接控制扩展关键性
Controlling extended criticality via modular connectivity
摘要：
临界性是神经网络动力学的一个重要组成部分。在临界阈值下运行需要精确的参数调整，相应的机制仍然是一个悬而未决的问题。最近的研究表明，在大脑网络中观察到的拓扑特征会引起格里菲斯阶段，导致大脑活动动力学的幂律和扩展参数区域中临界性的操作益处。越来越多的证据表明，神经相关的不同状态的意识，我们调查拓扑结构的变化如何影响格里菲斯阶段的表达。我们使用易感-感染-易感传播模型分析了模块化网络中的活动衰减，发现我们可以通过改变模块内和模块间的连接来控制格里菲斯阶段的扩展。我们发现，通过调整系统参数，我们可以抵消的变化，在关键的行为，并保持一个稳定的临界区域，尽管网络拓扑结构的变化。我们的研究结果提供了深入了解结构网络属性如何影响格里菲斯阶段的出现，以及它的功能是如何链接到既定的拓扑网络指标。我们将讨论这些发现如何有助于理解所观察到的功能性大脑网络的变化。最后，我们指出我们的研究结果可能是有用的疾病传播的研究。
英文摘要：
Criticality has been conjectured as an integral part of neuronal network dynamics. Operating at a critical threshold requires precise parameter tuning and a corresponding mechanism remains an open question. Recent studies have suggested that topological features observed in brain networks give rise to a Griffiths phase, leading to power-laws in brain activity dynamics and the operational benefits of criticality in an extended parameter region. Motivated by growing evidence of neural correlates of different states of consciousness, we investigate how topological changes affect the expression of a Griffiths phase. We analyze the activity decay in modular networks using a Susceptible-Infected-Susceptible propagation model and find that we can control the extension of the Griffiths phase by altering intra- and intermodular connectivity. We find that by adjusting system parameters, we can counteract changes in critical behavior and maintain a stable critical region despite changes in network topology. Our results give insight into how structural network properties affect the emergence of a Griffiths phase and how its features are linked to established topological network metrics. We discuss how those findings can contribute to understand the observed changes in functional brain networks. Finally, we indicate how our results could be useful in the study of disease spreading.
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