神经元映射网络中的混沌格里菲斯相
Chaotic Griffiths phase in neuron map networks
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中文总结 AI 辅助
本研究在神经元映射网络中发现，局部参数淬火异质性可独立产生混沌格里菲斯相，且与拓扑无序协同扩展临界区域，表现为簇大小幂律分布和正李雅普诺夫指数异常标度。
中文摘要 AI 辅助
格里菲斯相提供了一种在扩展参数区域内维持临界动力学的机制，而无需精细调节到孤立的转变点。这种行为主要与复杂网络中的结构异质性相关。在此，我们展示了局部参数中的淬火异质性可以在基于映射的神经元网络中产生混沌格里菲斯相。我们研究了具有局部神经元参数淬火无序的全局耦合Chialvo映射，从而将内在参数无序与拓扑无序分离开来。随着耦合强度的变化，混沌格里菲斯相在去同步和相干混沌动力学之间出现，其特征是神经元簇的间歇性形成和破裂，以及簇内神经元比例的剧烈波动。在该区域内，簇大小呈现幂律分布，其指数依赖于耦合强度，提供了在有限参数区间内存在临界行为的证据。混沌格里菲斯相在均匀极限中不存在，并随着参数异质性程度的增加而逐渐扩大。我们进一步通过小世界连接引入拓扑无序，并发现其与局部参数异质性的联合作用显著扩展了混沌格里菲斯相。在全局耦合和小世界网络中，正李雅普诺夫指数的数量随系统大小呈现异常标度。这些结果表明，内在动力学异质性构成了产生混沌格里菲斯相的独立机制，且其与结构无序的相互作用增强了神经元网络中的扩展临界性。
英文摘要
Griffiths phases provide a mechanism for sustaining critical dynamics over extended parameter regions without fine-tuning to an isolated transition point. This behavior has been mainly associated with structural heterogeneity in complex networks. Here we show that quenched heterogeneity in local parameters can generate a chaotic Griffiths phase in a network of map-based neurons. We study globally coupled Chialvo maps with quenched disorder in a local neuronal parameter, thereby isolating intrinsic parameter disorder from topological disorder. As the coupling strength is varied, a chaotic Griffiths phase emerges between desynchronized and coherent chaotic dynamics, characterized by intermittent formation and breakup of neuronal clusters and large fluctuations in the fraction of clustered neurons. Within this regime, cluster sizes exhibit power-law distributions with coupling-dependent exponents, providing evidence of critical behavior over a finite parameter interval. The chaotic Griffiths phase is absent in the homogeneous limit and broadens progressively as the degree of parameter heterogeneity increases. We further introduce topological disorder through small-world connectivity and find that its combined action with local parameter heterogeneity substantially extends the chaotic Griffiths phase. In both globally coupled and small-world networks, the number of positive Lyapunov exponents displays anomalous scaling with system size. These results demonstrate that intrinsic dynamical heterogeneity constitutes an independent mechanism for generating chaotic Griffiths phases and that its interplay with structural disorder enhances extended criticality in neuronal networks.
发表机构
- Okinawa Institute of Science and Technology Graduate University（冲绳科学技术大学院大学）
- Universidad Yachay Tech（亚查伊科技大学）
机构由 AI 辅助整理，请以论文原文为准。
