Inhibition causes ceaseless dynamics in networks of excitable nodes.
Inhibition causes ceaseless dynamics in networks of excitable nodes.
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DOI：
10.1103/physrevlett.112.138103
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发表时间：
2014-04-04
影响因子：
8.6
通讯作者：
Restrepo JG
中科院分区：
文献类型：
--
作者：
Larremore DB;Shew WL;Ott E;Sorrentino F;Restrepo JG
当引入抑制节点时，兴奋节点网络的集体动态会发生巨大变化。我们认为抑制节点可以像兴奋节点一样被激活，但在激活时会降低网络邻居激活的概率。我们表明，尽管抑制节点的直接影响是减少活动，但集体动力变得可以自我维持。我们通过定义和分析“分支函数”来解释这个违反直觉的结果，“分支函数”可以被认为是依赖于活动的分支比率。分支函数的形状意味着对于一系列全局耦合参数，动力学是自维持的。在参数空间的自我维持区域内存在着一条临界线，沿着这条线，动力学采取雪崩的形式，具有通用的尺寸和持续时间尺度，嵌入在不断的活动时间序列中。我们的分析经数值模拟证实，表明抑制可能在可兴奋网络中发挥违反直觉的作用。
The collective dynamics of a network of excitable nodes changes dramatically when inhibitory nodes are introduced. We consider inhibitory nodes which may be activated just like excitatory nodes but, upon activating, decrease the probability of activation of network neighbors. We show that, although the direct effect of inhibitory nodes is to decrease activity, the collective dynamics becomes self-sustaining. We explain this counterintuitive result by defining and analyzing a “branching function” which may be thought of as an activity-dependent branching ratio. The shape of the branching function implies that for a range of global coupling parameters dynamics are self-sustaining. Within the self-sustaining region of parameter space lies a critical line along which dynamics take the form of avalanches with universal scaling of size and duration, embedded in ceaseless timeseries of activity. Our analyses, confirmed by numerical simulation, suggest that inhibition may play a counterintuitive role in excitable networks.