Dynamics of random neural networks with bistable units.
Dynamics of random neural networks with bistable units.
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DOI：
10.1103/physreve.90.062710
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发表时间：
2014-12
期刊：
影响因子：
--
通讯作者：
Abbott LF
中科院分区：
文献类型：
--
作者：
Stern M;Sompolinsky H;Abbott LF
我们构建并分析了一个基于速率的神经网络模型，其中自交互单元代表具有强局部连接性的神经元簇，随机单元间连接反映了远程交互。当足够强时，自相互作用使个体单元相互作用。模拟结果、平均场计算和稳定性分析揭示了该网络的不同动态机制，并确定了其相变在参数空间中的位置。我们确定了一个有趣的动力学制度表现出短暂的，但长期的混沌活动，结合混沌和多个固定点吸引子的功能。
We construct and analyze a rate-based neural network model in which self-interacting units represent clusters of neurons with strong local connectivity and random inter-unit connections reflect long-range interactions. When sufficiently strong, the self-interactions make the individual units bistable. Simulation results, mean-field calculations and stability analysis reveal the different dynamic regimes of this network and identify the locations in parameter space of its phase transitions. We identify an interesting dynamical regime exhibiting transient but long-lived chaotic activity that combines features of chaotic and multiple fixed-point attractors.