Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity.
Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity.
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DOI：
10.3389/fncom.2014.00068
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发表时间：
2014
影响因子：
3.2
通讯作者：
Pfeiffer M
中科院分区：
文献类型：
--
作者：
Binas J;Rutishauser U;Indiveri G;Pfeiffer M
赢家通吃（WTA）网络是兴奋性和抑制性神经元的循环连接群体，代表了实现皮层计算的有前途的候选微电路。WTA可以执行强大的计算，从信号恢复到状态相关处理。然而，这样的网络需要微调的连接参数，以保持稳定的操作制度内的网络动态。在这篇文章中，我们将展示如何通过生物学上合理的可塑性机制，同时对网络的所有兴奋性和抑制性突触的相互作用，这种稳定性可以自主出现。从三重峰发放时间依赖塑性模型出发，导出了一个依赖于权重的塑性规则，并利用收缩理论分析了该规则在平均场情形下的稳定性。我们的主要结果提供了简单的约束的可塑性规则参数，而不是对权重本身，这保证了稳定的WTA行为。我们提出的塑料网络能够适应不断变化的输入条件，并动态地调整其增益，因此表现出自我稳定机制，这对于在互连子单元的大型网络中保持稳定运行至关重要。我们展示了分布式神经组件如何在尊重神经布线的解剖学约束的同时，自主地调整其参数以实现稳定的WTA功能。
Winner-Take-All (WTA) networks are recurrently connected populations of excitatory and inhibitory neurons that represent promising candidate microcircuits for implementing cortical computation. WTAs can perform powerful computations, ranging from signal-restoration to state-dependent processing. However, such networks require fine-tuned connectivity parameters to keep the network dynamics within stable operating regimes. In this article, we show how such stability can emerge autonomously through an interaction of biologically plausible plasticity mechanisms that operate simultaneously on all excitatory and inhibitory synapses of the network. A weight-dependent plasticity rule is derived from the triplet spike-timing dependent plasticity model, and its stabilization properties in the mean-field case are analyzed using contraction theory. Our main result provides simple constraints on the plasticity rule parameters, rather than on the weights themselves, which guarantee stable WTA behavior. The plastic network we present is able to adapt to changing input conditions, and to dynamically adjust its gain, therefore exhibiting self-stabilization mechanisms that are crucial for maintaining stable operation in large networks of interconnected subunits. We show how distributed neural assemblies can adjust their parameters for stable WTA function autonomously while respecting anatomical constraints on neural wiring.
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影响因子：
64.8
作者：
Bock, Davi D.;Lee, Wei-Chung Allen;Kerlin, Aaron M.;Andermann, Mark L.;Hood, Greg;Wetzel, Arthur W.;Yurgenson, Sergey;Soucy, Edward R.;Kim, Hyon Suk;Reid, R. Clay
通讯作者：
Reid, R. Clay
影响因子：
1.9
作者：
FUKUSHIMA, K
通讯作者：
FUKUSHIMA, K
影响因子：
3.2
作者：
Chen Y;McKinstry JL;Edelman GM
通讯作者：
Edelman GM
DOI：
10.1177/1073858413479824
发表时间：
2013-08
期刊：
The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry
影响因子：
--
作者：
Chen JL;Nedivi E
通讯作者：
Nedivi E
影响因子：
1.9
作者：
KOHONEN, T
通讯作者：
KOHONEN, T