Reliability of Layered Neural Oscillator Networks

Kevin K. Lin, E. Shea-Brown, L. Young
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引用次数: 23

Abstract

We study the reliability of large networks of coupled neural oscillators in response to fluctuating stimuli. Reliability means that a stimulus elicits essentially identical responses upon repeated presentations. We view the problem on two scales: neuronal reliability, which concerns the repeatability of spike times of individual neurons embedded within a network, and pooled-response reliability, which addresses the repeatability of the total synaptic output from the network. We find that individual embedded neurons can be reliable or unreliable depending on network conditions, whereas pooled responses of sufficiently large networks are mostly reliable. We study also the effects of noise, and find that some types affect reliability more seriously than others.
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层状神经振荡器网络的可靠性
我们研究了大型耦合神经振荡器网络响应波动刺激的可靠性。可靠性指的是一个刺激物在重复呈现时能引起本质上相同的反应。我们从两个角度来看待这个问题:神经元可靠性,它关注嵌入网络中的单个神经元峰值时间的可重复性;池响应可靠性,它关注网络中总突触输出的可重复性。我们发现单个嵌入的神经元可以是可靠的,也可以是不可靠的,这取决于网络的条件,而足够大的网络的池响应大多是可靠的。我们还研究了噪声的影响,发现某些类型对可靠性的影响比其他类型更严重。
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