The impact of spike-frequency adaptation on balanced network dynamics
The impact of spike-frequency adaptation on balanced network dynamics
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DOI：
10.1007/s11571-018-9504-2
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发表时间：
2019-02-01
影响因子：
3.7
通讯作者：
Li, Sida
中科院分区：
文献类型：
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作者：
Barranca, Victor J.;Huang, Han;Li, Sida
强兴奋性和抑制性神经元输入之间的动态平衡被假设在大脑的信息处理中起着关键作用。虽然有证据表明在几个皮质区域和理想化的神经元网络模型中存在平衡的操作机制，但平衡网络理论与更多生理神经元建模假设相协调非常重要。在这项工作中，我们研究了尖峰频率适应的影响，广泛观察到大脑中的神经元，平衡的动态。我们将适应二进制和集成和消防神经网络模型，分析适应在大的网络限制的理论效果，并进行了广泛的数值研究的模型适应参数空间。我们的分析表明，即使整个网络表现出适应性，适度的适应强度也能很好地保持平衡。在常见的生理情况下，只有兴奋性神经元进行适应，我们表明，平衡的操作制度，实际上扩大相对于非自适应的情况下。我们假设尖峰频率适应可能是通过进化选择的，以在不同的认知操作状态下稳健地促进平衡的动态。
A dynamic balance between strong excitatory and inhibitory neuronal inputs is hypothesized to play a pivotal role in information processing in the brain. While there is evidence of the existence of a balanced operating regime in several cortical areas and idealized neuronal network models, it is important for the theory of balanced networks to be reconciled with more physiological neuronal modeling assumptions. In this work, we examine the impact of spike-frequency adaptation, observed widely across neurons in the brain, on balanced dynamics. We incorporate adaptation into binary and integrate-and-fire neuronal network models, analyzing the theoretical effect of adaptation in the large network limit and performing an extensive numerical investigation of the model adaptation parameter space. Our analysis demonstrates that balance is well preserved for moderate adaptation strength even if the entire network exhibits adaptation. In the common physiological case in which only excitatory neurons undergo adaptation, we show that the balanced operating regime in fact widens relative to the non-adaptive case. We hypothesize that spike-frequency adaptation may have been selected through evolution to robustly facilitate balanced dynamics across diverse cognitive operating states.