Abstract：
Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their \"paradoxical response\", where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation-inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation-inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.
摘要：
强抑制性循环连接可以减少神经网络变得不稳定的趋势。这被称为抑制性稳定；由于其不稳定的兴奋性递归连接而在没有强抑制性反馈的情况下不稳定的网络被称为抑制稳定网络（ISN）。ISN的特征之一是它们的“矛盾反应”，其中，用额外的兴奋性输入干扰抑制性神经元会导致其活动在时间延迟后减少，而不是增加其活动。这里,我们建立了一个跨皮层不同层的神经元群模型。在每一层中，有一个群体的抑制性神经元和一个群体的兴奋性神经元。模型中不同群体之间的连接权重来自艾伦研究所提供的突触生理学数据库。该模型显示了皮质不同层的激发-抑制平衡梯度，与较深层相比，表层的抑制性更强。为了调查跨不同层的ISN的存在，我们测量了干扰抑制群体后模型中神经群体的膜电位。结果表明，模型中的第2/3层不在ISN体系中运行，而第4层和第5层在ISN体系中运行。这些结果与神经生理学发现一致，这些发现探索了跨皮质不同层的ISN的存在。结果表明，在皮质的不同层可能存在抑制稳定的系统宏观梯度，这取决于激发-抑制平衡的水平。并且矛盾响应的强度随着模型更接近分叉点而增加。
