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Breaking the Excitation-Inhibition Balance Makes the Cortical Network's Space-Time Dynamics Distinguish Simple Visual Scenes

机译:打破兴奋抑制平衡,使皮质网络的时空动力学区分出简单的视觉场景

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Brain dynamics are often taken to be temporal dynamics of spiking and membrane potentials in a balanced network. Almost all evidence for a balanced network comes from recordings of cell bodies of few single neurons, neglecting more than 99% of the cortical network. We examined the space-time dynamics of excitation and inhibition simultaneously in dendrites and axons over four visual areas of ferrets exposed to visual scenes with stationary and moving objects. The visual stimuli broke the tight balance between excitation and inhibition such that the network exhibited longer episodes of net excitation subsequently balanced by net inhibition, in contrast to a balanced network. Locally in all four areas the amount of net inhibition matched the amount of net excitation with a delay of 125 ms. The space-time dynamics of excitation-inhibition evolved to reduce the complexity of neuron interactions over the whole network to a flow on a low-(3)-dimensional manifold within 80 ms. In contrast to the pure temporal dynamics, the low dimensional flow evolved to distinguish the simple visual scenes.
机译:脑动力学通常被视为平衡网络中尖峰和膜电位的时间动力学。几乎所有有关平衡网络的证据都来自少数单个神经元的细胞体记录,而忽略了超过99%的皮质网络。我们在暴露于具有固定和移动物体的视觉场景的雪貂的四个视觉区域中,同时检查了树突和轴突中树突和轴突的激发和抑制的时空动力学。视觉刺激打破了激发与抑制之间的紧密平衡,因此与平衡网络相比,网络表现出更长的净激发发作,随后被净抑制所平衡。在所有四个区域中,局部的净抑制量与净激发的量匹配,延迟为125 ms。激发-抑制的时空动力学演变为在80毫秒内降低整个网络上神经元交互到低(3)维流形上的流的复杂性。与纯粹的时间动力学相反,低维流演变为区分简单的视觉场景。

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