一种生物衍生的感知模型,作为智能系统与其环境之间的接口

W. Freeman
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引用次数: 0

摘要

用适当的状态变量和操作来建模的神经功能主要有两个层次。微观活动可以在单个神经元脉冲序列的方差中看到(>99.9%),这在很大程度上是随机的,与神经元中其他神经元的脉冲序列不相关。宏观活动显示在大于0.1%的总方差的每个神经元,是协变与所有其他神经元在neuropil组成的群体。这是在记录为表面脑电图的树突电位中观察到的。这两个水平的“自发”背景活动是由兴奋性神经元群内的相互兴奋引起的。它的控制点吸引子是由宏观状态设定的,作为一个序参数来调节贡献神经元。点吸引子表现为均匀的白噪声场,可以用脉冲密度的连续时间状态变量来建模。Neuropil包括兴奋性神经元和抑制性神经元。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A biologically derived model for perception to serve as an interface between an intelligent system and its environments
There are two main levels of neural function to be modeled with appropriate state variables and operations. Microscopic activity is seen in the fraction of the variance of single neuron pulse trains (>99.9%) that is largely random and uncorrelated with pulse trains of other neurons in the neuropil. Macroscopic activity is revealed in the >0.1% of the total variance of each neuron that is covariant with all other neurons in neuropil comprising a population. It is observed in dendritic potentials recorded as surface EEGs. The "spontaneous" background activity of neuropil at both levels arises from mutual excitation within a population of excitatory neurons. Its governing point attractor is set by the macroscopic state, which acts as an order parameter to regulate the contributing neurons. The point attractor manifests a homogeneous field of white noise, which can be modeled by a continuous time state variable for pulse density. Neuropil comprises both excitatory and inhibitory neurons.
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