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经典听觉皮层回路中的分层计算。

Hierarchical computation in the canonical auditory cortical circuit.

机构信息

University of California, San Francisco/University of California, Berkeley Bioengineering Graduate Group, W. M. Keck Foundation Center for Integrative Neuroscience, and Coleman Memorial Laboratory, Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, CA 94143, USA.

出版信息

Proc Natl Acad Sci U S A. 2009 Dec 22;106(51):21894-9. doi: 10.1073/pnas.0908383106. Epub 2009 Nov 16.

Abstract

Sensory cortical anatomy has identified a canonical microcircuit underlying computations between and within layers. This feed-forward circuit processes information serially from granular to supragranular and to infragranular layers. How this substrate correlates with an auditory cortical processing hierarchy is unclear. We recorded simultaneously from all layers in cat primary auditory cortex (AI) and estimated spectrotemporal receptive fields (STRFs) and associated nonlinearities. Spike-triggered averaged STRFs revealed that temporal precision, spectrotemporal separability, and feature selectivity varied with layer according to a hierarchical processing model. STRFs from maximally informative dimension (MID) analysis confirmed hierarchical processing. Of two cooperative MIDs identified for each neuron, the first comprised the majority of stimulus information in granular layers. Second MID contributions and nonlinear cooperativity increased in supragranular and infragranular layers. The AI microcircuit provides a valid template for three independent hierarchical computation principles. Increases in processing complexity, STRF cooperativity, and nonlinearity correlate with the synaptic distance from granular layers.

摘要

感觉皮层解剖学确定了一个典型的微电路,该微电路是层间和层内计算的基础。这个前馈电路从颗粒层到超颗粒层再到颗粒下层串行地处理信息。这个基质与听觉皮层处理层次结构有何关联尚不清楚。我们在猫的初级听觉皮层(AI)中同时记录所有层的信息,并估计了频谱时间感受野(STRF)和相关的非线性。基于尖峰触发的平均 STRF 表明,根据分层处理模型,时间精度、频谱时间可分离性和特征选择性随层而变化。来自最大信息量维度(MID)分析的 STRF 证实了分层处理。对于每个神经元确定的两个协作 MID 中,第一个包含了颗粒层中大部分刺激信息。第二个 MID 的贡献和非线性协同作用在上颗粒层和颗粒下层中增加。AI 微电路为三个独立的分层计算原则提供了有效的模板。处理复杂性、STRF 协同性和非线性的增加与从颗粒层的突触距离相关。

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