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多个感觉神经元的刺激编码与特征提取。

Stimulus encoding and feature extraction by multiple sensory neurons.

作者信息

Krahe Rüdiger, Kreiman Gabriel, Gabbiani Fabrizio, Koch Christof, Metzner Walter

机构信息

Department of Biology, University of California, Riverside, California 92521, USA.

出版信息

J Neurosci. 2002 Mar 15;22(6):2374-82. doi: 10.1523/JNEUROSCI.22-06-02374.2002.

Abstract

Neighboring cells in topographical sensory maps may transmit similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the performance of single cells is a very important question for understanding the functioning of the nervous system. To tackle this problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells constitute the output neurons of the first central nervous stage of electrosensory processing. Using random amplitude modulations (RAMs) of a mimic of the fish's own electric field within behaviorally relevant frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To quantify the encoding of the RAM time course, we estimated the stimuli from simultaneously recorded spike trains and found significant improvements over single spike trains. The quality of stimulus reconstruction, however, was still inferior to the one measured for single primary sensory afferents. In an analysis of feature extraction, we found that spikes of pyramidal cell pairs coinciding within a time window of a few milliseconds performed significantly better at detecting upstrokes and downstrokes of the stimulus compared with isolated spikes and even spike bursts of single cells. Coincident spikes can thus be considered "distributed bursts." Our results suggest that stimulus encoding by primary sensory afferents is transformed into feature extraction at the next processing stage. There, stimulus-induced coincident activity can improve the extraction of behaviorally relevant features from the stimulus.

摘要

地形感觉图谱中的相邻细胞可能会将相似的信息传递到更高一级的处理阶段。附近神经元群体的信息传递与单个细胞的表现相比如何,这是理解神经系统功能的一个非常重要的问题。为了解决这个问题,我们通过对弱电鱼后脑同时记录的电感觉锥体细胞对的刺激编码和特征提取性能进行了量化。这些细胞构成了电感觉处理的第一个中枢神经阶段的输出神经元。使用行为相关频段内鱼自身电场模拟物的随机幅度调制(RAMs),我们发现具有重叠感受野的锥体细胞表现出强烈的刺激诱导相关性。为了量化RAM时间进程的编码,我们从同时记录的尖峰序列中估计刺激,发现与单个尖峰序列相比有显著改善。然而,刺激重建的质量仍然低于对单个初级感觉传入神经测量的质量。在特征提取分析中,我们发现,与单个细胞的孤立尖峰甚至尖峰爆发相比,在几毫秒的时间窗口内重合的锥体细胞对的尖峰在检测刺激的上升和下降方面表现明显更好。因此,重合的尖峰可以被视为“分布式爆发”。我们的结果表明,初级感觉传入神经的刺激编码在下一个处理阶段被转化为特征提取。在那里,刺激诱导的重合活动可以改善从刺激中提取行为相关特征的能力。

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