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优化皮层神经元的声音特征

Optimizing sound features for cortical neurons.

作者信息

deCharms R C, Blake D T, Merzenich M M

机构信息

Keck Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0732, USA.

出版信息

Science. 1998 May 29;280(5368):1439-43. doi: 10.1126/science.280.5368.1439.

Abstract

The brain's cerebral cortex decomposes visual images into information about oriented edges, direction and velocity information, and color. How does the cortex decompose perceived sounds? A reverse correlation technique demonstrates that neurons in the primary auditory cortex of the awake primate have complex patterns of sound-feature selectivity that indicate sensitivity to stimulus edges in frequency or in time, stimulus transitions in frequency or intensity, and feature conjunctions. This allows the creation of classes of stimuli matched to the processing characteristics of auditory cortical neurons. Stimuli designed for a particular neuron's preferred feature pattern can drive that neuron with higher sustained firing rates than have typically been recorded with simple stimuli. These data suggest that the cortex decomposes an auditory scene into component parts using a feature-processing system reminiscent of that used for the cortical decomposition of visual images.

摘要

大脑的大脑皮层将视觉图像分解为有关定向边缘、方向和速度信息以及颜色的信息。那么,皮层是如何分解所感知到的声音的呢?一种反向相关技术表明,清醒灵长类动物初级听觉皮层中的神经元具有复杂的声音特征选择性模式,这表明它们对频率或时间上的刺激边缘、频率或强度上的刺激转变以及特征结合敏感。这使得能够创建与听觉皮层神经元处理特性相匹配的刺激类别。为特定神经元的偏好特征模式设计的刺激,可以以比通常用简单刺激记录到的更高的持续放电率来驱动该神经元。这些数据表明,皮层使用一种类似于用于视觉图像皮层分解的特征处理系统,将听觉场景分解为各个组成部分。

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