Frequency resolution and spectral integration (critical band analysis) in single units of the cat primary auditory cortex
Frequency resolution and spectral integration (critical band analysis) in single units of the cat primary auditory cortex
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DOI：
10.1007/s003590050146
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发表时间：
1997-12-01
期刊：
影响因子：
--
通讯作者：
Schreiner, CE
中科院分区：
文献类型：
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作者：
Ehret, G;Schreiner, CE
通过细胞外记录不同带宽白色噪声中猫初级听觉皮层（AI）的音调反应，绘制了AI的频率分辨和频谱滤波。单音兴奋调谐曲线，临界带宽，和临界比率被确定为神经元的特征频率和音调水平的函数。单音兴奋性调谐曲线不足以衡量AI中的频率分辨率和频谱滤波，因为它们的形状（在大多数神经元中）与“复杂声音分析的调谐曲线”的形状有很大的偏差，临界带宽的频带限制决定了切是。光谱过滤的感知特性（强度独立性和频率依赖性）被发现在中央和腹侧AI神经元的平均临界带宽。中央和腹侧AI中的神经元达到的最高频率分辨率（最小临界带宽）等于心理物理频率分辨率。背侧AI是特殊的，因为那里的大多数神经元具有与频率分辨率的心理物理特征不相容的响应特性。在AI的任何区域的平均神经元反应中均未发现临界比率的感知特征。看来，频谱整合的方式提出的噪音中的音调的感知的基础是不存在的AI的水平。
Frequency resolution and spectral filtering in the cat primary auditory cortex (AI) were mapped by extracellular recordings of tone responses in white noise of various bandwidths. Single-tone excitatory tuning curves, critical bandwidths, and critical ratios were determined as a function of neuronal characteristic frequency and tone level. Single-tone excitatory tuning curves are inadequate measures of frequency resolution and spectral filtering in the AI, because their shapes (in most neurons) deviated substantially from the shapes of "tuning curves for complex sound analysis", the cut-yes determined by the band limits of the critical bandwidths. Perceptual characteristics of spectral filtering (intensity independence and frequency dependence) were found in average critical bandwidths of neurons from the central and ventral AI. The highest frequency resolution (smallest critical bandwidths) reached by neurons in the central and ventral AI equaled the psychophysical frequency resolution. The dorsal AI is special, since most neurons there had response properties incompatible with psychophysical features of frequency resolution. Perceptual characteristics of critical ratios were not found in the average neuronal responses in any area of the AI. It seems that spectral integration in the way proposed to be the basis for the perception of tones in noise is not present at the level of the AI.