Nonlinearity of coding in primary auditory cortex of the awake ferret.
Nonlinearity of coding in primary auditory cortex of the awake ferret.
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DOI：
10.1016/j.neuroscience.2009.10.034
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发表时间：
2010-01-20
期刊：
影响因子：
3.3
通讯作者：
Depireux DA
中科院分区：
文献类型：
--
作者：
Shechter B;Depireux DA
感觉系统中的神经计算通常被建模为线性系统。该一阶近似值是通过将刺激与其引起的尖峰序列反向关联来计算的。频谱-时间感受野 (STRF) 是该过程的概括，它表征了听觉通路中频率和时间的处理。虽然 STRF 在预测对新刺激的响应的整体过程方面表现良好，但它无法解释神经输出本质上非线性的方面（例如离散事件和非负尖峰率）。我们使用频谱时间调制听觉光栅或波纹测量了清醒雪貂初级听觉皮层 (AI) 中神经元的 STRF。我们通过将这些神经元的响应与其各自的 STRF 预测的响应进行比较来量化这些神经元的非线性程度。人工智能中大多数细胞的反应与用来唤起它们的刺激呈现出平方、非线性关系。因此，这些细胞的非线性是不平凡的，即它不仅仅是尖峰率校正或饱和的结果。通过将非线性建模为多项式静态输出函数，STRF 的预测能力得到显着提高。
Neural computation in sensory systems is often modeled as a linear system. This first order approximation is computed by reverse correlating a stimulus with the spike train it evokes. The spectro-temporal receptive field (STRF) is a generalization of this procedure which characterizes processing in the auditory pathway in both frequency and time. While the STRF performs well in predicting the overall course of the response to a novel stimulus, it is unable to account for aspects of the neural output which are inherently nonlinear (e.g. discrete events and non-negative spike rates). We measured the STRFs of neurons in the primary auditory cortex (AI) of the awake ferret using spectro-temporally modulated auditory gratings, or ripples. We quantified the degree of nonlinearity of these neurons by comparing their responses to the responses predicted from their respective STRFs. The responses of most cells in AI exhibited a squaring, nonlinear relation to the stimuli used to evoke them. Thus, the nonlinearity of these cells was nontrivial, i.e. it was not solely the result of spike rate rectification or saturation. By modeling the nonlinearity as a polynomial static output function, the predictive power of the STRF was significantly improved.
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