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刺激光谱对比度对蜗背侧核神经元感受野的影响。

Effects of stimulus spectral contrast on receptive fields of dorsal cochlear nucleus neurons.

作者信息

Reiss Lina A J, Bandyopadhyay Sharba, Young Eric D

机构信息

Center for Hearing and Balance, Johns Hopkins University, Baltimore, MD 21205, USA.

出版信息

J Neurophysiol. 2007 Oct;98(4):2133-43. doi: 10.1152/jn.01239.2006. Epub 2007 Aug 1.

Abstract

Neurons in the dorsal cochlear nucleus (DCN) exhibit strong nonlinearities in spectral processing. Low-order models that transform the stimulus spectrum into discharge rate using a combination of first- and second-order weighting of the spectrum (quadratic models) usually fail to predict responses to novel stimuli for principal neurons in the DCN, even though they work well in ventral cochlear nucleus. Here we investigate the effects of spectral contrast on the performance of such models. Typically, the models fail for stimuli with natural-sound-like spectral contrasts (~12 dB), but have good prediction performance at small (3-dB) contrasts. The weights also typically increase substantially in amplitude at smaller spectral contrast. These changes in weight size with contrast are partly inherited from similar effects seen in auditory nerve fibers, but there must be additional effects from inhibitory circuits in the DCN. These results provide insight into the reasons for the poor performance of spectrotemporal receptive field (STRF) models in predicting responses of auditory neurons. Because the general shapes of the weights do not change between low and high contrast, they also suggest that STRFs may capture meaningful properties of neural receptive fields, even though they do not do well at predicting responses.

摘要

耳蜗背核(DCN)中的神经元在频谱处理方面表现出强烈的非线性。使用频谱的一阶和二阶加权组合(二次模型)将刺激频谱转换为放电率的低阶模型,通常无法预测DCN中主要神经元对新刺激的反应,尽管它们在耳蜗腹核中表现良好。在此,我们研究频谱对比度对此类模型性能的影响。通常,这些模型对于具有自然声音般频谱对比度(约12分贝)的刺激会失效,但在小对比度(3分贝)时具有良好的预测性能。权重在较小的频谱对比度下通常也会在幅度上大幅增加。权重大小随对比度的这些变化部分继承自听觉神经纤维中观察到的类似效应,但DCN中的抑制性回路肯定还有其他作用。这些结果为理解频谱时间感受野(STRF)模型在预测听觉神经元反应时性能不佳的原因提供了线索。由于权重的一般形状在低对比度和高对比度之间没有变化,这也表明STRF可能捕捉到了神经感受野的有意义属性,尽管它们在预测反应方面表现不佳。

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