单一模型解释视觉和听觉皮层前区编码
A Single Model Explains both Visual and Auditory Precortical Coding
摘要：
皮层前神经系统对感官收集的信息进行编码，但编码的驱动原理仍然是一个争论的主题。我们提出了一个模型的视网膜编码是基于三个约束：信息保存，最小化的神经布线，和响应均衡。由此产生的新版本的稀疏主成分分析成功地捕获了一些已知的视网膜编码系统的特性，如中心-环绕感受野，颜色通道，时空响应，对应于大细胞和小细胞途径。此外，当在听觉数据上训练时，相同的模型学习感受野，该感受野通过伽马通滤波器很好地拟合，伽马通滤波器通常用于对皮层前听觉编码进行建模。这表明，有效的编码可能是一个统一的原则，前皮层编码的形式。
英文摘要：
Precortical neural systems encode information collected by the senses, but the driving principles of the encoding used have remained a subject of debate. We present a model of retinal coding that is based on three constraints: information preservation, minimization of the neural wiring, and response equalization. The resulting novel version of sparse principal components analysis successfully captures a number of known characteristics of the retinal coding system, such as center-surround receptive fields, color opponency channels, and spatiotemporal responses that correspond to magnocellular and parvocellular pathways. Furthermore, when trained on auditory data, the same model learns receptive fields well fit by gammatone filters, commonly used to model precortical auditory coding. This suggests that efficient coding may be a unifying principle of precortical encoding across modalities.
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