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Sparse coding of birdsong and receptive field structure in songbirds

机译:鸣禽中鸟鸣的稀疏编码和感受野结构

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摘要

Auditory neurons can be characterized by a spectro-temporal receptive field, the kernel of a linear filter model describing the neuronal response to a stimulus. With a view to better understanding the tuning properties of these cells, the receptive fields of neurons in the zebra finch auditory fore-brain are compared to a set of artificial kernels generated under the assumption of sparseness; that is, the assumption that in the sensory pathway only a small number of neurons need be highly active at any time. The sparse kernels are calculated by finding a sparse basis for a corpus of zebra-finch songs. This calculation is complicated by the highly-structured nature of the songs and requires regularization. The sparse kernels and the receptive fields, though differing in some respects, display several significant similarities, which are described by computing qualitative properties such as the seperability index and Q-factor. By comparison, an identical calculation performed on human speech recordings yields a set of kernels which exhibit widely different tuning. These findings imply that Field L neurons are specifically adapted to sparsely encode birdsong and supports the idea that sparsification may be an important element of early sensory processing.
机译:听觉神经元的特征在于光谱时空接受场,线性过滤器模型的核心描述了神经元对刺激的反应。为了更好地理解这些细胞的调节特性,将斑马雀科听觉前脑中神经元的感受野与在稀疏假设下产生的一组人造谷粒进行了比较。也就是说,在感觉途径中,只有少量神经元在任何时候都需要高度活跃的假设。稀疏内核是通过查找斑马雀科歌曲的稀疏基础来计算的。歌曲的高度结构化特性使计算变得复杂,需要进行正规化处理。稀疏内核和接受域尽管在某些方面有所不同,但显示出几个显着相似之处,这些相似之处通过计算定性属性(例如可分离性指数和Q因子)来描述。相比之下,对人类语音记录执行的相同计算会产生一组内核,这些内核表现出很大的差异。这些发现表明,Field L神经元特别适合稀疏地编码鸟鸣,并支持稀疏可能是早期感觉处理的重要元素的想法。

著录项

  • 来源
    《Network》 |2009年第3期|162-177|共16页
  • 作者单位

    School of Mathematics, Trinity College Dublin, Ireland;

    Gatsby Computational Neuroscience Unit, University College London, England School of Mathematics, Trinity College Dublin, Ireland;

    Hearing Research Center and Center for Biodynamics, Department of Biomedical Engineering, Boston University, USA;

    School of Mathematics, Trinity College Dublin, Ireland;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    auditory system; natural scenes; sparse coding; spectro-temporal receptive field;

    机译:听觉系统自然场景;稀疏编码光谱时域;
  • 入库时间 2022-08-18 01:51:59

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