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Auditory information coding by modeled cochlear nucleus neurons

机译:建模的耳蜗神经元神经元的听觉信息编码

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摘要

In this paper we use information theory to quantify the information in the output spike trains of modeled cochlear nucleus globular bushy cells (GBCs). GBCs are part of the sound localization pathway. They are known for their precise temporal processing, and they code amplitude modulations with high fidelity. Here we investigated the information transmission for a natural sound, a recorded vowel. We conclude that the maximum information transmission rate for a single neuron was close to 1,050 bits/s, which corresponds to a value of approximately 5.8 bits per spike. For quasi-periodic signals like voiced speech, the transmitted information saturated as word duration increased. In general, approximately 80% of the available information from the spike trains was transmitted within about 20 ms. Transmitted information for speech signals concentrated around formant frequency regions. The efficiency of neural coding was above 60% up to the highest temporal resolution we investigated (20 us). The increase in transmitted information to that precision indicates that these neurons are able to code information with extremely high fidelity, which is required for sound localization. On the other hand, only 20% of the information was captured when the temporal resolution was reduced to 4 ms. As the temporal resolution of most speech recognition systems is limited to less than 10 ms, this massive information loss might be one of the reasons which are responsible for the lack of noise robustness of these systems.
机译:在本文中,我们使用信息论来量化建模的耳蜗核球状丛生细胞(GBC)的输出峰值序列中的信息。 GBC是声音定位路径的一部分。它们以精确的时间处理而著称,并以高保真度编码幅度调制。在这里,我们研究了自然声音(录制的元音)的信息传输。我们得出的结论是,单个神经元的最大信息传输速率接近1,050比特/秒,相当于每个尖峰约5.8比特的值。对于诸如语音之类的准周期信号,随着单词持续时间的增加,传输的信息饱和。通常,来自尖峰序列的可用信息的大约80%在大约20毫秒内传输。语音信号的传输信息集中在共振峰频率区域附近。直到我们调查的最高时间分辨率(20微秒),神经编码的效率都超过60%。传输信息的精确度增加表明这些神经元能够以极高的保真度编码信息,这是声音定位所必需的。另一方面,当时间分辨率降低到4 ms时,仅捕获了20%的信息。由于大多数语音识别系统的时间分辨率限制在10 ms以内,因此大量的信息丢失可能是造成这些系统缺乏噪声鲁棒性的原因之一。

著录项

  • 来源
    《Journal of Computational Neuroscience》 |2011年第3期|p.529-542|共14页
  • 作者单位

    Institute of Medical Engineering, Technische Universitat Miinchen, BoltzmannstraBe 11, 85748 Garching, Germany,Infineon Technologies AG, Neubiberg, Germany,Bernstein Center for Computational Neuroscience,Munich, Germany;

    Institute of Medical Engineering, Technische Universitat Miinchen, BoltzmannstraBe 11, 85748 Garching, Germany,Bernstein Center for Computational Neuroscience,Munich, Germany;

    Max Plank Institute of Neurobiology, Munich, Germany,Bernstein Center for Computational Neuroscience,Munich, Germany;

    Institute of Medical Engineering, Technische Universitat Miinchen, BoltzmannstraBe 11, 85748 Garching, Germany,Infineon Technologies AG, Neubiberg, Germany,Bernstein Center for Computational Neuroscience,Munich, Germany;

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

    onset neuron; information theory; neural coding; automatic speech recognition; temporal resolution;

    机译:发作神经元信息论;神经编码;自动语音识别;时间分辨率;

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