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蝙蝠听觉神经系统如何在复杂环境中识别昆虫

丁炯 张宏 童勤业

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Citation:

蝙蝠听觉神经系统如何在复杂环境中识别昆虫

丁炯, 张宏, 童勤业

A probable explanation for bat's auditory nervous system identifying inserts in the complex surrounding

Ding Jiong, Zhang Hong, Tong Qin-Ye
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  • 生物声纳的高灵敏度和高可靠性一直是仿生设计所追求的目标, 然而至今仍没有一个令人信服的物理模型能很好得解释生物声纳优越性能的原因, 其主要是缺乏对动物听觉系统神经信息编码的认识. 本文从蝙蝠听觉神经系统的生理结构出发, 用圆映射和符号动力学方法讨论了蝙蝠听觉神经系统在复杂环境中处理多普勒信号的一种可能性方案, 并通过计算机仿真证明了其合理性. 针对蝙蝠神经系统的不稳定性, 用符号动力学的方法分析神经系统信息处理的机理具有良好的鲁棒性和高灵敏度. 这种新的信号处理方法的研究, 为生物声纳信号的处理过程的进一步认识提供了一种新的解释.
    The high sensitivity and reliability of the biosonar have attracted many bionic scientists' attention. However, there is no convincing physical model to explain the reasons of the superior performance of biosonar. The main reason is that the neuron coding of the nervous system is still uncertain. Based on the physiological structure of the bat's auditory nervous system, a probable explanation is proposed to discuss the Doppler signal process with the principle of circle maps and symbolic dynamics. Through the computer simulation, the rationality of this method is proved. For the instability of the nervous system, using symbolic dynamics to analye the mechanism of the neural information processing has high sensitivity and robustness. It is expected that the research of this new explanation will be able to promote the understanding of the biosonar signal processing and its applications.
    • 基金项目: 国家自然科学基金(批准号:60871085)资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 60871085).
    [1]

    Brock F M 2011 Science 333 528

    [2]

    Nobuo S 1990 Scientific American 262 60

    [3]

    Fontaine B, Peremans H 2009 J. Acoust. Soc. America 125 3052

    [4]

    Sanderson M I, Neretti N, Intrator N, Simmons J A 2003 J. Acoust. Soc. America 114 1648

    [5]

    Neretti N, Intrator N, Sanderson M I, Simmons J A, Cooper L N 2003 OCEANS 2003 Proceedings (San Diego, CA, USA: IEEE Xplore) p604

    [6]

    Müller R 2003 Network: Computation in Neural Systems 14 595

    [7]

    O'Neill W E, Nobuo S 1979 Science 203 69

    [8]

    Long C V, Flint J A, Lepper P A 2010 J. Acoust. Soc. America 128 2238

    [9]

    Ma X F, Suga N 2009 J. Neurosci 29 4888

    [10]

    Bear M F, Conors B W, Paradiso M A 2001 Neuroscience Exploring the Brain (2nd Ed.) (London: Lippincott Williams & Wilkins Inc) p350-p395

    [11]

    Nicholls J G, Martin A R, Wallace B G, Fuchs P A 2001 From Neuron to Brain (4th Ed) (Sunderland: Sinauer Associates, Inc) p429-442

    [12]

    Rose J E, Hind J E, Anderson D J, Brugge J F 1971 Journal of Neurophysiology 34 685

    [13]

    Edelman G M, Gally J A 2001 The National Academy of Sciences 98 13763

    [14]

    Zhang H, Liu S F, Qian M Q, Tong Q Y 2009 Acta Phys. Sin 58 7322 (in Chinese) [张宏, 刘淑芳, 钱鸣奇, 童勤业 2009 物理学报 58 7322]

    [15]

    Scheper V, Paasche G, Miller J M, Warnecke A, Berkingali N, Lenarz T, Stover T 2009 Journal of neuroscience resaerch 87 1389

    [16]

    Nayagam B A, Muniak M A, Ryugo D K 2011 Hearing Research 278 2

    [17]

    Berglund A M, Ryugo D K 1987 The Journal of Comparative Neurology 255 560

    [18]

    Mo J, Li Y Y, Wei C L, Yang M H, Gu H G, Qu S X, Ren W 2010 Chinese Phys. B 19 080513

    [19]

    Wang T T, Li W L, Chen Z H, Miao L 2010 Chinese Phys. B 19 076401

    [20]

    Zhou Z L 1997 System of Symbolic Dynamics (Shanghai: Shanghai Scientific and Technological Education Publishing House) (in Chinese) [周作领 1997 符号动力系统 (上海: 上海科技出版社)]

    [21]

    Zhang Z J, Chen S G 1989 Acta Phys. Sin. 38 1 (in Chinese) [张建忠, 陈式刚 1989 物理学报 38 1]

    [22]

    Zhang W Y, Li J M 2011 Chin. Phys. B 20 030701

    [23]

    Lakshmanan S, Balasubramaniam P 2011 Chin. Phys. B 20 040204

    [24]

    Tong Q Y, Qian M Q, Li X, Guo H J, Han X P, Li G, Shen G Y 2006 Sci. Chin. E 36 449 (in Chinese) [童勤业, 钱鸣奇, 郭宏基, 韩晓鹏, 李光, 沈公羽 2006 中国科学 E 36 449]

    [25]

    Tononi G, Edelman G M 1998 Science 282 1846

    [26]

    Edelman G M 1987 Neural Drawinism (New York: Basic Books)

    [27]

    Sporns O, Tononi G, Edelman G M 2000 Neural Networks 13 909

    [28]

    Cathy J P, Karl J F 2011 Trends in Cognitive Sciences 6 416

    [29]

    Zhang H, Fang L P, Tong Q Y 2007 Acta Phys. Sin. 56 7339 (in Chinese) [张宏, 方路平, 童勤业 2007 物理学报 56 7339]

    [30]

    Men C, Wang J, Qin Y M, Wei X L, Che Y Q, Deng Bin 2011 Chin. Phys. B 20 128704

  • [1]

    Brock F M 2011 Science 333 528

    [2]

    Nobuo S 1990 Scientific American 262 60

    [3]

    Fontaine B, Peremans H 2009 J. Acoust. Soc. America 125 3052

    [4]

    Sanderson M I, Neretti N, Intrator N, Simmons J A 2003 J. Acoust. Soc. America 114 1648

    [5]

    Neretti N, Intrator N, Sanderson M I, Simmons J A, Cooper L N 2003 OCEANS 2003 Proceedings (San Diego, CA, USA: IEEE Xplore) p604

    [6]

    Müller R 2003 Network: Computation in Neural Systems 14 595

    [7]

    O'Neill W E, Nobuo S 1979 Science 203 69

    [8]

    Long C V, Flint J A, Lepper P A 2010 J. Acoust. Soc. America 128 2238

    [9]

    Ma X F, Suga N 2009 J. Neurosci 29 4888

    [10]

    Bear M F, Conors B W, Paradiso M A 2001 Neuroscience Exploring the Brain (2nd Ed.) (London: Lippincott Williams & Wilkins Inc) p350-p395

    [11]

    Nicholls J G, Martin A R, Wallace B G, Fuchs P A 2001 From Neuron to Brain (4th Ed) (Sunderland: Sinauer Associates, Inc) p429-442

    [12]

    Rose J E, Hind J E, Anderson D J, Brugge J F 1971 Journal of Neurophysiology 34 685

    [13]

    Edelman G M, Gally J A 2001 The National Academy of Sciences 98 13763

    [14]

    Zhang H, Liu S F, Qian M Q, Tong Q Y 2009 Acta Phys. Sin 58 7322 (in Chinese) [张宏, 刘淑芳, 钱鸣奇, 童勤业 2009 物理学报 58 7322]

    [15]

    Scheper V, Paasche G, Miller J M, Warnecke A, Berkingali N, Lenarz T, Stover T 2009 Journal of neuroscience resaerch 87 1389

    [16]

    Nayagam B A, Muniak M A, Ryugo D K 2011 Hearing Research 278 2

    [17]

    Berglund A M, Ryugo D K 1987 The Journal of Comparative Neurology 255 560

    [18]

    Mo J, Li Y Y, Wei C L, Yang M H, Gu H G, Qu S X, Ren W 2010 Chinese Phys. B 19 080513

    [19]

    Wang T T, Li W L, Chen Z H, Miao L 2010 Chinese Phys. B 19 076401

    [20]

    Zhou Z L 1997 System of Symbolic Dynamics (Shanghai: Shanghai Scientific and Technological Education Publishing House) (in Chinese) [周作领 1997 符号动力系统 (上海: 上海科技出版社)]

    [21]

    Zhang Z J, Chen S G 1989 Acta Phys. Sin. 38 1 (in Chinese) [张建忠, 陈式刚 1989 物理学报 38 1]

    [22]

    Zhang W Y, Li J M 2011 Chin. Phys. B 20 030701

    [23]

    Lakshmanan S, Balasubramaniam P 2011 Chin. Phys. B 20 040204

    [24]

    Tong Q Y, Qian M Q, Li X, Guo H J, Han X P, Li G, Shen G Y 2006 Sci. Chin. E 36 449 (in Chinese) [童勤业, 钱鸣奇, 郭宏基, 韩晓鹏, 李光, 沈公羽 2006 中国科学 E 36 449]

    [25]

    Tononi G, Edelman G M 1998 Science 282 1846

    [26]

    Edelman G M 1987 Neural Drawinism (New York: Basic Books)

    [27]

    Sporns O, Tononi G, Edelman G M 2000 Neural Networks 13 909

    [28]

    Cathy J P, Karl J F 2011 Trends in Cognitive Sciences 6 416

    [29]

    Zhang H, Fang L P, Tong Q Y 2007 Acta Phys. Sin. 56 7339 (in Chinese) [张宏, 方路平, 童勤业 2007 物理学报 56 7339]

    [30]

    Men C, Wang J, Qin Y M, Wei X L, Che Y Q, Deng Bin 2011 Chin. Phys. B 20 128704

计量
  • 文章访问数:  5118
  • PDF下载量:  596
  • 被引次数: 0
出版历程
  • 收稿日期:  2011-12-22
  • 修回日期:  2012-01-12
  • 刊出日期:  2012-08-05

蝙蝠听觉神经系统如何在复杂环境中识别昆虫

  • 1. 浙江大学生物医学工程系, 杭州 310027;
  • 2. 浙江大学生物医学工程教育部重点实验室, 杭州 310027;
  • 3. 浙江大学神经信息学中心, 杭州 310027
    基金项目: 国家自然科学基金(批准号:60871085)资助的课题.

摘要: 生物声纳的高灵敏度和高可靠性一直是仿生设计所追求的目标, 然而至今仍没有一个令人信服的物理模型能很好得解释生物声纳优越性能的原因, 其主要是缺乏对动物听觉系统神经信息编码的认识. 本文从蝙蝠听觉神经系统的生理结构出发, 用圆映射和符号动力学方法讨论了蝙蝠听觉神经系统在复杂环境中处理多普勒信号的一种可能性方案, 并通过计算机仿真证明了其合理性. 针对蝙蝠神经系统的不稳定性, 用符号动力学的方法分析神经系统信息处理的机理具有良好的鲁棒性和高灵敏度. 这种新的信号处理方法的研究, 为生物声纳信号的处理过程的进一步认识提供了一种新的解释.

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