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Quantitative Modeling of Neuronal Dynamics in C. elegans

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Neural Information Processing. Theory and Algorithms (ICONIP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6443))

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Abstract

We present a mathematical model to quantitatively describe the neuronal dynamics in Caenorhabditis elegans. Since calcium imaging is a popular technique to visualize the neuronal activity in C. elegans, the model includes the variable of the fluorescence intensity in addition to the membrane potential and the intracellular calcium concentration. The fluorescence intensity is a quantity which is comparable with the experimental data. The parameters in the model are determined to reproduce the neurophysiological experimental data. Our model exhibits good agreement with the data. We apply the model to a neural circuit for chemotaxis and find that the neuronal activity measured by the fluorescence intensity shows quantitatively different behavior from that measured by the membrane potential in some neurons. The difference is discussed from the viewpoint of neuronal mechanisms.

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Authors and Affiliations

  1. Department of Intelligent System Engineering, Ibaraki University, Hitachi, Ibaraki, 316-8511, Japan

    Masahiro Kuramochi & Yuishi Iwasaki

Authors
  1. Masahiro Kuramochi
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  2. Yuishi Iwasaki
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Editor information

Editors and Affiliations

  1. School of Information Technology, Murdoch University, 6150, Murdoch, WA, Australia

    Kok Wai Wong

  2. The Australian National University, 0200, Canberra, ACT, Australia

    B. Sumudu U. Mendis

  3. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Northfields Avenue, 2522, P.O. Box, Wollongong, NSW, Australia

    Abdesselam Bouzerdoum

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© 2010 Springer-Verlag Berlin Heidelberg

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Kuramochi, M., Iwasaki, Y. (2010). Quantitative Modeling of Neuronal Dynamics in C. elegans . In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Theory and Algorithms. ICONIP 2010. Lecture Notes in Computer Science, vol 6443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17537-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-17537-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17536-7

  • Online ISBN: 978-3-642-17537-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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