Quantitative Modeling of Neuronal Dynamics in

Kuramochi, Masahiro; Iwasaki, Yuishi

doi:10.1007/978-3-642-17537-4_3

Quantitative Modeling of Neuronal Dynamics in C. elegans

Masahiro Kuramochi¹⁹ &
Yuishi Iwasaki¹⁹

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

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.

Keywords

C. elegans
membrane potential
intracellular calcium concentration
fluorescence intensity
chemotaxis circuit

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Authors and Affiliations

Department of Intelligent System Engineering, Ibaraki University, Hitachi, Ibaraki, 316-8511, Japan
Masahiro Kuramochi & Yuishi Iwasaki

Authors

Masahiro Kuramochi
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Yuishi Iwasaki
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Editors and Affiliations

School of Information Technology, Murdoch University, 6150, Murdoch, WA, Australia
Kok Wai Wong
The Australian National University, 0200, Canberra, ACT, Australia
B. Sumudu U. Mendis
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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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
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