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Flow-network adaptation in Physarum amoebae

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Abstract

Understanding how biological systems solve problems could aid the design of novel computational methods. Information processing in unicellular eukaryotes is of particular interest, as these organisms have survived for more than a billion years using a simple system. The large amoeboid plasmodium of Physarum is able to solve a maze and to connect multiple food locations via a smart network. This study examined how Physarum amoebae compute these solutions. The mechanism involves the adaptation of the tubular body, which appears to be similar to a network, based on cell dynamics. Our model describes how the network of tubes expands and contracts depending on the flux of protoplasmic streaming, and reproduces experimental observations of the behavior of the organism. The proposed algorithm based on Physarum is simple and powerful.

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Abbreviations

FS:

Food source

FT:

Fault tolerance

SMT:

Steiner minimum tree

TL:

Total length of the tube network

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Acknowledgments

This research was supported by Grants-in-aid for Scientific Research (nos. 18650054, 18654022 and 19340023) from the Japan Society for the Promotion of Science and by a Research Grant from the Human Frontier Science Program (no. RGP51/2007).

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Authors and Affiliations

  1. Research Institute for Electronic Science, Hokkaido University, Sapporo, 060-0812, Japan

    Atsushi Tero & Toshiyuki Nakagaki

  2. Department of Mathematics and Life Sciences, Hiroshima University, Higashi-Hiroshima, 739-8626, Japan

    Kenji Yumiki & Ryo Kobayashi

  3. School of Engineering, Hokkaido University, Sapporo, 060-8628, Japan

    Tetsu Saigusa

  4. Creative Research Initiative SOUSEI, Hokkaido University, Sapporo, 001-0821, Japan

    Toshiyuki Nakagaki

Authors
  1. Atsushi Tero
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  2. Kenji Yumiki
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  3. Ryo Kobayashi
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  4. Tetsu Saigusa
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  5. Toshiyuki Nakagaki
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Corresponding author

Correspondence to Toshiyuki Nakagaki.

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Tero, A., Yumiki, K., Kobayashi, R. et al. Flow-network adaptation in Physarum amoebae. Theory Biosci. 127, 89–94 (2008). https://doi.org/10.1007/s12064-008-0037-9

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  • DOI: https://doi.org/10.1007/s12064-008-0037-9

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