Literature DB >> 18415133

Flow-network adaptation in Physarum amoebae.

Atsushi Tero1, Kenji Yumiki, Ryo Kobayashi, Tetsu Saigusa, Toshiyuki Nakagaki.   

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.

Mesh:

Year:  2008        PMID: 18415133     DOI: 10.1007/s12064-008-0037-9

Source DB:  PubMed          Journal:  Theory Biosci        ISSN: 1431-7613            Impact factor:   1.919


  7 in total

1.  Maze-solving by an amoeboid organism.

Authors:  T Nakagaki; H Yamada; A Tóth
Journal:  Nature       Date:  2000-09-28       Impact factor: 49.962

2.  Path finding by tube morphogenesis in an amoeboid organism.

Authors:  T Nakagaki; H Yamada; A Tóth
Journal:  Biophys Chem       Date:  2001-08-30       Impact factor: 2.352

Review 3.  Smart behavior of true slime mold in a labyrinth.

Authors:  T Nakagaki
Journal:  Res Microbiol       Date:  2001-11       Impact factor: 3.992

4.  Smart network solutions in an amoeboid organism.

Authors:  Toshiyuki Nakagaki; Hiroyasu Yamada; Masahiko Hara
Journal:  Biophys Chem       Date:  2004-01-01       Impact factor: 2.352

5.  Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium.

Authors:  Toshiyuki Nakagaki; Ryo Kobayashi; Yasumasa Nishiura; Tetsuo Ueda
Journal:  Proc Biol Sci       Date:  2004-11-07       Impact factor: 5.349

6.  A mathematical model for adaptive transport network in path finding by true slime mold.

Authors:  Atsushi Tero; Ryo Kobayashi; Toshiyuki Nakagaki
Journal:  J Theor Biol       Date:  2006-07-24       Impact factor: 2.691

7.  Interaction between cell shape and contraction pattern in the Physarum plasmodium.

Authors:  T Nakagaki; H Yamada; T Ueda
Journal:  Biophys Chem       Date:  2000-05-15       Impact factor: 2.352

  7 in total
  8 in total

1.  Physics and the canalization of morphogenesis: a grand challenge in organismal biology.

Authors:  Michelangelo von Dassow; Lance A Davidson
Journal:  Phys Biol       Date:  2011-07-12       Impact factor: 2.583

Review 2.  A brief history of liquid computers.

Authors:  Andrew Adamatzky
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-10       Impact factor: 6.237

3.  A bio-inspired methodology of identifying influential nodes in complex networks.

Authors:  Cai Gao; Xin Lan; Xiaoge Zhang; Yong Deng
Journal:  PLoS One       Date:  2013-06-14       Impact factor: 3.240

4.  Multicommodity routing optimization for engineering networks.

Authors:  Alessandro Lonardi; Mario Putti; Caterina De Bacco
Journal:  Sci Rep       Date:  2022-05-06       Impact factor: 4.996

5.  A bio-inspired method for the constrained shortest path problem.

Authors:  Hongping Wang; Xi Lu; Xiaoge Zhang; Qing Wang; Yong Deng
Journal:  ScientificWorldJournal       Date:  2014-05-14

6.  The role of noise in self-organized decision making by the true slime mold Physarum polycephalum.

Authors:  Bernd Meyer; Cedrick Ansorge; Toshiyuki Nakagaki
Journal:  PLoS One       Date:  2017-03-29       Impact factor: 3.240

7.  Stepwise slime mould growth as a template for urban design.

Authors:  Raphael Kay; Anthony Mattacchione; Charlie Katrycz; Benjamin D Hatton
Journal:  Sci Rep       Date:  2022-01-25       Impact factor: 4.379

8.  Plant hairy root cultures as plasmodium modulators of the slime mold emergent computing substrate Physarum polycephalum.

Authors:  Vincent Ricigliano; Javed Chitaman; Jingjing Tong; Andrew Adamatzky; Dianella G Howarth
Journal:  Front Microbiol       Date:  2015-07-16       Impact factor: 5.640

  8 in total

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