TY - JOUR
T1 - Flow-network adaptation in Physarum amoebae
AU - Tero, Atsushi
AU - Yumiki, Kenji
AU - Kobayashi, Ryo
AU - Saigusa, Tetsu
AU - Nakagaki, Toshiyuki
N1 - Funding Information:
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).
PY - 2008/6
Y1 - 2008/6
N2 - 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.
AB - 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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U2 - 10.1007/s12064-008-0037-9
DO - 10.1007/s12064-008-0037-9
M3 - Article
C2 - 18415133
AN - SCOPUS:43849097416
SN - 1431-7613
VL - 127
SP - 89
EP - 94
JO - Theory in Biosciences
JF - Theory in Biosciences
IS - 2
ER -