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Adaptive Biological Networks

  • Mark D. Fricker
  • Lynne Boddy
  • Toshiyuki Nakagaki
  • Daniel P. Bebber
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

Mycelial fungi and acellular slime molds grow as self-organized networks that explore new territory to search for resources, whilst maintaining an effective internal transport system in the face of continuous attack or random damage. These networks adapt during development by selective reinforcement of major transport routes and recycling of the intervening redundant material to support further extension. In the case of fungi, the predicted transport efficiency of the weighted network is better than evenly weighted networks with the same topology, or standard reference networks. Experimentally, nutrient movement can be mapped using radio-tracers and scintillation imaging, and shows more complex transport dynamics, with synchronized oscillations and switching between different pre-existing routes. The significance of such dynamics to the interplay between transport control and topology is not yet known. In a similar manner, the resilience of the network can be tested in silico and experimentally using grazing invertebrates. Both approaches suggest that the same structures that confer good transport efficiency also show good resilience, with the persistence of a centrally connected core. The acellular slime mold, Physarum polycephalum also forms efficient networks between food sources, with a good balance between total cost, transit distance and fault tolerance. In this case, network formation can be captured by a mathematical model driven by non-linear positive reinforcement of tubes with high flux, and decay of tubes with low flux. We argue that organization of these simple planar networks has been honed by evolution, and they may exemplify potential solutions to real-world compromises between search strategy, transport efficiency, resilience and cost in other domains.

Keywords

Minimal Span Tree Weighted Network Steiner Point Slime Mold Physarum Polycephalum 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Mark D. Fricker
    • 1
  • Lynne Boddy
    • 2
  • Toshiyuki Nakagaki
    • 3
  • Daniel P. Bebber
    • 4
  1. 1.Department of Plant SciencesUniversity of OxfordOxfordUK
  2. 2.Cardiff School of BiosciencesCardiff UniversityCardiffUK
  3. 3.Research Institute for Electronic ScienceHokkaido UniversitySapporoJapan
  4. 4.Department of Plant SciencesUniversity of OxfordOxfordUK

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