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Adaptive biological networks

Fricker, Mark D., Boddy, Lynne, Nakagaki, Toshiyuki and Bebber, Daniel P. 2009. Adaptive biological networks. In: Gross, Thilo and Sayama, Hiroki eds. Adaptive Networks: Theory, Models and Applications, Understanding complex systems, New York: Springer, pp. 51-70. (10.1007/978-3-642-01284-6_4)

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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.

Item Type: Book Section
Date Type: Publication
Status: Published
Schools: Biosciences
Subjects: Q Science > Q Science (General)
Additional Information: Chapter 4
Publisher: Springer
ISBN: 9783642012839
Related URLs:
Last Modified: 04 Jun 2017 03:13
URI: http://orca.cf.ac.uk/id/eprint/18288

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