Cellular automata modelling of slime mould actin network signalling View Full Text


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Article Info

DATE

2019-03

AUTHORS

Richard Mayne, Andrew Adamatkzy

ABSTRACT

Actin is a cytoskeletal protein which forms dense, highly interconnected networks within eukaryotic cells. A growing body of evidence suggests that actin-mediated intra- and extracellular signalling is instrumental in facilitating organism-level emergent behaviour patterns which, crucially, may be characterised as natural expressions of computation. We use excitable cellular automata modelling to simulate signal transmission through cell arrays whose topology was extracted from images of Watershed transformation-derived actin network reconstructions; the actin networks sampled were from laboratory experimental observations of a model organism, slime mould Physarum polycephalum. Our results indicate that actin networks support directional transmission of generalised energetic phenomena, the amplification and trans-network speed of which of which is proportional to network density (whose primary determinant is the anatomical location of the network sampled). Furthermore, this model also suggests the ability of such networks for supporting signal-signal interactions which may be characterised as Boolean logical operations, thus indicating that a cell’s actin network may function as a nanoscale data transmission and processing network. We conclude by discussing the role of the cytoskeleton in facilitating intracellular computing, how computation can be implemented in such a network and practical considerations for designing ‘useful’ actin circuitry. More... »

PAGES

5-12

References to SciGraph publications

  • 2011-12. Towards a theoretical foundation for morphological computation with compliant bodies in BIOLOGICAL CYBERNETICS
  • 2015-03. Towards a slime Mould-FPGA interface in BIOMEDICAL ENGINEERING LETTERS
  • 2010-01. Neural cytoskeleton capabilities for learning and memory in JOURNAL OF BIOLOGICAL PHYSICS
  • 2002. Collision-Based Computing in NONE
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    URI

    http://scigraph.springernature.com/pub.10.1007/s11047-016-9559-0

    DOI

    http://dx.doi.org/10.1007/s11047-016-9559-0

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