8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)

Research Article

The Physarum polycephalum actin network: formalisation, topology and morphological correlates with computational ability

  • @INPROCEEDINGS{10.4108/icst.bict.2014.257821,
        author={Richard Mayne and Andrew Adamatzky},
        title={The Physarum polycephalum actin network: formalisation, topology and morphological correlates with computational ability},
        proceedings={8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)},
        publisher={ICST},
        proceedings_a={BICT},
        year={2015},
        month={2},
        keywords={slime mould physarum polycephalum cytoskeleton unconventional computing proximity graph},
        doi={10.4108/icst.bict.2014.257821}
    }
    
  • Richard Mayne
    Andrew Adamatzky
    Year: 2015
    The Physarum polycephalum actin network: formalisation, topology and morphological correlates with computational ability
    BICT
    ACM
    DOI: 10.4108/icst.bict.2014.257821
Richard Mayne,*, Andrew Adamatzky1
  • 1: University of the West of England
*Contact email: richard.mayne@uwe.ac.uk

Abstract

The plasmodial form of slime mould Physarum polycephalum is a macroscopic acellular organism that is capable of apparently intelligent behaviour, yet it lacks any features usually associated with intelligence. In this investigation, we study the morphology of the plasmodial actin cytoskeleton and formalise its network topology in efforts to correlate cytoskeletal morphology with slime mould computational abilities. The plasmodial actin network is a highly abundant, complex structure which links the functional components of the cell, whose topology may be approximated with a range of proximity graphs, depending on the physiological and environmental conditions within the plasmodium. Its topology is highly dynamical and is likely to rapidly alter in response to environmental stimuli to maximise network efficiency. We conclude by discussing the nature of the computational process in organic networks.