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Material-based non-neural analogues of lateral inhibition: A multi-agent approach
Author(s) -
Jeff Jones
Publication year - 2015
Publication title -
aip conference proceedings
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.177
H-Index - 75
eISSN - 1551-7616
pISSN - 0094-243X
DOI - 10.1063/1.4912537
Subject(s) - physarum polycephalum , lateral inhibition , inhibitory postsynaptic potential , slime mold , biological system , contrast (vision) , sensory system , computer science , chemistry , neuroscience , artificial intelligence , biology , biochemistry
Lateral Inhibition (LI) phenomena occur in a wide range of sensory modalities and are most famously described in the human visual system. In LI the activity of a stimulated neuron is itself excited and suppresses the activity of its local neighbours via inhibitory connections, increasing the contrast between spatial environmental stimuli. Simple organisms, such as the single-celled slime mould Physarum polycephalum possess no neural tissue yet, despite this, are known to exhibit complex computational behaviour. Could simple organisms such as slime mould approximate LI without recourse to neural tissue? We describe a model whereby LI can emerge without explicit inhibitory wiring, using only bulk transport effects. We use a multi-agent virtual material model of slime mould to reproduce the characteristic contrast amplification response of LI using excitation via attractant stimuli. Restoration of baseline activity occurs when the stimuli are removed. We also explore an opposite counterpart behaviour, Lateral Activation (LA), using repellent stimuli. These preliminary results suggest that simple organisms without neural tissue may approximate sensory contrast enhancement using alternative analogues of LI and suggests novel approaches towards generating collective contrast enhancement in distributed computing and robotic devices.

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