Material-based non-neural analogues of lateral inhibition: A multi-agent approach

Jones, Jeff

Abstract

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.

Citation

Jones, J. (2014, September). Material-based non-neural analogues of lateral inhibition: A multi-agent approach. Paper presented at Adaptive Materials, Devices and Systems Towards Unconventional Computing and Robotics: Modeling and Implementation

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: Adaptive Materials, Devices and Systems Towards Unconventional Computing and Robotics: Modeling and Implementation
• Start Date: Sep 22, 2014
• End Date: Sep 28, 2014
• Publication Date: Sep 1, 2014
• Peer Reviewed: Peer Reviewed
• Keywords: tissues, unconventional computing
• Publisher URL: http://dx.doi.org/10.1063/1.4912537
• Additional Information: Title of Conference or Conference Proceedings : Proceedings of Adaptive Materials, Devices and Systems Towards Unconventional Computing and Robotics: Modeling and Implementation