Deterministic coincidence detection and adaptation via delayed inputs

Yang, Zhijun ORCID: https://orcid.org/0000-0003-2615-4297, Murray, Alan and Huo, Juan (2008) Deterministic coincidence detection and adaptation via delayed inputs. Kůrková, V., Neruda, R. and Koutník, J., eds. Artificial Neural Networks - ICANN 2008: 18th International Conference, Prague, Czech Republic, September 3-6, 2008, Proceedings, Part II. In: 18th International Conference on Artificial Neural Networks (ICANN 2008), 03-06 Sept 2008, Prague, Czech Republic. pbk-ISBN 9783540875581, e-ISBN 9783540875598. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-540-87559-8_47)

Abstract

A model of one integrate-and-firing (IF) neuron with two afferent excitatory synapses is studied analytically. This is to discuss the influence of different model parameters, i.e., synaptic efficacies, synaptic and membrane time constants, on the postsynaptic neuron activity. An activation window of the postsynaptic neuron, which is adjustable through spike-timing dependent synaptic adaptation rule, is shown to be associated with the coincidence level of the excitatory postsynaptic potentials (EPSPs) under several restrictions. This simplified model, which is intrinsically the deterministic coincidence detector, is hence capable of detecting the synchrony level between intercellular connections. A model based on the proposed coincidence detection is provided as an example to show its application on early vision processing.

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