Temporal processing in a spiking model of the visual system

Abstract

Increasing amount of evidence suggests that the brain has the necessary mechanisms to and indeed does generate and process temporal information from the very early stages of sensory pathways. This paper presents a novel biologically motivated model of the visual system based on temporal encoding of the visual stimuli and temporally precise lateral geniculate nucleus (LGN) spikes. The work investigates whether such a network could be developed using an extended type of integrate-and-fire neurons (ADDS) and trained to recognise objects of different shapes using STDP learning. The experimental results contribute further support to the argument that temporal encoding can provide a mechanism for representing information in the visual system and has the potential to complement firing-rate-based architectures toward building more realistic and powerful models. © Springer-Vorlag Berlin Heidelberg 2006.