Temporal Processing in a Spiking Model of the Visual System

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

2 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationArtificial Neural Networks – ICANN 2006. ICANN 2006
Subtitle of host publication16th International Conference, Athens, Greece, September 10-14, 2006. Proceedings, Part I
EditorsStefanos D. Kollias, Andreas Stafylopatis, Włodzisław Duch, Erkki Oja
Place of PublicationBerlin
PublisherSpringer Verlag
Number of pages10
ISBN (Electronic)978-3-540-38627-8
ISBN (Print)978-3-540-38625-4
Publication statusPublished - 2006
Externally publishedYes
Event16th International Conference on Artificial Neural Networks - Athens, Greece
Duration: 10 Sep 200614 Sep 2006
Conference number: 16

Publication series

Name Lecture Notes in Computer Science


Conference16th International Conference on Artificial Neural Networks
Abbreviated titleICANN 2006


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