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dc.contributor.authorHOUGHTON, CONOR JAMESen
dc.date.accessioned2008-11-26T12:41:03Z
dc.date.available2008-11-26T12:41:03Z
dc.date.issued2009en
dc.date.submitted2009en
dc.identifier.citationHoughton, Conor, Studying spike trains using a van Rossum metric with a synapse-like filter, Journal of Computational Neuroscience, 26, 2009, 149 - 155en
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/25039
dc.descriptionPUBLISHEDen
dc.descriptionPMID: 18607707 </br> 0929-5313 (Print) 1573-6873 (Online)en
dc.description.abstractSpike trains are unreliable. For example, in the primary sensory areas, spike patterns and precise spike times will vary between responses to the same stimulus. Nonetheless, information about sensory inputs is communicated in the form of spike trains. A challenge in understanding spike trains is to assess the significance of individual spikes in encoding information. One approach is to define a spike train metric, allowing a distance to be calculated between pairs of spike trains. In a good metric, this distance will depend on the information the spike trains encode. This method has been used previously to calculate the timescale over which the precision of spike times is significant. Here, a new metric is constructed based on a simple model of synaptic conductances which includes binding site depletion. Including binding site depletion in the metric means that a given individual spike has a smaller effect on the distance if it occurs soon after other spikes. The metric proves effective at classifying neuronal responses by stimuli in the sample data set of electro-physiological recordings from the primary auditory area of the zebra finch fore-brain. This shows that this is an effective metric for these spike trains suggesting that in these spike trains the significance of a spike is modulated by its proximity to previous spikes. This modulation is a putative information-coding property of spike trains.en
dc.description.sponsorshipC.J.H. was supported by a International Human Frontiers Science Program Organization shortterm fellowship and by Science Foundation Ireland grant 06/RFP/BIM020.en
dc.format.extent149en
dc.format.extent155en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.relation.ispartofseriesJournal of Computational Neuroscienceen
dc.relation.ispartofseries26en
dc.rightsYen
dc.subjectPure & Applied Mathematicsen
dc.titleStudying spike trains using a van Rossum metric with a synapse-like filteren
dc.typeJournal Articleen
dc.contributor.sponsorScience Foundation Ireland
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/houghtcjen
dc.identifier.rssinternalid51678en
dc.identifier.rssurihttp://www.springerlink.com/content/j2q7174821lw0k04/fulltext.pdfen
dc.identifier.rssurihttp://www.springerlink.com/content/j2q7174821lw0k04/fulltext.pdfen


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