dc.contributor.author | Steuber, Volker | |
dc.contributor.author | De Schutter, E. | |
dc.date.accessioned | 2011-10-06T08:01:13Z | |
dc.date.available | 2011-10-06T08:01:13Z | |
dc.date.issued | 2002-06 | |
dc.identifier.citation | Steuber , V & De Schutter , E 2002 , ' Rank order decoding of temporal parallel fibre input patterns in a complex Purkinje cell model ' , Neurocomputing , vol. 44 , pp. 183-188 . https://doi.org/10.1016/S0925-2312(02)00388-0 | |
dc.identifier.issn | 0925-2312 | |
dc.identifier.other | ORCID: /0000-0003-0186-3580/work/133139205 | |
dc.identifier.uri | http://hdl.handle.net/2299/6589 | |
dc.description | Full text of this article is not available in the UHRA | |
dc.description.abstract | The processing speed of many neuronal systems requires temporal coding. Recently, a temporal rank order code has been suggested that uses the temporal order of spikes, disregarding their precise timing. A rank order-coded spike pattern can be decoded by an array of synaptic weights and a postsynaptic desensitization process. We show that a multi-compartmental model of a cerebellar Purkinje cell can implement rank order decoding of temporal parallel fibre input patterns. Basis of the temporal decoding is the activation of K-Ca channels in the Purkinje cell dendrites. The model responds preferentially to spatio-temporal patterns which are ordered according to increasing synaptic strengths. (C) 2002 Published by Elsevier Science B.V. | en |
dc.format.extent | 6 | |
dc.language.iso | eng | |
dc.relation.ispartof | Neurocomputing | |
dc.subject | cerebellum | |
dc.subject | Purkinje cells | |
dc.subject | temporal coding | |
dc.subject | pattern recognition | |
dc.subject | ACTIVE MEMBRANE MODEL | |
dc.subject | SIMULATION | |
dc.title | Rank order decoding of temporal parallel fibre input patterns in a complex Purkinje cell model | en |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
dc.contributor.institution | Department of Computer Science | |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | Centre of Data Innovation Research | |
dc.contributor.institution | Centre for Future Societies Research | |
dc.contributor.institution | Biocomputation Research Group | |
dc.description.status | Peer reviewed | |
rioxxterms.versionofrecord | 10.1016/S0925-2312(02)00388-0 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |