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dc.contributor.authorSteuber, Volker
dc.contributor.authorWillshaw, David
dc.date.accessioned2013-11-25T12:59:51Z
dc.date.available2013-11-25T12:59:51Z
dc.date.issued1997
dc.identifier.citationSteuber , V & Willshaw , D 1997 , How a single Purkinje cell could learn the adaptive timing of the classically conditioned eye-blink response . in Lecture Notes in Computer Science . vol. 1327 , pp. 115-120 , ICANN'97: Int Conf on Artificial Neural Networks , Lausanne , Switzerland , 8/10/97 . https://doi.org/10.1007/BFb0020142
dc.identifier.citationconference
dc.identifier.isbn978-3-540-63631-1
dc.identifier.isbn978-3-540-69620-9
dc.identifier.otherORCID: /0000-0003-0186-3580/work/133139261
dc.identifier.urihttp://hdl.handle.net/2299/12177
dc.description.abstractExperimental evidence supports the view that the cerebellum is involved in the adaptive timing of the classically conditioned eyeblink response. Previous modelling studies have demonstrated that a group of cerebellar Purkinje cells can learn the adaptive timing of the eye-blink response if the cells in the group have predefined response latencies which cover the range of conditionable interstimulus intervals (ISIS). Here we show how the timing can be learnt by a single Purkinje cell. Phosphorylation of metabotropic glutamate recptors (mGluRs) in our model causes the time delay between parallel fibre input and voltage response to be adaptive and makes it unnecessary to specify a conditionable ISI for each cell in advance. The model is able to learn conditioned responses (CRs) for delay conditioned ISIs between 200 and 1000 msec. Modification of parts of the intracellular signalling network might represent a general mechanism for neurons to learn the timing between input and outputen
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science
dc.titleHow a single Purkinje cell could learn the adaptive timing of the classically conditioned eye-blink responseen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionCentre of Data Innovation Research
dc.contributor.institutionCentre for Future Societies Research
rioxxterms.versionofrecord10.1007/BFb0020142
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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