Show simple item record

dc.contributor.authorPower, W.
dc.contributor.authorFrank, R.
dc.contributor.authorDone, D.J.
dc.contributor.authorDavey, N.
dc.date.accessioned2008-02-05T12:25:00Z
dc.date.available2008-02-05T12:25:00Z
dc.date.issued1999
dc.identifier.citationPower , W , Frank , R , Done , D J & Davey , N 1999 , ' A modular attractor model of semantic access ' , Lecture Notes in Computer Science , vol. 1606 , pp. 340-347 . https://doi.org/10.1007/BFb0098154
dc.identifier.issn0302-9743
dc.identifier.otherPURE: 101303
dc.identifier.otherPURE UUID: 876a29d8-5aa5-4203-9a64-916d3c619cdc
dc.identifier.otherdspace: 2299/1576
dc.identifier.otherScopus: 84957627058
dc.identifier.urihttp://hdl.handle.net/2299/1576
dc.descriptionThe original publication is available at www.springerlink.com . Copyright Springer. DOI : 10.1007/BFb0098154
dc.description.abstractThis paper presents results from lesion experiments on a modular attractor neural network model of semantic access. Real picture data forms the basis of perceptual input to the model. An ultrametric attractor space is used to represent semantic memory and is implemented using a biologically plausible variant of the Hopfield model. Lesioned performance is observed to be in agreement with neuropsychological data. A local field analysis of the attractor states of semantic space forms a basis for interpreting these results.en
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science
dc.rightsOpen
dc.titleA modular attractor model of semantic accessen
dc.contributor.institutionSchool of Computer Science
dc.description.statusPeer reviewed
dc.relation.schoolSchool of Computer Science
dcterms.dateAccepted1999
rioxxterms.versionofrecordhttps://doi.org/10.1007/BFb0098154
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record