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Article: A neurocomputational model of early psychosis

TitleA neurocomputational model of early psychosis
Authors
Issue Date2003
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Lecture Notes In Artificial Intelligence (Subseries Of Lecture Notes In Computer Science), 2003, v. 2774 PART 2, p. 1149-1155 How to Cite?
AbstractA neurocomputation model for early psychosis is implemented with an associative network using the Hebbian learning algorithm. The model emphasizes on longitudinal evolution of the weight matrix from the pre-psychotic phase through the psychotic phase to the recovery phase. Enhanced activity-dependent synaptic plasticity is postulated to underlie formation of spurious associative connections during psychosis. This parsimonious longitudinal model is capable of addressing the presence of low- grade psychotic symptoms in the prepsychotic phase, the formation of spurious associations during psychosis, as well as the persistence of some of these associations into the recovery process with encapsulation of psychotic features.
Persistent Identifierhttp://hdl.handle.net/10722/120129
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorChen, EYHen_HK
dc.date.accessioned2010-09-26T09:25:31Z-
dc.date.available2010-09-26T09:25:31Z-
dc.date.issued2003en_HK
dc.identifier.citationLecture Notes In Artificial Intelligence (Subseries Of Lecture Notes In Computer Science), 2003, v. 2774 PART 2, p. 1149-1155en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/120129-
dc.description.abstractA neurocomputation model for early psychosis is implemented with an associative network using the Hebbian learning algorithm. The model emphasizes on longitudinal evolution of the weight matrix from the pre-psychotic phase through the psychotic phase to the recovery phase. Enhanced activity-dependent synaptic plasticity is postulated to underlie formation of spurious associative connections during psychosis. This parsimonious longitudinal model is capable of addressing the presence of low- grade psychotic symptoms in the prepsychotic phase, the formation of spurious associations during psychosis, as well as the persistence of some of these associations into the recovery process with encapsulation of psychotic features.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)en_HK
dc.titleA neurocomputational model of early psychosisen_HK
dc.typeArticleen_HK
dc.identifier.emailChen, EYH: eyhchen@hku.hken_HK
dc.identifier.authorityChen, EYH=rp00392en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-8344225227en_HK
dc.identifier.hkuros82816en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-8344225227&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2774 PART 2en_HK
dc.identifier.spage1149en_HK
dc.identifier.epage1155en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridChen, EYH=7402315729en_HK

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