Neural modelling of cognitive disinhibition and neurotransmitter dysfunction in OCD

Jacques Ludik, Dan J. Stein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper an Elman recurrent neural network model of obsessive-compulsive disorder (OCD) is developed to provide a simulation of the relationship between the cognitive disinhibition and serotonin/dopamine dysfunction that characterize this disorder. Cognitive disinhibition in OCD is apparent when OCD patients are compared with other anxiety disorder patients on a Temporal Stroop test, with OCD patients showing reduced negative priming. Alterations of the color gain parameter, the context gain parameter, and maximum cycle number were made in order to simulate changes in monoamine neutransmitter function. The recurrent network model was able to simulate reduced cognitive inhibition as well as serotonergic and dopaminergic dysfunction in OCD.

Original languageEnglish
Title of host publicationArtificial Neural Networks, ICANN 1996 - 1996 International Conference, Proceedings
PublisherSpringer Verlag
Pages893-898
Number of pages6
ISBN (Print)3540615105, 9783540615101
DOIs
StatePublished - 1996
Externally publishedYes
Event1996 International Conference on Artificial Neural Networks, ICANN 1996 - Bochum, Germany
Duration: 16 Jul 199619 Jul 1996

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1112 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1996 International Conference on Artificial Neural Networks, ICANN 1996
Country/TerritoryGermany
CityBochum
Period16/07/9619/07/96

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