PMID: 9654382Jul 8, 1998Paper

An artificial neural network simulating performance of normal subjects and schizophrenics on the Wisconsin Card Sorting Test

Artificial Intelligence in Medicine
S Berdia, J T Metz

Abstract

Mental diseases such as schizophrenia are being modeled by artificial neural networks in an attempt to understand the underlying neuropathological processes. We studied hospitalized psychiatric patients that met the DSM-IIIR criteria for schizophrenia (N=19), and normal subjects with no psychiatric history (N=18). Performance on the Wisconsin Card Sorting Test (WCST) by schizophrenic patients was poorer than normal subjects as estimated by various scoring measurements. We then modeled an artificial neural network, motivated by biological considerations, that is able to simulate performance of normals and schizophrenics on the WCST. In order to model the complex nature of the WCST, we designed novel learning rules based on non-associative learning paradigms. We found that there must be a minimum amount of noise, or inherent synaptic instability, for our model to perform similar to schizophrenics.

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Citations

May 19, 2007·Journal of Computational Neuroscience·Anja StemmeAstrid Busch
Sep 6, 2003·Schizophrenia Research·Marilyn HartmanCandace Andersson
Jul 8, 1998·Artificial Intelligence in Medicine·E Ruppin, J A Reggia
Dec 14, 2005·Neural Networks : the Official Journal of the International Neural Network Society·Gülay B KaplanCüneyt Güzeliş
Oct 27, 2015·PLoS Computational Biology·Dimitrije MarkovićStefan J Kiebel
Aug 29, 2006·Medical & Biological Engineering & Computing·Gangmin NingXiaoxiang Zheng
Aug 17, 2020·Journal of Clinical Medicine·Alexander SteinkeBruno Kopp
Sep 24, 2020·Scientific Reports·Alexander SteinkeBruno Kopp
Dec 23, 2020·Brain Sciences·Alexander Steinke, Bruno Kopp
Aug 1, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Giovanni Granato, Gianluca Baldassarre

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