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A New Understanding of Mental DisordersComputational Models for Dimensional Psychiatry$
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Andreas Heinz

Print publication date: 2017

Print ISBN-13: 9780262036894

Published to MIT Press Scholarship Online: May 2018

DOI: 10.7551/mitpress/9780262036894.001.0001

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Computational Models of Learning Mechanisms in Psychosis

Computational Models of Learning Mechanisms in Psychosis

Chapter:
(p.75) 7 Computational Models of Learning Mechanisms in Psychosis
Source:
A New Understanding of Mental Disorders
Author(s):

Andreas Heinz

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262036894.003.0007

Psychotic experiences may best be described as an alteration in the self-ascription of thoughts and actions, which is associated with a profoundly altered experience of oneself and the surrounding world. Computational models of key symptoms of psychiatric disorders are discussed with respect to the attribution of salience and self-relatedness to otherwise irrelevant stimuli and the role of top-down modelling in the generation of delusions. Top-down and bottom-up approaches in understanding mental disorders and their computational models are compared and critically reflected.

Keywords:   Psychotic experiences, Self-ascription, Computational models, Psychiatric disorders, Stimuli, Top-down modelling

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