Computational Models of Learning Mechanisms in Psychosis
Computational Models of Learning Mechanisms in Psychosis
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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