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A Bayesian Account of Psychopathy: A Model of Lacks Remorse and Self-Aggrandizing

Authors :
Aaron Prosser
Karl J. Friston
Nathan Bakker
Thomas Parr
Source :
Computational Psychiatry, Vol 2, Pp 92-140 (2018)
Publication Year :
2018
Publisher :
Ubiquity Press, 2018.

Abstract

This article proposes a formal model that integrates cognitive and psychodynamic psychotherapeutic models of psychopathy to show how two major psychopathic traits called lacks remorse and self-aggrandizing can be understood as a form of abnormal Bayesian inference about the self. This model draws on the predictive coding (i.e., active inference) framework, a neurobiologically plausible explanatory framework for message passing in the brain that is formalized in terms of hierarchical Bayesian inference. In summary, this model proposes that these two cardinal psychopathic traits reflect entrenched maladaptive Bayesian inferences about the self, which defend against the experience of deep-seated, self-related negative emotions, specifically shame and worthlessness. Support for the model in extant research on the neurobiology of psychopathy and quantitative simulations are provided. Finally, we offer a preliminary overview of a novel treatment for psychopathy that rests on our Bayesian formulation.

Details

Language :
English
ISSN :
23796227
Volume :
2
Database :
Directory of Open Access Journals
Journal :
Computational Psychiatry
Publication Type :
Academic Journal
Accession number :
edsdoj.7d6728dae04453c93c6e885b8e0a72f
Document Type :
article
Full Text :
https://doi.org/10.1162/cpsy_a_00016