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

Computational Psychiatry

Nathan Bakker¹  Aaron Prosser²  Thomas Parr³  Karl J. Friston³ 

[1] Department of Psychiatry, University of Toronto, Toronto, Canada;Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Canada;Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK;

关键词: psychopathy;    psychopathic personality disorder;    antisocial personality disorder;    personality disorders;    active inference;    Bayesian brain;    predictive coding;    free-energy;   

DOI  :  10.1162/cpsy_a_00016

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown