期刊
SCHIZOPHRENIA RESEARCH
卷 245, 期 -, 页码 23-41出版社
ELSEVIER
DOI: 10.1016/j.schres.2021.01.023
关键词
Delusions; Psychosis; Schizophrenia; Inference; Beads task; Computational psychiatry
类别
资金
- National Institute of Mental Health [R01MH117323, R01MH114965]
- Columbia University [T32-MH018870]
Despite decades of research, the computational and neurobiological alterations leading to delusions are still poorly understood. This review focuses on recent work in computational psychiatry that aims to develop quantitative models of inference and explain the formation of delusional beliefs in psychosis. The study evaluates experimental paradigms commonly used to study inferential alterations in delusions and suggests that classic decision-making paradigms are not effective in isolating inferential processes. The review also discusses enhancements to standard paradigms that show promise in better understanding inferential processes and delusion-related alterations. The study proposes a specific failure mode for delusions involving overweighting in high-level causal inferences about partially observable hidden states and explores plausible neurobiological implementations for this failure mode.
Delusions are rigid beliefs held with high certainty despite contradictory evidence. Notwithstanding decades of research, we still have a limited understanding of the computational and neurobiological alterations giving rise to delusions. In this review, we highlight a selection of recent work in computational psychiatry aimed at developing quantitative models of inference and its alterations, with the goal of providing an explanatory account for the form of delusional beliefs in psychosis. First, we assess and evaluate the experimental paradigms most often used to study inferential alterations in delusions. Based on our review of the literature and theoretical considerations, we contend that classic draws-to-decision paradigms are not well-suited to isolate inferential processes, further arguing that the commonly cited 'jumping-to-conclusion' bias may reflect neither delusion-specific nor inferential alterations. Second, we discuss several enhancements to standard paradigms that show promise in more effectively isolating inferential processes and delusion-related alterations therein. We further draw on our recent work to build an argument for a specific failure mode for delusions consisting of prior overweighting in high-level causal inferences about partially observable hidden states. Finally, we assess plausible neurobiological implementations for this candidate failure mode of delusional beliefs and outline promising future directions in this area. (c) 2021 Published by Elsevier B.V.
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