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Computational mechanisms of belief updating in relation to psychotic-like experiences
INTRODUCTION: Psychotic-like experiences (PLEs) may occur due to changes in weighting prior beliefs and new evidence in the belief updating process. It is still unclear whether the acquisition or integration of stable beliefs is altered, and whether such alteration depends on the level of environmen...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196365/ https://www.ncbi.nlm.nih.gov/pubmed/37215663 http://dx.doi.org/10.3389/fpsyt.2023.1170168 |
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author | Fromm, Sophie Pauline Wieland, Lara Klettke, Arne Nassar, Matthew R. Katthagen, Teresa Markett, Sebastian Heinz, Andreas Schlagenhauf, Florian |
author_facet | Fromm, Sophie Pauline Wieland, Lara Klettke, Arne Nassar, Matthew R. Katthagen, Teresa Markett, Sebastian Heinz, Andreas Schlagenhauf, Florian |
author_sort | Fromm, Sophie Pauline |
collection | PubMed |
description | INTRODUCTION: Psychotic-like experiences (PLEs) may occur due to changes in weighting prior beliefs and new evidence in the belief updating process. It is still unclear whether the acquisition or integration of stable beliefs is altered, and whether such alteration depends on the level of environmental and belief precision, which reflects the associated uncertainty. This motivated us to investigate uncertainty-related dynamics of belief updating in relation to PLEs using an online study design. METHODS: We selected a sample (n = 300) of participants who performed a belief updating task with sudden change points and provided self-report questionnaires for PLEs. The task required participants to observe bags dropping from a hidden helicopter, infer its position, and dynamically update their belief about the helicopter's position. Participants could optimize performance by adjusting learning rates according to inferred belief uncertainty (inverse prior precision) and the probability of environmental change points. We used a normative learning model to examine the relationship between adherence to specific model parameters and PLEs. RESULTS: PLEs were linked to lower accuracy in tracking the outcome (helicopter location) (β = 0.26 ± 0.11, p = 0.018) and to a smaller increase of belief precision across observations after a change point (β = −0.003 ± 0.0007, p < 0.001). PLEs were related to slower belief updating when participants encountered large prediction errors (β = −0.03 ± 0.009, p = 0.001). Computational modeling suggested that PLEs were associated with reduced overall belief updating in response to prediction errors (β(PE) = −1.00 ± 0.45, p = 0.028) and reduced modulation of updating at inferred environmental change points (β(CPP) = −0.84 ± 0.38, p = 0.023). DISCUSSION: We conclude that PLEs are associated with altered dynamics of belief updating. These findings support the idea that the process of balancing prior belief and new evidence, as a function of environmental uncertainty, is altered in PLEs, which may contribute to the development of delusions. Specifically, slower learning after large prediction errors in people with high PLEs may result in rigid beliefs. Disregarding environmental change points may limit the flexibility to establish new beliefs in the face of contradictory evidence. The present study fosters a deeper understanding of inferential belief updating mechanisms underlying PLEs. |
format | Online Article Text |
id | pubmed-10196365 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101963652023-05-20 Computational mechanisms of belief updating in relation to psychotic-like experiences Fromm, Sophie Pauline Wieland, Lara Klettke, Arne Nassar, Matthew R. Katthagen, Teresa Markett, Sebastian Heinz, Andreas Schlagenhauf, Florian Front Psychiatry Psychiatry INTRODUCTION: Psychotic-like experiences (PLEs) may occur due to changes in weighting prior beliefs and new evidence in the belief updating process. It is still unclear whether the acquisition or integration of stable beliefs is altered, and whether such alteration depends on the level of environmental and belief precision, which reflects the associated uncertainty. This motivated us to investigate uncertainty-related dynamics of belief updating in relation to PLEs using an online study design. METHODS: We selected a sample (n = 300) of participants who performed a belief updating task with sudden change points and provided self-report questionnaires for PLEs. The task required participants to observe bags dropping from a hidden helicopter, infer its position, and dynamically update their belief about the helicopter's position. Participants could optimize performance by adjusting learning rates according to inferred belief uncertainty (inverse prior precision) and the probability of environmental change points. We used a normative learning model to examine the relationship between adherence to specific model parameters and PLEs. RESULTS: PLEs were linked to lower accuracy in tracking the outcome (helicopter location) (β = 0.26 ± 0.11, p = 0.018) and to a smaller increase of belief precision across observations after a change point (β = −0.003 ± 0.0007, p < 0.001). PLEs were related to slower belief updating when participants encountered large prediction errors (β = −0.03 ± 0.009, p = 0.001). Computational modeling suggested that PLEs were associated with reduced overall belief updating in response to prediction errors (β(PE) = −1.00 ± 0.45, p = 0.028) and reduced modulation of updating at inferred environmental change points (β(CPP) = −0.84 ± 0.38, p = 0.023). DISCUSSION: We conclude that PLEs are associated with altered dynamics of belief updating. These findings support the idea that the process of balancing prior belief and new evidence, as a function of environmental uncertainty, is altered in PLEs, which may contribute to the development of delusions. Specifically, slower learning after large prediction errors in people with high PLEs may result in rigid beliefs. Disregarding environmental change points may limit the flexibility to establish new beliefs in the face of contradictory evidence. The present study fosters a deeper understanding of inferential belief updating mechanisms underlying PLEs. Frontiers Media S.A. 2023-05-05 /pmc/articles/PMC10196365/ /pubmed/37215663 http://dx.doi.org/10.3389/fpsyt.2023.1170168 Text en Copyright © 2023 Fromm, Wieland, Klettke, Nassar, Katthagen, Markett, Heinz and Schlagenhauf. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Fromm, Sophie Pauline Wieland, Lara Klettke, Arne Nassar, Matthew R. Katthagen, Teresa Markett, Sebastian Heinz, Andreas Schlagenhauf, Florian Computational mechanisms of belief updating in relation to psychotic-like experiences |
title | Computational mechanisms of belief updating in relation to psychotic-like experiences |
title_full | Computational mechanisms of belief updating in relation to psychotic-like experiences |
title_fullStr | Computational mechanisms of belief updating in relation to psychotic-like experiences |
title_full_unstemmed | Computational mechanisms of belief updating in relation to psychotic-like experiences |
title_short | Computational mechanisms of belief updating in relation to psychotic-like experiences |
title_sort | computational mechanisms of belief updating in relation to psychotic-like experiences |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196365/ https://www.ncbi.nlm.nih.gov/pubmed/37215663 http://dx.doi.org/10.3389/fpsyt.2023.1170168 |
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