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乐观偏差的主动推理模型。

An Active Inference Model of the Optimism Bias.

作者信息

Fisher Elizabeth L, Whyte Christopher J, Hohwy Jakob

机构信息

Monash Centre for Consciousness and Contemplative Studies, Monash University, Melbourne, Australia.

Brain and Mind Centre, The University of Sydney, Sydney, Australia.

出版信息

Comput Psychiatr. 2025 Jan 31;9(1):3-22. doi: 10.5334/cpsy.125. eCollection 2025.

DOI:10.5334/cpsy.125
PMID:39897669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11784508/
Abstract

The optimism bias is a cognitive bias where individuals overestimate the likelihood of good outcomes and underestimate the likelihood of bad outcomes. Associated with improved quality of life, optimism bias is considered to be adaptive and is a promising avenue of research for mental health interventions in conditions where individuals lack optimism such as major depressive disorder. Here we lay the groundwork for future research on optimism as an intervention by introducing a domain general formal model of optimism bias, which can be applied in different task settings. Employing the active inference framework, we propose a model of the optimism bias as high precision likelihood biased towards positive outcomes. First, we simulate how optimism may be lost during development by exposure to negative events. We then ground our model in the empirical literature by showing how the developmentally acquired differences in optimism are expressed in a belief updating task typically used to assess optimism bias. Finally, we show how optimism affects action in a modified two-armed bandit task. Our model and the simulations it affords provide a computational basis for understanding how optimism bias may emerge, how it may be expressed in standard tasks used to assess optimism, and how it affects agents' decision-making and actions; in combination, this provides a basis for future research on optimism as a mental health intervention.

摘要

乐观偏差是一种认知偏差,个体在其中高估了好结果的可能性,而低估了坏结果的可能性。与生活质量的提高相关,乐观偏差被认为具有适应性,并且是在个体缺乏乐观情绪的情况下(如重度抑郁症)进行心理健康干预的一个有前景的研究途径。在这里,我们通过引入一个领域通用的乐观偏差形式模型,为将乐观作为一种干预措施的未来研究奠定基础,该模型可应用于不同的任务设置。利用主动推理框架,我们提出了一个将乐观偏差建模为对积极结果有偏向的高精度似然性的模型。首先,我们模拟了在发育过程中,通过接触负面事件,乐观情绪是如何可能丧失的。然后,我们通过展示在通常用于评估乐观偏差的信念更新任务中,发育过程中获得的乐观差异是如何体现的,将我们的模型与实证文献联系起来。最后,我们展示了乐观如何在一个修改后的双臂赌博任务中影响行动。我们的模型及其提供的模拟为理解乐观偏差如何出现、如何在用于评估乐观的标准任务中表现以及如何影响主体的决策和行动提供了一个计算基础;综合起来,这为将乐观作为一种心理健康干预措施的未来研究提供了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/f44c84fc1adb/cpsy-9-1-125-g8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/1326f045af3e/cpsy-9-1-125-g1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/deab4d5a55d5/cpsy-9-1-125-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/3f7f30ad9c8d/cpsy-9-1-125-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/4036971187f4/cpsy-9-1-125-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/4a7b7bd70a0c/cpsy-9-1-125-g7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/f44c84fc1adb/cpsy-9-1-125-g8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/1326f045af3e/cpsy-9-1-125-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/39f55bb61266/cpsy-9-1-125-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/e6319d6a2052/cpsy-9-1-125-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/deab4d5a55d5/cpsy-9-1-125-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/3f7f30ad9c8d/cpsy-9-1-125-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/4036971187f4/cpsy-9-1-125-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/4a7b7bd70a0c/cpsy-9-1-125-g7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a727/11784508/f44c84fc1adb/cpsy-9-1-125-g8.jpg

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本文引用的文献

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The Universal Optimism of the Self-Evidencing Mind.自证思维的普遍乐观主义。
Entropy (Basel). 2024 Jun 17;26(6):518. doi: 10.3390/e26060518.
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Fearful snake pictures make monkeys pessimistic.可怕的蛇的图片让猴子变得悲观。
iScience. 2023 Aug 12;26(9):107622. doi: 10.1016/j.isci.2023.107622. eCollection 2023 Sep 15.
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Individual differences in computational psychiatry: A review of current challenges.计算精神病学中的个体差异:当前挑战综述
Neurosci Biobehav Rev. 2023 May;148:105137. doi: 10.1016/j.neubiorev.2023.105137. Epub 2023 Mar 20.
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Computational Mechanisms of Addiction and Anxiety: A Developmental Perspective.成瘾与焦虑的计算机制:发展视角。
Biol Psychiatry. 2023 Apr 15;93(8):739-750. doi: 10.1016/j.biopsych.2023.02.004. Epub 2023 Feb 10.
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What is Computational Psychiatry Good For?计算精神病学有什么用?
Biol Psychiatry. 2023 Apr 15;93(8):658-660. doi: 10.1016/j.biopsych.2022.08.030. Epub 2022 Sep 9.
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