Anxiety, Avoidance, and Sequential Evaluation

Anxiety disorders are characterized by a range of aberrations in the processing of and response to threat, but there is little clarity what core pathogenesis might underlie these symptoms. Here we propose that a particular set of unrealistically pessimistic assumptions can distort an agent’s behavio...

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Main Authors: Samuel Zorowitz, Ida Momennejad, Nathaniel D. Daw
Format: Article
Language:English
Published: Ubiquity Press 2020-03-01
Series:Computational Psychiatry
Subjects:
Online Access:https://cpsyjournal.org/articles/51
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author Samuel Zorowitz
Ida Momennejad
Nathaniel D. Daw
author_facet Samuel Zorowitz
Ida Momennejad
Nathaniel D. Daw
author_sort Samuel Zorowitz
collection DOAJ
description Anxiety disorders are characterized by a range of aberrations in the processing of and response to threat, but there is little clarity what core pathogenesis might underlie these symptoms. Here we propose that a particular set of unrealistically pessimistic assumptions can distort an agent’s behavior and underlie a host of seemingly disparate anxiety symptoms. We formalize this hypothesis in a decision-theoretic analysis of maladaptive avoidance and a reinforcement learning model, which shows how a localized bias in beliefs can formally explain a range of phenomena related to anxiety. The core observation, implicit in standard decision-theoretic accounts of sequential evaluation, is that the potential for avoidance should be protective: If danger can be avoided later, it poses less threat now. We show how a violation of this assumption—via a pessimistic, false belief that later avoidance will be unsuccessful—leads to a characteristic, excessive propagation of fear and avoidance to situations far antecedent of threat. This single deviation can explain a range of features of anxious behavior, including exaggerated threat appraisals, fear generalization, and persistent avoidance. Simulations of the model reproduce laboratory demonstrations of abnormal decision-making in anxiety, including in situations of approach–avoid conflict and planning to avoid losses. The model also ties together a number of other seemingly disjoint phenomena in anxious disorders. For instance, learning under the pessimistic bias captures a hypothesis about the role of anxiety in the later development of depression. The bias itself offers a new formalization of classic insights from the psychiatric literature about the central role of maladaptive beliefs about control and self-efficacy in anxiety. This perspective also extends previous computational accounts of beliefs about control in mood disorders, which neglected the sequential aspects of choice.
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spelling doaj.art-39ed2d75981448e7b14b206f831944452022-12-22T04:05:20ZengUbiquity PressComputational Psychiatry2379-62272020-03-01411710.1162/CPSY_a_0002649Anxiety, Avoidance, and Sequential EvaluationSamuel Zorowitz0Ida Momennejad1Nathaniel D. Daw2Princeton Neuroscience Institute, Princeton University, Princeton, New JerseyDepartment of Biomedical Engineering, Columbia University, New York, New YorkPrinceton Neuroscience Institute, Princeton University, Princeton, New Jersey; Department of Psychology, Princeton University, Princeton, New JerseyAnxiety disorders are characterized by a range of aberrations in the processing of and response to threat, but there is little clarity what core pathogenesis might underlie these symptoms. Here we propose that a particular set of unrealistically pessimistic assumptions can distort an agent’s behavior and underlie a host of seemingly disparate anxiety symptoms. We formalize this hypothesis in a decision-theoretic analysis of maladaptive avoidance and a reinforcement learning model, which shows how a localized bias in beliefs can formally explain a range of phenomena related to anxiety. The core observation, implicit in standard decision-theoretic accounts of sequential evaluation, is that the potential for avoidance should be protective: If danger can be avoided later, it poses less threat now. We show how a violation of this assumption—via a pessimistic, false belief that later avoidance will be unsuccessful—leads to a characteristic, excessive propagation of fear and avoidance to situations far antecedent of threat. This single deviation can explain a range of features of anxious behavior, including exaggerated threat appraisals, fear generalization, and persistent avoidance. Simulations of the model reproduce laboratory demonstrations of abnormal decision-making in anxiety, including in situations of approach–avoid conflict and planning to avoid losses. The model also ties together a number of other seemingly disjoint phenomena in anxious disorders. For instance, learning under the pessimistic bias captures a hypothesis about the role of anxiety in the later development of depression. The bias itself offers a new formalization of classic insights from the psychiatric literature about the central role of maladaptive beliefs about control and self-efficacy in anxiety. This perspective also extends previous computational accounts of beliefs about control in mood disorders, which neglected the sequential aspects of choice.https://cpsyjournal.org/articles/51anxietyavoidancefear generalizationdecision theory
spellingShingle Samuel Zorowitz
Ida Momennejad
Nathaniel D. Daw
Anxiety, Avoidance, and Sequential Evaluation
Computational Psychiatry
anxiety
avoidance
fear generalization
decision theory
title Anxiety, Avoidance, and Sequential Evaluation
title_full Anxiety, Avoidance, and Sequential Evaluation
title_fullStr Anxiety, Avoidance, and Sequential Evaluation
title_full_unstemmed Anxiety, Avoidance, and Sequential Evaluation
title_short Anxiety, Avoidance, and Sequential Evaluation
title_sort anxiety avoidance and sequential evaluation
topic anxiety
avoidance
fear generalization
decision theory
url https://cpsyjournal.org/articles/51
work_keys_str_mv AT samuelzorowitz anxietyavoidanceandsequentialevaluation
AT idamomennejad anxietyavoidanceandsequentialevaluation
AT nathanielddaw anxietyavoidanceandsequentialevaluation