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: Zorowitz, Samuel, Momennejad, Ida, Daw, Nathaniel D.
Format: Article
Language:English
Published: Ubiquity Press 2020-03-01
Series:Computational Psychiatry
Online Access:https://www.mitpressjournals.org/doi/abs/10.1162/cpsy_a_00026
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author Zorowitz, Samuel
Momennejad, Ida
Daw, Nathaniel D.
author_facet Zorowitz, Samuel
Momennejad, Ida
Daw, Nathaniel D.
author_sort Zorowitz, Samuel
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-4368a93cbb864d22a9a94d7c3eb820512022-12-22T04:23:52ZengUbiquity PressComputational Psychiatry2379-62272020-03-01411710.1162/cpsy_a_00026Anxiety, Avoidance, and Sequential EvaluationZorowitz, SamuelMomennejad, IdaDaw, Nathaniel D.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.https://www.mitpressjournals.org/doi/abs/10.1162/cpsy_a_00026
spellingShingle Zorowitz, Samuel
Momennejad, Ida
Daw, Nathaniel D.
Anxiety, Avoidance, and Sequential Evaluation
Computational Psychiatry
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
url https://www.mitpressjournals.org/doi/abs/10.1162/cpsy_a_00026
work_keys_str_mv AT zorowitzsamuel anxietyavoidanceandsequentialevaluation
AT momennejadida anxietyavoidanceandsequentialevaluation
AT dawnathanield anxietyavoidanceandsequentialevaluation