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Computational modelling reveals slower safety learning and threat extinction are associated with higher anxiety severity in remote fear conditioning

Tim Kerr, Kirstin Purves, Thomas McGregor, Michelle G. Craske, Tom Barry, Kathryn J. Lester, Elena Constantinou, Michael Sun, Oliver J. Robinson, Thalia C. Eley

Research output: Contribution to journalArticlepeer-review

Abstract

Anxiety disorders are chronic, pervasive, and debilitating; characterised by a persistent or exaggerated response to distal or abstract threats. Impaired threat discrimination (distinguishing safe from threatening stimuli) and impaired threat extinction (learning a once threatening stimulus is now safe), are known risk factors in the development and persistence of anxiety disorders. These effects can be experimentally elicited through fear conditioning. First, repeated trials of paired aversive and neutral stimuli are delivered during a fear acquisition phase, followed by repeated trials with no aversive stimuli in a fear extinction phase. The effects are typically measured through comparison of end-phase data points, or simple descriptive or statistical models. Computational modelling, by contrast, can offer a hypothesis-driven, trial-by-trial mechanistic account of fear conditioning. This unmasks within subject task variance by estimating the rate of threat learning, safety learning, and threat extinction, examining individual differences in the cognitive mechanisms behind anxiety. A normative sample (n = 145) underwent a differential fear conditioning task on a bespoke smartphone app, in addition to completing an anxiety severity measure (GAD-7). Computational models fitted to task data estimated learning rates. Whilst the threat learning rate showed no association, the threat extinction and safety learning rates showed small negative associations with anxiety severity (ρ = –0.22, p = 0.01 & ρ = –0.21, p = 0.01 respectively). These findings are in keeping with prior studies using traditional analytical approaches, and indicate that anxious individuals are not quicker to develop fear of a stimulus, but take more time than their non-anxious counterparts to learn that a stimulus is safe. This study strengthens the evidence for impairments in fear extinction in those with anxiety, and the importance of learning rates as an index of anxiety severity, a previously hidden cognitive mechanism underlying anxiety persistence.

Original languageEnglish
Pages (from-to)18-35
Number of pages18
JournalComputational psychiatry (Cambridge, Mass.)
Volume10
Issue number1
Early online date25 Jan 2026
DOIs
Publication statusPublished - 19 Feb 2026

Funding

O.J.R. has completed consultancy work for Peak, IESO digital health, Roche and BlackThorn therapeutics and sat on the committee of the British Association for Psychopharmacology until 2022. M.G.C. receives payments from Oxford University Press for workbooks related to treatment for anxiety and depression. M.G.C. also receives payments for book royalties from American Psychological Association and from Elsevier (as Editor-in-Chief of Behaviour Research and Therapy) and payment for editorial work for UpToDate, Inc. She also receives funding from the NIMH. This study presents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. O.J.R. sits on the editorial board of the journal. T.K. is supported by the London Interdisciplinary Biosciences Consortium, the Biotechnology and Biological Sciences Research Council, King’s College London, and Torchbox. T.C.E. is partially supported by the UK Medical Research Council (MR/V012878/1). T.C.E. is partially supported by the UK Medical Research Council (MR/V012878/1).

FundersFunder number
NIMH
Biotechnology and Biological Sciences Research Council
UK Medical Research Council
King's College London
London Interdisciplinary Biosciences Consortium
Medical Research CouncilMR/V012878/1

Keywords

  • Anxiety
  • Computational Modelling
  • Fear Conditioning

ASJC Scopus subject areas

  • Psychology (miscellaneous)

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