Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance
Although avoidance is a prevalent feature of anxiety-related psychopathology, differences in the measurement of avoidance between humans and non-human animals hinder our progress in its theoretical understanding and treatment. To address this, we developed a novel translational measure of anxiety-re...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
eLife Sciences Publications Ltd
2023-11-01
|
| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/87720 |
| _version_ | 1827762512701947904 |
|---|---|
| author | Yumeya Yamamori Oliver J Robinson Jonathan P Roiser |
| author_facet | Yumeya Yamamori Oliver J Robinson Jonathan P Roiser |
| author_sort | Yumeya Yamamori |
| collection | DOAJ |
| description | Although avoidance is a prevalent feature of anxiety-related psychopathology, differences in the measurement of avoidance between humans and non-human animals hinder our progress in its theoretical understanding and treatment. To address this, we developed a novel translational measure of anxiety-related avoidance in the form of an approach-avoidance reinforcement learning task, by adapting a paradigm from the non-human animal literature to study the same cognitive processes in human participants. We used computational modelling to probe the putative cognitive mechanisms underlying approach-avoidance behaviour in this task and investigated how they relate to subjective task-induced anxiety. In a large online study (n = 372), participants who experienced greater task-induced anxiety avoided choices associated with punishment, even when this resulted in lower overall reward. Computational modelling revealed that this effect was explained by greater individual sensitivities to punishment relative to rewards. We replicated these findings in an independent sample (n = 627) and we also found fair-to-excellent reliability of measures of task performance in a sub-sample retested 1 week later (n = 57). Our findings demonstrate the potential of approach-avoidance reinforcement learning tasks as translational and computational models of anxiety-related avoidance. Future studies should assess the predictive validity of this approach in clinical samples and experimental manipulations of anxiety. |
| first_indexed | 2024-03-11T10:31:40Z |
| format | Article |
| id | doaj.art-63e67b40971c4d5a99f825e692d90561 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-03-11T10:31:40Z |
| publishDate | 2023-11-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-63e67b40971c4d5a99f825e692d905612023-11-14T17:21:10ZengeLife Sciences Publications LtdeLife2050-084X2023-11-011210.7554/eLife.87720Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidanceYumeya Yamamori0https://orcid.org/0000-0001-5508-7965Oliver J Robinson1https://orcid.org/0000-0002-3100-1132Jonathan P Roiser2https://orcid.org/0000-0001-8269-1228Institute of Cognitive Neuroscience, University College London, London, United KingdomInstitute of Cognitive Neuroscience, University College London, London, United Kingdom; Research Department of Clinical, Educational and Health Psychology, University College London, London, United KingdomInstitute of Cognitive Neuroscience, University College London, London, United KingdomAlthough avoidance is a prevalent feature of anxiety-related psychopathology, differences in the measurement of avoidance between humans and non-human animals hinder our progress in its theoretical understanding and treatment. To address this, we developed a novel translational measure of anxiety-related avoidance in the form of an approach-avoidance reinforcement learning task, by adapting a paradigm from the non-human animal literature to study the same cognitive processes in human participants. We used computational modelling to probe the putative cognitive mechanisms underlying approach-avoidance behaviour in this task and investigated how they relate to subjective task-induced anxiety. In a large online study (n = 372), participants who experienced greater task-induced anxiety avoided choices associated with punishment, even when this resulted in lower overall reward. Computational modelling revealed that this effect was explained by greater individual sensitivities to punishment relative to rewards. We replicated these findings in an independent sample (n = 627) and we also found fair-to-excellent reliability of measures of task performance in a sub-sample retested 1 week later (n = 57). Our findings demonstrate the potential of approach-avoidance reinforcement learning tasks as translational and computational models of anxiety-related avoidance. Future studies should assess the predictive validity of this approach in clinical samples and experimental manipulations of anxiety.https://elifesciences.org/articles/87720anxietycomputational modellingtranslationalapproach-avoidance conflictreinforcement learning |
| spellingShingle | Yumeya Yamamori Oliver J Robinson Jonathan P Roiser Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance eLife anxiety computational modelling translational approach-avoidance conflict reinforcement learning |
| title | Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance |
| title_full | Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance |
| title_fullStr | Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance |
| title_full_unstemmed | Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance |
| title_short | Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance |
| title_sort | approach avoidance reinforcement learning as a translational and computational model of anxiety related avoidance |
| topic | anxiety computational modelling translational approach-avoidance conflict reinforcement learning |
| url | https://elifesciences.org/articles/87720 |
| work_keys_str_mv | AT yumeyayamamori approachavoidancereinforcementlearningasatranslationalandcomputationalmodelofanxietyrelatedavoidance AT oliverjrobinson approachavoidancereinforcementlearningasatranslationalandcomputationalmodelofanxietyrelatedavoidance AT jonathanproiser approachavoidancereinforcementlearningasatranslationalandcomputationalmodelofanxietyrelatedavoidance |