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A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals
BACKGROUND: Real-life decisions are often complex because they involve making sequential choices that constrain future options. We have previously shown that to render such multi-step decisions manageable, people ‘prune’ (i.e. selectively disregard) branches of decision trees that contain negative o...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811346/ https://www.ncbi.nlm.nih.gov/pubmed/33706833 http://dx.doi.org/10.1017/S0033291721000799 |
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author | Faulkner, Paul Huys, Quentin J. M. Renz, Daniel Eshel, Neir Pilling, Stephen Dayan, Peter Roiser, Jonathan P. |
author_facet | Faulkner, Paul Huys, Quentin J. M. Renz, Daniel Eshel, Neir Pilling, Stephen Dayan, Peter Roiser, Jonathan P. |
author_sort | Faulkner, Paul |
collection | PubMed |
description | BACKGROUND: Real-life decisions are often complex because they involve making sequential choices that constrain future options. We have previously shown that to render such multi-step decisions manageable, people ‘prune’ (i.e. selectively disregard) branches of decision trees that contain negative outcomes. We have theorized that sub-optimal pruning contributes to depression by promoting an oversampling of branches that result in unsavoury outcomes, which results in a negatively-biased valuation of the world. However, no study has tested this theory in depressed individuals. METHODS: Thirty unmedicated depressed and 31 healthy participants were administered a sequential reinforcement-based decision-making task to determine pruning behaviours, and completed measures of depression and anxiety. Computational, Bayesian and frequentist analyses examined group differences in task performance and relationships between pruning and depressive symptoms. RESULTS: Consistent with prior findings, participants robustly pruned branches of decision trees that began with large losses, regardless of the potential utility of those branches. However, there was no group difference in pruning behaviours. Further, there was no relationship between pruning and levels of depression/anxiety. CONCLUSIONS: We found no evidence that sub-optimal pruning is evident in depression. Future research could determine whether maladaptive pruning behaviours are observable in specific sub-groups of depressed patients (e.g. in treatment-resistant individuals), or whether misuse of other heuristics may contribute to depression. |
format | Online Article Text |
id | pubmed-9811346 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98113462023-01-10 A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals Faulkner, Paul Huys, Quentin J. M. Renz, Daniel Eshel, Neir Pilling, Stephen Dayan, Peter Roiser, Jonathan P. Psychol Med Original Article BACKGROUND: Real-life decisions are often complex because they involve making sequential choices that constrain future options. We have previously shown that to render such multi-step decisions manageable, people ‘prune’ (i.e. selectively disregard) branches of decision trees that contain negative outcomes. We have theorized that sub-optimal pruning contributes to depression by promoting an oversampling of branches that result in unsavoury outcomes, which results in a negatively-biased valuation of the world. However, no study has tested this theory in depressed individuals. METHODS: Thirty unmedicated depressed and 31 healthy participants were administered a sequential reinforcement-based decision-making task to determine pruning behaviours, and completed measures of depression and anxiety. Computational, Bayesian and frequentist analyses examined group differences in task performance and relationships between pruning and depressive symptoms. RESULTS: Consistent with prior findings, participants robustly pruned branches of decision trees that began with large losses, regardless of the potential utility of those branches. However, there was no group difference in pruning behaviours. Further, there was no relationship between pruning and levels of depression/anxiety. CONCLUSIONS: We found no evidence that sub-optimal pruning is evident in depression. Future research could determine whether maladaptive pruning behaviours are observable in specific sub-groups of depressed patients (e.g. in treatment-resistant individuals), or whether misuse of other heuristics may contribute to depression. Cambridge University Press 2022-12 2021-03-12 /pmc/articles/PMC9811346/ /pubmed/33706833 http://dx.doi.org/10.1017/S0033291721000799 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Faulkner, Paul Huys, Quentin J. M. Renz, Daniel Eshel, Neir Pilling, Stephen Dayan, Peter Roiser, Jonathan P. A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals |
title | A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals |
title_full | A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals |
title_fullStr | A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals |
title_full_unstemmed | A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals |
title_short | A comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals |
title_sort | comparison of ‘pruning’ during multi-step planning in depressed and healthy individuals |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811346/ https://www.ncbi.nlm.nih.gov/pubmed/33706833 http://dx.doi.org/10.1017/S0033291721000799 |
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