Model-based prioritization for acquiring protection
- Creators
- Tashjian, Sarah M.
- Wise, Toby
- Mobbs, Dean
Abstract
Protection often involves the capacity to prospectively plan the actions needed to mitigate harm. The computational architecture of decisions involving protection remains unclear, as well as whether these decisions differ from other beneficial prospective actions such as reward acquisition. Here we compare protection acquisition to reward acquisition and punishment avoidance to examine overlapping and distinct features across the three action types. Protection acquisition is positively valenced similar to reward. For both protection and reward, the more the actor gains, the more benefit. However, reward and protection occur in different contexts, with protection existing in aversive contexts. Punishment avoidance also occurs in aversive contexts, but differs from protection because punishment is negatively valenced and motivates avoidance. Across three independent studies (Total N = 600) we applied computational modeling to examine model-based reinforcement learning for protection, reward, and punishment in humans. Decisions motivated by acquiring protection evoked a higher degree of model-based control than acquiring reward or avoiding punishment, with no significant differences in learning rate. The context-valence asymmetry characteristic of protection increased deployment of flexible decision strategies, suggesting model-based control depends on the context in which outcomes are encountered as well as the valence of the outcome.
Additional Information
© 2022 Tashjian et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. DM and SMT are supported by the US National Institute of Mental Health grant no. 2P50MH094258 and Templeton Foundation grant TWCF0366. TW is supported by a Professor Anthony Mellows Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Alexandra Hummel for her help with task development. Preregistration. The main hypotheses and methods were preregistered on the Open Science Framework (OSF), https://osf.io/4j3qz/registrations. The authors have declared that no competing interests exist.Attached Files
Published - pcbi.1010805.pdf
Supplemental Material - journal.pcbi.1010805.s001.tif
Supplemental Material - journal.pcbi.1010805.s002.tif
Supplemental Material - journal.pcbi.1010805.s003.tif
Supplemental Material - journal.pcbi.1010805.s004.tif
Supplemental Material - journal.pcbi.1010805.s005.tif
Supplemental Material - journal.pcbi.1010805.s006.xlsx
Supplemental Material - journal.pcbi.1010805.s007.xlsx
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Additional details
- PMCID
- PMC9810162
- Eprint ID
- 119529
- Resolver ID
- CaltechAUTHORS:20230227-87934600.4
- 2P50MH094258
- NIH
- TWCF0366
- John Templeton Foundation
- Professor Anthony Mellows Fellowship
- Created
-
2023-04-28Created from EPrint's datestamp field
- Updated
-
2023-04-28Created from EPrint's last_modified field
- Caltech groups
- Tianqiao and Chrissy Chen Institute for Neuroscience