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Model-based prioritization for acquiring protection

Tashjian, Sarah M. and Wise, Toby and Mobbs, Dean (2021) Model-based prioritization for acquiring protection. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20220714-54291000

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Abstract

Protection, or the mitigation of harm, often involves the capacity to prospectively plan the actions needed to combat a threat. The computational architecture of decisions involving protection remains unclear, as well as whether these decisions differ from other positive prospective actions. Here we examine effects of valence and context by comparing protection to reward, which occurs in a different context but is also positively valenced, and punishment, which also occurs in an aversive context but differs in valence. We applied computational modeling across three independent studies (Total N=600) using five iterations of a ‘two-step’ behavioral task to examine model-based reinforcement learning for protection, reward, and punishment in humans. Decisions motivated by acquiring safety via protection evoked a higher degree of model-based control than acquiring reward and 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.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.31234/osf.io/nv5u4DOIDiscussion Paper
https://osf.io/4j3qz/Related ItemSupplemental Materials
ORCID:
AuthorORCID
Tashjian, Sarah M.0000-0002-0946-6662
Wise, Toby0000-0002-9021-3282
Mobbs, Dean0000-0003-1175-3772
Additional Information:License: CC0 1.0 Universal. Created: December 21, 2021; Last edited: March 16, 2022. 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. 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. Data availability: Task code and raw data are available through OSF, https://osf.io/4j3qz/. Author Contributions: SMT developed the study concept with input from DM. SMT designed the study with input from DM and TW. Data collection was performed by SMT. Data analysis and interpretation were performed by SMT and TW. SMT drafted the manuscript, with critical revisions from DM. All authors approved of the manuscript. The authors declare no competing interests.
Group:Tianqiao and Chrissy Chen Institute for Neuroscience
Funders:
Funding AgencyGrant Number
NIH2P50MH094258
John Templeton FoundationTWCF0366
Professor Anthony Mellows FellowshipUNSPECIFIED
Subject Keywords:model-based control, protection, punishment, reinforcement learning, safety
DOI:10.31234/osf.io/nv5u4
Record Number:CaltechAUTHORS:20220714-54291000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220714-54291000
Official Citation:Tashjian, Sarah M., et al. “Model-based Prioritization for Acquiring Protection.” PsyArXiv, 21 Dec. 2021. Web; DOI: 10.31234/osf.io/nv5u4
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115531
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Jul 2022 15:48
Last Modified:14 Jul 2022 15:48

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