Computational mechanisms underlying latent value updating of unchosen actions

Author:

Ben-Artzi Ido123ORCID,Kessler Yoav4ORCID,Nicenboim Bruno5ORCID,Shahar Nitzan12ORCID

Affiliation:

1. School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.

2. Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.

3. Minducate Science of Learning Research and Innovation Center of the Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.

4. Department of Psychology and School of Brain Sciences and Cognition, Ben Gurion University of the Negev, Be'er Sheva, Israel.

5. Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, Netherlands.

Abstract

Current studies suggest that individuals estimate the value of their choices based on observed feedback. Here, we ask whether individuals also update the value of their unchosen actions, even when the associated feedback remains unknown. One hundred seventy-eight individuals completed a multi-armed bandit task, making choices to gain rewards. We found robust evidence suggesting latent value updating of unchosen actions based on the chosen action’s outcome. Computational modeling results suggested that this effect is mainly explained by a value updating mechanism whereby individuals integrate the outcome history for choosing an option with that of rejecting the alternative. Properties of the deliberation (i.e., duration/difficulty) did not moderate the latent value updating of unchosen actions, suggesting that memory traces generated during deliberation might take a smaller role in this specific phenomenon than previously thought. We discuss the mechanisms facilitating credit assignment to unchosen actions and their implications for human decision-making.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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