Tarantola, T;
Kumaran, D;
Dayan, P;
De Martino, B;
(2017)
Prior preferences beneficially influence social and non-social learning.
Nature Communications
, 8
, Article 817. 10.1038/s41467-017-00826-8.
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Abstract
Our personal preferences affect a broad array of social behaviors. This includes the way we learn the preferences of others, an ability that often relies on limited or ambiguous information. Here we report an egocentric influence on this type of social learning that is reflected in both performance and response times. Using computational models that combine inter-trial learning and intra-trial choice, we find transient effects of participants' preferences on the learning process, through the influence of priors, and persistent effects on the choice process. A second experiment shows that these effects generalize to non-social learning, though participants in the social learning experiment appeared to additionally benefit by using their knowledge about the popularity of certain preferences. We further find that the domain-general egocentric influences we identify can yield performance advantages in uncertain environments.People often assume that other people share their preferences, but how exactly this bias manifests itself in learning and decision-making is unclear. Here, authors show that a person's own preferences influence learning in both social and non-social situations, and that this bias improves performance.
Type: | Article |
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Title: | Prior preferences beneficially influence social and non-social learning |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1038/s41467-017-00826-8 |
Publisher version: | http://doi.org/10.1038/s41467-017-00826-8 |
Language: | English |
Additional information: | Copyright © The Author(s) 2017. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | Human behaviour, Learning algorithms, Operant learning, Reward, Social behaviour |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Institute of Cognitive Neuroscience UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10024775 |
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