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. 2022 Jan 31;6(4):555–564. doi: 10.1038/s41562-021-01263-w

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© The Author(s) 2022

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/.

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Fig. 5 — Centre, histograms of the participants in each experiment sorted according to normalized model-estimated asymmetry: (α⁺ − α⁻)/|(α⁺ + α⁻)|. Saturation of the bars indicates improvement in model fit (ΔBIC; darker colours indicate greater improvement) compared with the corresponding symmetric model (that is, Q1 in Exp. 1 and Q1* + P in Exps. 2–4). No improvements can be seen in Exp. 1, where symmetric model Q1 provided the best fit (see also Fig. 3e). The raster plots on the bottom of each panel show individual participant results. The majority of participants (n = 79 of 128) in the partial-feedback experiments (Exps. 2–4) showed strongly asymmetric updating either of winning or of losing items, with clear improvements in model fit. Left, mean choice behaviour of participants that were strongly biased towards losers (leftmost bars in the centre plots, Exps. 2–4). p, proportion of correct choices. Right, same as left, for participants strongly biased towards winners (rightmost bars in the centre plots). The white crosses indicate choice accuracies below chance (<0.50).