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. 2024 Feb 14;627(8002):174–181. doi: 10.1038/s41586-024-07084-x

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© The Author(s), 2024, corrected publication 2024

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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 8 — a, Actual and shuffled decoding performance for each animal’s choice to cooperate and discrimination of social cues. Actual and shuffled values are plotted to provide an example comparison for the shuffle-corrected plots completed for monkey 1, Fig. 4a and d. Shuffled decoder accuracies remained at chance levels (50%) across all sessions. This was also the case for every other decoding analyses in Fig. 4. b, Decoding performance for social cues, categories, and choice where the number of observations remained the same across all sessions and for each class. For each brain area, decoding accuracy still significantly improves during learning when the number of observations remains unchanged across sessions. All P-values are from linear regression and r is Pearson correlation coefficient. Social cues M1 dlPFC P = 0.0003, r = 0.75 and V4 P = 0.02, r = 0.53; M2 dlPFC P = 9.9e⁻⁴, r = 0.78 and V4 P = 0.0003, r = 0.83. Categories M1 dlPFC P = 1.3e-4, r = 0.78; M2 dlPFC P = 0.002, r = 0.76. Choice M1 dlPFC P = 6.84e-4, r = 0.72; M2 dlPFC P = 0.003, r = 0.68. c, The change in decoding performance for social cues (original model accuracy with all neurons minus model with n-1 accuracy), is sorted according to the descending weight of the removed neuron. X-axis represents the index of a neuron; only one neuron was removed from each model. Session-averaged change in accuracy is plotted. Removing neurons with high weights decreases performance but the effect is attenuated as neurons with lower weights are removed. The change in accuracy for the first 30 neurons (out of 104 total in V4, 102 total in dlPFC) of descending weights is shown for clarity. V4 P = 1.11e-5, r = −0.71 and dlPFC P = 0.0009, r = −0.57; linear regression and Pearson correlation. d, For V4 and dlPFC, histograms display the change in decoding accuracy from removing upper and lower deciles of neurons (11 neurons) with the highest (gold and blue) and lowest (red) weights, respectively. Informative and uninformative neurons have significantly different effects on model performance. V4 P = 0.005 and dlPFC P = 0.009, Wilcoxon rank-sum test. *P < 0.05, **P < 0.01, ***P < 0.001.