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. 2021 Mar 31;12:1985. doi: 10.1038/s41467-021-22195-z

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© The Author(s) 2021

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. 8 — These data support the idea of mixed selectivity. a The number of tuned neurons for self variables (self position, self direction, and self speed) when splitting data randomly (gray bar) or according to value of pursued prey (purple bar). Splitting by value increases proportion of tuned neurons, indicating that value modulates responding in a systematic way. b The number of significantly tuned neurons for prey variables (prey position, prey direction, and prey speed) when splitting data randomly (gray bar) or according to value of pursued prey (purple bar). The difference of value split was significant (p = 0.0221 for prey speed, and p < 0.001 for other prey variables), but not for random split. For the prey analysis, only single prey trial is included to reduce confounding (i.e., pursuing targets, transition of pursuit-avoidance behavior). c The number of significantly tuned neurons for egocentric (self position, self direction, and self speed) when splitting data randomly (gray bar) or according to value of pursued prey (purple bar). The difference of value split was significant (p < 0.001). We observed a difference in numbers of significantly tuned neurons between split data. This process was repeated for 50 times by bootstrapping. Significance was calculated by two-sided sign-rank test. n.s means it is not significant, and *** indicates p < 0.001.