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. 2023 Jul 19;620(7973):366–373. doi: 10.1038/s41586-023-06357-1

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© The Author(s) 2023

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. 2 — a–c, Sst44 cell activity is weakly correlated with overall circuit activity. a, Sample trace of mean population activity of Sst44+, Sst44-/Sst+ and non-Sst cells in PPC. b–c, Pearson correlation between population means of each cell type across sessions (b), and at different time lags (c). d–g, Similar correlation and clustering statistics between mazes that contain or do not contain a delay between the visual cue and T-intersection. d–e, Pearson correlation between cells of each cell type. f–g, Fraction of 10 nearest neighbours in activity space that are Sst44+. ** p < 0.01, Kolmogorov-Smirnov test. Mean and bootstrapped 95% confidence intervals are shown. Activity was smoothed with a 0.25 s gaussian filter for these analyses.