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. 2022 Mar 4;13:1167. doi: 10.1038/s41467-022-28784-w

Fig. 3. Neuronal population discrimination between CS+ and CS− pre-DFC predicts learning specificity.

Fig. 3

a Mean (±sem) SVM performance across pre-DFC sessions predicts learning specificity 24 h post-DFC (retrieval session 1). Statistics: two-tailed Spearman’s rank correlation, r(12) = 0.77, p = 0.001. b Mean (±sd) SVM performance 24 h pre-DFC does not predict learning specificity 24 h post-DFC. Statistics: two-tailed Spearman’s rank correlation, r(12) = 0.35, p = 0.247. c Mean (±sem) SVM performance pre-DFC correlates with the mean (±sem) Zdiff score pre-DFC. Fill color indicates learning specificity from retrieval session 1. Statistics: two-tailed Spearman’s rank correlation, r(12) = 0.93, p = <0.0001. d Correlation (mean r ± 95% CI) between SVM performance averaged across 3 imaging sessions preceding retrieval sessions 1 (blue), and 4 (orange). Dots represent individual bootstrapped correlation values (n = 1000). Statistics: two-tailed Spearman’s rank correlation: [Imaging session 2:4, retrieval session 1] r(12) = 0.65, p = 0.008; [6:8, 1] r(12) = 0.42, p = 0.155; [2:4, 4)] r(12) = 0.50, p = 0.073; [5:7, 4] r(12) = 0.34, p = 0.252. Black lines in a, b, and c show the best linear fit. †p < 0.1, *p < 0.05, **p < 0.01, ***p < 0.001, n.s.p > 0.10. Source data are provided as a Source data file.