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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: Nat Neurosci. 2021 Apr 19;24(6):886–896. doi: 10.1038/s41593-021-00841-5

Extended Data Fig. 9. Discriminant neurons in decoding cortical pattern identity and the fraction of distinguishable pairs using different neuron populations.

Extended Data Fig. 9

a, Discriminant neurons selected by feature elimination algorithm in decoding for each pattern pair. Note that the decoding often requires information from multiple HPC neurons, and all HPC neurons contributed to the decoding of some pattern pairs. b, The decoding results of cortical patterns using both the PYR and INT, the PYR only, and the INT only. Gray lines: the chance level fraction with P < 0.05. The chance level number of decodable pattern pairs (nc) was computed from the inverse of binomial cumulative distribution with probability 0.95 (one-sided binomial test, n = 28 pattern pairs). The chance level fraction was obtained by dividing nc with n = 28, the number of pattern pairs on which decoding was performed. PYR: pyramidal neurons, INT: interneurons. For PYR + INT, the p-values for mouse 1–6 are 2.24E-10, 5.10E-32, 5.10E-32, 2.60E-14, 9.17E-26, 8.42E-30. For PYR only, the p-values for mouse 1–6 are 1.26E-11, 8.42E-30, 9.63E-16, 0.16, 5.56E-7, 2.60E-14. For INT only, the p-values for mouse 1–6 are 0.76, 0.0023, 2.60E-14, 5.56E-7, 4.92E-5, 4.92E-5.