Extended Data Fig. 1: Prototypical response profiles in ALM.

a Example clusters from the primary dataset. Left, dots represent individual neurons in the t-SNE representation. Neurons are divided into 94 clusters. Colors indicate 7 example clusters. Right, PSTHs of individual neurons in the example clusters. b ePAIRS test for distribution of response profiles. Each neuron’s PSTH shape is represented by a 26-dimensional vector that contains the loadings of the top 26 principal components of the population activity. For continuous variation of response profiles (that is no clustering), the vectors are uniformly distributed around the origin, which can be quantified by computing the angle between nearest neighbors (ePAIRS test). The distribution of angles deviates significantly from uniform distribution (P <1 × 10⁻⁴ for k=1, P < 1 × 10⁻⁴ for k=10, one-sided test, Methods), indicating that ALM response profiles exhibit clusters of prototypical response profiles. The result is consistent across different number of nearest neighbors (k) used to calculate average angle. c Cell-cell co-clustering matrix for every pair of neurons in the primary dataset. Only neurons showing consistent modulation during the task are included (n = 7340 neurons, 73 mice). Neurons are sorted based on density peak clustering (left). Co-clustering matrix of the same neuron pairs is shown for Louvain-Jaccard clustering (right). The block structure along the matrix diagonal is preserved in Louvain-Jaccard clustering, indicating that if two neurons belong to the same cluster by density peak clustering, then their co-clustering probability is high for Louvain-Jaccard clustering. d Average PSTHs of the largest and smallest clusters from the primary dataset. Mean ± SEM across neurons. The largest clusters are reproducible in Louvain-Jaccard clustering. The small clusters are not reproduced. e Robustness of the clustering results. Left, number of clusters from density peak clustering as a function of population size. Neurons are subsampled. Mean ± S.D. across populations. Cluster number saturates rapidly after 1000 neurons. Dashed line, the primary dataset consists of 94 clusters after manual merging of some similar clusters (Methods). Right, reproducibility of clusters in Louvain-Jaccard clustering. For each cluster from density peak clustering, we quantified the fraction of its units captured by a matching cluster in Louvain-Jaccard clustering (Methods). Clusters with >0.5 of units captured are considered reproducible. f Clusters from the second dataset are matched to clusters from the primary dataset based on the similarity their PSTHs. The plot shows Pearson’s correlation between clusters from the second dataset with all the clusters from the primary dataset. Clusters are matched based on high correlation coefficient (Methods). This analysis focuses on 48 clusters from the second dataset that are most readily matched to a corresponding cluster in the primary dataset. Gray lines, individual clusters; black line, mean. g Average PSTHs of 8 example clusters. Mean ± SEM across neurons. Rows 1–4 show distinct mouse groups (n = 18 mice per group). Row 5 shows matching clusters from the second dataset. h Response profiles of all clusters from 4 distinct mouse groups. Each row shows average activity of one cluster. i Neuron pairs with similar response profiles exhibit noise correlation. Top, an example neuron pair from the same cluster. Spike raster and PSTHs show simultaneously recorded responses from the neuron pair. In trials where one neuron exhibits high spike rate, the other neuron also exhibits high spike rate. The two neurons are 200 µm apart. Bottom, noise correlation for all neuron pairs. Mean ± SEM across neuron pairs. Same as Fig. 1h but for noise correlation calculated in various epochs. Baseline, = 1.98 × 10⁻¹¹; sample, P = 1.94 × 10⁻³⁰; delay, P = 8.91 × 10⁻³⁵; response, P = 9.92 × 10⁻¹⁵, two-sided Wilcoxon rank sum test (Methods).