Extended Data Fig. 4: Activity modes are non-randomly mixed across ALM populations.

a Neuron weights in the t-SNE representation. Same as Fig. 3b, but for the second dataset. b Distribution of coding vector angles between nearest neighbors. Same as Fig. 3c, but for different number of nearest neighbors (k) used to calculate average angles (ePAIRS test, one-sided test; P = 0.049 for k=1, P < 1 × 10⁻⁴ for k=10, Methods). Data from the primary dataset. Only neurons with more than 5 error trials of each trial type are included (n = 3966). c Effect of neuronal population size on analysis of mixed selectivity. 100 neurons are randomly selected from the full dataset to generate subpopulations. The histogram shows the distribution of coding vector angles between nearest neighbors in the subpopulation (P = 0.54, ePAIRS test, one-sided test). The distribution is not significantly different from random distribution. Thus a population of 100 neurons appears to exhibit randomly mixed selectivity. d Power analysis showing the P value of ePAIRS test as a function of population size. Subsets of neurons are randomly selected from the full dataset to generate subpopulations. Detecting significant deviations from randomly mixed selectivity using a criterion of P < 0.01 (one-sided test) requires at least 400 neurons. e Generation of a synthetic population in which the coding of activity modes is randomly mixed. Each synthetic neuron’s PSTH is constructed from random combinations of the activity modes and eigenvectors of the original population response. This procedure preserved the activity modes but redistributed them randomly across the synthetic population. f PSTHs of example synthetic neurons. Blue, ‘lick right’ trials; red, ‘lick left’ trials. g Neuron weights in the t-SNE representation. Same as Fig. 3b, but for the synthetic population.