Extended Data Fig. 2: Cluster separability and consistency of neuronal responses across participants.

a, The d’ (d-prime) indices measuring separability between the distribution of the vectoral cosine distances among all words within a cluster (purple) and those among all words across clusters (gray). The d’ indices were all above 2.5 reflecting strong separability. b, Selectivity index of neurons (mean with 95% CL, n = 19) when semantic domains were refined by moving or removing words whose meanings did not intuitively fit with their respective labels (Extended Data Table 2). c, There was no significant difference (χ² = 2.33, p = 0.31) in the proportions of neurons that displayed semantic selectivity based on the participants’ clinical conditions of essential tremor (ET), Parkinson’s disease (PD) or cervical dystonia (CD). d, Left, the proportional contribution per participant based on the total percentage of neurons contributed. Right, the proportional contribution of semantically selective cells per participant based on the fraction contributed. Participants without selective cells are not shown. e, A leave one out cross-validation participant-dropping procedure demonstrated that population results remained similar. Here, we sequentially removed individual participants (i.e., participants #1-10) and then repeated our selectivity analysis. Semantic selectivity across neurons was largely unaffected by removal of any of the participants (one-way ANOVA, F(9, 44) = 0.11, p = 0.99). Here, the mean selectivity indices (± s.e.m.) are separately presented after removing each participant. f, A cross-validation participant-dropping procedure was used to determine whether any of the participants disproportionately contributed to the population decoding. Average decoding results and comparison to the shuffled data are separately presented after removing each participant (permutation test, p < 0.01; #1-10).