Fig. 5: Dimensions of animacy and similarity judgements.

a Similarity judgements multiarrangement task. During this task, object images were shown on a computer screen in a circular arena, and participants were asked to arrange the objects according to their similarity, such that similar objects were placed close together and dissimilar objects were placed further apart. Participants performed multiple arrangements of subsets of the images, enabling us to estimate the underlying perceptual similarity space (see Methods for details). b Multidimensional scaling plot of similarity judgements (mean across 19 participants, with metric stress criterion). c Animacy dimension RDM comparisons with similarity judgements RDMs. Bars show the correlation between the similarity judgements RDMs and each animacy dimension RDM. A significant correlation is indicated by an asterisk (one-sided Wilcoxon signed-rank test, p < 0.05 corrected). Error bars show the standard error of the mean based on single-participant correlations, i.e., correlations between the single-participant similarity judgements RDMs and animacy dimension RDM. Circles show single-participant correlations. The grey bar represents the noise ceiling, which indicates the expected performance of the true model given the noise in the data. Horizontal lines show significant pairwise differences between model performance (p < 0.05, FDR corrected across all comparisons), an asterisk to the right of horizontal lines indicates their significance. d Unique variance of each animacy dimension in explaining similarity judgements. For each animacy dimension m, the unique variance was computed by subtracting the total variance explained by the reduced GLM (excluding the dimension of interest) from the total variance explained by the full GLM. Specifically, for dimension m, we fit GLM on X = “all dimensions but m” and Y = data, then we subtract the resulting R2 from the total R2 (fit GLM on X = “all dimensions” and Y = data). We used non-negative least squares to find optimal weights. A significant unique variance is indicated by an asterisk (one-sided Wilcoxon signed-rank test, p < 0.05 corrected). The error bars show the standard error of the mean based on single-participant unique variance. Circles show single-participant unique variance. Horizontal lines show significant pairwise differences between model performance (p < 0.05, FDR corrected across all comparisons), an asterisk to the right of horizontal lines indicates their significance.