Figure 4
From: Visual sense of number vs. sense of magnitude in humans and machines
Representational similarity analysis. (A) Representational dissimilarity matrices for the best deep network architecture (distance measure: 1 – Pearson correlation) and the most relevant categorical models (distance measure: log distance between stimulus features). Each RDM was separately rank transformed and scaled into [0,1]. (B) Second-order correlation matrix showing the pairwise correlations between RDMs. (C) Relatedness between the model’s RDM and the categorical RDMs, measured as the Kendall rank correlation between dissimilarity matrices. Asterisks indicate significance in a one-sided signed rank test, thresholded at FDR < 0.01. Error bars indicate the standard error of the correlation estimate. Grey horizontal lines represent noise ceiling (i.e., the highest correlation that could be achieved considering the data variability).
