Representational similarity analysis

Comparison of the pairwise relationships among measured or model response patterns. The same stimuli are presented to the systems being compared, and their representational dissimilarity matrices are related. A match can constrain representation without requiring one-to-one unit correspondence or establishing the underlying learning rule.

A matrix whose entry $D_{ij}$ describes how differently a system responds to stimuli $i$ and $j$. One convention is $D_{ij}=1-\mathrm{corr}(z_i,z_j)$ when the response vectors have nonzero variance. Such a dissimilarity need not satisfy every metric axiom. Model comparison must control fitted transformations and use held-out data.