Figure 3.

Representational dissimilarity matrices (RDMs) and MDS arrangements for human IT and judgments. Human IT activity patterns and human similarity judgments both show an inherently categorical representation of real-world object images with an animate/inanimate top-level division. At the same time, the similarity judgments show additional categorical divisions and stronger clustering than the hIT similarity representation. (A) RDMs based on hIT activity patterns and human similarity judgments. Each RDM is based on data from multiple subjects (4 and 16, respectively), averaged at the level of the dissimilarities. Each entry of a matrix represents hIT activity-pattern dissimilarity (1-r, where r is Pearson correlation coefficient; 316 most visually responsive bilateral hIT voxels defined using independent data) or judged dissimilarity (relative Euclidean distance as measured by the MA method) for a pair of objects. The matrices were independently transformed into percentiles (see color bar). (B) Multidimensional scaling (MDS; criterion: metric stress) was used to visualize the hIT and judgment similarity representations of the 96 real-world object images. Distances between images reflect the dissimilarities that are shown in the RDMs in (A): images that elicited similar activity patterns or that were judged as similar are placed close together; images that elicited dissimilar activity patterns or were judged as dissimilar are placed further apart.