Figure 7.

MDS of DMs from LOC and behavioral ratings. A, 2D MDS solution that reflects the best fit Euclidean distances for all 13 input matrices (12 subjects plus the behavioral DM) computed using individual differences scaling (Takane et al., 1977). B, Individual differences are reflected in the weights assigned to each dimension for each input matrix. The weights reflect the importance of each dimension to each DM. The LOC DMs all have high weights on Dimension 1 and low weights on Dimension 2. Four subjects had weights equal to zero on Dimension 2, which means that the MDS solutions for those subjects are equivalent to a projection of the stimulus points onto the x-axis in A, and scaled along the x-axis by the weight on Dimension 1. Thus, for those subjects a single-dimensional solution with primates at one end and bugs at the other accounted for the most variance in LOC. Dim, Dimension.