The sizable difficulty in matching unfamiliar faces differing only moderately in orientation in depth is a function of image dissimilarity

Abstract

Attempting to match unfamiliar, highly similar faces at moderate differences in orientation in depth is surprisingly difficult. No neurocomputational account of these costs that addressed the representation of faces by which a face-similarity metric can be derived has been offered. A metric specifying the similarity of the to-be-distinguished faces is required as the rotation costs will be a function of the difficulty in distinguishing the faces. Consequently, rotation costs have typically been described in terms of angle of disparity, rather than the dissimilarity of the faces produced by the rotation. We assessed the effects of orientation disparity in a match-to-sample paradigm of a simultaneous presentation of a triangular display of three faces. Two lower test faces, a matching face and a foil, were always at the same orientation and differed by 0° to 20° from the sample on top. The similarity of the images was scaled by a model based on simple cell tuning, modeled as Gabor wavelets, that correlates almost perfectly with psychophysical similarity. Two measures of face similarity, with approximately additive effects on reaction times, accounted for matching performance: a) the decrease in similarity between the images of the matching and sample faces produced by increases in their orientation disparity, and b) the similarity between the matching face and the selection of a particular foil. The 20° orientation disparity was sufficient to yield a sizeable 301 msec increase in reaction time. An implication of the results is that the activity in V1 produced by viewing a face is fed forward to areas responsible for the individuation of that face.