Abstract
Face recognition and reading are two expert forms of human visual processing. Recent evidence show that they involve overlapping cerebral networks in the right and left hemispheres, leading the many-to-many hypothesis to predict that a lesion to the left fusiform gyrus that causes pure alexia will also be associated with mild impairments in face processing. Our goal was to determine if alexic subjects showed face identity processing deficits similar but milder to those seen in prosopagnosia following right fusiform lesions, or if they had different, complementary face processing deficits, which would be predicted if there were hemispheric lateralization of different face perceptual functions. We tested three patients with pure alexia from left fusiform lesions and one prosopagnosic subject with a right fusiform lesion. First, they had standard neuropsychologic tests of face identity recognition. Second, we atested their ability to discriminate faces in images reduced to high-contrast linear contours, similar to letters. Third, we assessed their ability to detect and discriminate facial speech patterns, and to identify these and integrate them with speech sounds in the McGurk effect (Campbell et al, 1986). Alexic subjects had normal familiarity for face identity on the Cambridge Face Memory Test. However, they were impaired in matching faces for identity across viewpoint, which was worse with line-contour faces. The prosopagnosic patient was also impaired in matching faces across viewpoints, but did well with line-contour faces. Alexic patients could detect facial speech patterns but had trouble identifying them and integrating them with speech sounds, whereas identification and integration was intact in the prosopagnosic subject. We conclude that, in addition to visual word processing, the left fusiform gyrus is involved in processing linear contour information and speech patterns in faces, a contribution complementary to the face identity processing of the right fusiform gyrus.
Meeting abstract presented at VSS 2017