Superior single dimension relative to "exclusive or" categorization performance by a patient with category-specific visual agnosia: empirical data and an ALCOVE simulation

Abstract

ELM, a patient with category-specific visual agnosia, was tested on a single-dimension categorization problem, and the "exclusive or" (XOR) categorization problem. Stimuli were computer-generated shapes in which exemplars within a shape set shared values across two visual dimensions (curvature and thickness). In single-dimension categorization only curvature was relevant, and ELM performed as well as normal participants. In the XOR problem, categorization depended on being able to extract from memory values on curvature AND thickness for each exemplar, and ELM was significantly impaired on this task. A computer simulation using ALCOVE (Kruschke, 1992) reproduced ELM's behavior by changing a single (specificity) parameter related to how easily proximate objects within a multidimensional shape space could be disambiguated.