NEURAL-NETWORK MODELS AS EVIDENCE FOR DIFFERENT TYPES OF VISUAL REPRESENTATIONS

Cook (1995) criticizes the work of Jacobs and Kosslyn (1994) on spatia l relations, shape representations, and receptive fields in neural net work models on the grounds that first-order correlations between input and output unit activities can explain the results. We reply briefly to Cook's arguments here (and in Kosslyn, Chabris, Marsolek, Jacobs, & Koenig, 1995) and discuss how new simulations can confirm the importa nce of receptive field size as a crucial variable in the encoding of c ategorical and coordinate spatial relations and the corresponding shap e representations; such simulations would testify to the computational distinction between the different types of representations.