| Abstract: | A theoretical framework for perceptual representation is presented which proposes that information is coded in hierarchical networks of nonverbal propositions. The hierarchical structure of the representations implies selective organization: Some subsets of a figure will be encoded as integral, structural units of that figure, while others will not. A context-sensitive metric for the “goodness” of a part within a figure is developed, corresponding to the probability that the subset will be encoded as a structural unit. Converging evidence supporting this position is presented from four different tasks using simple, straight-line figures. The tasks studied are (a) dividing figures into “natural” parts, (b) rating the “goodness” of parts within figures, (c) timed verification of parts within figures, and (d) timed mental synthesis of spatially separated parts into unitary figures. The results are discussed in terms of the proposed theory of representation, the processes that operate on those representations, and the general implications of the data for perceptual theories. |
