Object categorization performance modeled using multidimensional scaling and category-consistent features

• Participants provided similarity ratings for 144 objects (from 4 superordinate-level categories, each with 4 nested basic-level, and 3 nested subordinate categories). • Similarity ratings were obtained using the spatial arrangement method (SpAM; Hout et al., 2013, 2016). • 25 randomly selected items were first located outside a usable “arena.” They were arranged on screen and placed at distances (relative to one another) that represented the observer’s perception of similarity between each pair of items (closer in space denotes “more similar”). • Each participant completed 20 SpAM trials. There were 62 and 49 participants from NMSU and Stony Brook, respectively. Object categorization performance modeled using multidimensional scaling and category-consistent features Michael C. Hout 1, Justin Maxfield 2, Arryn Robbins 1, and Gregory J. Zelinsky 2 1New Mexico State University 2Stony Brook University