title: Training 'greeble' experts: a framework for studying expert object recognition processes.
abstract: Twelve participants were trained to be experts at identifying a set of 'Greebles', novel objects that, like faces, all share a common spatial configuration. Tests comparing expert with novice performance revealed: (1) a surprising mix of generalizability and specificity in expert object recognition processes; and (2) that expertise is a multi-faceted phenomenon, neither adequately described by a single term nor adequately assessed by a single task. Greeble recognition by a simple neural-network model is also evaluated, and the model is found to account surprisingly well for both generalization and individuation using a single set of processes and representations.
authors.affiliation: Department of Psychology, Yale University, New Haven, CT 06520, USA. isabel.gauthier@yale.edu
authors.forename: I
authors.initials: I
authors.lastname: Gauthier
authors.forename: P
authors.initials: P
authors.lastname: Williams
authors.forename: M J
authors.initials: MJ
authors.lastname: Tarr
authors.forename: J
authors.initials: J
authors.lastname: Tanaka
mesh_terms: D003198:Computer Simulation; D004192:Discrimination, Psychological; D005556:Form Perception / Q000502:physiology*; D006801:Humans; D007858:Learning; D008568:Memory; D011930:Reaction Time