title: Human category learning 2.0.
abstract: During the 1990s and early 2000s, cognitive neuroscience investigations of human category learning focused on the primary goal of showing that humans have multiple category-learning systems and on the secondary goals of identifying key qualitative properties of each system and of roughly mapping out the neural networks that mediate each system. Many researchers now accept the strength of the evidence supporting multiple systems, and as a result, during the past few years, work has begun on the second generation of research questions-that is, on questions that begin with the assumption that humans have multiple category-learning systems. This article reviews much of this second generation of research. Topics covered include (1) How do the various systems interact? (2) Are there different neural systems for categorization and category representation? (3) How does automaticity develop in each system? and (4) Exactly how does each system learn?
authors.affiliation: Department of Psychology, University of California, Santa Barbara, California.Department of Psychology, University of Texas, Austin, Texas.
authors.forename: F Gregory
authors.initials: FG
authors.lastname: Ashby
authors.affiliation: Department of Psychology, University of California, Santa Barbara, California.Department of Psychology, University of Texas, Austin, Texas.
authors.forename: W Todd
authors.initials: WT
authors.lastname: Maddox
mesh_terms: D000818:Animals; D001332:Automatism / Q000523:psychology; D001519:Behavior / Q000502:physiology; D001931:Brain Mapping / Q000145:classification; D003071:Cognition / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007858:Learning / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000033:anatomy & histology / Q000502:physiology; D009488:Neurosciences / Q000379:methods / Q000639:trends; D012106:Research