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Little, Daniel R.; Nosofsky, Robert M.; Donkin, Christopher; Denton, Stephen E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
A classic distinction in perceptual information processing is whether stimuli are composed of separable dimensions, which are highly analyzable, or integral dimensions, which are processed holistically. Previous tests of a set of logical-rule models of classification have shown that separable-dimension stimuli are processed serially if the…
Descriptors: Classification, Stimuli, Reaction Time, Models
Stanton, Roger D.; Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
Researchers have proposed that an explicit reasoning system is responsible for learning rule-based category structures and that a separate implicit, procedural-learning system is responsible for learning information-integration category structures. As evidence for this multiple-system hypothesis, researchers report a dissociation based on…
Descriptors: Classification, Psychological Studies, Learning Strategies, Cognitive Processes
Gureckis, Todd M.; James, Thomas W.; Nosofsky, Robert M. – Journal of Cognitive Neuroscience, 2011
Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of…
Descriptors: Incidental Learning, Learning Processes, Diagnostic Tests, Brain Hemisphere Functions
Nosofsky, Robert M.; Little, Daniel R.; Donkin, Christopher; Fific, Mario – Psychological Review, 2011
Exemplar-similarity models such as the exemplar-based random walk (EBRW) model (Nosofsky & Palmeri, 1997b) were designed to provide a formal account of multidimensional classification choice probabilities and response times (RTs). At the same time, a recurring theme has been to use exemplar models to account for old-new item recognition and to…
Descriptors: Short Term Memory, Classification, Probability, Cognitive Development
Fific, Mario; Little, Daniel R.; Nosofsky, Robert M. – Psychological Review, 2010
We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli…
Descriptors: Visual Stimuli, Models, Classification, Probability
Fific, Mario; Nosofsky, Robert M.; Townsend, James T. – Journal of Experimental Psychology: Human Perception and Performance, 2008
A growing methodology, known as the systems factorial technology (SFT), is being developed to diagnose the types of information-processing architectures (serial, parallel, or coactive) and stopping rules (exhaustive or self-terminating) that operate in tasks of multidimensional perception. Whereas most previous applications of SFT have been in…
Descriptors: Stimuli, Classification, Research Methodology, Cognitive Development
Nosofsky, Robert M.; Stanton, Roger D. – Journal of Experimental Psychology: Human Perception and Performance, 2005
Speeded perceptual classification experiments were conducted to distinguish among the predictions of exemplar-retrieval, decision-boundary, and prototype models. The key manipulation was that across conditions, individual stimuli received either probabilistic or deterministic category feedback. Regardless of the probabilistic feedback, however, an…
Descriptors: Experimental Psychology, Classification, Models, Perception

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