NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Fific, Mario; Townsend, James T. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2010
Failure to selectively attend to a facial feature, in the part-to-whole paradigm, has been taken as evidence of holistic perception in a large body of face perception literature. In this article, we demonstrate that although failure of selective attention is a necessary property of holistic perception, its presence alone is not sufficient to…
Descriptors: Human Body, Recognition (Psychology), Visual Perception, Holistic Approach
Peer reviewed Peer reviewed
Direct linkDirect link
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