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Nosofsky, Robert M.; Meagher, Brian J.; Kumar, Parhesh – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
A classic issue in the cognitive psychology of human category learning has involved the contrast between exemplar and prototype models. However, experimental tests to distinguish the models have relied almost solely on use of artificially-constructed categories composed of simplified stimuli. Here we contrast the predictions from the models in a…
Descriptors: Cognitive Psychology, Natural Sciences, Experimental Psychology, Prediction
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Nosofsky, Robert M.; Cao, Rui; Harding, Samuel M.; Shiffrin, Richard M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2021
Participants gave recognition judgments for short lists of pictures of everyday objects. Pictures in a given list were an equal mixture of three types that varied according to the way they were used as targets and foils earlier in the same session. Under consistent-mapping (CM), targets and foils never switch roles; under varied-mapping (VM),…
Descriptors: Long Term Memory, Short Term Memory, Recognition (Psychology), Cognitive Mapping
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Cao, Rui; Nosofsky, Robert M.; Shiffrin, Richard M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across…
Descriptors: Short Term Memory, Recall (Psychology), Item Response Theory, Learning Processes
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Donkin, Chris; Newell, Ben R.; Kalish, Mike; Dunn, John C.; Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
The strength of conclusions about the adoption of different categorization strategies--and their implications for theories about the cognitive and neural bases of category learning--depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and…
Descriptors: Classification, Learning, Learning Strategies, Identification
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Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
In a highly systematic literature, researchers have investigated the manner in which people make feature inferences in paradigms involving uncertain categorizations (e.g., Griffiths, Hayes, & Newell, 2012; Murphy & Ross, 1994, 2007, 2010a). Although researchers have discussed the implications of the results for models of categorization and…
Descriptors: Models, Classification, Inferences, Cognitive Psychology
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Nosofsky, Robert M.; Donkin, Chris – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
We report an experiment designed to provide a qualitative contrast between knowledge-limited versions of mixed-state and variable-resources (VR) models of visual change detection. The key data pattern is that observers often respond "same" on big-change trials, while simultaneously being able to discriminate between same and small-change…
Descriptors: Short Term Memory, Probability, Models, Prediction
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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
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Nosofsky, Robert M.; Cox, Gregory E.; Cao, Rui; Shiffrin, Richard M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across…
Descriptors: Short Term Memory, Long Term Memory, Recognition (Psychology), Cognitive Processes
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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
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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
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Little, Daniel R.; Nosofsky, Robert M.; Denton, Stephen E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2011
A recent resurgence in logical-rule theories of categorization has motivated the development of a class of models that predict not only choice probabilities but also categorization response times (RTs; Fific, Little, & Nosofsky, 2010). The new models combine mental-architecture and random-walk approaches within an integrated framework and…
Descriptors: Classification, Reaction Time, Stimuli, College Students
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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
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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
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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
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Nosofsky, Robert M.; Stanton, Roger D. – Journal of Experimental Psychology: Human Perception and Performance, 2006
Observers made speeded old-new recognition judgments of color stimuli embedded in a multidimensional similarity space. The paradigm used multiple lists but with the underlying similarity structures repeated across lists, to allow for quantitative modeling of the data at the individual-participant and individual-item levels. Correct rejection…
Descriptors: Recognition (Psychology), Multidimensional Scaling, Visual Stimuli, Color