Biomedical subjects

Roger D Stanton

Publications and source records attributed to Roger D Stanton.

5 recordsLinked to original sources

PubMed2006

Speeded old-new recognition of multidimensional perceptual stimuli: modeling performance at the individual-participant and individual-item levels.

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 response times (RTs) got systematically faster as the similarity of foils to the old study items decreased. There were also intricate patterns of speed-accuracy trade-offs that varied across individual items and participants. An exemplar-based random-walk model provided a good overall quantitative account of the recognition choice probabilities, mean correct RTs, and mean error RTs associated with the individual items on the basis of their positions in multidimensional similarity space. However, the model failed to predict the very long RTs associated with correct rejections of a prototype foil.

Adult↗

PubMed2005

Speeded classification in a probabilistic category structure: contrasting exemplar-retrieval, decision-boundary, and prototype models.

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 ideal observer would always classify the stimuli by using an identical linear decision boundary. Subjects classified the probabilistic stimuli with lower accuracy and longer response times than they classified the deterministic stimuli. These results are in accord with the predictions of the exemplar model and challenge the predictions of the prototype and decision-boundary models.

Analysis of Variance↗

PubMed2005

Procedural interference in perceptual classification: implicit learning or cognitive complexity?

Researchers have argued that an implicit procedural-learning system underlies performance for information integration category structures, whereas a separate explicit system underlies performance for rule-based categories. One source of evidence is a dissociation in which procedural interference harms performance in information integration structures, but not in rule-based ones. The present research provides evidence that some form of overall difficulty or category complexity lies at the root of the dissociation. The authors report studies in which procedural interference is observed for even simple rule-based structures under more sensitive testing conditions. Furthermore, the magnitude of the interference is large when the nature of the rule is made more complex. By contrast, the magnitude of interference is greatly reduced for an information integration structure that is cognitively simple. These results challenge the view that a procedural-learning system mediates performance on information integration categories, but not on rule-based ones.

Adult↗

PubMed2003

Prototype and exemplar accounts of category learning and attentional allocation: a reassessment.

In a recent article. J. P. Minda and J. D. Smith (2002; see record 2002-00620-002) argued that an exemplar model provided worse quantitative fits than an alternative prototype model to individual subject data from the classic D. L. Medin and M. M. Schaffer (1978) 5/4 categorization paradigm. In addition, they argued that the exemplar model achieved its fits by making untenable assumptions regarding how observers distribute their attention. In this article, we demonstrate that when the models are equated in terms of their response-rule flexibility, the exemplar model provides a substantially better account of the categorization data than does a prototype or mixed model. In addition, we point to shortcomings in the attention-allocation analyses conducted by J. P. Minda and J. D. Smith (2002). When these shortcomings are corrected, we find no evidence that challenges the attention-allocation assumptions of the exemplar model.

Attention↗

PubMed2002

Comparisons between exemplar similarity and mixed prototype models using a linearly separable category structure.

Nosofsky and Zaki (2002) found that an exemplar similarity model provided better accounts of individual subject classification and generalization performance than did a mixed prototype model proposed by Smith and Minda (1998; Minda & Smith, 2001). However, these previous tests used a nonlinearly separable category structure. In the present work, the authors extend the previous findings by demonstrating a superiority for the exemplar generalization model over the mixed prototype model in a case involving a linearly separable structure. Because this structure has numerous features that Minda and Smith argued should be conducive to prototype-based processing, the results pose a significant challenge to the mixed prototype view.

Generalization, Psychological↗