title: Moving beyond pure signal-detection models: comment on Wixted (2007).
abstract: The dual-process signal-detection (DPSD) model assumes that recognition memory is based on recollection of qualitative information or on a signal-detection-based familiarity process. The model has proven useful for understanding results from a wide range of memory research, including behavioral, neuropsychological, electrophysiological, and neuroimaging studies. However, a number of concerns have been raised about the model over the years, and it has been suggested that an unequal-variance signal-detection (UVSD) model that incorporates separate recollection and familiarity processes (J. T. Wixted, 2007) may provide an equally good, or even better, account of the data. In this article, the authors show that the results of studies that differentiate these models support the predictions of the DPSD model and indicate that recognition does not reflect the summing of 2 signal-detection processes, as the new UVSD model assumes. In addition, the assumptions of the DPSD model are clarified in order to address some of the common misconceptions about the model. Although important challenges remain, hybrid models such as this provide a more useful framework within which to understand human memory than do pure signal-detection models.
authors.affiliation: Department of Psychology, University of California, Davis, CA 95616, USA. cmparks@ucdavis.edu
authors.forename: Colleen M
authors.initials: CM
authors.lastname: Parks
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Yonelinas
mesh_terms: D006801:Humans; D008960:Models, Psychological; D011582:Psychological Theory; D011584:Psychology / Q000379:methods* / Q000706:statistics & numerical data*; D012372:ROC Curve; D017603:Signal Detection, Psychological