Robert M. Nosofsky
Distinguished Professor
812-855-2534 (office) |
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Robert Nosofsky s primary research is in the area of computational modeling of human category learning and representation, and relations between categorization and memory. He is best known for his development and testing of the generalized context model (GCM), which a major review article characterized as one of the most influential formal models in all of psychology . The GCM formalizes the idea that people represent categories by storing numerous individual examples of the categories in memory, and classify objects on the basis of their similarity to the stored examples. Nosofsky also pioneered the rigorous application of similarity-scaling techniques in combination with the formal model to allow for quantitative prediction of classification performance at the level of individual items. Important extensions of the model also allow it to account for the time course of categorization decision making and the prediction of classification response times. Because of its individual-example-storage assumption, the GCM and its extensions also provide a unified account of relations between categorization and old-new recognition memory. In his current work, Nosofsky has been scaling up the application of the model to real-world natural category domains; using a variety of complementary techniques for deriving high-dimensional similarity spaces for the objects under study; and applying the model to help guide the search for effective procedures for teaching science categories.
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Research Interests
My research is organized around the development and testing of formal mathematical models of perceptual category learning and representation. A main theme of the research involves studying relations between categorization and other fundamental cognitive processes, including old-new recognition memory, the development of automaticity, and decision making. Current research projects include: 1) using formal models of human category learning to enhance educational practice in the teaching of scientific classifications, 2) modeling the time course of categorization and recognition judgments, 3) studying the properties of visual working memory, 4) examining the basis for neural and behavioral dissociations between categorization and memory performance.
Curriculum Vitae
Online Papers
Meagher, B. J., & Nosofsky, R. M. (in press). Testing formal cognitive models of classification and old-new recognition in a real-world high-dimensional category domain. Cognitive Psychology
Hussaindeen, J. R., Ramakrishnan, B., Ravi, A., Sundaraj, M., Rakshit, A., Nosofsky, R. M., & Candy, T. R. (2023). Discrimination of pediatric acuity test optotypes by six-year-old children, Ophthalmic and Physiological Optics, 43, 964-971.
Zheng, R., Busemeyer, J. R., & Nosofsky, R. M. (2023). Integrating categorization and decision making. Cognitive Science, 47.
Nosofsky, R.M., & Hu, M. (2022). Category structure and region-specific selective attention. Memory & Cognition
Nosofsky, R.M., & Hu, M. (2022). Generalization in distant regions of a rule-described category space: A mixed exemplar and logical-rule-based account. Computational Brain & Behavior.
Nosofsky, R. M, & Meagher, B. J. (2022). Retention of exemplar-specific information in learning of real-world high-dimensional categories: Evidence from modeling of old-new item recognition. Proceedings for the 44th Annual Meeting of the Cognitive Science Society. Toronto, Canada. [Accepted for talk at the conference, top 27% of submissions]
Nosofsky, R. M., Meagher, B. J., & Kumar, P. (2022). Comparing exemplar and prototype models in a natural-science category domain. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48, 1970-1994.
Hu, M, & Nosofsky, R. M. (2022). Exemplar-model account of categorization and recognition when training instances never repeat. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48, 1947-1969.
Meagher, B. J., McDaniel, M. A., & Nosofsky, R. M. (2021). Effects of feature highlighting and causal explanations on category learning in a natural-science domain. Journal of Experimental Psychology:Applied, 28, 283.
Nosofsky, R. M., Cao, R., Harding, S., & Shiffrin, R. M. (2021). Modeling short- and long-term memory contributions to recent event recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 47, 316.
Nosofsky, R. M., Meagher, B. J., & Kumar, P. (2020). Comparing exemplar and prototype models in a natural-science category domain. Proceedings for the 42nd Annual Meeting of the Cognitive Science Society. Toronto, Canada. [Accepted for talk at the conference, top 20% of submissions]
Sanders, C. A., & Nosofsky, R. M. (2020). Training deep networks to construct a psychological feature space for a natural-object category domain. Computational Brain & Behavior, 1-23.
Nosofsky, R. M., Sanders, C. A., Meagher, B. J., & Douglas, B. J. (2020). Search for the missing dimensions: building a feature-space representation for a natural-science category domain. Computational Brain & Behavior, 3(1), 13-33.
Le Pelley, M., Newell, B., & Nosofsky, R.M. (2019). Deferred feedback does not dissociate implicit and explicit category learning systems: Commentary on Smith et al. (2014). Psychological Science, 30(9), 1403-1409.
Nosofsky, R. M., Slaughter, C., & McDaniel, M. A. (2019). Learning hierarchically organized science categories: Simultaneous instruction at the high and subtype levels. Cognitive Research: Principles and Implications, 4(1), 1-17.
Nosofsky, R. M., Sanders, C. A., Meagher, B. J., & Douglas, B. J. (2019). Search for the missing dimensions: Building a feature-space representation for a natural-science category domain. Computational Brain & Behavior.
Miyatsu, T., Gouravajhala, R., Nosofsky, R.M., & McDaniel, M.A. (2019). Feature highlighting enhances learning of complex natural-science categories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45, 1-16.
Nosofsky, R. M., & McDaniel, M. A. (2019). Recommendations from cognitive psychology for enhancing the teaching of natural-science categories. Policy Insights from the Behavioral and Brain Sciences: FABBS, 6, 21-28.
Nosofsky, R. M., Sanders, C. A., Zhu, X., & McDaniel, M. A. (2019). Model-guided search for optimal training exemplars in a natural-science category domain. Psychonomic Bulletin & Review, 26, 48-76.
Meagher, B.J., Cataldo, K., Douglas, B.J., McDaniel, M.A., & Nosofsky, R.M. (2018). Training of rock classifications: The use of computer images versus physical-rock samples. Journal of Geoscience Education, 66(3), 221-230.
Nosofsky, R. M., & Gold, J. M. (2018). Biased guessing in a complete-identification visual-working-memory task: Further evidence for mixed-state models. Journal of Experimental Psychology: Human Perception & Performance, 44 , 603-625.
Nosofsky, R. M., Sanders, C. A., & McDaniel, M. A. (2018). Tests of an exemplar-memory model of classification learning in a high-dimensional natural-science category domain. Journal of Experimental Psychology: General, 147, 328-353.
Nosofsky, R.M., Sanders, C., & McDaniel, M. (2018). A formal psychological model of classification applied to natural-science category learning. Current Directions in Psychological Science, 27, 129-135.
Sanders, C. A., & Nosofsky, R. M. (2018). Using deep-learning representations of complex natural stimuli as input to psychological models of classification. Proceedings of the 40th Annual Conference of the Cognitive Science Society.
Meagher, B.J., Carvalho, P.F., Goldstone, R.L., & Nosofsky, R.M. (2017). Organized simultaneous displays facilitate learning of complex natural science categories. Psychonomic Bulletin & Review.
Nosofsky, R.M., Sanders, C., Meagher, B.J., & Douglas, B.J (2018). Toward the development of a feature-space representation for a complex natural category domain. Behavior Research Methods, 50, 530-556 doi:10.3758/s13428-017-0884-8.
Nosofsky, R.M., Sanders, C., Gerdom, A., Douglas, B., & McDaniel, M. (2017). On learning natural science categories that violate the family-resemblance principle. Psychological Science, 28, 104-114.
Nosofsky, R.M., & Donkin, C. (2016). Qualitative contrast between knowledge-limited mixed-state and variable-resources models of visual change detection. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42, 1507-1525.
Little, D. R., Wang, T., & Nosofsky, R. M. (2016). Sequence-sensitive exemplar and decision-bound accounts of speeded-classification performance in a modified Garner-tasks paradigm. Cognitive Psychology, 89, 1-38.
Cao, R., Nosofsky, R.M., & Shiffrin, R.M. (2016). The development of automaticity in short-term memory search: Item-response learning and category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition. DOI: 10.1037/xlm0000355
Nosofsky, R. M. (2016). An exemplar-retrieval model of short-term memory search: Linking categorization and probe recognition. Psychology of Learning and Motivation, 65, 47-84..
Nosofsky, R.M., & Donkin, C. (2016). Response-time evidence for mixed memory states in a sequential-presentation change-detection task. Cognitive Psychology, 84, 31-62.
Nosofsky, R.M. (2015). An exemplar-model account of feature inference from uncertain categorizations. Journal of Experimental Psychology: Learning, Memory and Cognition, 41, 1929-1941.
Nosofsky, R.M., & Gold, J. (2015). Memory strength versus memory variability in visual change detection. Attention, Perception, & Psychophysics. DOI 10.3758/s13414-015-0992-4
Donkin, C., Newell, B. R., Kalish, M., Dunn, J. C., & Nosofsky, R. M. (2014). Identifying Strategy Use in Category Learning Tasks: A Case for More Diagnostic Data and Models. Journal of Experimental Psychology: Learning, Memory, and Cognition, Advance online publication. .
Nosofsky, R.M. (2014). The generalized context model: an exemplar model of classification. In M. Pothos and A. Wills (Eds.), Formal Approaches in Categorizaton. Cambridge University Press: New York.
Stanton, R.D., & Nosofsky, R.M. (2013). Category number impacts rule-based and information-integration category learning: A reassessment of evidence for dissociable category-learning systems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 1174-1191.
Donkin, C., Tran, S.C., & Nosofsky, R.M. (2014). Landscaping analyses of the ROC predictions of discrete-slots and signal-detection models of visual working memory. Attention, Perception & Psychophysics. DOI 10.3758/s13414-013-0561-7
Donkin, C., Nosofsky, R.M., Gold, J., & Shiffrin, R.M. (2014). Verbal labeling, gradual decay, and sudden death in visual short-term memory. Psychonomic Bulletin & Review. DOI 10.3758/s13423-014-0675-5
Nosofsky, R. M., Cox, G. E., Cao, R., & Shiffrin, R. M. (2014). An exemplar-familiarity model predicts short-term and long-term probe recognition across diverse forms of memory search. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication. http://dx.doi.org/10.1037/xlm0000015
Nosofsky, R. M., Cao, R., Cox, G. E., & Shiffrin R. M. (2014). Familiarity and categorization processes in memory search. Cognitive Psychology, 75, 97-129.
Nosofsky, R.M., & Palmeri, T.J. (2015). An exemplar-based random-walk model of categorization and recognition. In J.R. Busemeyer, J.T. Townsend, Z.J. Wang, & A Eidels (Eds.), Oxford Handbook of Computational and Mathematical Psychology.
Donkin, C., Nosofsky, R.M., Gold, J.M., & Shiffrin, R.M. (2013). Discrete-slots models of visual working-memory response times. Psychological Review, 120, 873-902. [Supplementary materials]
Donkin, C., & Nosofsky, R.M. (2012). The structure of short-term memory scanning: an investigation using response time distribution models. Psychonomic Bulletin & Review, 19, 363-394.
Nosofsky, R.M., Denton, S.E., Zaki, S.R., Murphy-Knudsen, A.F., & Unverzagt, F.W. (2012). Studies of implicit prototype extraction in patients with mild cognitive impairment and early Alzheimer's disease. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 860-880.
Little, D.R., Nosofsky, R.M., Donkin, C., & Denton, S.E. (2013). Logical rules and the classification of integral-dimension stimuli. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 801-820.
Nosofsky, R.M., Little, D.R., & James, T.W. (2012). Activation in the neural network responsible for categorization and recognition reflects parameter changes. Proceedings of the National Academy of Sciences, 109, 333-338. [Supporting Information]
Donkin, C., & Nosofsky, R.M. (2012). A power law model of psychological memory strength in short- and long-term recognition. Psychological Science, 23, 625-634.
Nosofsky, R.M., Little, D.R., Donkin, C., & Fific, M. (2011). Short-term memory scanning viewed as exemplar-based categorization. Psychological Review, 118, 280-315.
Fific, M., Little, D. R., & Nosofsky, R. M.(2010). Logical-rule models of classification response times: A synthesis of mental-architecture, random-walk, and decision-bound approaches. Psychological Review, 117, 309-348. [Supplemental files]
Gureckis, T. M., James, T. W., & Nosofsky, R. M.(2011). Re-evaluating dissociations between implicit and explicit category learning: An event-related fMRI study. Journal of Cognitive Neuroscience, 23, 1697-1709.
Little, D. R., Nosofsky, R. M., & Denton, S. E. (2011). Response-time tests of logical-rule models of categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 1-27.
Nosofsky, R. M., & Little, D. R.(2010). Classification response times in probabilistic rule-based category structures: Contrasting exemplar-retrieval and decision-bound models. Memory & Cognition, 38, 916-927. [Supplemental files]
Fific, M., Nosofsky, R. M., & Townsend, J. T. (2008). Information-Processing Architectures in Multidimensional Classification: A Validation Test of the Systems Factorial Technology. Journal of Experimental Psychology: Human Perception and Performance, 34, 356-375.
Nosofsky, R. M., & Bergert, F. B. (2007). Limitations of Exemplar Models of Multi-Attribute Probabilisitic Inference. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 999-1019.
Bergert, F. B., & Nosofsky, R. M. (2007). A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 107-129.
Zaki, S. R., & Nosofsky, R. M. (2007). A high-distortion enhancement effect in the prototype-learning paradigm: Dramatic effects of category learning during test. Memory & Cognition, 35, 2088-2096.
Stanton, R. D., & Nosofsky, R. M. (2007). Feedback interference and dissociations of classification: Evidence against the multiple-learning-systems hypothesis. Memory & Cognition, 35, 1747-1758.
Nosofsky, R. M., & Stanton, R. D. (2006). Speeded Old New Recognition of Multidimensional Perceptual Stimuli: Modeling Performance at the Individual-Participant and Individual-Item Levels. Journal of Experimental Psychology: Human Perception and Performance, 32, 314-334
Knapp, B. R., Nosofsky, R. M., & Busey, T. A. (2006). Recognizing distinctive faces: A hybrid-similarity exemplar model account. Memory & Cognition, 34, 877-889.
Nosofsky, R. M., & Kantner, J. (2006). Exemplar similarity, study-list homogeneity, and short-term perceptual recognition. Memory & Cognition, 34, 112-124.
Nosofsky, R. M., Stanton, R. D., & Zaki, S. R. (2005). Procedural interference in perceptual classification: Implicit learning or cognitive complexity? Memory & Cognition, 33, 1256-1271.
Nosofsky, R. M., & Stanton, R. D. (2005). Speeded classification in a probabilistic category structure: Contrasting exemplar-retrieval, decision-boundary, and prototype models. Journal of Experimental Psychology: Human Perception and Performance, 31(3), 608-629.
Zaki, S. R., & Nosofsky, R. M. (2004). False prototype enhancement effects in dot pattern categorization. Memory & Cognition, 32(3), 390-398.
Zaki, S. R., Nosofsky, R. M., Stanton, R. D., & Cohen, A. L. (2003). Prototype and exemplar accounts of category learning and attentional allocation: A reassessment. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(6), 1160-1173.
Zaki, S. R., Nosofsky, R. M., Jessup, N. M., & Unversagt, F. W. (2003). Categorization and recognition performance of a memory-impaired group: Evidence for single-system models. Journal of the International Neuropsychological Society, 9(3), 394-406.
Nosofsky, R. M., & Zaki, S. R. (2003). A hybrid-similarity exemplar model for predicting distinctiveness effects in perceptual old-new recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(6), 1194-1209.
Cohen, A. L., & Nosofsky, R. M. (2003). An extension of the exemplar-based random-walk model to separable-dimension stimuli. Journal of Mathematical Psychology, 47(2), 150-165.
Treat, T. A., McFall, R. M., Viken, R. J., Nosofsky, R. M., MacKay, D. B., & Kruschke, J. K. (2002). Assessing clinically relevant perceptual organization with multidimensional scaling techniques. Psychological Assessment, 14(3), 239-252.
Nosofsky, R. M., & Zaki, S. R. (2002). Exemplar and prototype models revisited: Response strategies, selective attention, and stimulus generalization. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(5), 924-940.
Viken, R. J., Treat, T. A., Nosofsky, R. M., McFall, R. M., & Palmeri, T. J. (2002). Modeling individual differences in perceptual and attentional processes related to bulimic symptoms. Journal of Abnormal Psychology, 111(4), 598-609.
Stanton, R. D., Nosofsky, R. M., & Zaki, S. R. (2002). Comparisons between exemplar similarity and mixed prototype models using a linearly separable category structure. Memory & Cognition, 30(6), 934-944.
Palmeri, T. J., & Nosofsky, R. M. (2001). Central tendencies, extreme points, and prototype enhancement effects in ill-defined perceptual categorization. Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 54A(1), 197-235.
Zaki, S. R., & Nosofsky, R. M. (2001). Exemplar accounts of blending and distinctiveness effects in perceptual old-new recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27(4), 1022-1041.
Zaki, S. R., & Nosofsky, R. M. (2001). A single-system interpretation of dissociations between recognition and categorization in a task involving object-like stimuli. Cognitive, Affective & Behavioral Neuroscience, 1(4), 344-359.
Cohen, A. L., Nosofsky, R. M., & Zaki, S. R. (2001). Category variability, exemplar similarity, and perceptual classification. Memory & Cognition, 29(8), 1165-1175.
Nosofsky, R. M., & Johansen, M. K. (2000). Exemplar-based accounts of multiple-system phenomena in perceptual categorization. Psychonomic Bulletin & Review, 7(3), 375-402.
Nosofsky, R. M. (2000).Exemplar representation without generalization? Comment on Smith and Minda's (2000) Thirty categorization results in search of a model. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(6), 1735-1743.
Cohen, A. L., & Nosofsky, R. M. (2000). An exemplar-retrieval model of speeded same-different judgments. Journal of Experimental Psychology: Human Perception & Performance, 26(5), 1549-1569.
Nosofsky, R. M., & Alfonso-Reese, L. A. (1999).Effects of similarity and practice on speeded classification response times and accuracies: Further tests of an exemplar-retrieval model. Memory & Cognition, 27(1), 78-93.
Nosofsky, R. M., & Palmeri, T. J. (1998). A rule-plus-exception model for classifying objects in continuous-dimension spaces. Psychonomic Bulletin & Review, 5(3), 345-369.
Nosofsky, R. M., & Zaki, S. R. (1998). Dissociations between categorization and recognition in amnesic and normal individuals: An exemplar-based interpretation. Psychological Science, 9(4), 247-255.
Nosofsky, R. M. (1998). Selective attention and the formation of linear decision boundaries: Reply to maddox and ashby (1998). Journal of Experimental Psychology: Human Perception & Performance, 24(1), 322-339.
Nosofsky, R. M., & Palmeri, T. J. (1997). An exemplar-based random walk model of speeded classification. Psychological Review, 104(2), 266-300.
Nosofsky, R. M., & Palmeri, T. J. (1997). Comparing exemplar-retrieval and decision-bound models of speeded perceptual classification. Perception & Psychophysics, 59(7), 1027-1048.
Nosofsky, R. M. (1997). An exemplar-based random-walk model of speeded categorization and absolute judgment. In A. A. J. Marley (Ed.), Choice, decision, and measurement: Essays in honor of R. Duncan Luce (pp. 347-365). Mahwah, NJ, US: Lawrence Erlbaum Associates, Publishers.
McKinley, S. C., & Nosofsky, R. M. (1996). Selective attention and the formation of linear decision boundaries. Journal of Experimental Psychology: Human Perception & Performance, 22(2), 294-317.
Nosofsky, R. M., & Palmeri, T. J. (1996). Learning to classify integral-dimension stimuli. Psychonomic Bulletin & Review, 3(2), 222-226.
Palmeri, T. J., & Nosofsky, R. M. (1995). Recognition memory for exceptions to the category rule. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(3), 548-568.
McKinley, S. C., & Nosofsky, R. M. (1995). Investigations of exemplar and decision bound models in large, ill-defined category structures. Journal of Experimental Psychology: Human Perception & Performance, 21(1), 128-148.
Shiffrin, R. M., & Nosofsky, R. M. (1994). Seven plus or minus two: A commentary on capacity limitations. Psychological Review, 101(2), 357-361.
Nosofsky, R. M., Palmeri, T. J., & McKinley, S. C. (1994). Rule-plus-exception model of classification learning. Psychological Review, 101(1), 53-79.
Nosofsky, R. M., Gluck, M. A., Palmeri, T. J., & McKinley, S. C. (1994). Comparing models of rule-based classification learning: A replication and extension of Shepard, Hovland, and Jenkins (1961). Memory & Cognition, 22(3), 352-369.
Nosofsky, R. M., Kruschke, J. K., & McKinley, S. C. (1992). Combining exemplar-based category representations and connectionist learning rules. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18(2), 211-233.
Nosofsky, R. M., & Smith, J. K. (1992). Similarity, identification, and categorization: Comment on Ashby and Lee (1991). Journal of Experimental Psychology: General, 121(2), 237-245.
Nosofsky, R. M. (1992). Exemplars, prototypes, and similarity rules. In A. F. Healy, & S. M. Kosslyn (Eds.), Essays in honor of William K. Estes, vol. 1: From learning theory to connectionist theory; vol. 2: From learning processes to cognitive processes (pp. 149-167). Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc.
Nosofsky, R. M. (1992). Exemplar-based approach to relating categorization, identification, and recognition. In F. G. Ashby (Ed.), Multidimensional models of perception and cognition. Scientific psychology series (pp. 363-393). Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc.
Nosofsky, R. M. (1992). Similarity scaling and cognitive process models. Annual Review of Psychology, 43, 25-53.
Shin, H. J., & Nosofsky, R. M. (1992). Similarity-scaling studies of dot-pattern classification and recognition. Journal of Experimental Psychology: General, 121(3), 278-304.
Nosofsky, R. M. (1991). Relation between the rational model and the context model of categorization. Psychological Science, 2(6), 416-421.
Nosofsky, R. M. (1991). Typicality in logically defined categories: Exemplar-similarity versus rule instantiation. Memory & Cognition, 19(2), 131-150.
Nosofsky, R. M. (1991). Tests of an exemplar model for relating perceptual classification and recognition memory. Journal of Experimental Psychology: Human Perception & Performance, 17(1), 3-27.
Nosofsky, R. M. (1991). Stimulus bias, asymmetric similarity, and classification. Cognitive Psychology, 23(1), 94-140.
Nosofsky, R. M. (1990). Relations between exemplar-similarity and likelihood models of classification. Journal of Mathematical Psychology, 34(4), 393-418.
Nosofsky, R. M., Clark, S. E., & Shin, H. J. (1989). Rules and exemplars in categorization, identification, and recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15(2), 282-304.
Nosofsky, R. M. (1989). Further tests of an exemplar-similarity approach to relating identification and categorization. Perception & Psychophysics, 45(4), 279-290.
Nosofsky, R. M. (1988). Similarity, frequency, and category representations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(1), 54-65.
Nosofsky, R. M. (1988). Exemplar-based accounts of relations between classification, recognition, and typicality. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(4), 700-708.
Nosofsky, R. M. (1988). On exemplar-based exemplar representations: Reply to Ennis (1988). Journal of Experimental Psychology: General, 117(4), 412-414.
Nosofsky, R. M. (1987). Attention and learning processes in the identification and categorization of integral stimuli. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13(1), 87-108.
Nosofsky, R. M. (1986). Attention, similarity, and the identification-categorization relationship. Journal of Experimental Psychology: General, 115(1), 39-57.
Nosofsky, R. (1985). Overall similarity and the identification of separable-dimension stimuli: A choice model analysis. Perception & Psychophysics, 38(5), 415-432.
Nosofsky, R. M. (1985). Luce's choice model and Thurstone's categorical judgment model compared: Kornbrot's data revisited. Perception & Psychophysics, 37(1), 89-91.
Nosofsky, R. M. (1984). Choice, similarity, and the context theory of classification. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10(1), 104-114.
Nosofsky, R. M. (1983). Shifts of attention in the identification and discrimination of intensity. Perception & Psychophysics, 33(2), 103-112.
Nosofsky, R. M. (1983). Information integration and the identification of stimulus noise and criterial noise in absolute judgment. Journal of Experimental Psychology: Human Perception & Performance, 9(2), 299-309.
Luce, R. D., Nosofsky, R. M., Green, D. M., & Smith, A. F. (1982). The bow and sequential effects in absolute identification. Perception & Psychophysics, 32(5), 397-408.