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Found 179 results
Author [ Title(Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
C
J Smith, D., Johnston J. J. R., Musgrave R. D., Zakrzewski A. C., Boomer J., Church B. A., et al. (2014).  Cross-modal information integration in category learning. Attention, Perception, & Psychophysics. 76(5), 1473-1484.
F Ashby, G., Paul E. J., & ToddMaddox W. (2011).  COVIS. In E. M. Pothos & A. J. Wills (Eds.), Formal approaches in categorization. 65-87.
F Ashby, G. (1987).  Counting and timing models in psychophysics and the conjoint Weber's law. Journal of Mathematical Psychology. 31, 419–428.
Waldschmidt, J. G., & F Ashby G. (2011).  Cortical and striatal contributions to automaticity in information-integration categorization.. Neuroimage. 56(3), 1791-802.
F Ashby, G., Turner B. O., & Horvitz J. C. (2010).  Cortical and basal ganglia contributions to habit learning and automaticity. Trends in Cognitive Science. 14(5), 208-215.
Crossley, M. J., F Ashby G., & W Maddox T. (2014).  Context-dependent savings in procedural category learning. Brain and Cognition. 92C, 1-10.
Valentin, V. V., W Maddox T., & F Ashby G. (2014).  A computational model of the temporal dynamics of plasticity in procedural learning: Sensitivity to feedback timing. Frontiers in Psychology. 5, 643.
F Ashby, G., & Crossley M. J. (2011).  A computational model of how cholinergic interneurons protect striatal-dependent learning.. J Cogn Neurosci. 23(6), 1549-66.
Ashby, F. G., & Wang Y-W. (2023).  Computational cognitive neuroscience models of categorization. In R. Sun (Ed.), The Cambridge Handbook of Computational Cognitive Sciences (pp.400-425). Cambridge University Press.
F Ashby, G., & Valentin V. V. (2007).  Computational cognitive neuroscience: Building and testing biologically plausible computational models of neuroscience, neuroimaging, and behavioral data. Statistical and process models for cognitive neuroscience and aging. 15–58.
Ashby, F. G. (2018).  Computational cognitive neuroscience. In W. Batchelder, H. Colonius, E. Dzhafarov, & J. Myung (Eds.), New handbook of mathematical psychology, Volume 2. NY: Cambridge University Press. 223-270.
F Ashby, G., & W Maddox T. (1992).  Complex decision rules in categorization: Contrasting novice and experienced performance. Journal of Experimental Psychology: Human Perception and Performance. 18, 50.
F Ashby, G., W Lee W., & Balakrishnan JD. (1992).  Comparing the biased choice model and multidimensional decision bound models of identification. Mathematical Social Sciences. 23, 175–197.
W Maddox, T., & F Ashby G. (1993).  Comparing decision bound and exemplar models of categorization. Perception & psychophysics. 53, 49–70.
F Ashby, G., & Casale M. B. (2003).  The cognitive neuroscience of implicit category learning. Advances in consciousness research. 48, 109–142.
F Ashby, G., Noble S., J Filoteo V., Waldron E. M., & Ell S. W. (2003).  Category learning deficits in Parkinson's disease. Neuropsychology. 17(1), 115-24.
F Ashby, G., & O'Brien J. B. (2005).  Category learning and multiple memory systems. Trends in Cognitive Science. 9(2), 83-89.
W Maddox, T., Glass B. D., O'Brien J. B., J Filoteo V., & F Ashby G. (2010).  Category label and response location shifts in category learning. Psychological Research. 74(2), 219-236.
Soto, F. A., & Ashby F. G. (2015).  Categorization training increases the perceptual separability of novel dimensions. Cognition. 139, 105-129.
F Ashby, G., Boynton G., & W Lee W. (1994).  Categorization response time with multidimensional stimuli. Perception & Psychophysics. 55, 11–27.
Ashby, F. G., & Valentin V. V. (2018).  The categorization experiment: Experimental design and data analysis. In E. J. Wagenmakers & J. T. Wixted (Eds.), Stevens handbook of experimental psychology and cognitive neuroscience, Fourth Edition, Volume Five: Methodology. New York: Wiley. 307-.
F Ashby, G., & Alfonso-Reese L. A. (1995).  Categorization as probability density estimation. Journal of Mathematical Psychology. 39, 216–233.
F Ashby, G., & Berretty P. M. (1997).  Categorization as a special case of decision-making or choice. In A. A. J. Marley (Ed.), Choice, decision, and measurement: Essays in honor of R. Duncan Luce .
Ashby, FG. (2001).  Categorization and similarity models: Neuroscience applications.
B
Soto, F. A., Waldschmidt J. G., Helie S., & F Ashby G. (2013).  Brain activity across the development of automatic categorization: a comparison of categorization tasks using multi-voxel pattern analysis. NeuroImage. 71, 284-297.

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