Publications
Reprint Requests
COVIS.
In E. M. Pothos & A. J. Wills (Eds.), Formal approaches in categorization. 65-87.
(2011). Computational cognitive neuroscience models of categorization.
In R. Sun (Ed.), The Cambridge Handbook of Computational Cognitive Sciences (pp.400-425). Cambridge University Press.
(2023). 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.
(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-.
(2018). Complex decision rules in categorization: Contrasting novice and experienced performance.
Journal of Experimental Psychology: Human Perception and Performance. 18, 50.
(1992). Categorization as probability density estimation.
Journal of Mathematical Psychology. 39, 216–233.
(1995). 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 .
(1997). Category learning deficits in Parkinson's disease.
Neuropsychology. 17(1), 115-24.
(2003). Category learning and multiple memory systems.
Trends in Cognitive Science. 9(2), 83-89.
(2005). Cortical and basal ganglia contributions to habit learning and automaticity.
Trends in Cognitive Science. 14(5), 208-215.
(2010). The cognitive neuroscience of implicit category learning.
Advances in consciousness research. 48, 109–142.
(2003). 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.
(2007).
(2001). Categorization response time with multidimensional stimuli.
Perception & Psychophysics. 55, 11–27.
(1994). Comparing the biased choice model and multidimensional decision bound models of identification.
Mathematical Social Sciences. 23, 175–197.
(1992). Counting and timing models in psychophysics and the conjoint Weber's law.
Journal of Mathematical Psychology. 31, 419–428.
(1987). A computational model of how cholinergic interneurons protect striatal-dependent learning..
J Cogn Neurosci. 23(6), 1549-66.
(2011). Context-dependent savings in procedural category learning.
Brain and Cognition. 92C, 1-10.
(2014). Category label and response location shifts in category learning.
Psychological Research. 74(2), 219-236.
(2010). Comparing decision bound and exemplar models of categorization.
Perception & psychophysics. 53, 49–70.
(1993). Cross-modal information integration in category learning.
Attention, Perception, & Psychophysics. 76(5), 1473-1484.
(2014). Categorization training increases the perceptual separability of novel dimensions.
Cognition. 139, 105-129.
(2015). A computational model of the temporal dynamics of plasticity in procedural learning: Sensitivity to feedback timing.
Frontiers in Psychology. 5, 643.
(2014). Cortical and striatal contributions to automaticity in information-integration categorization..
Neuroimage. 56(3), 1791-802.
(2011).