Publications
Reprint Requests
Multiple systems of perceptual category learning: Theory and cognitive tests.
Handbook of categorization in cognitive science. 547–572.
(2005). Multiple stages of learning in perceptual categorization: evidence and neurocomputational theory.
Psychonomic Bulletin & Review. 22(6), 1598-1613.
(2015). Multiple attention systems in perceptual categorization.
Memory & Cognition. 30, 325–339.
(2002). Multidimensional signal detection theory.
In: J. R. Busemeyer, Z. Wang, J. T. Townsend, & A. Eidels (Eds.), Oxford handbook of computational and mathematical psychology. 13–34.
(2015). Modulation of dopamine for adaptive learning: A neurocomputational model.
Computational Brain & Behavior. 1–19.
(2020). A model of dopamine modulated cortical activation.
Neural Networks. 16(7), 973-984.
(2003). Methods of modeling capacity in simple processing systems.
Cognitive theory. 3, 200–239.
(1978). Measurement scales and statistics: The misconception misconceived..
Psychological Bulletin. 96, 394 401.
(1984). Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data.
PLOS Computational Biology. 14(10), e1006470.
(2018). Linear separability, irrelevant variability, and categorization difficulty.
Journal of Experimental Psychology: Learning, Memory, & Cognition. 48, 159-172.
(2022). Length of the state trace: A method for partitioning model complexity.
Journal of Mathematical Psychology. 113, 102755.
(2023). Learning robust cortico-cortical associations with the basal ganglia: an integrative review.
Cortex. 64, 123-35.
(2015). Learning and transfer of category knowledge in an indirect categorization task.
Psychological Research. 76(3), 292-303.
(2012). Just Do It: A Neuropsychological Theory of Agency, Cognition, Mood, and Dopamine.
Journal of Experimental Psychology: General. in press.
(2024). Integrating information from separable psychological dimensions.
Journal of Experimental Psychology: Human Perception and Performance. 16, 598.
(1990). Initial training with difficult items facilitates information integration, but not rule-based category learning.
Psychological Science. 19(11), 1169-1177.
(2008). Information-integration category learning and the human uncertainty response.
Memory & Cognition. 39(3), 536-554.
(2011). Influence of positive affect on the subjective utility of gains and losses: It's just not worth the risk..
Journal of Personality and Social Psychology. 55, 710-717.
(1988). Increased cognitive load enables unlearning in procedural category learning.
Journal of Experimental Psychology: Learning, Memory, & Cognition. 44, 1845-1853.
(2018). Implicit and explicit category learning by macaques (Macaca mulatta) and humans (Homo sapiens).
Journal of Experimental Psychology: Animal Behavior Processes. 36(1), 54-65.
(2010). Implicit and explicit category learning by capuchin monkeys (Cebus apella).
Journal of Comparative Psychology. 126(3), 294-304.
(2012). Implicit and explicit categorization: A tale of four species.
Neuroscience and Biobehavioral Reviews. 36(10), 2355-2369.
(2012). The impact of category separation on unsupervised categorization.
Attention, Perception, & Psychophysics. 74(2), 466-475.
(2012). Human category learning, neural basis.
The encyclopedia of the mind. 130–134.
(2013). Human category learning 2.0.
Annals of the New York Academy of Sciences. 1224, 147-161.
(2011).