Publications

Found 178 results
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Journal Article
J Smith, D., Zakrzewski A. C., Johnston J. J. R., Roeder J. L., Boomer J., Ashby F. G., et al. (2015).  Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta). Journal of Experimental Psychology: Animal Learning & Cognition. 41(4), 322-335.
Turner, B. O., Crossley M. J., & Ashby F. G. (2017).  Hierarchical control of procedural and declarative category-learning systems. NeuroImage. 150, 150-161.
F Ashby, G., & W Maddox T. (2005).  Human category learning. Annual Review of Psychology. 56, 149-178.
F Ashby, G., & W Maddox T. (2011).  Human category learning 2.0. Annals of the New York Academy of Sciences. 1224, 147-161.
F Ashby, G. (2013).  Human category learning, neural basis. The encyclopedia of the mind. 130–134.
Ell, S. W., & F Ashby G. (2012).  The impact of category separation on unsupervised categorization. Attention, Perception, & Psychophysics. 74(2), 466-475.
J Smith, D., Berg M. E., Cook R. G., Murphy M. S., Crossley M. J., Boomer J., et al. (2012).  Implicit and explicit categorization: A tale of four species. Neuroscience and Biobehavioral Reviews. 36(10), 2355-2369.
J Smith, D., Crossley M. J., Boomer J., Church B. A., Beran M. J., & F Ashby G. (2012).  Implicit and explicit category learning by capuchin monkeys (Cebus apella). Journal of Comparative Psychology. 126(3), 294-304.
J Smith, D., Beran M. J., Crossley M. J., Boomer J., & F Ashby G. (2010).  Implicit and explicit category learning by macaques (Macaca mulatta) and humans (Homo sapiens). Journal of Experimental Psychology: Animal Behavior Processes. 36(1), 54-65.
Crossley, M. J., Maddox W. T., & Ashby F. G. (2018).  Increased cognitive load enables unlearning in procedural category learning. Journal of Experimental Psychology: Learning, Memory, & Cognition. 44, 1845-1853.
Isen, A. M., Nygren T. E., & F Ashby G. (1988).  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.
Paul, E. J., Boomer J., J Smith D., & F Ashby G. (2011).  Information-integration category learning and the human uncertainty response. Memory & Cognition. 39(3), 536-554.
Spiering, B. J., & F Ashby G. (2008).  Initial training with difficult items facilitates information integration, but not rule-based category learning. Psychological Science. 19(11), 1169-1177.
F Ashby, G., & W Maddox T. (1990).  Integrating information from separable psychological dimensions. Journal of Experimental Psychology: Human Perception and Performance. 16, 598.
Ashby, F. G., Zetzer H. A., Conoley C. W., & Pickering A. D. (2024).  Just Do It: A Neuropsychological Theory of Agency, Cognition, Mood, and Dopamine. Journal of Experimental Psychology: General. in press.
Helie, S., & F Ashby G. (2012).  Learning and transfer of category knowledge in an indirect categorization task. Psychological Research. 76(3), 292-303.
Helie, S., Ell S. W., & Ashby F. G. (2015).  Learning robust cortico-cortical associations with the basal ganglia: an integrative review. Cortex. 64, 123-35.
Ashby, F. G. (2023).  Length of the state trace: A method for partitioning model complexity. Journal of Mathematical Psychology. 113, 102755.
Rosedahl, L. A., & Ashby F. G. (2022).  Linear separability, irrelevant variability, and categorization difficulty. Journal of Experimental Psychology: Learning, Memory, & Cognition. 48, 159-172.
Soto, F. A., Vucovich L. E., & Ashby F. G. (2018).  Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data. PLOS Computational Biology. 14(10), e1006470.
Townsend, J. T., & F Ashby G. (1984).  Measurement scales and statistics: The misconception misconceived.. Psychological Bulletin. 96, 394 401.
Townsend, J. T., & F Ashby G. (1978).  Methods of modeling capacity in simple processing systems. Cognitive theory. 3, 200–239.
F Ashby, G., & Casale M. B. (2003).  A model of dopamine modulated cortical activation. Neural Networks. 16(7), 973-984.
Inglis, J. B., Valentin V. V., & F Ashby G. (2020).  Modulation of dopamine for adaptive learning: A neurocomputational model. Computational Brain & Behavior. 1–19.
Ashby, F. G., & Soto F. A. (2015).  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.

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