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Found 184 results
[ Author(Desc)] Title 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
Crossley, M. J., F Ashby G., & W Maddox T. (2014).  Context-dependent savings in procedural category learning. Brain and Cognition. 92C, 1-10.
Crossley, M. J., F Ashby G., & W Maddox T. (2013).  Erasing the engram: The unlearning of procedural skills. Journal of Experimental Psychology: General. 142(3), 710-741.
Crossley, M. J., Madsen N. R., & F Ashby G. (2012).  Procedural learning of unstructured categories. Psychonomic Bulletin & Review. 19(6), 1202-1209.
Crossley, M. J., Paul E. J., Roeder J. L., & Ashby F. G. (2016).  Declarative strategies persist under increased cognitive load. Psychonomic Bulletin & Review. 23(1), 213-22.
Crossley, M. J., Horvitz J. C., Balsam P. D., & Ashby F. G. (2016).  Expanding the role of striatal cholinergic interneurons and the midbrain dopamine system in appetitive instrumental conditioning. Journal of Neurophysiology. 115(1), 240-54.
Crossley, M. J., Roeder J. L., Helie S., & Ashby F. G. (2018).  Trial-by-trial switching between procedural and declarative categorization systems. Psychological Research. 82, 371-384.
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.
Crossley, M. J., Pelzer B. O., & Ashby F. G. (2026).  Is there a criterion in criterial learning? Insights from studying feedback delays. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication, https://dx.doi.org/10.1037/xlm0001590.
E
Ell, S. W., & F Ashby G. (2012).  The impact of category separation on unsupervised categorization. Attention, Perception, & Psychophysics. 74(2), 466-475.
Ell, S. W., F Ashby G., & Hutchinson S. (2012).  Unsupervised category learning with integral-dimension stimuli. Quarterly Journal of Experimental Psychology. 65(8), 1537-1562.
Ell, S. W., & F Ashby G. (2006).  The effects of category overlap on information-integration and rule-based category learning. Perception & Psychophysics. 68(6), 1013-1026.
Ell, S. W., & F Ashby G. (2004).  Dynamical trajectories in category learning. Perception & Psychophysics. 66(8), 1318-1340.
Ennis, D. M., & F Ashby G. (1993).  The relative sensitivities of same-different and identification judgment models to perceptual dependence. Psychometrika. 58, 257–279.
Ennis, D. M., & F. Ashby G. (2003).  Fitting decision bound models to identification or categorization data.
F
J Filoteo, V., Paul E. J., F Ashby G., Frank G. K. W., Helie S., Rockwell R., et al. (2014).  Simulating category learning and set shifting deficits in patients weight-restored from anorexia nervosa. Neuropsychology. 28(5), 741-51.
Filoteo, J. V., Maddox W. T., & Ashby F. G. (2017).  Quantitative modeling of category learning deficits in various patient populations. Neuropsychology. 31, 862-876.
H
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.
Helie, S., Roeder J. L., Vucovich L., Rünger D., & F Ashby G. (2015).  A neurocomputational model of automatic sequence production. Journal of Cognitive Neuroscience. 27(7), 1412-1426.
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., Paul E. J., & F Ashby G. (2012).  A neurocomputational account of cognitive deficits in Parkinson's disease. Neuropsychologia. 50(9), 2290-2302.
Helie, S., Paul E. J., & F Ashby G. (2012).  Simulating the effects of dopamine imbalance on cognition: From positive affect to Parkinson's disease. Neural Networks. 32, 74-85.
Helie, S., Waldschmidt J. G., & F Ashby G. (2010).  Automaticity in rule-based and information-integration categorization. Attention, Perception, & Psychophysics. 72(4), 1013-1031.
Helie, S., Roeder J. L., & F Ashby G. (2010).  Evidence for cortical automaticity in rule-based categorization. Journal of Neuroscience. 30(42), 14225-14234.
Helie, S., Turner B. O., Crossley M. J., Ell S. W., & Ashby F. G. (2017).  Trial-by-trial identification of categorization strategy using iterative decision-bound modeling. Behavioral Research Methods. 49(3), 1146-1162.
I
Inglis, J. B., Valentin V. V., & F Ashby G. (2020).  Modulation of dopamine for adaptive learning: A neurocomputational model. Computational Brain & Behavior. 1–19.

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