Publications

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Found 179 results
Author [ Title(Desc)] 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
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. (1987).  Counting and timing models in psychophysics and the conjoint Weber's law. Journal of Mathematical Psychology. 31, 419–428.
F Ashby, G., Paul E. J., & ToddMaddox W. (2011).  COVIS. In E. M. Pothos & A. J. Wills (Eds.), Formal approaches in categorization. 65-87.
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.
D
F Ashby, G., W Maddox T., & W Lee W. (1994).  On the dangers of averaging across subjects when using multidimensional scaling or the similarity-choice model. Psychological Science. 5, 144–151.
F Ashby, G., & Gott R. E. (1988).  Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology: Learning, Memory, and Cognition. 14, 33.
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.
F Ashby, G., & Townsend J. T. (1980).  Decomposing the reaction time distribution: Pure insertion and selective influence revisited. Journal of Mathematical Psychology. 21, 93–123.
Mumford, J. A., Turner B. O., F Ashby G., & Poldrack R. A. (2012).  Deconvolving BOLD activation in event-related designs for multivoxel pattern classification analyses. NeuroImage. 59(3), 2636-2643.
J Smith, D., Boomer J., Zakrzewski A. C., Roeder J. L., Church B. A., & F Ashby G. (2014).  Deferred feedback sharply dissociates implicit and explicit category learning. Psychological Science. 25(2), 447-457.
W Maddox, T., F Ashby G., & Bohil C. J. (2003).  Delayed feedback effects on rule-based and information-integration category learning. Journal of Experimental Psychology: Learning, Memory & Cognition. 29(4), 650-662.
F Ashby, G. (1982).  Deriving exact predictions from the cascade model. Psychological Review. 89, 599 607.
Ashby, F. G., Valentin V. V., & von Meer S. S. (2015).  Differential effects of dopamine-directed treatments on cognition. Neuropsychiatric Disease and Treatment. 11, 1859-1875.
Rosedahl, L., & Ashby F. G. (2019).  A difficulty predictor for perceptual category learning. Journal of Vision. 19(6), 20.
W Maddox, T., F Ashby G., A Ing D., & Pickering A. D. (2004).  Disrupting feedback processing interferes with rule-based but not information-integration category learning. Memory & Cognition. 32(4), 582-591.
Soto, F. A., Bassett D. S., & Ashby F. G. (2016).  Dissociable changes in functional network topology underlie early category learning and development of automaticity. NeuroImage. 141, 220-241.
W Maddox, T., & F Ashby G. (2004).  Dissociating explicit and procedural-learning based systems of perceptual category learning. Behavioral Processes. 66(3), 309-332.
Ashby, F. G., Smith J. D., & Rosedahl L. (2020).  Dissociations between rule-based and information-integration categorization are not caused by differences in task difficulty. Memory & Cognition. 48, 541-552.
F Ashby, G., Queller S., & Berretty P. M. (1999).  On the dominance of unidimensional rules in unsupervised categorization. Perception & Psychophysics. 61, 1178–1199.
Valentin, V. V., Maddox W. T., & Ashby F. G. (2016).  Dopamine dependence in aggregate feedback learning: A computational cognitive neuroscience approach. Brain & Cognition. 109, 1-18.
Ell, S. W., & F Ashby G. (2004).  Dynamical trajectories in category learning. Perception & Psychophysics. 66(8), 1318-1340.

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