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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 
I
Inglis, J. B., Bird J., & Ashby F. G. (2022).  A general recognition theory model for identifying an ideal stimulus. Attention, Perception, & Psychophysics. 84, 2408–2421.
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.
K
Kovacs, P., Helie S., Tran A. N., & Ashby F. G. (2021).  A neurocomputational theory of how rule-guided behaviors become automatic. Psychological Review. 128, 488-508.
Kovacs, P., & Ashby F. G. (2022).  On what it means to automatize a rule. Cognition. 226, 105168.
M
MacCallum, R., & F Ashby G. (1986).  Relationships between linear systems theory and covarian ce structure modeling. Journal of Mathematical Psychology. 30, 1–27.
W Maddox, T., & F Ashby G. (1993).  Comparing decision bound and exemplar models of categorization. Perception & psychophysics. 53, 49–70.
W Maddox, T., Prinzmetal W., Ivry R. B., & F Ashby G. (1994).  A probabilistic multidimensional model of location information. Psychological Research. 56, 66–77.
W Maddox, T., F Ashby G., & Waldron E. M. (2002).  Multiple attention systems in perceptual categorization. Memory & Cognition. 30, 325–339.
W Maddox, T., F Ashby G., & Gottlob L. R. (1998).  Response time distributions in multidimensional perceptual categorization. Perception & Psychophysics. 60, 620–637.
W Maddox, T., Glass B. D., O'Brien J. B., J Filoteo V., & F Ashby G. (2010).  Category label and response location shifts in category learning. Psychological Research. 74(2), 219-236.
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.
W Maddox, T., & F Ashby G. (2004).  Dissociating explicit and procedural-learning based systems of perceptual category learning. Behavioral Processes. 66(3), 309-332.
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.
W Maddox, T., & F Ashby G. (1998).  Selective attention and the formation of linear decision boundaries: Comment on McKinley and Nosofsky (1996). Journal of Experimental Psychology: Human Perception & Performance. 24, 301-321.
W Maddox, T., & F Ashby G. (1996).  Perceptual separability, decisional separability, and the identification–speeded classification relationship. Journal of Experimental Psychology: Human perception and performance. 22, 795.
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.
P
Paul, E. J., J Smith D., Valentin V. V., Turner B. O., Barbey A. K., & Ashby F. G. (2015).  Neural networks underlying the metacognitive uncertainty response. Cortex. 71, 306-22.
Paul, E. J., & F Ashby G. (2013).  A neurocomputational theory of how explicit learning bootstraps early procedural learning. Frontiers in Computational Neuroscience. 7, 177.
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.
Perrin, N. A., & F Ashby G. (1991).  A test for perceptual independence with dissimilarity data. Applied Psychological Measurement. 15, 79–93.
Q
Qadri, M. A. J., Ashby F. G., Smith J. D., & Cook R. G. (2019).  Testing analogical rule transfer in pigeons (Columba livia). Cognition. 183, 256-268.
R
Roeder, J. L., & Ashby F. G. (2016).  What is automatized during perceptual categorization?. Cognition. 154, 22-33.
Rosedahl, L., & F Ashby G. (2018).  A New Stimulus Set for Cognitive Research.
Rosedahl, L. A., Eckstein M. P., & F Ashby G. (2018).  Retinal-specific category learning. Nature Human Behaviour. 1.
Rosedahl, L., & Ashby F. G. (2019).  A difficulty predictor for perceptual category learning. Journal of Vision. 19(6), 20.

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