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Found 179 results
[ Author(Asc)] 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 
W
Wang, Y-W., & Ashby F. G. (2020).  A role for the medial temporal lobes in category learning. Learning & Memory. 27, 441-450.
Waldschmidt, J. G., & F Ashby G. (2011).  Cortical and striatal contributions to automaticity in information-integration categorization.. Neuroimage. 56(3), 1791-802.
Waldron, E. M., & F Ashby G. (2001).  The effects of concurrent task interference on category learning: Evidence for multiple category learning systems. Psychonomic Bulletin & Review. 8, 168–176.
V
Valentin, V. V., W Maddox T., & F Ashby G. (2014).  A computational model of the temporal dynamics of plasticity in procedural learning: Sensitivity to feedback timing. Frontiers in Psychology. 5, 643.
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.
T
Turner, B. O., Mumford J. A., Poldrack R. A., & F Ashby G. (2012).  Spatiotemporal activity estimation for multivoxel pattern analysis with rapid event-related designs. NeuroImage. 62(3), 1429-1438.
Turner, B. O., Crossley M. J., & Ashby F. G. (2017).  Hierarchical control of procedural and declarative category-learning systems. NeuroImage. 150, 150-161.
Townsend, J. T., & F Ashby G. (1978).  Methods of modeling capacity in simple processing systems. Cognitive theory. 3, 200–239.
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. (1982).  Experimental test of contemporary mathematical models of visual letter recognition.. Journal of Experimental Psychology: Human Perception and Performance. 8, 834.
Townsend, J. T., Hu G. G., & F Ashby G. (1981).  Perceptual sampling of orthogonal straight line features. Psychological Research. 43, 259–275.
Townsend, J. T., Hu G. G., & F Ashby G. (1980).  A test of visual feature sampling independence with orthogonal straight lines. Bulletin of the Psychonomic Society. 15, 163–166.
Townsend, J. T., & F Ashby G. (1983).  Stochastic modeling of elementary psychological processes.
S
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.
Spiering, B. J., & F Ashby G. (2008).  Response processes in information-integration category learning. Neurobiology of Learning and Memory. 90(2), 330-338.
Soto, F. A., & Ashby F. G. (2015).  Categorization training increases the perceptual separability of novel dimensions. Cognition. 139, 105-129.
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.
Soto, F. A., Waldschmidt J. G., Helie S., & F Ashby G. (2013).  Brain activity across the development of automatic categorization: a comparison of categorization tasks using multi-voxel pattern analysis. NeuroImage. 71, 284-297.
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.
Soto, F. A., Zheng E., Fonseca J., & Ashby F. G. (2017).  Testing separability and independence of perceptual dimensions with general recognition theory: A tutorial and new R package (grtools). Frontiers in Psychology. 8, 696.
Soto, F. A., Vucovich L., Musgrave R., & Ashby F. G. (2015).  General recognition theory with individual differences: a new method for examining perceptual and decisional interactions with an application to face perception. Psychonomic Bulletin & Review. 22(1), 88-111.
Soto, F. A., & Ashby F. G. (2019).  Novel representations that support rule-based categorization are acquired on-the-fly during category learning. Psychological Research. 83, 544-566.
Soto, F. A., & Ashby F. G. (2023).  Encoding models in neuroimaging. In F. G. Ashby, H. Colonius, & E. Dzhafarov (Eds.), The new handbook of mathematical psychology, Volume 3 (pp. 421-472). Cambridge University Press.
J Smith, D., Zakrzewski A. C., Herberger E. R., Boomer J., Roeder J. L., F Ashby G., et al. (2015).  The time course of explicit and implicit categorization. Attention, Perception, & Psychophysics. 77(7), 2476-2490.
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.

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