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Found 178 results
[ Author(Desc)] Title Type Year
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S
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.
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., F Ashby G., Berg M. E., Murphy M. S., Spiering B., Cook R. G., et al. (2011).  Pigeons' categorization may be exclusively nonanalytic. Psychonomic Bulletin & Review. 18(2), 414-421.
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.
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., 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., 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., 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., & 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., & 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.
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.
T
Townsend, J. T., & F Ashby G. (1983).  Stochastic modeling of elementary psychological processes.
Townsend, J. T., & F Ashby G. (1978).  Methods of modeling capacity in simple processing systems. Cognitive theory. 3, 200–239.
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., Hu G. G., & F Ashby G. (1981).  Perceptual sampling of orthogonal straight line features. Psychological Research. 43, 259–275.
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., & F Ashby G. (1984).  Measurement scales and statistics: The misconception misconceived.. Psychological Bulletin. 96, 394 401.
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.
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.

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