Publications

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Found 179 results
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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.
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.

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