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Dr. Corey Bohil is a professor in the Psychology Department’s Applied Experimental and Human Factors Program.  He received his M.A. in cognitive psychology from Arizona State University, and his Ph.D. in cognitive psychology from the University of Texas at Austin.  Dr. Bohil completed a postdoctoral fellowship in quantitative psychology at the University of Illinois, and was a visiting assistant professor in the Department of Telecommunication, Information Studies & Media at Michigan State University.  Dr. Bohil’s research focuses on the cognitive processes that underlie categorization and decision making.  Recent topics of research include the contributions of separate learning systems in the brain to category rule learning, and the influence of base-rate (relative prevalence) and reward information on decision criterion learning.  His research makes use of computational modeling techniques, as well as functional near-infrared spectroscopy for neuroimaging of cortical activity.


Bohil, C.J., Wismer, A.J., Schiebel, T., & Williams, S.E. (2015). Best-classifier feedback in diagnostic classification training. Journal of Applied Research in Memory and Cognition

Bohil, C.J., & Wismer, A.J., (2015). Implicit learning mediates base rate acquisition in perceptual categorization. Psychonomic Bulletin & Review, 22(2), 586-593.

Bohil, C.J., Szalma, J.L., & Hancock, P.A. (2015). Psychophysical methods and signal detection: Recent advances in theory. In J.L. Szalma, Scerbo, R., Parasuraman, P.A., Hancock, P.A., & Hoffman, R.R. (Eds). Cambridge Handbook of Applied Perception Research.

Bohil, C.J., Higgins, N.A., & Keebler, J.R. (2014). Predicting and interpreting identification errors in military vehicle training using multidimensional scaling. Ergonomics, 57(6), 844-855.

Bohil, C.J., Alicea, B., & Biocca, F.A. (2011). Virtual reality in neuroscience research and therapy. Nature Reviews Neuroscience, 12, 752-762.