Areas of Study
Email Address
Taylor Science Center 3058

Vikranth Bejjanki’s research is concerned with examining the neural and computational mechanisms that allow humans to learn from their experiences. He uses a range of methods, including psychophysics, computational modeling, and functional neuroimaging, to study learning at multiple levels of analysis. His published work can be found in journals such as Nature Neuroscience, Proceedings of the National Academy of Sciences, PLoS Computational Biology, Neural Computation and the Journal of Vision.

Bejjanki earned bachelor’s degrees in computer engineering and cognitive science from the University at Buffalo, and a master’s degree and doctorate in brain and cognitive sciences from the University of Rochester. He comes to Hamilton from Princeton University, where he was a postdoctoral researcher at the Princeton Neuroscience Institute.

Recent Courses Taught

Fundamentals of Human Neuroscience
Psychology and Neuroscience of Learning
Introduction to Psychology

Select Publications

  • Bejjanki V.R., DaSilveira R.A., Cohen J.D., Turk-Browne N.B. (2017). Noise correlations in the human brain and their impact on pattern classification. PLoS Computational Biology, 13 (8), e1005674.
  • Bejjanki V.R., Knill D.C., Aslin R.N. (2016). Learning and inference using complex generative models in a spatial localization task. Journal of Vision, 16(5):9, 1–13.
  • Bejjanki V.R., Zhang R., Li R., Pouget A., Green C.S., Lu Z-L., Bavelier D. (2014). Action video game play facilitates the development of better perceptual templates. Proceedings of the National Academy of Sciences, 111(47), 16961–16966.
  • Bejjanki, V. R., Beck, J. M., Lu Z-L., Pouget A. (2011). Perceptual learning as improved probabilistic inference in early sensory areas. Nature Neuroscience, 14, 642-648.
  • Bejjanki, V. R., Clayards, M., Knill, D. C., Aslin, R. N., (2011). Cue integration in categorical tasks: insights from audio-visual speech perception. PLoS ONE 6, e19812.
  • Beck, J., Bejjanki, V. R., Pouget A. (2011). Insights from a simple expression for linear Fischer information in a recurrently connected population of spiking neurons. Neural Computation, 23, 1484-1502.
  • Anstey J., Pape D., Shapiro, S. C., Rao V. (2003). Virtual drama with intelligent agents. Proceedings of the Ninth International Conference in Virtual Systems and Multimedia (VSMM). Montreal, Canada.
  • Bejjanki, V. R., Turk-Browne N. B. (2014). Background connectivity in human visual cortex during perceptual learning. Poster at the Society for Neuroscience (SfN) meeting, Washington D.C.
  • Bejjanki, V. R., Knill, D. C., Aslin, R. N. (2013). Learning and optimal inference in a novel spatial localization task. Poster at the Vision Sciences Society (VSS) meeting, Naples, FL.
  • Bejjanki, V. R., Sims, C. R., Green, C. S., Bavelier, D., (2012). Evidence for action video game induced 'learning to learn' in a perceptual decision making task. Talk at the Vision Sciences Society (VSS) meeting, Naples, FL.
  • Zhang, R., Bejjanki, V. R., Lu, Z. L., Green, C. S., Pouget, A., Bavelier, D., (2012). Action video game playing improves learning to learn in perceptual learning. Poster at the Vision Sciences Society (VSS) meeting, Naples, FL.
  • Bejjanki, V. R., Beck, J. M., Pouget, A. (2012). Attention, information, normalization and correlations. Poster at the Computational and Systems Neuroscience (CoSyNe) conference, Salt Lake City, UT.

Professional Affiliations

Society for Neuroscience
Vision Sciences Society
Sigma Xi Scientific Honor Society
American Association for the Advancement of Science

Appointed to the Faculty


Educational Background

Ph. D., University of Rochester
M.A., University of Rochester
B.A., State University of New York at Buffalo
B.S., State University of New York at Buffalo

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