Nicholas Turk-Browne uses behavioural, neuroimaging, computational and patient studies to develop an integrated understanding of the mind and brain.
The theme of his research is that cognitive processes such as perception, attention, learning and memory are inherently interactive, and that exploring such interactions can be an especially effective way to understand how these processes work. For example, he has published extensively on ‘statistical learning’ – an automatic, often unconscious process by which we extract and represent regularities in our experience and use them to generate
predictions and facilitate processing.
Young Investigator Award, Vision Sciences Society, 2016
Distinguished Scientific Award for Early Career Contribution to Psychology, American
Psychological Association, 2015
Robert L. Fantz Memorial Award, American Psychological Foundation, 2014
Rising Star, Association for Psychological Science, 2012
Aly, M., & Turk-Browne, N.B. (2016). Attention promotes episodic encoding by stabilizing hippocampal representations. Proceedings of the National Academy of Sciences, 113 E420–E429.
Hindy, N. C., Ng, F. Y., & Turk-Browne, N.B. (2016). Linking pattern completion in the hippocampus to predictive coding in visual cortex. Nature Neuroscience, 19(5), 665–67. DOI: 10.1038/nn.4284.
deBettencourt, M.T., Cohen, J.D., Lee, R.F., Norman, K.A., Turk-Browne, N.B. (2015). Closed-loop training of attention with real-time brain imaging. Nature Neuroscience, 18(3), 470–75. DOI: 10.1038/nn.3940.
Turk-Browne, N.B. (2013). Functional interactions as big data in the human brain. Science, 342(6158), 580–84. DOI: 10.1126/science.1238409.
Zhao, J., Al-Aidroos, N., & Turk-Browne, N.B. (2013). Attention is spontaneously biased toward regularities. Psychological Science, 24(5), 667–77. DOI: 10.1177/0956797612460407.