About
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.
Awards
- Early Investigator Award, Society of Experimental Psychologists, 2018
- Young Investigator Award, Cognitive Neuroscience Society, 2017
- Young Investigator Award, Vision Sciences Society, 2016
- Distinguished Scientific Award for Early Career Contribution to Psychology American Psychological, 2015
- Association Robert L. Fantz Memorial Award, American Psychological Foundation, 2014
Relevant Publications
Fan, J. E., Wammes, J. D., Gunn, J. B., Yamins, D. L. K., Norman, K. A., & Turk-Browne, N. B. (2020). Relating visual production and recognition of objects in human visual cortex. Journal of Neuroscience, 40, 1710-1721.
Kok, P., Rait, L. I., & Turk-Browne, N. B. (2020). Content-based dissociation of hippocampal involvement in prediction. Journal of Cognitive Neuroscience, 32, 527-545.
Sherman, B. E., Graves, K. N., & Turk-Browne, N. B. (2020). The prevalence and importance of statistical learning in human cognition and behavior. Current Opinion in Behavioral Sciences, 32, 15-20.
Cordova, N. I., Turk-Browne, N. B., & Aly, M. (2019). Focusing on what matters: Modulation of the human hippocampus by relational attention. Hippocampus, 29, 1025-1037
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.