Funded Ph.D. Candidate Position - Recurrent Network Models of Statistical Learning, Basque Center on Cognition, Brain and Language, Donostia-San Sebastian, Spain
Statistical learning (SL) is a crucial capacity supporting efficient cognition and action throughout the lifespan. SL is an organism’s ability to attune to coherent covariation in its environment (e.g., an infant learning sound patterns of a language, or visual patterns corresponding to objects). This project uses recurrent neural network modeling to investigate the types of computations that may support human SL. The modeling motivates EEG and MEG studies with human subjects. Together, the modeling and experiments will advance our understanding of the nature and computational basis for human SL.