Brain Networks, Language Learning, and Big Data: Individual Differences and Neuroplasticity Revealed

Ping Li
Pennsylvania State University

Abstract:
In recent years there has been a surge of interest in using brain networks to understnd changes in cognitive and linguistic behaviors. This interest, combined with research efforts in the study of language learning and teaching, has led to promising new findings in the integration of knowledge about learning, neuroplasticity, and individual differences.  The human brain produces complex and dynamic time-series big data in response to cognitive and linguistic tasks, and our ability to analyze these data is critical for insights into the mind and the brain. In this talk, I briefly review research in this domain, focusing on language learning and individual differences. Specifically, I ask how second language experience shapes functional and neuroanatomical networks on top of one’s experience with a first language, and present evidence based on our longitudinal and short-term training studies from learners. Our research attempts to identify (a) how brain networks adapt as a function of linguistic experience in a new language, (b) how such changes may capture learning success, effectiveness, and knowledge acquisition in general, and (c) whether such neurocognitive changes may be predicted based on the learner’s individual cognitive abilities and on big data from brain responses. Our findings highlight the significance of individual differences and neuroplasticity in language learning, and the implications this approach has for understanding the brain-behavior-cognition relationships more generally.