Leila Wehbe: University of California at Berkeley
Tuesday, March 27, 2018 - 12:00pm to 1:00pm
Leila Wehbe: Studying the Brain Basis of Language with Naturalistic Experiments: Opportunities, Challenges and Progress¿
Abstract: The advent of machine learning has allowed us to supplement hypothesis-driven science with data-driven science. In neuroscience. Most language experiments to date have studied the brain by crafting conditions designed to isolate a single hypothesis. My research focuses on naturalistic language experiments in which subjects process a rich text, and use machine learning and natural language processing techniques to discover and test multiple hypotheses. In this talk, I will describe a framework for making inferences about what the brain represents along three levels. Level 1 focuses on correct inference for a single naturalistic task (reading). Level 2 is concerned with combining data across subjects and tasks (reading, writing, speaking).Level 3 addresses the reproducibility of inferences drawn across subjects and tasks in entirely different experimental paradigms (controlled vs. naturalistic). My framework consists of a promising collaboration between machine learning, natural language processing and cognitive neuroscience that could help us better understand language processing in the brain.
Dr. Elizabeth Marsh