Capturing cortical dynamics to build a time-varying model of the brain – implications in neuroscience and brain-computer interface

Date

June 12, 2012

Speaker

Adrian KC Lee

Affiliation

University of Washington

Overview

Understanding brain dynamics involved in many perceptual and cognitive tasks is of particular interest to scientists in the fields of speech & hearing, as well as neuroscience at large. Furthermore, this knowledge can be combined in an engineering approach to improve our brain-computer interface (BCI) designs, as well as providing us with crucial information on computation modeling, e.g., in speech production. In this talk, I will introduce an emerging neuroimaging technique—known as magnetoencephalography (MEG)—that has just arrived at the University of Washington. I will present our ongoing work on mapping the cortical network involved in auditory attention using a multimodal imaging approach (combining MEG with electroencephalography and magnetic resonance imaging). I will also discuss why the interface between neuroscience and engineering will be the crucial juncture on which new discoveries depend.

Speakers

Adrian KC Lee

Adrian KC Lee is Assistant Professor in the Department of Speech and Hearing Sciences and Institute for Learning and Brain Sciences at the University of Washington. He graduated with a BEng (Elec) at University of New South Wales, Australia and obtained his doctoral degree at the Harvard-MIT Division of Health Sciences and Technology in Cambridge, Massachusetts, USA. His research focuses on understanding how humans attend to different sounds in a complex acoustical environment (e.g., a cocktail party). His laboratory uses a multimodal neuroimaging approach (combining magneto- and electro-encephalography as well as magnetic resonance imaging) to map the cortical network involved in auditory attention. The goal of his laboratory is to combine neuroscience knowledge with state-of-the-art engineering approaches to design next-generation brain-computer interfaces that enable users to dynamically tune their prosthetic devices using only their minds.