Decoding the Information Encoded in Neural Activity
Dr. Tom Mitchell
E. Fredkin University Professor, Carnegie Mellon
Brain imaging methods have revolutionized brain science by making it possible to observe neural activity in humans and animals at a level of detail never before possible. But understanding the brain requires that we understand more than what neural activity exists — we must understand the information it encodes, and how it operates on this information. We will describe a family of machine learning methods for auto-matically decoding the information encoded by neural activity, and their use to uncover new knowledge of how the brain represents meaning during reading.
Live Broadcast: coe.miami.edu/speaker/mitchell
Dr. Tom M. Mitchell is the E. Fredkin University Professor at Carnegie Mellon University, where he founded the world’s first Machine Learning Department. His research uses machine learning to develop computers that are learning to read the web, and uses brain imaging to study how the human brain understands what it reads. Mitchell is a member of the U.S. National Academy of Engineering, the American Academy of Arts and Sciences, a Fellow of the American Association for the Advancement of Science (AAAS), and a Fellow and Past President of the Association for the Advancement of Artificial Intelligence (AAAI). In 2015 he received an honorary Doctor of Laws degree from Dalhousie University for his contributions to machine learning and cognitive neuroscience.