|It would be great to understand the brain. It's an incredibly difficult problem, because all of our complex thoughts emerge from intricate connections between billions of relatively simple neurons. We still have a long way to go, but we now have some fundamental principles that explain how the system works. First and simplest, the brain looks for change. Why? Because change is where the action is. This basic idea can explain a huge variety of evidence, as I'll demonstrate with some nifty optical illusions. Second, neural circuits are kinky. This means that neurons have nonlinear responses, which unbend and untwist the natural patterns of sensory inputs until they're in a form that neurons can easily use. Third, the brain knows what it doesn't know. More specifically, the brain handles probabilities at a low level, weighing its options based on how reliable its evidence is. We're beginning to understand how neural circuits actually implement these computations, and these principles have a lot to teach us as we attempt to engineer ever more intelligent computing machines.
Wednesday, April 9, 2014
9:30am - McMurtry Auditorium, Duncan Hall
2014 ECE Affiliates Meeting
3 Ships - Leadership, Internship, and Entrepreneurship
Assistant Professor, Department of Electrical and Computer Engineering.
Assistant Professor of Computational Neuroscience, Baylor College of Medicine.