BIOLOGY SEMINAR: Dr. Stephanie Palmer
March 9 @ 12:30 pm - 1:30 pm
CANCELLED: We will update with new date once rescheduled
An animal eye is only as efficient as the organism’s behavioral constraints demand it to be. While efficient coding has been a successful organizational principle in vision, to make a more general theory, behavioral, mechanistic, and even evolutionary constraints need to be added to this framework. In our work, we use a mix of known computational hurdles and detailed behavioral measurements to add constraints to the notion of optimality in vision. Accurate visual prediction is one such constraint. Prediction is essential for interacting fluidly and accurately with our environment because of the delays inherent to all brain circuits. In order to interact appropriately with a changing environment, the brain must respond not only to the current state of sensory inputs but must also make rapid predictions of the future. In our work, we explore how our visual system makes these predictions, starting as early as the eye. We borrow techniques from statistical physics and information processing to assess how we get terrific, predictive vision from these imperfect (lagged and noisy) component parts. To test whether the visual system performs optimal predictive compression and computation, we compute the past and future stimulus information in populations of retinal ganglion cells, and in the vertical motion sensing system of the fly. In the fly, we anchor our calculations with careful measurements from the Dickinson group on fast evasive flight maneuvers. This survival-critical behavior requires fast and accurate control of flight, which we show can be achieved by visual prediction in the fly vertical sensing system, via a specific wiring motif. Moving on from behavior, developing a general theory of the evolution of computation is a current research direction in our group. We use the repeated evolution of tetra-chromatic color vision in butterflies to test hypotheses about whether neural computations contain shadows of the evolutionary history of the organism.
Stephanie Palmer is an AssociateProfessor in the Department of Organismal Biology and Anatomy and in the Department of Physics at the University of Chicago. She has a PhD in theoretical physics from Oxford University where she was a Rhodes Scholar, and works on questions at the interface of neuroscience and statistical physics. Her recent work explores the question of how the visual system processes incoming information, to make fast and accurate predictions about the future positions of moving objects in the environment. She was named an Alfred P. Sloan Foundation Fellow and holds a CAREER award from the NSF. Starting during her undergraduate years at Michigan State University, Stephanie has been teaching chemistry, physics, math, and biology to a wide range of students. At the University of Chicago, she founded and runs the Brains! Program, which brings local middle school kids from the South Side of Chicago to her lab to learn hands-on neuroscience.