A key challenge is scale -- how can we relate the responses of large neuronal populations to complex stimuli and behavior that are themselves high-dimensional? Computation is crucial; it lets us model and interpret the functional relationship between stimulus, neuronal response, and behavior, and it helps us design stimuli and experiments to test specific hypotheses about neuronal coding.
In my PhD work, I focused on the visual system of the primate. Working at multiple levels with multiple techniques -- from the retina to extra-striate cortex, using physiology and behavior -- I elucidated key principles of visual encoding. In the visual cortex, I identified novel forms of visual coding using controlled, naturalistic stimuli, and in the retina, I characterized nonlinearities in ganglion cells using online, large-scale model fitting and targeted stimulus delivery.
I plan to combine my computational approaches to data analysis and experimental design with the rich variety of tools available in genetic model organisms.