She received her PhD in theoretical physics from Michigan State University in 2001, and completed her postdoctoral training in computational and theoretical neuroscience at the University of California, San Francisco. Tatyana uses methods from statistical physics and information theory to study how the brain encodes sensory stimuli. She is interested in how sensory processing in the brain is matched to the statistics of real-world signals, why might the evolved hierarchy of neural representations be optimal, and how it can be best adapted to track rapid changes in the statistics of inputs.