New recording technologies have revolutionized neuroscience, allowing scientists to record the spiking activity of thousands of neurons simultaneously. One of the most surprising findings to arise from these new capabilities is that orofacial movements, including eye movements, are much more predictive of neural activity in mouse visual cortex than previously thought. To better understand the relationship between face and eye movements and visual coding, however, we need new machine learning methods for relating these neural and behavioral time series. I will present my lab's research on deep probabilistic models for