Abstract:

Machine learning is rapidly advancing and fundamentally changing neuroscience research. In this lecture, I will present our work on measuring and modeling brain-behavior interactions with the goal of reverse engineering how the brain adapts to changes in the environment. Specifically, I will discuss our work on computer vision algorithms for markerless motion capture, our efforts to merge this data with neural data with new machine learning methods, and our work on using large-language models for behavioral analysis.