Modeling the Brain: Machine Learning and Neuroscience

This lecture delves into the interplay between machine learning and neuroscience, focusing on how machine learning tools are used to model and understand the brain. It explores the concept of task-driven modeling, where behavior is linked to neural codes, and showcases how deep neural networks can predict neural responses. The discussion also touches on the adaptive nature of the sensory motor system and the challenges faced by AI in robotics. Through examples and research findings, the lecture highlights the successful application of machine learning in studying various sensory modalities and the potential for creating better models of biological systems.