Reinforcement Learning in the Brain

Throughout this course, we only briefly mentioned some relations between aspects of machine learning and the brain. This included the basic filters of Gabor-like functions in the visual system, the human ability to leverage Bayesian decision-making in taking priors into account, the layered structure of neural networks, and the implementation of associative memory with recurrent networks. While these are important components to consider in neuroscience, one of the most amazing stories of the interaction between learning theory, behavioral and cognitive science, and system neuroscience is related to reinforcement learning. This brief lesson presents a brief outlook into this fascinating area.