Attractor Networks and Generalizations

This lecture by the instructor covers the topic of attractor networks and generalizations of the Hopfield model in computational neuroscience. The lecture delves into concepts such as low-activity patterns, attractor memory in realistic networks, and the dynamics of attractor memory with low activity patterns. The presentation explores the neuronal dynamics of cognition, discussing the flow to fixed points in attractor models and the capacity calculations for attractor networks.