In this episode, Xavier Bonilla has a dialogue with Grace Lindsay about the computational approach that can be used to understand the brain. They discuss what computational neuroscience is and provide a brief overview and review of neuroanatomy. They talk about action potentials and the comparisons with an electrical circuit. They discuss the Hopfield Network as a way to understand various forms of memory in the brain, specifically within the hippocampus. They explain how early computer science research helped in creating a model for visual sequencing. They also discuss the future of computational neuroscience such as the Bayesian model, backpropagation, and many other topics. 
Grace Lindsay is a computational neuroscientist at the Sainsbury Wellcome Centre/Gatsby Computational Neuroscience Unit University College London. She received her PhD in Neurobiology and Behavior at Columbia University. Her first book, Models of the Mind: How Physics, Engineering, and Mathematics Have Shaped Our Understanding of the Brain discusses many of the elements discussed in this episode. You can purchase that book here. You can find her at her website. Twitter: @neurograce