Grace Lindsay, author of 'Models of the Mind', discusses the history of electricity in neuroscience, limitations of pen and paper calculations, failed neuroscience papers, origins of AI and the perceptron, neural coding and information processing, hierarchy of feature extractors in the visual system, firing rate models and ring networks, different types of models in computational neuroscience, reinforcement learning, and challenges in theoretical neuroscience.

Grace Lindsay, an Assistant Professor at NYU and author of "Models of the Mind," explores the fascinating world of theoretical neuroscience. She discusses the intricate interplay between mathematics and biology in understanding brain efficiency and the historical context of electrical models in neurobiology. Lindsay highlights the surprising complexities of a lobster's digestive neural circuitry and the challenges of studying the motor cortex. The conversation also touches on the synergy between neuroscience and AI, aiming to address big questions, including climate change.

Grace Lindsay, an assistant professor at NYU specializing in psychology and data science, discusses her book, which bridges neuroscience with physics and mathematics. She explores the benefits and limitations of mathematical models in understanding complex biological systems, using the whimsical 'spherical cow' analogy. Lindsay also delves into the intricacies of neuronal communication, lobster brain functionality, and the challenges of the motor cortex, emphasizing the importance of interdisciplinary collaboration in advancing neuroscience and addressing societal issues.