Institution: Stanford School of Medicine
Talk Title: Mapping neuronal representations in the visual cortex using deep learning
Abstract: My talk will explore how we use deep learning as a powerful tool to enhance our understanding of neuronal representations within the visual cortex. By employing deep neural networks as digital twins for specific cortical areas in both mice and macaques, we facilitate comprehensive in-silico experiments that precede and inform targeted in-vivo verification. This method integrates large-scale neuronal recordings with advanced AI models to systematically analyze how visual neurons encode diverse stimuli attributes, ranging from isolated object features to more complex scenarios involving internal brain states and contextual information. This approach not only deepens our understanding of the functional organization within the visual cortex but also establishes a link between biological and artificial vision systems.