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This lecture covers the neural modeling of sensory systems, focusing on proprioception, touch, vision, and motor control. It discusses the role of deep neural networks in modeling the proprioceptive pathway and inferring muscle dynamics, as well as the use of task-driven networks in understanding brain function. The presentation also explores the implications of biomechanical simulations and physics engines in modeling biological systems, such as action segmentation and animal identification.