This lecture discusses the role of brain-computer interfaces (BCIs) in systems neuroscience, focusing on their potential to enhance neuroprosthetics and assist individuals with disabilities. The instructor introduces the concept of BCIs, explaining how they enable users to control external devices through neural signals. The lecture covers the mechanisms of recording neural activity, building decoding algorithms, and calculating control parameters for devices. It emphasizes the importance of understanding neural circuits and dynamics to improve BCI technology. The instructor highlights the significance of sensory feedback in BCI applications, which allows users to receive real-time information about their interactions with the environment. Additionally, the lecture explores the use of BCIs as tools for studying learning processes in the brain, showcasing recent advancements in the field. The discussion includes various research studies and technologies that contribute to the development of effective BCIs, ultimately aiming to bridge the gap between neural activity and external device control.