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About

J. Randall Flanagan is a leading figure in the fields of sensorimotor control, motor learning, and the neural basis of skilled manipulation. His research fundamentally explores how the brain predicts and controls the complex dynamics of interacting with objects, from grasping a coffee cup to using a tool. A central contribution is his work on internal models—neural representations that allow the brain to predict the sensory consequences of motor commands. His highly cited studies, such as "Multiple Grasp-Specific Representations of Tool Dynamics Mediate Skillful Manipulation" (70 citations) and "Neural Correlates of Internal-Model Loading" (69 citations), have been instrumental in showing that the brain forms distinct, context-dependent motor memories for different tool orientations and loads. Flanagan has also significantly advanced our understanding of how the visual system supports action, as seen in "Functional Use of Eye Movements for an Acting System" (87 citations), and the role of haptic feedback in learning to handle nonrigid objects (40 citations). With over 380 citations across his top ten papers, his work bridges cognitive science and robotics, providing a computational framework for dexterous manipulation. Notably, his 2010 Q&A article, "Robotics as a tool to understand the brain," underscores his commitment to using robotic interfaces to uncover the principles of human motor control, making him a pivotal figure for students and researchers in motor neuroscience.