Event Details:
Brain-machine interfaces (BMIs) is a novel technology that holds great potential to aid large numbers of people with sensory, motor and cognitive disabilities. BMIs provide also a framework for examining basic neuroscience questions, especially those related to the understanding of how neural plasticity relates to the acquisition and consolidation of neuroprosthetic skills, i.e. accurate, readily-recalled control of disembodied actuators irrespective of natural physical movement. In this talk I will postulate that achieving skillful, natural control of a multi-degree-of-freedom prosthetic device will entail synergizing two different types of adaptation processes: natural (brain plasticity) and artificial (decoder adaptation), as well as providing realistic sensory feedback from the prosthetic device. I will present recent work from our laboratory showing that 1) neuroplasticity facilitates consolidation of neuroprosthetic motor skill in a way that resembles that of natural motor learning; 2) corticostriatal plasticity is necessary for neuroprosthetic skill learning, and 3) closed-loop decoder adaptation (CLDA) techniques can expedite the learning process by adapting the decoder parameters during closed-loop BMI operation (i.e., while the subject is using the BMI). We believe that BMI systems capable of exploiting both neuroplasticity and CLDA will be able to boost learning, generalize well to novel movements and environments, and ultimately achieve a level of control and dexterity comparable to that of natural arm movements.
Everyone is welcome to attend (students, postdocs, faculty, staff). There will be plenty of time for Q&A and interaction. Dinner will be provided at 6:30pm. The seminar will be held in Sloan Hall, Math Bldg 380, Room 380-C, lower level courtyard side, followed by dinner in the courtyard outside of Jordan Hall, Bldg 420, Room 050. *Please RSVP for the Monday, May 19 Dinner to lehope@stanford.edu by Tuesday, May 13