Brain-Machine Interfaces (BMIs) are devices that can record and/or manipulate neural activity in the brain for clinical or consumer applications. The past decade has seen explosive growth in the range of BMI applications, including sensory and motor prostheses, treatment of neurological and neuropsychiatric disorders, and human-computer interaction. As brain interface devices improve and the application space expands, there is an increased need for better statistical and signal processing tools. Dr. Sabes will provide an overview of the BMI field, with an emphasis on statistical, computational and data-related challenges.
Speaker: Philip Sabes, PhD, Professor Emeritus of Physiology, UCSF
Register: http://eepurl.com/g1X35P