Catalog Description: The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester.
Units: 1-3
Prerequisites: Consent of instructor.
Formats:
Fall: 1-3 hours of lecture per week
Spring: 1-3 hours of lecture per week
Grading basis: letter
Final exam status: No final exam
Also listed as: EL ENG 290P
Department Notes: The aim of this course is to provide the student with an overall view of the multiple components that take part in a BMI system, and the different disciplines and levels of abstraction needed for design and implementation of these systems. Brain-machine interface (BMI) technology is meant to have a strong impact in society in the near future. BMIs are powerful tools that use brain-derived signals to control artificial devices such as computer cursors and robots. This novel paradigm contends that a user can perceive sensory information and enact voluntary motor actions through a direct interface between the brain and an artificial actuator in virtually the same way that we see, walk or grab an object with our own natural limbs. In the short/mid-term future, BMIs will improve the quality of life for millions of people suffering from neurological disorders and other disabilities. The impact of this technology in the clinical realm will drive neural technology to the next level: augmentation of sensory, motor and cognitive capabilities in healthy subjects. Ultimately this technology may impact society in many different ways, allowing direct wireless communication (internet, sensor networks, mobile devices, etc) and interaction (control of artificial devices) with the real world. While significant breakthroughs have been achieved in recent years and the field is rapidly taking off, there are challenges that need to be met before BMI technology becomes part of our daily lives. In this course we will address some of these challenges and discuss solutions and future directions. Lecture Format and Guest Speakers The first 90minute part of each day will be dedicated to lecture, while the second part will be dedicated to paper discussion or project work. Speakers will cover a broad range of topics from neuroscience, engineering and clinical perspectives, that are related to BMI systems. Confirmed speakers: Pieter Abbeel, EECS, UC Berkeley Jose Carmena, EECS, Cognitive Science and Neuroscience, UC Berkeley Jack Gallant, Psychology and Neuroscience, UC Berkeley Michael Gastpar, EECS, UC Berkeley Michel Maharbiz, EECS, UC Berkeley Robert Knight, Psychology and Neuroscience, UC Berkeley Jan Rabaey, EECS, UC Berkeley Philip Sabes, Keck Center for Integrative Neuroscience, UCSF Krishna Shenoy, EE and Neuroscience, Stanford University Intended Audience This course is being offered to graduate students from EECS, ME, BioE and Neuroscience programs. It is highly multidisciplinary, covering engineering, basic science, and clinical aspects of BMI systems. There are no prerequisites. Course Materials There is no required textbook for the course. Lecture materials will be provided, consisting of journal papers and chapters from several texts. Suggested texts are: * Methods for Neural Ensemble Recordings. Miguel Nicolelis (Ed.). CRC Press 1999. ISBN 0-8493-3351-2 * Neuroprosthetics: Theory and Practice. Horch and Dillon (Eds.). World Scientific 2004. ISBN 981-238-022-1