Thursday, June 17th, 1999
Jonathan R. Wolpaw, Wadsworth Center, New York State Dept Health and SUNY, Albany, NY
Charles W. Anderson, Department of Computer Science, Colorado State University, Fort Collins, CO
Brain-Computer interface research at Colorado State University (8:45am)
Jessica D. Bayliss and Dana H. Ballard, department of Computer Science, University of Rochester, Rochester, NY
A virtual reality testbed for brain-computer interface research (9:00am)
Luigi Bianchi and Febo Cincotti, Universita degli Studi “Tor Vergata” and Ospedale di Riabilitazione, IRCCS “S. Lucia,” Rome, Italy
EEG recognition of imagined movements through signal space projection (9:15am)
Neils Birnbaumes, Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen, Tuebingen Germany
The thought translation device (TTD) (9:30am)
Gary E Birch and Steven G Mason, Neil Squire Foundation, Vancouver and ILY Technologies, Victoria, B.C., Canada
Brain-computer interface research at the Neil Squire Foundation (9:45am)
John K. Chapin, Department of Anatomy and Neurobiology, Hahnemann University, Philadelphia, PA
Robotic Control from realtime transformation of multi-neuronal population vectors (10:30am)
Emanuel Donchin, Beckman Institute and Department of Psychology, University of Illinois, Champaign, IL
The mental prosthesis: assessing the speed of a P300-based brain-computer interface (10:45am)
Robert E. Issacs, Chemical, Biological, and Materials Engineering, Arizona State University, Tempe, AZ
Real-time control of a cortical neural prosthesis (11:00am)
Andrew Junker, Brain Actuated Technologies, Inc., Yellow Springs, OH
Cyberlink control (11:15am)
Philip R. Kennedy, Neural Signals, Inc. and Emory University, Atlanta, GA
Direct control of a computer from the human nervous system (11:30am)
Aleksander Kostov, Laboratory for Advanced Assistive Technologies, Edmonton, Alberta, Canada
Parallel man-machine training in development of EEG-based cursor control (2:00pm)
Simon P. Levine, Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, MI
A direct brain interface based upon detection of event related potentials in an electrocortigram (2:15pm)
Scott Makeig, Cognitive Psychophysiology Laboratory, Naval Health Research Center, San Diego, CA
Near real-time alterness measures: their application to brain-computer interfaces (2:30pm)
Matt S. Middendorf, Scientific Services, Inc. and Air Force Research Laboratory, Wright-Patterson Air Force Base, Daytona, OH
Brain-computer interfaces based on the steady-state visual evoked response (2:45pm)
Christa Neuper, University of Technology, Department of Medical Informatics, Graz, Austria
Current trends in Graz brain-computer interface (BCI) research (3:00pm)
P. Hunter Peckham, Rehabilitation Engineering Center, Case Western Reserve University, Cleveland, OH
An EEG-based controller for the hand-grasp neuroprosthesis (3:45pm)
William D. Penny, Department of Electrical Engineering, Imperial College, London, England
EEG-based communication: a pattern recognition approach (4:00pm)
Jamie A. Pineda, Cognitive Neuroscience Laboratory, University of California, San Diego, CA
Real-time recognition of EEG patterns: machines and practical work (4:15pm)
Jonathan R. Wolpaw, Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health and State University of New York, Albany, NY
EEG-based brain-computer interface research at the Wadsworth Center (4:30pm)
Louis A. Quatrano, National Center for Medical Rehabilitation Research, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
Funding BCI research projects (4:45pm)
Friday, June 18th, 1999
Discussion Session 1 (8:30-10:00am)
Definition and essential features of a brain-computer interface
Job Wolpaw (Chair), Eleanor Curran, Alan Gevins, Andrew Junker, Steve Mason, Charlie Robinson
1. What is a brain-computer interface (BCI)?
2. What are the essential features of a BCI?
3. What are the major issues that must addressed in developing a BCI?
4. How does one evaluate its performances (e.g. information transfer rate (bit rate), more specific measures)?
5. How does one separate system performance from subject performance?
6. What functions could a BCI serve?
Discussion Session 2 (10:20am-12:00pm)
EEG components that might be used as control signals
Neils Birbaumer(Chair), Febo Cincotti, Irina Goncharova, Scott Makeig, Christa Neuper, Jamie Pineda
1. What EEG components might be considered for use as control signals?
2. What areas of the CNS are likely to produce signals of value for communication?
3. What are the advantages and disadvantages of time-domain and frequency-domain components?
4. Are certain components likely to be especially useful or useless for people with certain disabilities?
5. How are different components likely to differ in their adaptation to use as control signals?
Discussion Session 3 (4:00-5:30pm)
Bill Heetderks(Chair), Luigi Bianchi, John Chapin, Gyongi Gaal, Robert Isaacs, Phil Kennedy, Simon Levine
1. What are the possible locations of implanted electrodes?
2. What signals will they record?
3. What are the options for obtaining stable recording capability over months and years?
4. What patients might be best suited, by liability and/or by needs, for implanted electrodes?
5. To what extent will the control provided by recording neurons be able to be independent of the presence of normal feedback from other CNS areas?
6. What other improvements in recording technologies might help BCI development
7. Are other recently developed technologies such as magnetoencephalography, positron emission tomography, and magnetic resonance imaging of possible use for BCI purposes?
Saturday, June 19th, 1999
Discussion Session 4 (8:30-10:00am)
Dennis McFarland(Chair), Jessica Bayliss, Gary Birch, Christof Gueger, Thilo Hinterberger, Tzyy-Ping Jung, Will Penny
1. What are the factors to consider in choosing methods for recording EEG components as control signals?
2. For what frequency- and time-domain components, what methods are available and what are the advantages and disadvantages of each?
3. What spatial filters are available, what are the key characteristics and advantages and disadvantages of each?
4. What other methods are available for detection and elimination of noise, whether EEG or non-EEG?
5. What are the best methods for detecting non-EEG artifacts, such as EMG, eye-movements, eye blinks?
6. Are there general principles of signal detection that apply to all brain-computer interface applications?
Discussion Session 5 (10:30am-12:00pm)
Translation of EEG components into device control signals
Hunter Peckham(Chair), Charles Anderson, Dana Ballard, Georg Fabiani, Aleksandar Kostov, Jouri Perelmounter, Gerv Schalk
1. What are the possible methods for translating EEG signals into device commands?
2. How does one go about choosing a translation algorithm?
3. How does one use an individual’s EEG and past performance to choose a translation algorithm?
4. How should translation algorithms be tested and compared?
5. How does one manage the interaction of the two adaptive controllers, the user and the BCI, that is probably an inevitable feature of any BCI system?
6. How does one define what aspects of EEG signals, translation algorithm, algorithm parameters, etc. should adapt on an initial or continuing basis, and determine optimum rate and extent of adaptation?
7. What aspects have been subjected to adaptation up to the present?
8. How does one adjust, initially and continually, the algorithm and its parameters to the individual?
9. How should possible adaptation methods be tested and compared?
10. How does one ensure that a translation algorithm promotes development and maintenance of EEG control?
11. Are there general principles for designing training protocols?
12. How might one turn a BCI system on and off?
Discussion Session 6 (4:00-5:30pm)
Applications of BCI Technology
Manny Donchin(Chair), Jane Huggins, Andrea Kuebler, Rich Lauer, Matt Middendorf, Mark Polak
1. How does one go about choosing an application for a BCI?
2. What criteria should the BCI and the application meet?
3. What applications seen particularly promising?
4. How does one evaluate performance?
5. What performance levels (e.g., bit rates, speed, accuracy) might be expected in the near future? In the more distant future?
6. How does one evaluate performance?
7. What are the major impediments to increasing the range and capacities of applications?
8. How might BCI communication supplement or combine with conventional communication technologies?
9. What are the advantages of focusing on a prototype laboratory task?
10. Should we define a recommended prototype application, such as a cursor movement or menu selection, for use in development of BCI systems in research laboratories?
Sunday, June 20th, 1999
Summary breakfast and closing (9:00-11:00am)