[Comp-neuro] CFP: IEEE SIGNAL PROCESSING MAGAZINE Special Issue on Brain-Computer Interfaces

Paul Sajda ps629 at columbia.edu
Wed Oct 25 18:03:57 CEST 2006


Special Issue on Brain-Computer Interfaces

Developing real-time systems for decoding neural activity so as to  
provide a direct interface between brain and machine is no longer  
science fiction, instead it is an active area of research that has  
been termed brain computer interfaces (BCI). BCI research is highly  
multidisciplinary, integrating neuroscience, rehabilitation  
engineering, human computer interface design, machine learning and  
signal processing into either invasive or non-invasive systems that  
are capable of decoding brain activity so as to generate control/ 
communication signals for interpretation by computers. The  
application and utility of BCI ranges from systems for aiding those  
with severe neurological disease to systems optimizing the workload  
of a user by modulating information delivery based on the user's  
current "brain state".

BCI research is an excellent example of "applied signal processing",  
since at its core lies the real-time, online decoding of noisy multi- 
dimensional signals. Though the BCI field has made tremendous  
progress in recent years, there are still serious challenges, many of  
which could potentially be addressed by advances/improvements in  
signal processing, including increasing information transmission  
rates, more robust neural decoding algorithms, adaptive multi-channel  
filtering, etc.

This CFP is aimed at researchers applying signal processing  
techniques to build BCI systems. The special issue will cover a broad  
range of topics including hardware, software, algorithmic and  
application areas of BCI specifically focused on signal processing.  
High-quality tutorial-style papers are solicited from the following  
non-exhaustive list of topics.

Scope of topics:

Multi-electrode technologies interfacing with the motor system of  
primates or humans for decoding planned/intended movement (MEMs  
electrodes, LNA circuits, etc.).
Non-invasive BCI systems (electroencephalography or EEG,  
electrocorticography or ECoG, and functional near infrared imaging or  
fNIR) for decoding neural activity in humans.
Review and comparisons of linear versus non-linear signal processing  
for decoding neural activity.
Multi-modal neural imaging methods for BCI.
Systems for monitoring brain state to enable cognitive user interfaces.
On-line algorithms for data compression necessary for low bandwidth  
wired or wireless communication to/from implanted systems (e.g.,  
spike sorting, lossy compression).
On-line algorithms for decoding neural activity, including circuit  
implementations or implantable systems.
Implantable telemetry systems for communication to/from implanted  
systems (e.g., optimal frequency considerations, low power  
Signal processing methods for handling artifacts in BCI systems
Submission Procedure:
Prospective authors should submit white papers to the web submission  
system at http://www.ee.columbia.edu/spm/ according to the following  
timetable. White papers, limited to 2 single-column double-spaced  
pages, should summarize the motivation, the significance of the  
topic, a brief history, and an outline of the content. In all cases,  
prospective contributors should make sure to emphasize the signal  
processing in their submission.
Schedule (all deadlines are firm no exceptions)

White paper due:
December 1, 2006
Invitation notification:
January 1, 2007
Manuscript due:
May 1, 2007
Acceptance Notification:
August 1, 2007
Final Manuscript due:
September 15, 2007
Publication date:
January, 2008

Guest Editors:

Paul Sajda
Columbia University
ps629 at columbia.edu
Klaus-Robert Müller
Technical University of Berlin and Fraunhofer FIRST
klaus at first.fhg.de
Krishna V. Shenoy
Stanford University
shenoy at stanford.edu

Paul Sajda, Ph.D.
Associate Professor
Department of Biomedical Engineering
Columbia University
351 Engineering Terrace Building, Mail Code 8904
1210 Amsterdam Avenue
New York, NY 10027
tel: (212) 854-5279
fax: (212) 854-8725
email: ps629 at columbia.edu

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