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Research Labs
 Michael R. Chicoine, M.D.Ralph G. Dacey, M.D., and
Hans Dietrich, Ph.D.Jeffrey M. Gidday, Ph.D., and
T.S. Park, M.D.Eric Leuthardt MDKeith M. Rich, M.D.Matthew D. Smyth,
MD, FACS, FAAP
Thomas A. Woolsey, M.D.Gregory J. Zipfel M.D. and
Henry Han Ph.D.
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Department of Neurosurgery
Washington University
School of Medicine
Campus Box 8057
660 S. Euclid Ave.
St. Louis, MO 63110
(314) 362-3577 |
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Principal Investigator:
Eric Leuthardt MD
Lab Personnel
Nicholas Andersen MS
Timothy Blakely BS
Collaborators:
Daniel Moran PhD
Dennis Barbour, PhD
Gerwin Schalk MS
Guy Genin, PhD
Research Interests:
Over the last decade the idea of machines that could be controlled by one’s thoughts have emerged from the realm of fiction to one of serious scientific inquiry. The most common technical term for these types of devices is a Brain Computer Interface or BCI. Other synonymous terms include motor neuroprosthetics, Direct Brain Interface (DBI), Brain Machine Interface (BMI), and neurorobotics. Most simply put, these are machines that create a new output channel from the brain other than the natural motor and hormonal commands. BCIs recognize some form of electrophysiological alteration in the brain of a subject and use these changes as signals to either communicate with or control some element of the outside world which is consistent with the intentions of that subject. Concrete examples of such applications would be some type of brain signal controlling a cursor on a computer screen, a prosthetic limb, or one’s own limb. These types of devices hold tremendous promise for improving the quality of life of individuals who are cognitively intact yet motor impaired. This includes patients with spinal cord injury, stoke, neuromuscular disorders, and amputees. These are patients for whom, up to now, the field of neurosurgery has not been able to offer any substantive intervention. Moreover, these populations are increasing in size and relevance due to the aging population and improved survival following stroke and trauma.
Now with the improved understanding of the electrophysiological underpinnings of motor related cortical function, rapid development of inexpensive and fast computing, and a growing awareness of the needs of the severely motor impaired , the notion of a practical and clinically viable BCI now is beginning to deserve serious consideration. It will be essential for the neurosurgical community to understand what these devices are and their implications towards patient care. This will require a fundamental framework of how these systems operate, what are the current BCI platforms and their limitations, relevant issues when applied clinically, and what are the important milestones for their evolution towards entering standard neurosurgical practice.
Our lab is focusing on the use of electrocorticography, or ECoG, as a potential signal platform for clinical BCIs in the future. ECoG is a very promising intermediate BCI modality because it has higher spatial resolution, better signal-to-noise ratio, wider frequency range, and lesser training requirements than scalp-recorded EEG, and at the same time has lower technical difficulty, lower clinical risk, and probably superior long-term stability than intracortical single-neuron recording. This feature profile and recent evidence of the high level of control with minimal training requirements in human subjects shows potential for real world application for people with motor disabilities.
We are also extending these techniques to novel forms of brain mapping and seizure detection.
Eric Leuthardt, MD, director of the Center for Innovation in Neurosciences and Technology (CINT), is interviewed on the “Evolution of Brain Computer Interfaces” for a podcast produced by the journal Neurosurgical Focus. View the CINT website.
Recent Publications:
Leuthardt EC. What's holding us back? Understanding barriers to innovation in academic neurosurgery. Surg Neurol. 2006 Oct;66(4):347-9.
Leuthardt EC, Schalk G, Moran D, Ojemann JG. The Emerging World of Motor Neuroprosthetics: A Neurosurgical Perspective. Neurosurgery. 2006 Jul;59(1):1-14.
Schalk, G, Leuthardt, EC, Moran, D., Miller, KJ, Ojemann, J, Wolpaw, JR Towards two-dimensional cursor control using electrocorticographic signals. Proceedings to the 11th International Conference on Human-Computer Interaction, in press.
Leuthardt EC, Miller KJ, Schalk G, Rao RP, Ojemann JG. Electrocorticography-Based Brain Computer Interface--The Seattle Experience. IEEE Trans Neural Syst Rehabil Eng. 2006 Jun;14(2):194-8.
Bayly PV, Cohen TS, Leister EP, Ajo D, Leuthardt EC, Genin GM. Acceleration-induced deformation of the human brain. Journal of Neurotrauma. 2005 Aug; 22(8): 845-856.
Leuthardt EC, Schalk G, Wolpaw JW, Ojemann JG, Moran DW. A brain computer interface using electrocorticographic signals in humans. Journal of Neural Engineering. 2004 June: 1(2): 63-62. |
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