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Gerwin Schalk, Ph.D.

  • Gerwin Schalk

    Gerwin Schalk, Ph.D.

    • National Center for Adaptive Neurotechnologies
    • Associate Professor, School of Public Health, Biomedical Sciences

    • Ph.D., Rensselaer Polytechnic Institute (2006)
    • M.S., Rensselaer Polytechnic Institute (2001)
    • M.S., Graz University of Technology (1999)

    gerwin.schalk@health.ny.gov
    (518) 486-2559

Research Interests

Our laboratory integrates and advances scientific, engineering, and clinical concepts to innovate, develop and test new neurotechnologies and to apply them to basic and applied research. These multidisciplinary efforts span a variety of areas, including computational, cognitive, and systems neuroscience, signal processing, machine learning, statistics, computer science, and neurology/neurosurgery.

Our vision is to revolutionize the way we can study the brain, and to develop important new clinical tools for diagnosis or treatment of nervous system function. To pursue this research, we acquire signals from the brain and integrate them with anatomical and behavioral measurements, use computational and statistical techniques, and develop software tools in different programming languages such as C++, Matlab and Python.

Select Publications

Schalk G.
A general framework for dynamic cortical function: the function-through-biased-oscillations (FBO) hypothesis.
Front Hum Neurosci.
(2015)
9
352.
Brunner P, Ritaccio AL, Lynch TM, Emrich JF, Wilson JA, Williams JC, Aarnoutse EJ, Ramsey NF, Leuthardt EC, Bischof H, Schalk G.
A practical procedure for real-time functional mapping of eloquent cortex using electrocorticographic signals in humans.
Epilepsy & Behavior.
(2009)
15
(3):
278-86.
Schalk G, Kubánek J, Miller KJ, Anderson NR, Leuthardt EC, Ojemann JG, Limbrick D, Moran D, Gerhardt LA, Wolpaw JR.
Decoding two-dimensional movement trajectories using electrocorticographic signals in humans.
J Neural Eng.
(2007)
4
(3):
264-275.
Leuthardt EC, Schalk G, Wolpaw JR, Ojemann JG, Moran DW.
A brain-computer interface using electrocorticographic signals in humans.
J Neural Eng.
(2004)
1
(2):
63-71.
Schalk G, McFarland DJ, Hinterberger T, Birbaumer N, Wolpaw JR.
BCI2000: a general-purpose brain-computer interface (BCI) system.
IEEE Trans Biomed Eng.
(2004)
51
(6):
1034-1043.