Jacek Dmochowski
Faculty and Staff Profiles
Jacek Dmochowski
Assistant Professor
School/Division
Department
- Grove School of Engineering
- Biomedical Engineering
Office
Room 460
Building:
Steinman Hall
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Education
Description:
Ph.D., Telecommunications, 2008 (Institut National de la Recherche Scientifique, Canada)
M. A. Sc., Electrical Engineering, 2005 (Carleton University, Canada)
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Affiliation
Description:
08/2015 - Current: City College of New York - Assistant Professor (Biomedical Engineering)
06/2013 - 07/2015: Stanford University - Research Associate (Psychology)
09/2008 - 05/2013: City College of New York - Post-Doctoral Fellow (Biomedical Engineering)
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Research Interests
Description:
Research in the Dmochowski Lab is aimed at developing new techniques for non-invasive brain stimulation. We are investigating techniques that employ electric currents, near-infrared lasers, and ultrasonic waves to perturb neural activity in a specific and reversible manner. These interventions are coupled with recordings of brain activity using EEG and fMRI in order to understand the effects of the stimulation on the brain. A central challenge in brain stimulation research is that there is an infinite set of possible configurations with which to stimulate. Moreover, the system being stimulated (i.e., the brain) is dynamic and highly non-linear. Therefore, deriving general principles to guide rational use of brain stimulation is necessary to advance neuromodulation to clinical care. This is the overarching goal of our research.
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Publications
Description:
Selected Publications:
Dmochowski, J. P., Datta, A., Bikson, M., Su, Y., & Parra, L. C. (2011). Optimized multi-electrode stimulation increases focality and intensity at target. Journal of neural engineering, 8(4), 046011.
Dmochowski, J. P., Sajda, P., Dias, J., & Parra, L. C. (2012). Correlated components of ongoing EEG point to emotionally laden attention–a possible marker of engagement?. Frontiers in human neuroscience, 6, 112.
Dmochowski, J. P., Bezdek, M. A., Abelson, B. P., Johnson, J. S., Schumacher, E. H., & Parra, L. C. (2014). Audience preferences are predicted by temporal reliability of neural processing. Nature communications, 5.