Combining TMS and EEG for Characterizing Motor Network Interactions and Improving Motor Recovery after Stroke
Year: 2016
Type: dissertation
Abstract: University of Minnesota Ph.D. dissertation. December 2016. Major: Biomedical Engineering. Advisor: Bin He. 1 computer file (PDF); viii, 109 pages.
Author: Nessa Johnson
Language: English
Subfield: Neurology
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funders: National Science Foundation, University of Minnesota, Achievement Rewards for College Scientists Foundation, National Institutes of Health, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, National Center for Complementary and Integrative Health
Awards: A Brain Centered Neuroengineering Approach for Motor Recovery after Stroke: Combined rTMS and BCI Training, Mind-body awareness training and brain-computer interface, G39219656, Spatio-temporal dynamic imaging of seizure sources, IGERT: Interacting with the Brain: Mechanisms, Optimization, and Innovation, Electrophysiological Source Imaging of Partial Epilepsy
OpenAlex ID: W2945501609