Baxter, Bryan2019-09-172019-09-172017-07https://hdl.handle.net/11299/206688University of Minnesota Ph.D. dissertation. July 2017. Major: Biomedical Engineering. Advisor: Bin He. 1 computer file (PDF); vii, 123 pages.Brain-computer interfaces (BCIs) and neuromodulation technologies have recently begun to fulfill their promises of restoring function, improving rehabilitation, and enhancing abilities and learning. However, lengthy user training to achieve acceptable accuracy is a barrier to BCI acceptance and use by patients and the general population. Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulation technology whereby a low level of electrical current is injected into the brain to alter neural activity and has been found to improve motor learning and task performance. A barrier to optimizing behavioral effects of tDCS is that we do not yet understand how neural networks are affected by stimulation and how stimulation interacts with ongoing endogenous activity. The purpose of this dissertation was to elucidate strategies to improve BCI control by targeting the user through two approaches: 1. Subject control of a robotic arm to enhance user motivation and 2. tDCS application to improve behavioral outcomes and alter networks underlying sensorimotor rhythm-based BCI performance. The primary results illustrate that targeted tDCS of the motor network interacts with task specific neural activity to improve BCI performance and alter neural electrophysiology. This effect on neural activity extended across the task network, beyond the area of direct stimulation, and altered connectivity unilaterally and bilaterally between frontal and parietal cortical regions. These findings suggest targeted neuromodulation interacts with endogenous neural activity and can be used to improve motor-cognitive task performance.enBCIBrain Computer InterfaceConnectivitytDCSTranscranial Current StimulationTranscranial Direct Current StimulationThesis or Dissertation