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dc.contributor.authorGanguly, Karunesh
dc.date.accessioned2018-02-12T18:57:31Z
dc.date.available2018-02-12T18:57:31Z
dc.date.issued2018-02-05
dc.identifier.urihttp://hdl.handle.net/1853/59337
dc.descriptionPresented on February 5, 2018 at 11:15 a.m. in the Krone Engineered Biosystems Building, Room 1005.en_US
dc.descriptionKarunesh Ganguly is an Associate Professor of Neurology at the University of California, San Francisco. His research interests include online and offline processing in motor cortex during neuroprosthetic learning, offline processing during natural motor skill acquisition, and cortical basis of recovery after stroke or traumatic brain injury.en_US
dc.descriptionRuntime: 60:08 minutesen_US
dc.description.abstractIt is commonly hypothesized that restoration of normal neural dynamics in the injured brain can improve function. However, we lack a precise neurophysiological framework for such an approach. Here we show that low-frequency oscillatory (LFO) dynamics play an important role in the execution of skilled behaviors in both the intact and injured brain. We chronically recorded local field potentials and spiking during motor training in both healthy and post-stroke rats. Interestingly, we found that task-related LFOs emerged with skilled performance under both conditions and were a robust predictor of recovery. We further hypothesized that boosting LFOs might improve function in animals with persistent deficits. Strikingly, we found that direct current stimulation could boost LFOs, and when applied in a novel, task-dependent manner, significantly improved function in those with chronic deficits. Together, our results demonstrate that LFOs are essential for skilled controlled and represent a novel target for modulation after injury.en_US
dc.format.extent60:07 minutes
dc.language.isoen_USen_US
dc.relation.ispartofseriesGT Neuro Seminar Seriesen_US
dc.subjectEngineeringen_US
dc.subjectMotoren_US
dc.subjectNeuralen_US
dc.subjectStrokeen_US
dc.titleA Systems Neuroscience Approach to Motor Recoveryen_US
dc.typeLectureen_US
dc.typeVideoen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Neural Engineering Centeren_US
dc.contributor.corporatenameUniversity of California, San Francisco. Dept. of Neurologyen_US


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