Sri Sarma, PhD, SM
Highlights
Languages
- English
Gender
FemaleJohns Hopkins Affiliations:
- Johns Hopkins School of Medicine Faculty
About Sri Sarma
Background
Sridevi Sarma received the B.S. degree in electrical engineering from Cornell University, Ithaca NY, in 1994; and an M.S. and Ph.D. degrees in electrical engineering and computer science from Massachusetts Institute of Technology, Cambridge MA, in 1997 and 2006, respectively. From 2000 to 2003 she took a leave of absence to start a data analytics company. From 2006 to 2009, Dr. Sarma was a postdoctoral fellow in the brain and cognitive sciences department at the Massachusetts Institute of Technology, Cambridge. She is now an associate professor in the Institute for Computational Medicine, Department of Biomedical Engineering, at Johns Hopkins University. Her research interests include modeling, estimation and control of neural systems using electrical stimulation. She is a recipient of the GE Faculty for the Future scholarship, a National Science Foundation graduate research fellow, a L'Oreal for Women in Science fellow, the Burroughs Wellcome Fund Careers at the Scientific Interface Award, the Krishna Kumar New Investigator Award from the North American Neuromodulation Society, and a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) and the Whiting School of Engineering Robert B. Pond Excellence in Teaching Award.
Centers and Institutes
Additional Academic Titles
Joint Appointment in Neurology, Joint Appointment in Neuroscience
Contact for Research Inquiries
Phone: (410) 516-4381
Research Interests
Brain-machine interactive control of fast movements, Closed-loop deep brain stimulation for Parkinsons Disease (PD), Closed-loop stimulation for epilepsy
Research Summary
My research interests are centered in three key areas: closed-loop deep brain stimulation for Parkinson’s Disease (PD); closed-loop stimulation for epilepsy; and brain-machine interactive control of fast movements.
With respect to closed-loop deep brain stimulation (DBS) for Parkinson’s Disease, my focus is on the modeling of basal ganglia (in health and PD), the modeling effect of DBS, and feedback control design of DBS strategies.
Seizure detection from invasive EEG signals, and seizure foci localization from invasive EEG signals are central to analysis of closed-loop stimulation of epilepsy.
Brain-machine interactive control of fast movements entails the modeling of cerebro-cerebellar regions from human and primate data, as well as optimization the design of a decoder-compensator.
Selected Publications
Burns SP, Sritharan D, Jouny C, Bergey G, Crone N, Anderson WS, Sarma SV. A network analysis of the dynamics of seizure. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:4684-7. doi: 10.1109/EMBC.2012.6347012. PMID: 23366973
Pedoto G, Santaniello S, Fiengo G, Glielmo L, Hallett M, Zhuang P, Sarma SV. Point process modeling reveals anatomical non-uniform distribution across the subthalamic nucleus in Parkinson's disease. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:2539-42. doi: 10.1109/EMBC.2012.6346481. PMID: 23366442
Santaniello S, Gale JT, Montgomery EB Jr, Sarma SV. Reinforcement mechanisms in putamen during high frequency STN DBS: A point process study. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:1214-7. doi: 10.1109/EMBC.2012.6346155. PMID: 23366116
Sritharan D, Sarma SV. Fragility in Dynamic Networks: Application to Neural Networks in the Epileptic Cortex. Neural Comput. 2014 Jul 24:1-34. [Epub ahead of print] PMID: 25058705
Yaffe R, Burns S, Gale J, Park HJ, Bulacio J, Gonzalez-Martinez J, Sarma SV. Brain state evolution during seizure and under anesthesia: a network-based analysis of stereotaxic eeg activity in drug-resistant epilepsy patients. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:5158-61. doi: 10.1109/EMBC.2012.6347155. PMID: 23367090