Dr. Amy Orsborn joined UW in 2018 as a Clare Boothe Luce Assistant Professor in Electrical & Computer Engineering and Bioengineering. She works at the intersection of engineering and neuroscience to develop therapeutic neural interfaces. She completed her Ph.D. at the UC Berkeley/UCSF Joint Graduate Program in Bioengineering developing co-adaptive strategies for brain-machine interfaces where machine-learning and neural adaptation collaborate to improve system performance. In her postdoctoral training at NYU’s Center for Neural Science, she developed novel neural implants for multi-scale, multi-modal interrogation and monitoring of neural circuits in non-human primates. These implants enable new ways to study neural mechanisms of learning in large-scale networks. Her work has been supported by NSF Graduate Research Fellowship, a pre-doctoral award from the American Heart Association, and a L’Oreal USA for Women in Science postdoctoral award.
Dr. Orsborn’s lab Her explores neural interfaces as adaptive closed-loop systems that engage neural plasticity and adaptation. She uses engineering approaches to leverage neural adaptation for system performance, and uses neural interfaces as a tool to study neural mechanisms of learning in circuits. The lab also specializes in system integration for advancing neurotechnologies to study neural circuits in awake primates for basic science and towards human translation.
Awards and Honors
Clare Boothe Luce professorship, 2018 – 2024
L’Oréal USA for Women in Science postdoctoral fellowship, 2016
American Heart Association, Western States Affiliate, Pre-doctoral fellowship, 2011
National Science Foundation Graduate Research Fellowship, 2008
See http://faculty.washington.edu/aorsborn/research.html for latest projects.
A.L. Orsborn and B. Pesaran (2017) Parsing learning in networks using brain-machine interfaces, Current Opinions in Neurobiology (link)
M. Shanechi*,A. L. Orsborn*, H.G. Moorman*, S. Gowda*, and J.M. Carmena (2017). Rapid control and feedback rates enhance neuroprosthetic control. Nature Communications (link, open)
M. Shanechi , A.L. Orsborn*, and J.M. Carmena (2016). Robust brain-machine interface design using optimal feedback control modeling and adaptive point process filtering. PLoS Computational Biology F1000 recommended (link, open)
A.L. Orsborn, H.G. Moorman, S.A. Overduin, M. M. Shanechi, D. Dimitrov, and J.M. Carmena (2014) Closed-loop decoder adaptation shapes neural plasticity for skillful neuroprosthetic control, Neuron (journal cover article) (link)
S. Dangi, S. Gowda, H.G. Moorman, A.L. Orsborn, K. So, M. M. Shanechi, and J.M. Carmena (2014) Continuous closed-loop decoder adaptation with a recursive maximum likelihood algorithm allows for rapid performance acquisition in brain-machine interfaces, Neural Computation (link)
S. Gowda, A.L. Orsborn, S.A. Overduin, H.G. Moorman, and J.M. Carmena (2014) Designing dynamical properties of brain-machine interfaces to optimize task-specific performance, IEEE Transactions on Neural Systems and Rehabilitation Engineering (link)
K. So*, S. Dangi*, A.L. Orsborn, M.C. Gastpar, and J.M. Carmena (2014) Subject-specific modulation of local field potential spectral power during brain-machine interface control in primates, Journal of Neural Engineering (link)
S. Dangi*, A.L. Orsborn*, H.G. Moorman, and J.M. Carmena (2013) Design and analysis of closed-loop decoder adaptation algorithms for brain-machine interfaces. Neural Computation(link)
A.L. Orsborn and J.M. Carmena (2013) Creating new functional circuits for action via brain-machine interfaces, Frontiers in Computational Neuroscience(link, open)
A.L. Orsborn, S. Dangi, H.G. Moorman, and J.M. Carmena (2012) Closed-loop decoder adaptation on intermediate time-scales facilitates rapid BMI performance improvements independent of decoder initialization conditions. IEEE Transactions on Neural Systems and Rehabilitation Engineering (link)
Select conference papers
J. Kleinbart, A. L. Orsborn, John S. Choi, C. Wang, S. Qiao, J. Viventi, B. Pesaran (2018) A modular implant system for multimodal recording and manipulation of the primate brain, 39th International conference IEEE EMBS, Honolulu, HI. (link)
J. S. Choi, V. Goncharov, J. Kleinbart, A. L. Orsborn, B. Pesaran (2018) Monkey-MIMMS: Towards automated cellular resolution large-scale two-photon microscopy in the awake macaque monkey, 39th International conference IEEE EMBS, Honolulu, HI. (link)
S. Qiao, K. Brown, A. L. Orsborn, B. Ferrentino, B. Pesaran (2016) Development of semi-chronic microdrive system for large-scale circuit mapping in macaque mesolimbic and basal ganglia systems, 38th International conference IEEE EMBS, Orlando, FL. (link)
A. L. Orsborn, C. Wang, K. Chiang, M. M. Maharbiz, J. Viventi, and B. Pesaran (2015) Semi-chronic chamber system for simultaneous subdural electrocorticography, local field potential, and spike recordings, Proceedings of the 7th International Conference IEEE EMBS Neural Engineering, Montpellier, France. (link)