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.
- Brain-machine interfaces
- Multi-learner adaptive systems
- Computation in neural networksmulti-scale, multi-modal and large-scale
- Neural recording technologies
- System integration for advancing neurotechnologies
- Motor learning and motor control
- M. Shanechi*, A. L. Orsborn* (equal contribution), H.G. Moorman*, S.
Gowda*, and J.M. Carmena (2017). Rapid control and feedback rates enhance
neuroprosthetic control. Nature Communications, 8:13825,
- A.L. Orsborn and B. Pesaran (2017) Parsing learning in networks using
brain-machine interfaces, Current Opinions in Neurobiology, 46:76-83, doi:
- M. Shanechi , A.L. Orsborn* (equal contribution), and J.M. Carmena
(2016). Robust brain-machine interface design using optimal feedback
control modeling and adaptive point process filtering. PLoS Computational
Biology 12(4):e1004730. doi:10.1371/journal.pcbi.10047
30 (F1000 recommended)
- 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 82, pp.
1380-1393. (journal cover article)
- 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, 20(4), pp. 468 – 477.
Postdoctoral Researcher, 2014-2018
Pesaran Lab, Center for Neural Science, New York University
University of California, Berkeley/University of California, San Francisco, Joint Graduate Program in Bioengineering, 2013
B.S. Engineering Physics, 2007
Case Western Reserve University