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.
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, doi:10.1038/ncomms13825
A.L. Orsborn and B. Pesaran (2017) Parsing learning in networks using brain-machine interfaces, Current Opinions in Neurobiology, 46:76-83, doi: 10.1016/j.conb.2017.08.002
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.1004730 (F1000 recommended)
A.L. Orsborn, K. So, S. Dangi, and J.M. Carmena (2013) Comparison of neural activity during closed-loop control of spike- or LFP-based brain-machine interfaces. Proceedings of the 6th International Conference IEEE EMBS Neural Engineering, San Diego, CA.
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 and J.M. Carmena (2013) Creating new functional circuits for action via brain-machine interfaces, Frontiers in Computational Neuroscience, 7:157, doi: 10.3389/fncom.2013.00157
S. Dangi*, A.L. Orsborn* (equal contribution), H.G. Moorman, and J.M. Carmena (2013) Design and analysis of closed-loop decoder adaptation algorithms for brain-machine interfaces. Neural Computation, 25(7), pp. 1693-1731.
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.