I have trained as an electrical engineer and as a systems neurobiologist. Over the past ten years I have investigated how motor cortices guide arm movements and how this neural activity can be used to control prosthetic arms and computer cursors. I now recognize that a major new research direction is imperative if we are to truly understand the neural control of movement in the ?real-world? and design neural prostheses for large numbers of people. The fundamental assumption which I call into question, and aim to address, is that cortical-motor activity is the same across behavioral contexts, contexts as different as sitting quietly in a dark room without moving ones eyes or head (conventional experimental setting) and actively moving around in a large space with lights, sounds and body posture constantly varying (the proposed ?real world? setting). We must begin conducting electrophysiological experiments in monkeys able to freely move around in large spaces, which will serve as an animal model for freely moving humans. This is a dramatically new and different direction, which is only now plausible due to tremendous advances in microelectronics technology and the major new technological and experimental paradigms proposed here. I proposed to build a new suite of recording, wireless telemetery and behavioral monitoring technology to enable this new brand of basic and applied neuroscience investigation. We will also conduct a definitive set of neurophysiological and neural prosthetic experiments, to highlight the power and broad applicability of this new paradigm in addition to documenting initial, and likely highly surprising, discoveries. If successful, I anticipate this new experimental paradigm and results to greatly change basic neuroscience investigations of motor control, applied neuroscience/neuroengineering aimed at designing robust and high-performance neural prostheses, and large patient populations whose quality of life will be dramatically improved by restoring lost motor function.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
NIH Director’s Pioneer Award (NDPA) (DP1)
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Special Emphasis Panel (ZGM1-NDPA-B (02))
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Quatrano, Louis A
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Stanford University
Engineering (All Types)
Schools of Engineering
United States
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Nuyujukian, Paul; Fan, Joline M; Kao, Jonathan C et al. (2015) A high-performance keyboard neural prosthesis enabled by task optimization. IEEE Trans Biomed Eng 62:21-9
Stavisky, Sergey D; Kao, Jonathan C; Nuyujukian, Paul et al. (2015) A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes. J Neural Eng 12:036009
Christie, Breanne P; Tat, Derek M; Irwin, Zachary T et al. (2015) Comparison of spike sorting and thresholding of voltage waveforms for intracortical brain-machine interface performance. J Neural Eng 12:016009
Ames, K Cora; Ryu, Stephen I; Shenoy, Krishna V (2014) Neural dynamics of reaching following incorrect or absent motor preparation. Neuron 81:438-51
Fan, Joline M; Nuyujukian, Paul; Kao, Jonathan C et al. (2014) Intention estimation in brain-machine interfaces. J Neural Eng 11:016004
Kaufman, Matthew T; Churchland, Mark M; Ryu, Stephen I et al. (2014) Cortical activity in the null space: permitting preparation without movement. Nat Neurosci 17:440-8
Ozden, Ilker; Wang, Jing; Lu, Yao et al. (2013) A coaxial optrode as multifunction write-read probe for optogenetic studies in non-human primates. J Neurosci Methods 219:142-54
Churchland, Mark M; Cunningham, John P; Kaufman, Matthew T et al. (2012) Neural population dynamics during reaching. Nature 487:51-6
Sussillo, David; Nuyujukian, Paul; Fan, Joline M et al. (2012) A recurrent neural network for closed-loop intracortical brain-machine interface decoders. J Neural Eng 9:026027
Gilja, Vikash; Nuyujukian, Paul; Chestek, Cindy A et al. (2012) A high-performance neural prosthesis enabled by control algorithm design. Nat Neurosci 15:1752-7

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