Paul Nuyujukian

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. doi request reprint Monkey models for brain-machine interfaces: the need for maintaining diversity
    Paul Nuyujukian
    Department of Bioengineering and Stanford Medical School, Stanford University, Stanford, CA 94305, USA
    Conf Proc IEEE Eng Med Biol Soc 2011:1301-5. 2011
  2. doi request reprint A brain machine interface control algorithm designed from a feedback control perspective
    Vikash Gilja
    Dept of Computer Science, Stanford University, Stanford, CA, USA
    Conf Proc IEEE Eng Med Biol Soc 2012:1318-22. 2012
  3. pmc Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex
    Cynthia A Chestek
    Department of Electrical Engineering, Stanford University, Stanford, CA, USA
    J Neural Eng 8:045005. 2011
  4. pmc A high-performance neural prosthesis enabled by control algorithm design
    Vikash Gilja
    Department of Computer Science, Stanford University, Stanford, California, USA
    Nat Neurosci 15:1752-7. 2012
  5. doi request reprint Neural prosthetic systems: current problems and future directions
    Cindy A Chestek
    Dept of Electrical Engineering, Stanford University, Stanford, CA, USA
    Conf Proc IEEE Eng Med Biol Soc 2009:3369-75. 2009
  6. pmc A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces
    John P Cunningham
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305 4075, USA
    J Neurophysiol 105:1932-49. 2011
  7. doi request reprint A framework for relating neural activity to freely moving behavior
    Justin D Foster
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
    Conf Proc IEEE Eng Med Biol Soc 2012:2736-9. 2012
  8. pmc A recurrent neural network for closed-loop intracortical brain-machine interface decoders
    David Sussillo
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305 9505, USA
    J Neural Eng 9:026027. 2012
  9. pmc Autonomous head-mounted electrophysiology systems for freely behaving primates
    Vikash Gilja
    Dept of Computer Science, Stanford University, Stanford, CA 94305, USA
    Curr Opin Neurobiol 20:676-86. 2010
  10. pmc Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces
    Julie Dethier
    Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
    J Neural Eng 10:036008. 2013

Collaborators

Detail Information

Publications11

  1. doi request reprint Monkey models for brain-machine interfaces: the need for maintaining diversity
    Paul Nuyujukian
    Department of Bioengineering and Stanford Medical School, Stanford University, Stanford, CA 94305, USA
    Conf Proc IEEE Eng Med Biol Soc 2011:1301-5. 2011
    ..Given the physiological diversity of neurological injury and disease, we suggest a need to maintain the current diversity of animal models and to explore additional alternatives, as each mimic different aspects of injury or disease...
  2. doi request reprint A brain machine interface control algorithm designed from a feedback control perspective
    Vikash Gilja
    Dept of Computer Science, Stanford University, Stanford, CA, USA
    Conf Proc IEEE Eng Med Biol Soc 2012:1318-22. 2012
    ....
  3. pmc Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex
    Cynthia A Chestek
    Department of Electrical Engineering, Stanford University, Stanford, CA, USA
    J Neural Eng 8:045005. 2011
    ..This suggests that neural prosthetic systems may provide high performance over multiple years in human clinical trials...
  4. pmc A high-performance neural prosthesis enabled by control algorithm design
    Vikash Gilja
    Department of Computer Science, Stanford University, Stanford, California, USA
    Nat Neurosci 15:1752-7. 2012
    ..Using this algorithm, we demonstrate repeatable high performance for years after implantation in two monkeys, thereby increasing the clinical viability of neural prostheses...
  5. doi request reprint Neural prosthetic systems: current problems and future directions
    Cindy A Chestek
    Dept of Electrical Engineering, Stanford University, Stanford, CA, USA
    Conf Proc IEEE Eng Med Biol Soc 2009:3369-75. 2009
    ..In all, this study suggests that research in cortically-controlled prosthetic systems may require reprioritization to achieve performance that is acceptable for a clinically viable human system...
  6. pmc A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces
    John P Cunningham
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305 4075, USA
    J Neurophysiol 105:1932-49. 2011
    ..These findings illustrate the type of discovery made possible by the OPS, and so we hypothesize that this novel testing approach will help in the design of prosthetic systems that will translate well to human patients...
  7. doi request reprint A framework for relating neural activity to freely moving behavior
    Justin D Foster
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
    Conf Proc IEEE Eng Med Biol Soc 2012:2736-9. 2012
    ..Such encouraging results hint at potential utility of the freely-moving experimental paradigm...
  8. pmc A recurrent neural network for closed-loop intracortical brain-machine interface decoders
    David Sussillo
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305 9505, USA
    J Neural Eng 9:026027. 2012
    ..Taken together, these results suggest that RNNs in general, and the FORCE decoder in particular, are powerful tools for BMI decoder applications...
  9. pmc Autonomous head-mounted electrophysiology systems for freely behaving primates
    Vikash Gilja
    Dept of Computer Science, Stanford University, Stanford, CA 94305, USA
    Curr Opin Neurobiol 20:676-86. 2010
    ..Moving forward, this class of technologies, along with advances in neural signal processing and behavioral monitoring, have the potential to dramatically expand the scope and scale of electrophysiological studies...
  10. pmc Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces
    Julie Dethier
    Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
    J Neural Eng 10:036008. 2013
    ..In particular, intracortical prostheses must satisfy stringent power dissipation constraints so as not to damage cortex...
  11. doi request reprint HermesC: low-power wireless neural recording system for freely moving primates
    Cynthia A Chestek
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
    IEEE Trans Neural Syst Rehabil Eng 17:330-8. 2009
    ..The HermesC-INI3 system was used to record and telemeter one channel of broadband neural data at 15.7 kSps from a monkey performing routine daily activities in the home cage...