Advances in neuroprosthetic learning and control

PLoS Biol. 2013;11(5):e1001561. doi: 10.1371/journal.pbio.1001561. Epub 2013 May 21.

Abstract

Significant progress has occurred in the field of brain-machine interfaces (BMI) since the first demonstrations with rodents, monkeys, and humans controlling different prosthetic devices directly with neural activity. This technology holds great potential to aid large numbers of people with neurological disorders. However, despite this initial enthusiasm and the plethora of available robotic technologies, existing neural interfaces cannot as yet master the control of prosthetic, paralyzed, or otherwise disabled limbs. Here I briefly discuss recent advances from our laboratory into the neural basis of BMIs that should lead to better prosthetic control and clinically viable solutions, as well as new insights into the neurobiology of action.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Artificial Intelligence*
  • Haplorhini
  • Humans
  • Neural Prostheses*
  • Robotics
  • User-Computer Interface*

Grants and funding

The Alfred P. Sloan Foundation, the Christopher and Dana Reeve Foundation, the National Science Foundation CAREER Award #0954243, and the Defense Advanced Research Projects Agency contract N66001-10-C-2008. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.