Cognitive neural prosthetics.

Cognitive neural prosthetics. Andersen, R. A., Burdick, J. W., Musallam, S., Pesaran, B., & Cham, J. G. Trends Cogn Sci, 8(11):486-93, 2004.
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Research on neural prosthetics has focused largely on using activity related to hand trajectories recorded from motor cortical areas. An interesting question revolves around what other signals might be read out from the brain and used for neural prosthetic applications. Recent studies indicate that goals and expected value are among the high-level cognitive signals that can be used and will potentially enhance the ability of paralyzed patients to communicate with the outside world. Other new findings show that local field potentials provide an excellent source of information about the cognitive state of the subject and are much easier to record and maintain than spike activity. Finally, new movable probe technologies will enable recording electrodes to seek out automatically the best signals for decoding cognitive variables.

@Article{Andersen2004,
  author   = {R. A. Andersen and J. W. Burdick and S. Musallam and B. Pesaran and J. G. Cham},
  journal  = {Trends Cogn Sci},
  title    = {Cognitive neural prosthetics.},
  year     = {2004},
  number   = {11},
  pages    = {486-93},
  volume   = {8},
  abstract = {Research on neural prosthetics has focused largely on using activity
	related to hand trajectories recorded from motor cortical areas.
	An interesting question revolves around what other signals might
	be read out from the brain and used for neural prosthetic applications.
	Recent studies indicate that goals and expected value are among the
	high-level cognitive signals that can be used and will potentially
	enhance the ability of paralyzed patients to communicate with the
	outside world. Other new findings show that local field potentials
	provide an excellent source of information about the cognitive state
	of the subject and are much easier to record and maintain than spike
	activity. Finally, new movable probe technologies will enable recording
	electrodes to seek out automatically the best signals for decoding
	cognitive variables.},
  doi      = {10.1016/j.tics.2004.09.009},
  keywords = {Action Potentials, Animals, Brain, Cognition, Computer-Assisted, Electrodes, Haplorhini, Humans, Implanted, Language, Memory, Nerve Net, Neurons, Non-P.H.S., Non-U.S. Gov't, P.H.S., Paralysis, Prostheses and Implants, Research Support, Robotics, Signal Processing, U.S. Gov't, User-Computer Interface, 15491902},
}

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