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This Article Full Text Full Text (PDF) All Versions of this Article: 579/3/603    most recent jphysiol.2006.127209v1 Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Donoghue, J. P. Articles by Hochberg, L. R. Search for Related Content PubMed PubMed Citation Articles by Donoghue, J. P. Articles by Hochberg, L. R. Related Collections Review articles

¹ Department of Neuroscience, Division of Engineering, Department of Computer Science, Brown University, Providence, RI 02912, USA

This review describes the rationale, early stage development, and initial human application of neural interface systems (NISs) for humans with paralysis. NISs are emerging medical devices designed to allow persons with paralysis to operate assistive technologies or to reanimate muscles based upon a command signal that is obtained directly from the brain. Such systems require the development of sensors to detect brain signals, decoders to transform neural activity signals into a useful command, and an interface for the user. We review initial pilot trial results of an NIS that is based on an intracortical microelectrode sensor that derives control signals from the motor cortex. We review recent findings showing, first, that neurons engaged by movement intentions persist in motor cortex years after injury or disease to the motor system, and second, that signals derived from motor cortex can be used by persons with paralysis to operate a range of devices. We suggest that, with further development, this form of NIS holds promise as a useful new neurotechnology for those with limited motor function or communication. We also discuss the additional potential for neural sensors to be used in the diagnosis and management of various neurological conditions and as a new way to learn about human brain function.

(Received 21 December 2006; accepted after revision 17 January 2007; first published online 25 January 2007)
Corresponding author J. P. Donoghue: Department of Neuroscience, Division of Engineering, Department of Computer Science, Brown University, Providence, RI 02912, USA. Email: john_donoghue{at}brown.edu

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