Paralysis Research Today is a free monthly online journal that collates and summarizes the latest research about Paralysis, including details on treatment, diagnosis, facial paralysis, sleep paralysis.

Selecting the signals for a brain-machine interface.

Andersen RA, Musallam S, Pesaran B

Division of Biology, Mail Code 216-76, California Institute of Technology, Pasadena, California 91125, USA. andersen@vis.caltech.edu

Brain-machine interfaces are being developed to assist paralyzed patients by enabling them to operate machines with recordings of their own neural activity. Recent studies show that motor parameters, such as hand trajectory, and cognitive parameters, such as the goal and predicted value of an action, can be decoded from the recorded activity to provide control signals. Neural prosthetics that use simultaneously a variety of cognitive and motor signals can maximize the ability of patients to communicate and interact with the outside world. Although most studies have recorded electroencephalograms or spike activity, recent research shows that local field potentials (LFPs) offer a promising additional signal. The decode performances of LFPs and spike signals are comparable and, because LFP recordings are more long lasting, they might help to increase the lifetime of the prosthetics.

Published 7 December 2004 in Curr Opin Neurobiol, 14(6): 720-6.
Full-text of this article is available online (may require subscription).

© 2004-2008 Paralysis Research Today. All Rights Reserved.