TY - JOUR
T1 - Selecting the signals for a brain-machine interface
AU - Andersen, Richard A.
AU - Musallam, Sam
AU - Pesaran, Bijan
N1 - Funding Information:
We thank K Pejsa, L Martel, V Shcherbatyuk and T Yao for the support that has made this work possible, and H Scherberger, B Corneil, B Greger, J Burdick, I Fineman, D Meeker, D Rizzuto, G Mulliken, R Battacharyya H Glidden, M Nelson and K Bernheim for stimulating discussion. We thank the National Eye Institute, the Defense Advanced Research Projects Agency, the James G. Boswell Foundation, the Office of Naval Research, the Sloan-Swartz Center for Theoretical Neurobiology at Caltech, the Christopher Reeve Paralysis Foundation and the Burroughs–Welcome Fund for their generous support.
Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2004/12
Y1 - 2004/12
N2 - 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.
AB - 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.
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U2 - 10.1016/j.conb.2004.10.005
DO - 10.1016/j.conb.2004.10.005
M3 - Review article
C2 - 15582374
AN - SCOPUS:9644270644
SN - 0959-4388
VL - 14
SP - 720
EP - 726
JO - Current Opinion in Neurobiology
JF - Current Opinion in Neurobiology
IS - 6
ER -