We have located links that may give you full text access.
COMPARATIVE STUDY
JOURNAL ARTICLE
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
RESEARCH SUPPORT, U.S. GOV'T, NON-P.H.S.
Decoding spoken words using local field potentials recorded from the cortical surface.
Journal of Neural Engineering 2010 October
Pathological conditions such as amyotrophic lateral sclerosis or damage to the brainstem can leave patients severely paralyzed but fully aware, in a condition known as 'locked-in syndrome'. Communication in this state is often reduced to selecting individual letters or words by arduous residual movements. More intuitive and rapid communication may be restored by directly interfacing with language areas of the cerebral cortex. We used a grid of closely spaced, nonpenetrating micro-electrodes to record local field potentials (LFPs) from the surface of face motor cortex and Wernicke's area. From these LFPs we were successful in classifying a small set of words on a trial-by-trial basis at levels well above chance. We found that the pattern of electrodes with the highest accuracy changed for each word, which supports the idea that closely spaced micro-electrodes are capable of capturing neural signals from independent neural processing assemblies. These results further support using cortical surface potentials (electrocorticography) in brain-computer interfaces. These results also show that LFPs recorded from the cortical surface (micro-electrocorticography) of language areas can be used to classify speech-related cortical rhythms and potentially restore communication to locked-in patients.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app