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Neuroscience Journal
Volume 2013, Article ID 594624, 12 pages
Clinical Study

Detecting Silent Vocalizations in a Locked-In Subject

1Georgia Institute of Technology, Atlanta, GA 30313, USA
2Neural Signals Inc., Duluth, GA 30096, USA

Received 29 January 2013; Revised 7 August 2013; Accepted 3 September 2013

Academic Editor: Stephanie A. Kolakowsky-Hayner

Copyright © 2013 Elina Sarmah and Philip Kennedy. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Problem Addressed. Decoding of silent vocalization would be enhanced by detecting vocalization onset. This is necessary in order to improve decoding of neural firings and thus synthesize near conversational speech in locked-in subjects implanted with brain computer interfacing devices. Methodology. Cortical recordings were obtained during attempts at inner speech in a mute and paralyzed subject (ER) implanted with a recording electrode to detect and analyze lower beta band peaks meeting the criterion of a minimum 0.2% increase in the power spectrum density (PSD). To provide supporting data, three speaking subjects were used in a similar testing paradigm using EEG signals recorded over the speech area. Results. Conspicuous lower beta band peaks were identified around the time of assumed speech onset. The correlations between single unit firings, recorded at the same time as the continuous neural signals, were found to increase after the lower beta band peaks as compared to before the peaks. Studies in the nonparalyzed control individuals suggested that the lower beta band peaks were related to the movement of the articulators of speech (tongue, jaw, and lips), not to higher order speech processes. Significance and Potential Impact. The results indicate that the onset of silent and overt speech is associated with a sharp peak in lower beta band activity—an important step in the development of a speech prosthesis. This raises the possibility of using these peaks in online applications to assist decoding paradigms being developed to decode speech from neural signal recordings in mute humans.