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J Neural Eng. 2011 Jun;8(3):036004. doi: 10.1088/1741-2560/8/3/036004. Epub 2011 Apr 7.

Using the electrocorticographic speech network to control a brain-computer interface in humans.

Author information

1
Department of Biomedical Engineering, Washington University in St. Louis, Campus Box 8057, 660 South Euclid, St Louis, MO 63130, USA. leuthardte@wudosis.wustl.edu

Abstract

Electrocorticography (ECoG) has emerged as a new signal platform for brain-computer interface (BCI) systems. Classically, the cortical physiology that has been commonly investigated and utilized for device control in humans has been brain signals from the sensorimotor cortex. Hence, it was unknown whether other neurophysiological substrates, such as the speech network, could be used to further improve on or complement existing motor-based control paradigms. We demonstrate here for the first time that ECoG signals associated with different overt and imagined phoneme articulation can enable invasively monitored human patients to control a one-dimensional computer cursor rapidly and accurately. This phonetic content was distinguishable within higher gamma frequency oscillations and enabled users to achieve final target accuracies between 68% and 91% within 15 min. Additionally, one of the patients achieved robust control using recordings from a microarray consisting of 1 mm spaced microwires. These findings suggest that the cortical network associated with speech could provide an additional cognitive and physiologic substrate for BCI operation and that these signals can be acquired from a cortical array that is small and minimally invasive.

PMID:
21471638
PMCID:
PMC3701859
DOI:
10.1088/1741-2560/8/3/036004
[Indexed for MEDLINE]
Free PMC Article

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