Differentiating closed-loop cortical intention from rest: building an asynchronous electrocorticographic BCI

Objective. Recent experiments have shown that electrocorticography (ECoG) can provide robust control signals for a brain-computer interface (BCI). Strategies that attempt to adapt a BCI control algorithm by learning from past trials often assume that the subject is attending to each training trial....

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Bibliographic Details
Published in:Journal of neural engineering 2013-08, Vol.10 (4), p.046001-046001
Main Authors: Williams, Jordan J, Rouse, Adam G, Thongpang, Sanitta, Williams, Justin C, Moran, Daniel W
Format: Article
Language:English
Subjects:
Active control
Algorithms
Animals
Attention - physiology
BCI ECoG
Biofeedback, Psychology - instrumentation
Biofeedback, Psychology - physiology
Brain-Computer Interfaces
Control theory
Devices
Electrocardiography - instrumentation
Electrocardiography - methods
Electrodes, Implanted
Human-computer interface
Intention
Macaca mulatta
Modulation
Movement
Pattern Recognition, Automated - methods
Primates
Reproducibility of Results
Rest
Sensitivity and Specificity
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Summary:Objective. Recent experiments have shown that electrocorticography (ECoG) can provide robust control signals for a brain-computer interface (BCI). Strategies that attempt to adapt a BCI control algorithm by learning from past trials often assume that the subject is attending to each training trial. Likewise, automatic disabling of movement control would be desirable during resting periods when random brain fluctuations might cause unintended movements of a device. To this end, our goal was to identify ECoG differences that arise between periods of active BCI use and rest. Approach. We examined spectral differences in multi-channel, epidural micro-ECoG signals recorded from non-human primates when rest periods were interleaved between blocks of an active BCI control task. Main Results. Post-hoc analyses demonstrated that these states can be decoded accurately on both a trial-by-trial and real-time basis, and this discriminability remains robust over a period of weeks. In addition, high gamma frequencies showed greater modulation with desired movement direction, while lower frequency components demonstrated greater amplitude differences between task and rest periods, suggesting possible specialized BCI roles for these frequencies. Significance. The results presented here provide valuable insight into the neurophysiology of BCI control as well as important considerations toward the design of an asynchronous BCI system.
ISSN:1741-2560
1741-2552
DOI:10.1088/1741-2560/10/4/046001