Faculty Collaboration Database

Differentiating closed-loop cortical intention from rest: building an asynchronous electrocorticographic BCI. J Neural Eng 2013 Aug;10(4):046001

Date

05/30/2013

Pubmed ID

23715295

DOI

10.1088/1741-2560/10/4/046001

Scopus ID

2-s2.0-84883151862 (requires institutional sign-in at Scopus site)   43 Citations

Abstract

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.

Author List

Williams JJ, Rouse AG, Thongpang S, Williams JC, Moran DW

Author

Jordan J. Williams MD, PhD Assistant Professor in the Biomedical Engineering department at Marquette University

MESH terms used to index this publication - Major topics in bold

Algorithms
Animals
Attention
Biofeedback, Psychology
Brain-Computer Interfaces
Electrocardiography
Electrodes, Implanted
Intention
Macaca mulatta
Pattern Recognition, Automated
Reproducibility of Results
Sensitivity and Specificity