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Title:

Neural correlates of learning in an electrocorticographic motor-imagery brain-computer interface

Author(s):

Blakely TM, Olson JD, Miller KJ, Rao RPN, and Ojemann JG

Year:

2014

Publication Info:

Brain-Computer Interfaces, 1(3-4):147-157

Abstract:

Human subjects can learn to control a one-dimensional electrocorticographic (ECoG) brain-computer interface (BCI) using modulation of primary motor (M1) high-gamma activity (signal power in the 75-200 Hz range). However, the stability and dynamics of the signals over the course of new BCI skill acquisition have not been investigated. In this study, we report 3 characteristic periods in evolution of the high-gamma control signal during BCI training: initial, low task accuracy with corresponding low power modulation in the gamma spectrum, followed by a second period of improved task accuracy with increasing average power separation between activity and rest, and a final period of high task accuracy with stable (or decreasing) power separation and decreasing trial-to-trial variance. These findings may have implications in the design and implementation of BCI control algorithms.

Link to Article:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4295512/

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