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BCI Use and Its Relation to Adaptation in Cortical Networks

Authors :
Jeremiah D. Wander
Kurt E. Weaver
Jeffrey G. Ojemann
Kaitlyn Casimo
Source :
IEEE Transactions on Neural Systems and Rehabilitation Engineering. 25:1697-1704
Publication Year :
2017
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2017.

Abstract

Brain-computer interfaces (BCIs) carry great potential in the treatment of motor impairments. As a new motor output, BCIs interface with the native motor system, but acquisition of BCI proficiency requires a degree of learning to integrate this new function. In this review, we discuss how BCI designs often take advantage of the brain's motor system infrastructure as sources of command signals. We highlight a growing body of literature examining how this approach leads to changes in activity across cortex, including beyond motor regions, as a result of learning the new skill of BCI control. We discuss the previous research identifying patterns of neural activity associated with BCI skill acquisition and use that closely resembles those associated with learning traditional native motor tasks. We then discuss recent work in animals probing changes in connectivity of the BCI control site, which were linked to BCI skill acquisition, and use this as a foundation for our original work in humans. We present our novel work showing changes in resting state connectivity across cortex following the BCI learning process. We find substantial, heterogeneous changes in connectivity across regions and frequencies, including interactions that do not involve the BCI control site. We conclude from our review and original work that BCI skill acquisition may potentially lead to significant changes in evoked and resting state connectivity across multiple cortical regions. We recommend that future studies of BCIs look beyond motor regions to fully describe the cortical networks involved and long-term adaptations resulting from BCI skill acquisition.

Details

ISSN :
15580210 and 15344320
Volume :
25
Database :
OpenAIRE
Journal :
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Accession number :
edsair.doi.dedup.....6865beee83618315c997b88e4734dced
Full Text :
https://doi.org/10.1109/tnsre.2017.2681963