Feasibility of identifying the ideal locations for motor intention decoding using unimodal and multimodal classification at 7T-fMRI.

ABSTRACT: Invasive Brain-Computer Interfaces (BCIs) require surgeries with high health-risks. The risk-to-benefit ratio of the procedure could potentially be improved by pre-surgically identifying the ideal locations for mental strategy classification. We recorded high-spatiotemporal resolution blood-oxygenation-level-dependent (BOLD) signals using functional MRI at 7 Tesla in eleven healthy participants during two motor imagery tasks. BCI diagnostic task isolated the intent to imagine movements, while BCI simulation task simulated the neural states that may be yielded in a real-life BCI-operation scenario. Imagination of movements were classified from the BOLD signals in sub-regions of activation within a single or multiple dorsal motor network regions. Then, the participant's decoding performance

SUBMITTER: Yoo PE 

PROVIDER: S-EPMC6197258 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature