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

PE Yoo; TJ Oxley; SE John; NL Opie; RJ Ordidge; TJ O’Brien; MA Hagan; YT Wong; BA Moffat

Journal article

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

PE Yoo, TJ Oxley, SE John, NL Opie, RJ Ordidge, TJ O’Brien, MA Hagan, YT Wong, BA Moffat

Scientific Reports | NATURE PORTFOLIO | Published : 2018

DOI: 10.1038/s41598-018-33839-4

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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 wit..

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University of Melbourne Researchers

Thomas Oxley Author

Sam John Author

Nicholas Opie Author

Bradford Moffat Author

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Awarded by Defense Advanced Research Projects Agency

Funding Acknowledgements

The research was supported by US Defense Advanced Research Projects Agency (DARPA) Microsystems Technology Office contract N66001-12-1-4045; National Health and Medical Research Council of Australia (NHMRC) Project Grant APP1062532. P.E.Y. acknowledges the Faculty of Medicine, University of Melbourne for the Leslie Eric Paddle Scholarship in Neurology and the Melbourne Neuroscience Institute for the Strategic Australian Postgraduate Award. We acknowledge the facilities, and the scientific and technical assistance of the Australian National Imaging Facility at the Melbourne Brain Centre Imaging Unit.