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. 2020 Jul 15:341:108719.
doi: 10.1016/j.jneumeth.2020.108719. Epub 2020 May 18.

Development of a combined, sequential real-time fMRI and fNIRS neurofeedback system to enhance motor learning after stroke

Affiliations

Development of a combined, sequential real-time fMRI and fNIRS neurofeedback system to enhance motor learning after stroke

Jake D Rieke et al. J Neurosci Methods. .

Abstract

Background: After stroke, wrist extension dyscoordination precludes functional arm/hand. We developed a more spatially precise brain signal for use in brain computer interface (BCI's) for stroke survivors.

New method: Combination BCI protocol of real-time functional magnetic resonance imaging (rt-fMRI) sequentially followed by functional near infrared spectroscopy (rt-fNIRS) neurofeedback, interleaved with motor learning sessions without neural feedback. Custom Matlab and Python code was developed to provide rt-fNIRS-based feedback to the chronic stroke survivor, system user.

Results: The user achieved a maximum of 71 % brain signal accuracy during rt-fNIRS neural training; progressive focus of brain activation across rt-fMRI neural training; increasing trend of brain signal amplitude during wrist extension across rt-fNIRS training; and clinically significant recovery of arm coordination and active wrist extension.

Comparison with existing methods: Neurorehabilitation, peripherally directed, shows limited efficacy, as do EEG-based BCIs, for motor recovery of moderate/severely impaired stroke survivors. EEG-based BCIs are based on electrophysiological signal; whereas, rt-fMRI and rt-fNIRS are based on neurovascular signal.

Conclusion: The system functioned well during user testing. Methods are detailed for others' use. The system user successfully engaged rt-fMRI and rt-fNIRS neurofeedback systems, modulated brain signal during rt-fMRI and rt-fNIRS training, according to volume of brain activation and intensity of signal, respectively, and clinically significantly improved limb coordination and active wrist extension. fNIRS use in this case demonstrates a feasible/practical BCI system for further study with regard to use in chronic stroke rehab, and fMRI worked in concept, but cost and some patient-use issues make it less feasible for clinical practice.

Keywords: BCI; BMI; Biofeedback; Coordination; MRI; NIRS; Neural feedback; Stroke; motor control.

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