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      Brain-Computer Interface Training With Functional Electrical Stimulation: Facilitating Changes in Interhemispheric Functional Connectivity and Motor Outcomes Post-stroke

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          Abstract

          While most survivors of stroke experience some spontaneous recovery and receive treatment in the subacute setting, they are often left with persistent impairments in upper limb sensorimotor function which impact autonomy in daily life. Brain-Computer Interface (BCI) technology has shown promise as a form of rehabilitation that can facilitate motor recovery after stroke, however, we have a limited understanding of the changes in functional connectivity and behavioral outcomes associated with its use. Here, we investigate the effects of EEG-based BCI intervention with functional electrical stimulation (FES) on resting-state functional connectivity (rsFC) and motor outcomes in stroke recovery. 23 patients post-stroke with upper limb motor impairment completed BCI intervention with FES. Resting-state functional magnetic resonance imaging (rs-fMRI) scans and behavioral data were collected prior to intervention, post- and 1-month post-intervention. Changes in rsFC within the motor network and behavioral measures were investigated to identify brain-behavior correlations. At the group-level, there were significant increases in interhemispheric and network rsFC in the motor network after BCI intervention, and patients significantly improved on the Action Research Arm Test (ARAT) and SIS domains. Notably, changes in interhemispheric rsFC from pre- to both post- and 1 month post-intervention correlated with behavioral improvements across several motor-related domains. These findings suggest that BCI intervention with FES can facilitate interhemispheric connectivity changes and upper limb motor recovery in patients after stroke.

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          Most cited references63

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              Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

              An MRI time course of 512 echo-planar images (EPI) in resting human brain obtained every 250 ms reveals fluctuations in signal intensity in each pixel that have a physiologic origin. Regions of the sensorimotor cortex that were activated secondary to hand movement were identified using functional MRI methodology (FMRI). Time courses of low frequency (< 0.1 Hz) fluctuations in resting brain were observed to have a high degree of temporal correlation (P < 10(-3)) within these regions and also with time courses in several other regions that can be associated with motor function. It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                27 September 2021
                2021
                : 15
                : 670953
                Affiliations
                [1] 1Department of Biomedical Engineering, University of Wisconsin-Madison , Madison, WI, United States
                [2] 2Department of Radiology, University of Wisconsin-Madison , Madison, WI, United States
                Author notes

                Edited by: Christoph Guger, g.tec Medical Engineering GmbH, Austria

                Reviewed by: Pavel Bobrov, Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences (RAS), Russia; Takashi Hanakawa, Kyoto University, Japan

                *Correspondence: Anita M. Sinha, amsinha@ 123456wisc.edu

                This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2021.670953
                8503522
                34646112
                7e339180-5ae8-4272-a022-e890392043d8
                Copyright © 2021 Sinha, Nair and Prabhakaran.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 February 2021
                : 30 August 2021
                Page count
                Figures: 3, Tables: 4, Equations: 0, References: 63, Pages: 13, Words: 10907
                Funding
                Funded by: National Institutes of Health, doi 10.13039/100000002;
                Award ID: 1R01NS105646-01A1
                Categories
                Neuroscience
                Original Research

                Neurosciences
                brain-computer interface,stroke,upper extremity,resting-state fmri,neurorehabilitation,motor recovery

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