Abstract
Despite the established effectiveness of the brain-computer interface (BCI) therapy during stroke rehabilitation (Song et al., 2014a, 2015; Young et al., 2014a,b,c, 2015; Remsik et al., 2016), little is understood about the connections between motor network reorganization and functional motor improvements. The aim of this study was to investigate changes in the network reorganization of the motor cortex during BCI therapy. Graph theoretical approaches are used on resting-state functional magnetic resonance imaging (fMRI) data acquired from stroke patients to evaluate these changes. Correlations between changes in graph measurements and behavioral measurements were also examined. Right hemisphere chronic stroke patients (average time from stroke onset = 38.23 months, standard deviation (SD) = 46.27 months, n = 13, 6 males, 10 right-handed) with upper-extremity motor deficits received interventional rehabilitation therapy using a closed-loop neurofeedback BCI device. Eyes-closed resting-state fMRI (rs-fMRI) scans, along with T-1 weighted anatomical scans on 3.0T MRI scanners were collected from these patients at four test points. Immediate therapeutic effects were investigated by comparing pre and post-therapy results. Results displayed that th average clustering coefficient of the motor network increased significantly from pre to post-therapy. Furthermore, increased regional centrality of ipsilesional primary motor area (p = 0.02) and decreases in regional centrality of contralesional thalamus (p = 0.05), basal ganglia (p = 0.05 in betweenness centrality analysis and p = 0.03 for degree centrality), and dentate nucleus (p = 0.03) were observed (uncorrected). These findings suggest an overall trend toward significance in terms of involvement of these regions. Increased centrality of primary motor area may indicate increased efficiency within its interactive network as an effect of BCI therapy. Notably, changes in centrality of the bilateral cerebellum regions have strong correlations with both clinical variables [the Action Research Arm Test (ARAT), and the Nine-Hole Peg Test (9-HPT)]
Highlights
Eight lakhs Americans experience a stroke each year, a number that is predicted to rise by 22% by 2030 (Go et al, 2013)
Thirteen patients who suffer from persistent upper extremity motor impairment caused by ischemic or hemorrhagic stroke were enrolled for the brain-computer interface (BCI) therapy
This study demonstrates the effectiveness of rs-functional magnetic resonance imaging (fMRI) using graph theoretical methods to capture brain changes during the stroke recovery following rehabilitative therapy. resting-state fMRI (rs-fMRI) requires about 10 min for image acquisition without any exogenous task demands on the subject
Summary
Eight lakhs Americans experience a stroke each year, a number that is predicted to rise by 22% by 2030 (Go et al, 2013). The growing number of stroke survivors continue to struggle as their independence are notably diminished These survivors often suffer from persistent functional deficits, resulting in billions of dollars of economic costs each year (Towfighi and Saver, 2011). Kelly-Hayes et al (2003) shows that acquisition of a lasting motor impairment is one of the most prominent sources of such functional deficits, with up to 50% of survivors suffering from hemiparesis, and 26% requiring assistance with activities of daily living (ADLs) 6 months post-stroke. This expanding population of stroke survivors increases the demand for effective stroke rehabilitation therapies and mechanistic break-down of stroke recovery
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