Brain-Computer Interface Training after Stroke Affects Patterns of Brain-Behavior Relationships in Corticospinal Motor Fibers

Brittany M Young; Julie M Stamm; Jie Song; Alexander B Remsik; Veena A Nair; Mitchell E Tyler; Dorothy F Edwards; Kristin Caldera; Justin A Sattin; Justin C Williams; Vivek Prabhakaran

doi:10.3389/fnhum.2016.00457

Brain-Computer Interface Training after Stroke Affects Patterns of Brain-Behavior Relationships in Corticospinal Motor Fibers

Front Hum Neurosci. 2016 Sep 16:10:457. doi: 10.3389/fnhum.2016.00457. eCollection 2016.

Authors

Affiliations

¹ Department of Radiology, University of Wisconsin Hospital and Clinics, University of Wisconsin - Madison, MadisonWI, USA; Medical Scientist Training Program, University of Wisconsin - Madison, MadisonWI, USA; Neuroscience Training Program, University of Wisconsin - Madison, MadisonWI, USA.
² Department of Radiology, University of Wisconsin Hospital and Clinics, University of Wisconsin - Madison, Madison WI, USA.
³ Department of Radiology, University of Wisconsin Hospital and Clinics, University of Wisconsin - Madison, MadisonWI, USA; Department of Biomedical Engineering, University of Wisconsin - Madison, MadisonWI, USA.
⁴ Department of Biomedical Engineering, University of Wisconsin - Madison, Madison WI, USA.
⁵ Department of Kinesiology and Department of Medicine, University of Wisconsin - Madison, MadisonWI, USA; Department of Neurology, University of Wisconsin - Madison, MadisonWI, USA.
⁶ Department of Orthopedics and Rehabilitation, University of Wisconsin - Madison, Madison WI, USA.
⁷ Department of Neurology, University of Wisconsin - Madison, Madison WI, USA.
⁸ Neuroscience Training Program, University of Wisconsin - Madison, MadisonWI, USA; Department of Biomedical Engineering, University of Wisconsin - Madison, MadisonWI, USA; Department of Neurosurgery, University of Wisconsin - Madison, MadisonWI, USA.
⁹ Department of Radiology, University of Wisconsin Hospital and Clinics, University of Wisconsin - Madison, MadisonWI, USA; Medical Scientist Training Program, University of Wisconsin - Madison, MadisonWI, USA; Neuroscience Training Program, University of Wisconsin - Madison, MadisonWI, USA; Department of Orthopedics and Rehabilitation, University of Wisconsin - Madison, MadisonWI, USA; Department of Psychology and Department of Psychiatry, University of Wisconsin - Madison, MadisonWI, USA.

Abstract

Background: Brain-computer interface (BCI) devices are being investigated for their application in stroke rehabilitation, but little is known about how structural changes in the motor system relate to behavioral measures with the use of these systems. Objective: This study examined relationships among diffusion tensor imaging (DTI)-derived metrics and with behavioral changes in stroke patients with and without BCI training. Methods: Stroke patients (n = 19) with upper extremity motor impairment were assessed using Stroke Impact Scale (SIS), Action Research Arm Test (ARAT), Nine-Hole Peg Test (9-HPT), and DTI scans. Ten subjects completed four assessments over a control period during which no training was administered. Seventeen subjects, including eight who completed the control period, completed four assessments over an experimental period during which subjects received interventional BCI training. Fractional anisotropy (FA) values were extracted from each corticospinal tract (CST) and transcallosal motor fibers for each scan. Results: No significant group by time interactions were identified at the group level in DTI or behavioral measures. During the control period, increases in contralesional CST FA and in asymmetric FA (aFA) correlated with poorer scores on SIS and 9-HPT. During the experimental period (with BCI training), increases in contralesional CST FA were correlated with improvements in 9-HPT while increases in aFA correlated with improvements in ARAT but with worsening 9-HPT performance; changes in transcallosal motor fibers positively correlated with those in the contralesional CST. All correlations p < 0.05 corrected. Conclusion: These findings suggest that the integrity of the contralesional CST may be used to track individual behavioral changes observed with BCI training after stroke.

Keywords: brain–computer interface; diffusion tensor imaging; neuroplasticity; rehabilitation; stroke; upper extremity.

Abstract

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