Think to move

A neuromagnetic brain-computer interface (BCI) system for chronic stroke

Ethan Buch, Cornelia Weber, Leonardo G. Cohen, Christoph Braun, Michael A. Dimyan, Tyler Ard, Jurgen Mellinger, Andrea Caria, Surjo Soekadar, Alissa Fourkas, Niels Birbaumer

Research output: Contribution to journalArticle

361 Citations (Scopus)

Abstract

BACKGROUND AND PURPOSE - Stroke is a leading cause of long-term motor disability among adults. Present rehabilitative interventions are largely unsuccessful in improving the most severe cases of motor impairment, particularly in relation to hand function. Here we tested the hypothesis that patients experiencing hand plegia as a result of a single, unilateral subcortical, cortical or mixed stroke occurring at least 1 year previously, could be trained to operate a mechanical hand orthosis through a brain-computer interface (BCI). METHODS - Eight patients with chronic hand plegia resulting from stroke (residual finger extension function rated on the Medical Research Council scale=0/5) were recruited from the Stroke Neurorehabilitation Clinic, Human Cortical Physiology Section of the National Institute for Neurological Disorders and Stroke (NINDS) (n=5) and the Clinic of Neurology of the University of Tübingen (n=3). Diagnostic MRIs revealed single, unilateral subcortical, cortical or mixed lesions in all patients. A magnetoencephalography-based BCI system was used for this study. Patients participated in between 13 to 22 training sessions geared to volitionally modulate μ rhythm amplitude originating in sensorimotor areas of the cortex, which in turn raised or lowered a screen cursor in the direction of a target displayed on the screen through the BCI interface. Performance feedback was provided visually in real-time. Successful trials (in which the cursor made contact with the target) resulted in opening/closing of an orthosis attached to the paralyzed hand. RESULTS - Training resulted in successful BCI control in 6 of 8 patients. This control was associated with increased range and specificity of μ rhythm modulation as recorded from sensors overlying central ipsilesional (4 patients) or contralesional (2 patients) regions of the array. Clinical scales used to rate hand function showed no significant improvement after training. CONCLUSIONS - These results suggest that volitional control of neuromagnetic activity features recorded over central scalp regions can be achieved with BCI training after stroke, and used to control grasping actions through a mechanical hand orthosis.

Original languageEnglish
Pages (from-to)910-917
Number of pages8
JournalStroke
Volume39
Issue number3
DOIs
Publication statusPublished - Mar 2008

Fingerprint

Brain-Computer Interfaces
Computer Systems
Hand
Stroke
Orthotic Devices
Paralysis
National Institute of Neurological Disorders and Stroke
Magnetoencephalography
Neurology
Scalp
Fingers
Biomedical Research

Keywords

  • Brain-computer interface
  • MEG
  • Motor
  • Plasticity
  • Stroke

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Neuroscience(all)
  • Medicine(all)

Cite this

Buch, E., Weber, C., Cohen, L. G., Braun, C., Dimyan, M. A., Ard, T., ... Birbaumer, N. (2008). Think to move: A neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke, 39(3), 910-917. https://doi.org/10.1161/STROKEAHA.107.505313

Think to move : A neuromagnetic brain-computer interface (BCI) system for chronic stroke. / Buch, Ethan; Weber, Cornelia; Cohen, Leonardo G.; Braun, Christoph; Dimyan, Michael A.; Ard, Tyler; Mellinger, Jurgen; Caria, Andrea; Soekadar, Surjo; Fourkas, Alissa; Birbaumer, Niels.

In: Stroke, Vol. 39, No. 3, 03.2008, p. 910-917.

Research output: Contribution to journalArticle

Buch, E, Weber, C, Cohen, LG, Braun, C, Dimyan, MA, Ard, T, Mellinger, J, Caria, A, Soekadar, S, Fourkas, A & Birbaumer, N 2008, 'Think to move: A neuromagnetic brain-computer interface (BCI) system for chronic stroke', Stroke, vol. 39, no. 3, pp. 910-917. https://doi.org/10.1161/STROKEAHA.107.505313
Buch, Ethan ; Weber, Cornelia ; Cohen, Leonardo G. ; Braun, Christoph ; Dimyan, Michael A. ; Ard, Tyler ; Mellinger, Jurgen ; Caria, Andrea ; Soekadar, Surjo ; Fourkas, Alissa ; Birbaumer, Niels. / Think to move : A neuromagnetic brain-computer interface (BCI) system for chronic stroke. In: Stroke. 2008 ; Vol. 39, No. 3. pp. 910-917.
@article{85c802e33b4347da8467c4bc992e5d4e,
title = "Think to move: A neuromagnetic brain-computer interface (BCI) system for chronic stroke",
abstract = "BACKGROUND AND PURPOSE - Stroke is a leading cause of long-term motor disability among adults. Present rehabilitative interventions are largely unsuccessful in improving the most severe cases of motor impairment, particularly in relation to hand function. Here we tested the hypothesis that patients experiencing hand plegia as a result of a single, unilateral subcortical, cortical or mixed stroke occurring at least 1 year previously, could be trained to operate a mechanical hand orthosis through a brain-computer interface (BCI). METHODS - Eight patients with chronic hand plegia resulting from stroke (residual finger extension function rated on the Medical Research Council scale=0/5) were recruited from the Stroke Neurorehabilitation Clinic, Human Cortical Physiology Section of the National Institute for Neurological Disorders and Stroke (NINDS) (n=5) and the Clinic of Neurology of the University of T{\"u}bingen (n=3). Diagnostic MRIs revealed single, unilateral subcortical, cortical or mixed lesions in all patients. A magnetoencephalography-based BCI system was used for this study. Patients participated in between 13 to 22 training sessions geared to volitionally modulate μ rhythm amplitude originating in sensorimotor areas of the cortex, which in turn raised or lowered a screen cursor in the direction of a target displayed on the screen through the BCI interface. Performance feedback was provided visually in real-time. Successful trials (in which the cursor made contact with the target) resulted in opening/closing of an orthosis attached to the paralyzed hand. RESULTS - Training resulted in successful BCI control in 6 of 8 patients. This control was associated with increased range and specificity of μ rhythm modulation as recorded from sensors overlying central ipsilesional (4 patients) or contralesional (2 patients) regions of the array. Clinical scales used to rate hand function showed no significant improvement after training. CONCLUSIONS - These results suggest that volitional control of neuromagnetic activity features recorded over central scalp regions can be achieved with BCI training after stroke, and used to control grasping actions through a mechanical hand orthosis.",
keywords = "Brain-computer interface, MEG, Motor, Plasticity, Stroke",
author = "Ethan Buch and Cornelia Weber and Cohen, {Leonardo G.} and Christoph Braun and Dimyan, {Michael A.} and Tyler Ard and Jurgen Mellinger and Andrea Caria and Surjo Soekadar and Alissa Fourkas and Niels Birbaumer",
year = "2008",
month = "3",
doi = "10.1161/STROKEAHA.107.505313",
language = "English",
volume = "39",
pages = "910--917",
journal = "Stroke",
issn = "0039-2499",
publisher = "Lippincott Williams and Wilkins",
number = "3",

}

TY - JOUR

T1 - Think to move

T2 - A neuromagnetic brain-computer interface (BCI) system for chronic stroke

AU - Buch, Ethan

AU - Weber, Cornelia

AU - Cohen, Leonardo G.

AU - Braun, Christoph

AU - Dimyan, Michael A.

AU - Ard, Tyler

AU - Mellinger, Jurgen

AU - Caria, Andrea

AU - Soekadar, Surjo

AU - Fourkas, Alissa

AU - Birbaumer, Niels

PY - 2008/3

Y1 - 2008/3

N2 - BACKGROUND AND PURPOSE - Stroke is a leading cause of long-term motor disability among adults. Present rehabilitative interventions are largely unsuccessful in improving the most severe cases of motor impairment, particularly in relation to hand function. Here we tested the hypothesis that patients experiencing hand plegia as a result of a single, unilateral subcortical, cortical or mixed stroke occurring at least 1 year previously, could be trained to operate a mechanical hand orthosis through a brain-computer interface (BCI). METHODS - Eight patients with chronic hand plegia resulting from stroke (residual finger extension function rated on the Medical Research Council scale=0/5) were recruited from the Stroke Neurorehabilitation Clinic, Human Cortical Physiology Section of the National Institute for Neurological Disorders and Stroke (NINDS) (n=5) and the Clinic of Neurology of the University of Tübingen (n=3). Diagnostic MRIs revealed single, unilateral subcortical, cortical or mixed lesions in all patients. A magnetoencephalography-based BCI system was used for this study. Patients participated in between 13 to 22 training sessions geared to volitionally modulate μ rhythm amplitude originating in sensorimotor areas of the cortex, which in turn raised or lowered a screen cursor in the direction of a target displayed on the screen through the BCI interface. Performance feedback was provided visually in real-time. Successful trials (in which the cursor made contact with the target) resulted in opening/closing of an orthosis attached to the paralyzed hand. RESULTS - Training resulted in successful BCI control in 6 of 8 patients. This control was associated with increased range and specificity of μ rhythm modulation as recorded from sensors overlying central ipsilesional (4 patients) or contralesional (2 patients) regions of the array. Clinical scales used to rate hand function showed no significant improvement after training. CONCLUSIONS - These results suggest that volitional control of neuromagnetic activity features recorded over central scalp regions can be achieved with BCI training after stroke, and used to control grasping actions through a mechanical hand orthosis.

AB - BACKGROUND AND PURPOSE - Stroke is a leading cause of long-term motor disability among adults. Present rehabilitative interventions are largely unsuccessful in improving the most severe cases of motor impairment, particularly in relation to hand function. Here we tested the hypothesis that patients experiencing hand plegia as a result of a single, unilateral subcortical, cortical or mixed stroke occurring at least 1 year previously, could be trained to operate a mechanical hand orthosis through a brain-computer interface (BCI). METHODS - Eight patients with chronic hand plegia resulting from stroke (residual finger extension function rated on the Medical Research Council scale=0/5) were recruited from the Stroke Neurorehabilitation Clinic, Human Cortical Physiology Section of the National Institute for Neurological Disorders and Stroke (NINDS) (n=5) and the Clinic of Neurology of the University of Tübingen (n=3). Diagnostic MRIs revealed single, unilateral subcortical, cortical or mixed lesions in all patients. A magnetoencephalography-based BCI system was used for this study. Patients participated in between 13 to 22 training sessions geared to volitionally modulate μ rhythm amplitude originating in sensorimotor areas of the cortex, which in turn raised or lowered a screen cursor in the direction of a target displayed on the screen through the BCI interface. Performance feedback was provided visually in real-time. Successful trials (in which the cursor made contact with the target) resulted in opening/closing of an orthosis attached to the paralyzed hand. RESULTS - Training resulted in successful BCI control in 6 of 8 patients. This control was associated with increased range and specificity of μ rhythm modulation as recorded from sensors overlying central ipsilesional (4 patients) or contralesional (2 patients) regions of the array. Clinical scales used to rate hand function showed no significant improvement after training. CONCLUSIONS - These results suggest that volitional control of neuromagnetic activity features recorded over central scalp regions can be achieved with BCI training after stroke, and used to control grasping actions through a mechanical hand orthosis.

KW - Brain-computer interface

KW - MEG

KW - Motor

KW - Plasticity

KW - Stroke

UR - http://www.scopus.com/inward/record.url?scp=41249093155&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=41249093155&partnerID=8YFLogxK

U2 - 10.1161/STROKEAHA.107.505313

DO - 10.1161/STROKEAHA.107.505313

M3 - Article

VL - 39

SP - 910

EP - 917

JO - Stroke

JF - Stroke

SN - 0039-2499

IS - 3

ER -