Brain–Machine Interface Induced Morpho-Functional Remodeling of the Neural Motor System in Severe Chronic Stroke

  • Andrea CariaEmail author
  • Josué Luiz Dalboni da Rocha
  • Giuseppe Gallitto
  • Niels Birbaumer
  • Ranganatha Sitaram
  • Ander Ramos Murguialday
Original Article


Brain–machine interfaces (BMI) permit bypass motor system disruption by coupling contingent neuroelectric signals related to motor activity with prosthetic devices that enhance afferent and proprioceptive feedback to the somatosensory cortex. In this study, we investigated neural plasticity in the motor network of severely impaired chronic stroke patients after an EEG-BMI-based treatment reinforcing sensorimotor contingency of ipsilesional motor commands. Our structural connectivity analysis revealed decreased fractional anisotropy in the splenium and body of the corpus callosum, and in the contralesional hemisphere in the posterior limb of the internal capsule, the posterior thalamic radiation, and the superior corona radiata. Functional connectivity analysis showed decreased negative interhemispheric coupling between contralesional and ipsilesional sensorimotor regions, and decreased positive intrahemispheric coupling among contralesional sensorimotor regions. These findings indicate that BMI reinforcing ipsilesional brain activity and enhancing proprioceptive function of the affected hand elicits reorganization of contralesional and ipsilesional somatosensory and motor-assemblies as well as afferent and efferent connection–related motor circuits that support the partial re-establishment of the original neurophysiology of the motor system even in severe chronic stroke.

Key Words

Brain–machine interface stroke DTI functional connectivity motor recovery 



This work was supported by the German Federal Ministry of Education and Research (BMBF, Förderzeichen 01GQ0831); Deutsche Forschungsgemeinschaft (DFG) Koselleck (BI 195/58-1); European Research Council (ERC 227632); European Union FP7-ICT-2009-231724 - HUMOR: Human Behavioral Modeling for Enhancing Learning by Optimizing Human-Robot Interaction, FP7-ICT-2009-247935 – BETTER: BNCI-driven Robotic Physical Therapies in Stroke Rehabilitation of Gait Disorders; Italian Ministry of Health GR-2009-159190; BW-Stiftung (ROB-1); Werner Reichardt Centre for Integrative Neuroscience (CIN). The authors would like to thank Balint Varkuti, Leonhard Läer, Pavel Terekhin, Nicolas Lindau, and Bjorn Schiffler for their support.

Required Author Forms

Disclosure forms provided by the authors are available with the online version of this article.

Compliance with Ethical Standards

Informed consent, including informed consent to publish identifying information/images in an online open-access publication, was obtained from all patients involved. The study was approved by the ethics committee of the Faculty of Medicine of the University of Tübingen. The methods carried out in this work are in accordance with the approved guidelines and regulations.

Competing Interests

The authors declare that they have no competing interests.

Supplementary material

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Copyright information

© The American Society for Experimental NeuroTherapeutics, Inc. 2019

Authors and Affiliations

  1. 1.Department of Psychology and Cognitive SciencesUniversity of TrentoRoveretoItaly
  2. 2.Istituto di Ricovero e Cura a Carattere ScientificoFondazione Ospedale San CamilloVeniceItaly
  3. 3.Institut für Medizinische Psychologie und VerhaltensneurobiologieUniversität TübingenTübingenGermany
  4. 4.Brain and Language Laboratory, Department of Clinical NeuroscienceUniversity of GenevaGenevaSwitzerland
  5. 5.Institute of Biological and Medical EngineeringPontificia Universidad Católica de ChileSantiagoChile
  6. 6.Department of Psychiatry, Section of Neuroscience, School of MedicinePontificia Universidad Católica de ChileSantiagoChile
  7. 7.Laboratory for Brain-Machine Interfaces and Neuromodulation, School of MedicinePontificia Universidad Católica de ChileSantiagoChile
  8. 8.Health Technologies DepartmentTECNALIASan SebastianSpain

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