Affiliations: Division of Functional and Restorative Neurosurgery & Division of Translational Neurosurgery, Department of Neurosurgery, Eberhard Karls University Tuebingen, Tuebingen, Germany | Neuroprosthetics Research Group, Werner Reichardt Centre for Integrative, Neuroscience, Eberhard Karls University Tuebingen, Tuebingen, Germany | Department of Computer Engineering, Wilhelm-Schickard Institute for Computer, Science, Eberhard Karls University Tuebingen, Tuebingen, Germany | Department of Computer Engineering, University of Leipzig, Leipzig, Germany | Institute for Medical Psychology and Behavioural Neurobiology, Eberhard Karls, University Tuebingen, Tuebingen, Germany
Note: [] Corresponding author: Dr. Alireza Gharabaghi, Division of Functional and Restorative Neurosurgery, & Division of Translational Neurosurgery, Department of Neurosurgery Eberhard Karls University Otfried-Mueller-Str. 45, 72076 Tuebingen, Germany. Tel.: +49 7071 29 83550; Fax: +49 7071 29 25104; E-mail: alireza.gharabaghi@uni-tuebingen.de
Abstract: Purpose: Today's implanted brain-computer interfaces make direct contact with the brain or even penetrate the tissue, bearing additional risks with regard to safety and stability. What is more, these approaches aim to control prosthetic devices as assistive tools and do not yet strive to become rehabilitative tools for restoring lost motor function. Methods: We introduced a less invasive, implantable interface by applying epidural electrocorticography in a chronic stroke survivor with a persistent motor deficit. He was trained to modulate his natural motor-related oscillatory brain activity by receiving online feedback. Results: Epidural recordings of field potentials in the beta-frequency band projecting onto the anatomical hand knob proved most successful in discriminating between the attempt to move the paralyzed hand and to rest. These spectral features allowed for fast and reliable control of the feedback device in an online closed-loop paradigm. Only seven training sessions were required to significantly improve maximum wrist extension. Conclusions: For patients suffering from severe motor deficits, epidural implants may decode and train the brain activity generated during attempts to move with high spatial resolution, thus facilitating specific and high-intensity practice even in the absence of motor control. This would thus transform them from pure assistive devices to restorative tools in the context of reinforcement learning and neurorehabilitation.
