In future, three projects at the University of Tübingen will be funded by the Neurobotics research programme of the Baden-Württemberg Foundation. The foundation is providing a total of four million euros to support research ideas from the fields of Neurotechnology, Neuronal Computing and Neuronally-inspired Robotics in order to do justice to the increasing importance of these fields. Among the nine selected research consortia, three are located at the University of Tübingen, the University Hospital Tübingen and the NMI Natural and Medical Sciences Institute at the University of Tübingen - together they will receive approximately 1.5 million euros for a total of three years.
The project "NeuroControl: Control of physiological activity in retinal neuronal networks" focuses on how activity in the neuronal networks of the retina can be controlled. Although retinal visual prostheses are clinically successful, their operation is still based on comparatively simple stimulation patterns. In RetNetControl, the research group of PD Dr. Philipp Berens (Research Institute of Ophthalmology, Werner Reichardt Centre for Integrative Neurosciences and Bernstein Centre for Computational Neuroscience) intends to establish theoretical network models of retinal cells in order to test alternative stimulation patterns. Based on the model predictions, Dr. Günther Zeck's research group (Natural and Medical Sciences Institute Reutlingen NMI and Bernstein Centre for Computational Neuroscience) will use experimental laboratory experiments to investigate the extent to which such stimulation patterns can trigger responses in blind retinas that are comparable to those of healthy retinas. The insights gained can lead to an improvement in retinal implants and generally in invasive neurostimulators.
In the project "NemoPlast: Learning with neurorobots: human-machine interfaces for the promotion of motor plasticity", scientists led by Professor Alireza Gharabaghi (Section of functional and stereotactical surgery, Department of Neurosurgery at the University Hospital of Tübingen and Werner Reichardt Centre for Integrative Neurosciences) are developing a novel training system for stroke patients; many of them are still significantly restricted in their motor skills years after the event. For these patients, NemoPlast is developing a training neurorobot that links an exoskeleton with a non-invasive brain stimulator. The exoskeleton is controlled by brain activity (brain-machine interface) and can support paralysed persons during hand and arm movements. The brain stimulator simultaneously activates previously unused neuronal networks and connections between the brain and muscles in order to strengthen them in a targeted and sustained manner (closed-loop stimulation). This integrated neuroprosthetic training approach aims at promoting plasticity and restoring the motor functions of the patients so that they can in the long term perform independent movements without technical aids.
Univ.-Prof. Dr. med. Alireza Gharabaghi
Sektion Funktionelle und Restaurative Neurochirurgie
The research project "KONSENS-NHE: Development of a context-sensitive neural-controlled hand exoskeleton for the restoration of everyday ability and autonomy after brain and spinal cord injuries" combines the know-how of the Universities of Tübingen, Stuttgart and Reutlingen in the fields of Brain-Machine Interface, Robotics and Computer Science. The researchers are developing a brain-controlled hand exoskeleton that can be used in everyday life, enabling paralysed people to grasp everyday objects and thus live more independently. Dr. Surjo Soekadar, head of the Applied Neurotechnology research group at the University Hospital of Tübingen and project coordinator, is sure that this will substantially improve the quality of life for paralysed persons. The control of the hand exoskeleton is based on a Brain/Neural-Computer Interaction (BNCI) system. The brain waves are measured at the head using polyamide electrodes and combined with other biosignals, for example from eye movements. The mere idea of a finger movement that leads to a characteristic brain current signal is translated into a control signal for the hand exoskeleton, which finally moves the paralysed hand in real time.
Dr. med. Surjo R. Soekadar
Arbeitsgruppe Angewandte Neurotechnologie
Modified and translated from the original text by Antja Karbe (in German), University of Tübingen.