The BFNT-Chair Neuroinformatics is headed by Dario Farina.
The generation of a movement is the combination of discrete events (action potentials) generated in the brain, spinal cord, nerves, and muscles. These discrete events are the result of ion exchanges across membranes, electrochemical mechanisms, and active ion pumping through energy expenditure. The ensemble of spike trains discharged in the various parts of the neuromuscular system constitutes the neural code for movements. Recording and interpretation of this code provides the means for decoding the motor system. The main current limitation in the investigation of the motor system is the impossibility of detecting and processing in the intact human the activity of a sufficiently large number of neural cells and sensory afferents to associate a functional meaning to the cellular mechanisms that ultimately determine a movement. This limitation in turn impedes to answer many fundamental questions on the control of human movements, with important implications in neurorehabilitation technologies, such as man-machine interfaces.
Signals used for controlling man-machine interfaces may be detected from the brain, peripheral nerves, muscles, or can be directly the forces produced by the motor system. These levels correspond to decreased levels of complexity in interpretation as the level of “biological decoding” increases. Within the Bernstein Center, this project plan addresses the decoding of the neural code at the peripheral nerve and muscle level for new paradigms of man-machine interfaces.
The project will advance electrodes for interfacing motor neuron and nerve activity, either with implantation into nerves and muscles or with non-invasive systems, and develop novel strategies for decoding spike trains from these recordings. These methods will be used for furthering our understanding of the neural control of human movement and for the design of new paradigms of control of man-machine interface systems, especially myoelectric prostheses. The approach proposed will be based on a deeper understanding of fundamental open issues in motor control, on which the new man-machine interface systems will be based.
The project is characterized by the link between new knowledge on the neural mechanisms that are the determinants of movement and the motor functions, in vivo in humans. If the task is successful, it will be possible to decode the neural code underlying movements. In addition to the contributions to our understanding on human movement, this achievement will permit development of interfaces with external devices in a robust and intuitive way, which will lead to a new generation of closed-loop man-machine interfaces.