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New FRIAS Project Group

New FRIAS Project Group "Neural networks of motor control and motor learning"

The Freiburg Institute for Advanced Studies - FRIAS has approved funding to inverstigate the neural networks underlying motor control and motor learning. The FRIAS Project Group brings together six research teams from different faculties of the University of Freiburg combining expertise in all relevant fields, from motor neurophysiology to computational motor control to clinical movement neuroscience and neural network modeling: Prof. Ilka Diester (Faculty of Biology), Jun.Prof. Christian Leukel (Faculty of Economics and Behavioral Sciences & Bernstein Center Freiburg), Prof. Carsten Mehring (Faculty of Biology & Bernstein Center Freiburg), Prof. Stefan Rotter (Faculty of Biology & Bernstein Center Freiburg), Dr. Robert Schmidt (Faculty of Biology, BrainLinksBrainTools & Bernstein Center Freiburg), Prof. Cornelius Weiller (Neurocenter University Clinics & Bernstein Center Freiburg).

The research of the FRIAS Project Group aims at a better understanding of neural networks of motor control and motor learning: The only way we can interact with the world is through movement, be it by using tools, manipulating objects or by speaking. Humans vastly surpass the flexibility and motor learning ability of any man made robot. Scientists still scarcely understand the mechanisms that underlie these unique human capabilities. In recent years, computational models have been developed that accurately describe human behaviour in a variety of motor tasks. While these models advanced our understanding of basic principles underlying motor control and motor learning, their neural underpinnings remain unclear. On the other hand, neuroanatomical and –physiological studies have produced a wealth of data on the cellular mechanisms of movement control and how neural activities relate to behaviour. The link of these discoveries to computational findings, however, is mostly obscure. We believe that a fundamental advance in our understanding will be accomplished by investigating the motor system on the level of neuronal networks, merging findings from different approaches studying motor control. Surprisingly, this level of analysis has been largely ignored in present research on the motor system. To achieve this goal, a group of scientists teams up for this project – combining expertise in all relevant fields, from motor neurophysiology, over computational motor control to clinical movement neuroscience and neuronal network modeling – and aims to unravel neuronal networks underlying motor control and motor learning.