Eye-hand coordination is the very basis of human behaviour and thus a major issue in Neuroscience. No matter what we do with our hands, vision provides essential information about the movement goal to the motor system. However, in order to produce accurate movements, the brain must take the actual configuration of the eyes with respect to the head and body into account. Indeed, the hand has to move with respect to the arm and the shoulder whereas the target is projected onto the retina. The difference between these 'reference frames' is largely governed by the non-linear mathematics of rotations and the brain has thus to solve this problem to send a precise movement command to the involved muscles. Here, we propose to establish a fundamental framework to exp lain how the brain performs this reference frame transformation problem in eye-hand coordination. We will apply a multidisciplinary approach using mathematical and medical research tools to provide an overall understanding of how the system works. Therefore, we will for the first time establish an algorithmic and a physiologically realistic neural network model to get insight into the computational nature of the underlying brain areas. Resulting hypotheses and predictions will be tested experimentally by performing behavioural studies of eye-hand coordination on healthy human subjects. We will also directly identify the involved neural structures using functional Magnetic Resonance Imaging (fMRI) techniques. The results we expect will have a high impact in t he neural control of movement field because it describes how movement is created accurately. Furthermore, we will provide mathematical and physiological models for the understanding of neural diseases and future theoretical lesion studies. In addition, this first insight into the basic functional properties of the cortex will offer the unique knowledge to the prosthetics research community needed to develop neural prosthetic devices.
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