Credit assignment in movement planning and movement execution

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How we plan and execute movements is one of the fundamental questions in neuroscience. Inaccuracies in either process generally result in movement errors that provide insight into underlying brain processes. E.g. when planning reaches with the head tilted to one shoulder, observed head-roll-dependent reach errors correlate with brain under-estimated head angles required to counter-rotate tilted visual information on the retina. Similarly, one can interpret systematic biases in reach endpoints under altered arm weight (e.g. while carrying a full grocery bag in the elbow) as a consequence of the brain mis-estimating the altered arm dynamics. The problem is, these interpretations rely on the assumption that planning and control are functionally separate and separable. Given the large overlap of brain areas for planning and control, it is questionable whether this assumption is justified; but this could never be explicitly tested because a key missing piece in the field is a model that seamlessly integrates motor planning and movement execution to disambiguate the origin of movement errors. Models can link functional mechanisms in the brain to behaviour. Without an integrated model, we run the risk of erroneously crediting errors to the wrong underlying mechanism, slowing progress in understanding the brain. It is thus crucial to address this problem and examine the potential cause of movement errors in the light of a combined movement planning and execution model to either confirm or correct current interpretations. ******Assigning movement errors to specific processes requires an integrated characterization of the potential causes and their interactions. To achieve this, we need a new model combining known movement planning features with modern motor control theories. Planning processes include converting sensory signals to different coordinate frames and integrating complementary sources of information. Optimal feedback control best captures movement execution, relying on the optimal estimation of body state, an internal model of the body dynamics and the use of noisy sensory feedback. Our lab has expertise in both planning and control; we thus uniquely qualified to develop a planning n design new behavioural, imaging and stimulation experiments that disambiguate alternative error sources. This multi-disciplinary project will provide an ideal training environment; HQP will lead all aims.