Credit assignment in movement planning and movement execution

我们如何计划和执行动作是神经科学的基本问题之一。这两个过程中的不准确通常会导致运动错误，从而深入了解潜在的大脑过程。 例如，当头部倾斜到一个肩膀进行规划时，观察到的头部侧倾相关的到达误差与视网膜上反向旋转倾斜的视觉信息所需的大脑低估的头部角度相关。类似地，人们可以将在改变手臂重量的情况下（例如，在手肘携带满的杂货袋时）到达终点的系统性偏差解释为大脑错误估计改变的手臂动力学的结果。问题是，这些解释依赖于这样一个假设，即计划和控制在功能上是分离的。 考虑到大脑中用于计划和控制的区域有很大的重叠，这一假设是否合理是值得怀疑的;但这永远无法得到明确的验证，因为该领域中缺少的一个关键部分是一个无缝集成运动计划和运动执行的模型，以消除运动错误的起源。模型可以将大脑中的功能机制与行为联系起来。如果没有一个完整的模型，我们就有可能错误地将错误归因于错误的潜在机制，从而减缓对大脑的理解。因此，至关重要的是要解决这个问题，并根据一个综合的移动规划和执行模型来检查移动错误的潜在原因，以确认或纠正当前的解释。将运动误差转移到特定过程需要对潜在原因及其相互作用进行综合表征。为了实现这一点，我们需要一个新的模型结合已知的运动规划功能与现代运动控制理论。规划过程包括将感官信号转换为不同的坐标框架，并整合互补的信息源。最佳反馈控制最好地捕捉运动执行，依赖于身体状态的最佳估计，身体动力学的内部模型和噪声感觉反馈的使用。我们的实验室在计划和控制方面都有专业知识;因此，我们唯一有资格制定计划HQP将领导所有目标。

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 HQP will lead all aims.