Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK.
Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK; Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.
Neuron. 2021 May 5;109(9):1567-1581.e12. doi: 10.1016/j.neuron.2021.03.009. Epub 2021 Mar 30.
Across a range of motor and cognitive tasks, cortical activity can be accurately described by low-dimensional dynamics unfolding from specific initial conditions on every trial. These "preparatory states" largely determine the subsequent evolution of both neural activity and behavior, and their importance raises questions regarding how they are, or ought to be, set. Here, we formulate motor preparation as optimal anticipatory control of future movements and show that the solution requires a form of internal feedback control of cortical circuit dynamics. In contrast to a simple feedforward strategy, feedback control enables fast movement preparation by selectively controlling the cortical state in the small subspace that matters for the upcoming movement. Feedback but not feedforward control explains the orthogonality between preparatory and movement activity observed in reaching monkeys. We propose a circuit model in which optimal preparatory control is implemented as a thalamo-cortical loop gated by the basal ganglia.
在一系列运动和认知任务中，皮质活动可以通过在每次试验中从特定初始条件展开的低维动力学来准确描述。这些“预备状态”在很大程度上决定了神经活动和行为的后续演变，它们的重要性引发了关于它们如何（或应该如何）设定的问题。在这里，我们将运动准备表述为对未来运动的最佳预测性控制，并表明该解决方案需要对皮质回路动力学进行内部反馈控制的一种形式。与简单的前馈策略相反，反馈控制通过选择性地控制对即将到来的运动重要的小子空间中的皮质状态，从而实现快速的运动准备。反馈而不是前馈控制解释了在猴子中观察到的预备和运动活动之间的正交性。我们提出了一个电路模型，其中最优预备控制作为基底神经节门控的丘脑-皮质回路来实现。
