Control Theoretic Model of the Cerebellum

小脑的控制理论模型

• 批准号: RGPIN-2018-05640
• 负责人: Broucke, Mireille
• 金额: $ 2.04万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=646331
• 关键词: Control; Theoretic; Model; Cerebellum

The aim of this research is to develop a mathematical model of the human cerebellum, the part of the brain responsible for motor control. A complete understanding of the cerebellum is one of the great open problems of neurobiology today. A mathematical model of the cerebellum would contribute fundamental knowledge to science, and it would enable better understanding of neurological disorders such as ataxia, Huntington's disease, and Parkinson's disease. Initially, we will focus on experimental findings from cognitive psychology over the last 30 years on motor adaptation. Adaptation to visuomotor rotations is an experiment in which a human subject must make a fast reach with the hand to a target disk on a horizontal screen, by observing a cursor on the screen. When the cursor position is verdigal, humans are able to hit the target disk within the first attempt. Instead, when the cursor angle is rotated from the hand angle by an unknown amount, an implicit (subconscious) process of adaptation is initiated in which the human brain corrects for the observed error through consecutive trials. It is believed that the cerebellum is responsible for implicit adaptation. There has been an outpouring of research focusing on this experiment because it exposes a number of behaviours and principles of adaptation.******We have recently discovered a linear time-invariant (LTI) state model that explains adaptation in the visuomotor rotation experiment. Our model recovers the dynamic behaviours observed in experiments, and moreover, we are the first to reconcile newly reported results on the so-called error clamp paradigm. Unlike previous models, our model reveals a plausible architecture for the computations underlying adaptation, and it has states with a physical meaning. Our model was derived using regulator theory; this is the first time regulator theory has been applied to derive a model of motor adaptation. ******Our methodology to find a mathematical model of the cerebellum will contrast with all other approaches taken by psychologists today. We interpret the problem of adaptation as a problem of control synthesis: to synthesize a control law to achieve tracking in the presence of an unknown disturbance. The power of our methodology derives from the fact that, like Newton's laws that tell us about immutable limits on the motion of bodies in a gravitational field, so too regulator theory informs us on immutable limits of a control system: this is the internal model principle. Such immutable limits narrow the search for a plausible mathematical model. As such, regulator theory appears to provide a new body of evidence beyond experimentation about the computations occurring (in the cerebellum) when implicit adaptation in a motor task occurs.******I have dedicated my sabbatical year to launch this new research initiative. I am excited to bring a new perspective to neuroscience and to open a door to a fuller understanding of the human cerebellum.

这项研究的目的是开发人类小脑的数学模型，小脑是大脑中负责运动控制的部分。对小脑的完整理解是当今神经生物学的重大悬而未决的问题之一。小脑的数学模型将为科学贡献基础知识，并且有助于更好地理解共济失调、亨廷顿病和帕金森病等神经系统疾病。首先，我们将重点关注过去 30 年认知心理学关于运动适应的实验结果。适应视觉运动旋转是一项实验，其中人类受试者必须通过观察屏幕上的光标，用手快速到达水平屏幕上的目标盘。当光标位置为垂直时，人类能够在第一次尝试内击中目标盘。相反，当光标角度从手部角度旋转未知量时，会启动隐式（潜意识）适应过程，其中人脑通过连续试验纠正观察到的错误。人们认为小脑负责内隐适应。有大量的研究集中在这个实验上，因为它揭示了适应的许多行为和原理。******我们最近发现了一个线性时不变（LTI）状态模型，可以解释视觉运动旋转中的适应实验。我们的模型恢复了实验中观察到的动态行为，而且，我们是第一个在所谓的误差钳范式上协调新报告的结果的人。与以前的模型不同，我们的模型揭示了适应基础计算的合理架构，并且它具有具有物理意义的状态。我们的模型是利用调节器理论推导出来的；这是首次应用调节器理论来推导电机适应模型。 ******我们寻找小脑数学模型的方法将与当今心理学家采用的所有其他方法形成鲜明对比。我们将自适应问题解释为控制综合问题：综合控制律以在存在未知干扰的情况下实现跟踪。我们方法论的力量源自这样一个事实：就像牛顿定律告诉我们物体在引力场中运动的不变极限一样，调节器理论也告诉我们控制系统的不变极限：这就是内部模型原理。这种不可变的限制缩小了对合理数学模型的搜索范围。因此，调节器理论似乎提供了超越实验的新证据，表明运动任务中发生内隐适应时（小脑中）发生的计算。********我花了一年的休假时间来启动这项新研究倡议。我很高兴能为神经科学带来新的视角，并为更全面地了解人类小脑打开一扇大门。