Control Theoretic Model of the Cerebellum

小脑的控制理论模型

• 批准号: RGPIN-2019-05728
• 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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=751569
• 关键词: Control; Theoretic; Model; Cerebellum

My research concerns the development of a control theoretic model of the cerebellum. A complete understanding of the cerebellum is one of the great open problems of neuroscience today, not very different from Kepler's problem on the motion of the planets, in its day. The cerebellum has remarkable features. It contains about half the neurons of the brain (more than the cerebral cortex), it has a purely feedforward neural architecture (in contrast with the recurrent architecture of the cerebral cortex), it operates on a timescale of milliseconds, 1-2 orders of magnitude faster than the cerebral cortex. Most importantly, despite the many regulatory functions it performs and independently of the particular function it is regulating (e.g. motor control, locomotion, eye movement, speech timing, emotion regulation), the computations are identical. What are those computations? Since the 1960's, control theory and robotics have offered plausible explanations. Yet no complete model has been found, to date. I initiated research on modeling the cerebellum during my sabbatical in 2017. I began with an experiment in cognitive psychology on adaptation to visuomotor rotations. A human subject is presented with a task to make a fast reach with the hand to a target disk on a horizontal screen. When the cursor angle is rotated from the hand angle by an amount unknown to the subject, an implicit (subconscious) process of adaptation takes place. This process is believed to reside in the cerebellum. We developed a model that predicts the dynamic phenomena observed in the experiments. The cerebellum is also involved in eye movement. Behaviours of the oculomotor system include the vestibuloocular reflex, smooth pursuit, saccades, and the optokinetic reflex. The computations (in the cerebellum) are the same for both the visuomotor experiment and the oculomotor system. We developed a second generation model that both recovers the behaviours of the oculomotor system and reveals the computations of the cerebellum. Rather than deriving a mathematical model based on analysis of experimental data, I approach the cerebellum modeling problem as one of synthesis: to synthesize a control law using tools from control theory. An advantage of applying control theory in this way is that, like Newton's laws that tell us about immutable limits on the motion of bodies in a gravitational field, so too control theory explains the immutable limits of a control system to achieve tracking in the presence of unknown disturbances. In essence, control theory narrows the search for a plausible mathematical model. The first phase of our research to develop a control-theoretic model of the cerebellum is well underway. The second phase is to relate the model to the neurophysiology of the cerebellum. We hope our work can contribute to basic science as well as to understanding neurological disorders such as ataxia, Huntington's disease, and Parkinson's disease.

我的研究涉及小脑控制理论模型的发展。对小脑的完整理解是当今神经科学的重大开放问题之一，与当时开普勒关于行星运动的问题没有太大不同。 小脑具有显着的特征。它包含大约一半的大脑神经元（比大脑皮层更多），它具有纯粹的前馈神经架构（与大脑皮层的循环架构相反），它的运行时间尺度为毫秒，1-2 个数量级速度比大脑皮层快。最重要的是，尽管它执行许多调节功能并且独立于它所调节的特定功能（例如运动控制、运动、眼球运动、言语定时、情绪调节），但计算是相同的。这些计算是什么？自 20 世纪 60 年代以来，控制理论和机器人技术提供了合理的解释。但迄今为止，尚未发现完整的模型。 2017 年休假期间，我开始研究小脑建模。我从一项关于适应视觉运动旋转的认知心理学实验开始。人类受试者面临的任务是用手快速到达水平屏幕上的目标盘。当光标角度从手部角度旋转主体未知的量时，就会发生隐式（潜意识）的适应过程。据信这个过程存在于小脑中。我们开发了一个模型来预测实验中观察到的动态现象。小脑也参与眼球运动。动眼系统的行为包括前庭眼反射、平滑追踪、眼跳和视动反射。视觉运动实验和动眼神经系统的计算（在小脑中）是相同的。我们开发了第二代模型，既可以恢复动眼神经系统的行为，又可以揭示小脑的计算。我没有根据实验数据分析推导数学模型，而是将小脑建模问题视为综合问题之一：使用控制理论的工具综合控制律。以这种方式应用控制理论的一个优点是，就像牛顿定律告诉我们重力场中物体运动的不可变限制一样，控制理论也解释了控制系统在存在以下情况下实现跟踪的不可变限制：未知的干扰。从本质上讲，控制理论缩小了对合理数学模型的搜索范围。 我们开发小脑控制理论模型的第一阶段研究正在顺利进行。第二阶段是将模型与小脑的神经生理学联系起来。我们希望我们的工作能够为基础科学以及理解共济失调、亨廷顿病和帕金森病等神经系统疾病做出贡献。