Understanding the Distributed Control of Flexible Behavior

了解灵活行为的分布式控制

• 批准号: 10640703
• 负责人: Stefan Lemke
• 金额: $ 6.95万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10640703
• 关键词: Address; Angelman Syndrome; Animal Model; Animals; Area; Automobile Driving; Basal Ganglia; Behavior; Behavioral; Behavioral Model; Brain; Brain Diseases; Cerebellum; Disease; Environment; Functional disorder; Genetic Diseases; Goals; Hand; Impairment; Knockout Mice; Left; Lesion; Light; Link; Manuals; Modeling; Motor; Motor Cortex; Motor Skills; Movement; Mus; Muscle; Neural Network Simulation; Neurodegenerative Disorders; Neurodevelopmental Disorder; Neurons; Obsessive-Compulsive Disorder; Pattern; Policies; Population; Problem Solving; Production; Site; Stroke; System; Thalamic structure; Translating; UBE3A gene; Work; autism spectrum disorder; behavioral phenotyping; control theory; flexibility; imprint; insight; model design; motor control; motor deficit; mouse model; multitask; nervous system disorder; neural; neurophysiology; neuropsychiatric disorder; neuroregulation; recurrent neural network; restoration; targeted treatment; transmission process

ABSTRACT Our brains have the remarkable ability to both produce precise, consistent movements in an invariant environment and dynamically adjust behavior to a changing environment. Almost all our everyday actions, such as driving a car or riding a bike, necessitate such flexible multi-tasking. Losing the ability to flexibly adjust behavior is dramatic and debilitating, as evidenced by disorders such as obsessive-compulsive disorder (OCD) or profound forms of autism spectrum disorder (ASD). While considerable work has examined how the brain’s distributed motor network controls consistent movements in an invariant environment, the mechanisms that allow for flexibility in movement control remain unknown. In this project, I develop a behavioral model to study the flexible production of multiple distinct reaching movements in mice. The extensive previous work that has characterized the neural control of reaching movements provides a powerful framework to precisely understand the neural control of flexibility. I use this model to investigate the distributed control of flexible movements across the primary motor cortex (M1), basal ganglia (BG), and cerebellum (CB). While the M1-BG and M1-CB networks have been previously investigated in isolation, how all three regions interact is largely unexplored. I leverage (1) large-scale multi-site neurophysiology in M1, BG, and CB, (2) genetically controlled thalamic manipulations of M1-BG and M1-CB networks, (3) multi-region recurrent neural network models, and (4) mouse models of OCD and ASD that display behavioral inflexibility to uncover fundamental principles by which the brain’s distributed motor network governs flexibility in movement control and shed light on how these mechanisms dysfunction in brain disorders.

抽象的 我们的大脑具有出色的能力，可以在不变的情况下产生精确，一致的动作 环境并动态调整行为对不断变化的环境。我们几乎每天的行动， 当驾驶汽车或骑自行车时，必要的如此灵活的多任务处理。失去灵活调整的能力 行为是戏剧性的，令人衰弱，如强迫症（OCD）等疾病所证明 或自闭症谱系障碍（ASD）的深刻形式。虽然大量工作检查了大脑的方式 分布式电机网络控制不变环境中的一致运动，这些机制允许 为了灵活，控制控制仍然未知。在这个项目中，我开发了一种行为模型来研究 在小鼠中灵活产生多个不同的到达运动。以前广泛的工作 表征了到达运动的神经控制权提供了一个有力的框架来精确理解 灵活性的神经控制。我使用此模型调查了对灵活运动的分布式控制 主要运动皮层（M1），基底神经节（BG）和小脑（CB）。而M1-BG和M1-CB网络 以前已经孤立地研究了这三个区域的相互作用是很大程度上出乎意料的。我利用（1） M1，BG和CB中的大规模多站点神经生理学，（2）遗传控制的丘脑操纵 M1-BG和M1-CB网络，（3）多区域复发性神经网络模型以及（4）OCD的鼠标模型 和ASD表现出行为僵化，以发现大脑分布的基本原理 电机网络控制运动控制的灵活性，并阐明这些机制功能障碍如何 脑疾病。