Linking motor cortex activity and movement in the mouse orofacial system.

将小鼠口面部系统的运动皮层活动和运动联系起来。

• 批准号: 10367341
• 负责人: Michael Nicholas Economo
• 金额: $ 41.25万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10367341
• 关键词: Area; Automobile Driving; Behavior; Behavioral; Behavioral Paradigm; Biomimetics; Brain; Brain Stem; Brain region; Cell Nucleus; Cells; Cognitive; Complex; Computer Models; Coupled; Dimensions; Evaluation; Exhibits; Genetic; Goals; Individual; Influentials; Learning; Link; Mammals; Maps; Mediating; Methods; Modeling; Motor; Motor Activity; Motor Cortex; Motor Neurons; Motor output; Movement; Movement Disorders; Mus; Neurons; Neurosciences; Outcome; Output; Pathway interactions; Pattern; Physiology; Play; Population; Primates; Production; Role; Signal Transduction; Silicon; Space Models; Specificity; Spinal; Structure; System; Testing; Time; Tongue; Variant; Viral; brain machine interface; cell type; cognitive process; data modeling; experimental study; flexibility; hypoglossal nucleus; improved; motor control; neural circuit; neural patterning; neurophysiology; neurotransmission; next generation; nonhuman primate; optogenetics; orofacial; prevent; relating to nervous system; response; sensory feedback; tool

Information flow through neural circuits is dynamic. The set of brain areas that are engaged in computation are ever changing according to behavioral demands. How circuits in the brain are functionally coupled and uncoupled on behavioral time scales so that information can be relayed to the appropriate place at the appropriate time remains a major outstanding question in systems neuroscience. This question is of particular relevance in the motor system. The production of movements is one of the most fundamental functions of the brain, and in mammals, flexible movements depend on the motor cortex. Neural activity in the motor is cortex complex, made up of control signals that drive movements in addition to activity related to motor planning, learning, and other cognitive processes. This wide array of signals is multiplexed within the same circuit and, often, within the same cells. How does the brain regulate which activity patterns are communicated to the periphery to drive movements and which are confined to local circuits for local cortical computation? An influential hypothesis proposed to explain why only some activity patterns generate movements – the null space model – provides a biologically plausible computational strategy for segregating cognitive signals from those that are transmitted to the periphery to produce movement. The null space model suggests that cognitive signals are restricted to patterns whose impact on downstream motor areas effectively cancel out – they are ‘output-null.’ Preliminary evidence suggests that activity patterns in the primate motor cortex may be consistent with the null space model, but thus far it has been challenging to establish a causal link between these neural activity patterns and behavior. In this proposal, we examine the flow of neural signals from the motor cortex to the motor neurons that control the musculature to determine whether the null space model accurately predicts which neural signals have a causal role in generating movements. Powerful, emerging methods for multi-regional physiology allow us to examine neural activity at each processing stage along this pathway, an essential requirement for understanding how cortical activity patterns are transformed into movements. Cell-type specific optogenetic perturbations allow us to disambiguate the neural signals that drive movements from those that are simply a consequence and will help to establish a causal relationship between neural activity and movements. Understanding how neural activity relates to behavior will ultimately help us better interpret the deficits expressed in movement disorders and motivate improved brain-machine interfaces and biomimetic control strategies for use in the next generation of artificial systems.

通过神经回路的信息流是动态的。参与计算的大脑区域是 根据行为需求不断变化。大脑中的电路是如何在功能上耦合的， 在行为时间尺度上解耦，以便信息可以传递到适当的地方， 适当的时间仍然是系统神经科学中一个重大的悬而未决的问题。这个问题特别 与运动系统相关。生产运动是最基本的功能之一， 在哺乳动物中，灵活的运动取决于运动皮层。运动神经的活动是大脑皮层 复杂，由控制信号组成，除了与运动规划相关的活动外，还驱动运动， 学习和其他认知过程。这种宽阵列的信号在同一电路内被多路复用， 通常是在同一个细胞内。大脑如何调节哪些活动模式被传达给大脑？ 哪些局限于局部皮层计算的局部回路？一个 一个有影响力的假设，提出了解释为什么只有一些活动模式产生运动-零 空间模型-提供了一种生物学上合理的计算策略，用于将认知信号与 那些被传递到外围以产生运动的信号。零空间模型表明， 认知信号仅限于对下游运动区的影响有效抵消的模式， 它们是“输出空”。初步证据表明，灵长类动物运动皮层的活动模式可能是 与零空间模型一致，但到目前为止，建立两者之间的因果关系一直具有挑战性。 这些神经活动模式和行为 在这个提议中，我们研究了从运动皮层到控制运动的运动神经元的神经信号流。 肌肉组织，以确定零空间模型是否准确地预测哪些神经信号具有 产生运动的因果作用。强大的、新兴的多区域生理学方法使我们能够 检查神经活动在每个处理阶段沿着这一途径，一个基本要求， 了解皮层活动模式如何转化为运动。细胞类型特异性光遗传学 扰动使我们能够将驱动运动的神经信号与那些仅仅是运动的神经信号区分开来。 这将有助于建立神经活动和运动之间的因果关系。 了解神经活动与行为的关系将最终帮助我们更好地解释这些缺陷。 表现在运动障碍和激励改善脑机接口和仿生控制 用于下一代人工系统的策略。