Linking Motor Cortex Activity and Movement in the Mouse Orofacial System

将小鼠口面部系统中的运动皮层活动和运动联系起来

• 批准号: 10759697
• 负责人: Michael Nicholas Economo
• 金额: $ 3.62万
• 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/10759697
• 关键词: Area; Automobile Driving; Behavior; Behavioral; Behavioral Paradigm; Biomimetics; Brain; Brain Stem; Brain region; Cell Nucleus; Cells; Cognitive; Communication; Complex; Computer Models; Coupled; Dedications; 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; Vertebral column; Viral; brain machine interface; cell type; cognitive process; data modeling; experimental study; flexibility; hypoglossal nucleus; improved; motor control; neural; neural circuit; neural patterning; neurophysiology; neurotransmission; next generation; nonhuman primate; optogenetics; orofacial; prevent; response; segregation; sensory feedback; tool; transmission process

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动是动态的。从事计算的大脑区域的集合是 根据行为需求而改变。大脑中的电路如何在功能上耦合以及 在行为时间尺度上取消耦合，以便可以将信息传达到适当的位置 适当的时间仍然是系统神经科学中的一个主要问题。这个问题特别 与电机系统相关。运动的产生是最基本的功能之一 大脑和哺乳动物中，柔性运动取决于运动皮层。电动机中的神经活动是皮层 复杂的，由控制信号组成，除了与运动计划有关的活动外，驱动运动 学习和其他认知过程。这种广泛的信号在同一电路中是多路复用的，并且 通常，在同一细胞内。大脑如何调节哪些活动模式被传达给 驱动运动的外围，哪些仅限于局部皮层计算的本地电路？一个 提出的有影响力的假设可以解释为什么只有某些活动模式会产生运动 - 零 太空模型 - 提供了一种具有生物学上合理的计算策略，用于将认知信号从 那些传播到周围的人会产生运动。空空间模型表明 认知信号仅限于对下游运动区域的影响有效取消的模式 - 它们是“输出无关”。初步证据表明，主要运动皮层中的活动模式可能是 与空空间模型一致，但到目前为止，建立因果关系是挑战 这些神经元活动模式和行为。 在此提案中，我们检查了从运动皮质到控制的运动神经元的神经元的流动 确定无效空间模型是否准确预测哪些神经信号的肌肉组织 因果关系在产生运动中的作用。强大的，新兴的多区域生理方法使我们能够 在该途径沿每个处理阶段检查神经元活动，这是对 了解如何将皮质活动模式转化为运动。细胞型特异性光遗传学 扰动使我们能够消除驱动动作动作的神经信号的歧义 结果，将有助于建立神经活动与运动之间的因果关系。 了解神经活动与行为的关系最终将有助于我们更好地解释缺陷 在运动障碍中表达并激励改善脑机界面和仿生控制 在下一代人造系统中使用的策略。