Mechanisms of persistent neural activity

持续神经活动的机制

• 批准号: 10652453
• 负责人: Alexander C Huk
• 金额: $ 52.95万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10652453
• 关键词: Algorithms; Alzheimer' s Disease; Animals; Architecture; Area; Behavior; Behavioral Paradigm; Biological; Biological Models; Brain; Brain Diseases; Brain region; Calcium; Callithrix; Chronic; Code; Cognition; Complex; Computer Models; Data; Data Set; Development; Disease; Electrodes; Electrophysiology (science); Exhibits; FarGo; Genetic; Health; Human; Image; Individual; Intelligence; Knowledge; Link; Macaca; Maintenance; Maps; Measurement; Measures; Memory; Modeling; Modernization; Motor; Motor Activity; Neurons; Neurophysiology - biologic function; Output; Parietal; Parietal Lobe; Parkinson Disease; Performance; Primates; Recurrence; Resolution; Rodent; Role; Saccades; Schizophrenia; Sensory; Short-Term Memory; Signal Transduction; Specificity; Statistical Data Interpretation; Statistical Models; Techniques; Testing; Thalamic structure; Time; Training; Visual; Work; cell type; clinically relevant; cognitive neuroscience; data-driven model; density; experimental study; extracellular; flexibility; foot; insight; large scale data; motor behavior; network models; neural; neural circuit; neuronal circuitry; neurophysiology; nonhuman primate; novel; oculomotor; repaired; response; sensory input; theories; tool; two-photon

PROJECT SUMMARY / ABSTRACT Although many well-studied aspects of neural function involve activity driven by sensory inputs or occurring at the time of motor actions, the brain often links such fleeting sensory and motor signals with persistent activity. Somehow, neural circuits and individual neurons are capable of maintaining activity without additional input. This is a fundamental aspect of neural function and a critical building block of cognition. The mechanisms underlying persistent neural activity have long been considered in both experiment and theory, but there is little definitive mechanistic understanding of the circuit and cellular contributions to persistent activity. Indeed, theories of persistent activity are far more biologically nuanced than current empirical knowledge— especially in the nonhuman primate, from which our understanding should have greatest clinical relevance given the number of disorders that involve persistent activity. Here, we propose work that leverages advanced techniques for multiple scales (and specificities) of neural recordings with corresponding analyses of large- scale datasets to test detailed theories of how the brain generates and maintains persistent activity. Specific Aim 1. Establish the marmoset as a powerful complementary model system for dissecting persistent activity mechanisms in primate brains. We will demonstrate the viability of studying memory-guided saccades and persistent activity in the marmoset, using successful training approaches, electrophysiology, and calcium imaging to elicit the key behavior and to characterize the important brain areas in this exciting primate model system. Specific Aim 2. Characterize the large-scale circuitry underlying oculomotor persistent activity. Using large scale recordings of extracellular activity across multiple brain regions collecting during performance of a memory-guided saccade task, we will acquire a dataset of unprecedented scale to assess the large-scale circuitry underlying persistent activity. We will adapt, develop, and deploy advanced statistical models to capture the functional interactions between neurons and brain areas. Specific Aim 3. Test and refine theories of persistent activity with novel measurements at fine spatial and genetic resolution. We will perform both 2-photon imaging and high density electrophysiological measures of neural activity. The imaging will allow us to test the local circuit components of the theory, as well as to assess cell-type-specific contributions to persistent activity. High density electrophysiology will reveal the local circuit architecture and signal flow that are not accessible with coarser techniques. Integrated within our analysis framework, the resultant model of persistent activity will be supported and refined by multiple scales and forms of empirical evidence, all collected in the primate brain.

项目摘要 /摘要 尽管神经功能的许多知识良好的方面涉及感官输入驱动或发生在 运动动作的时间，大脑经常将这种感觉和运动信号与持续活动联系起来。 某种程度上，神经元和单个神经元能够保持活性而无需其他输入。 这是神经功能的基本方面，也是认知的关键基础。机制 在实验和理论中，长期以来都考虑了潜在的持续神经活动，但是很少有 对电路的定义机械理解和对持续活动的细胞贡献。的确， 持续活动的理论在生物学上比目前的经验知识更为细微，尤其是 在非人类的灵长类动物中，我们的理解应具有最大的临床意义 涉及持续活动的疾病数量。在这里，我们提出了利用高级的工作 神经记录的多个尺度（和特定城市）的技术，并进行了相应的分析 比例数据集测试有关大脑如何生成和保持持续活动的详细理论。 特定目标1。建立摩尔马斯作为一种强大的互补模型系统 灵长类动物大脑中的持续活动机制。 我们将证明研究记忆引导的扫视和泥泞的活动的生存能力， 使用成功的训练方法，电生理学和钙成像来引起关键行为和 在这个令人兴奋的私人模型系统中表征重要的大脑区域。 特定目标2。表征动眼持续活动的大规模电路。 在收集期间收集的多个大脑区域的细胞外活动的大规模记录 执行记忆引导的扫视任务，我们将获得一个前所未有的规模数据集来评估 持续活动的大规模电路。我们将适应，开发和部署高级统计信息 模型以捕获神经元与大脑区域之间的功能相互作用。 特定的目标3。在空间上进行新颖的测量，测试和重新持续活动的理论 和遗传解决方案。 我们将同时执行2光子成像和神经活性的高密度电生理测量方法。这 成像将使我们能够测试该理论的本地电路成分，并评估细胞类型 持续活动的贡献。高密度电生理学将揭示本地电路结构和 使用更粗的技术无法访问的信号流。集成在我们的分析框架中 由多种量表和经验形式支持和确定持续活动的结果模型 证据，全部收集在主要大脑中。