Integration of Experience-Induced Gene Expression and Circuit Functions

经验诱导的基因表达和电路功能的整合

• 批准号: 9897551
• 负责人: MEYER B. JACKSON
• 金额: $ 40.37万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9897551
• 关键词: Address; Affect; Amygdaloid structure; Attention; Basic Science; Behavior; Behavioral; Behavioral Paradigm; Binding Proteins; Brain; Brain region; Cells; Chromatin; Cognition; Complex; Computer Models; Computing Methodologies; Data; Disease; Environment; Feedback; Frequencies; Gene Expression; Gene Expression Profiling; Genes; Genetic; Genetic Recombination; Hippocampus (Brain); Hybrids; Image; Information Networks; Interneuron function; Interneurons; Lead; Link; Machine Learning; Mediating; Methodology; Molecular; Molecular Probes; Neuronal Plasticity; Neurons; Neurosciences; Parvalbumins; Pathway Analysis; Pharmacology; Physiology; Play; Population; Prefrontal Cortex; Property; Pyramidal Cells; Rabies virus; Regulation; Regulator Genes; Research Personnel; Role; Running; Sensory; Shapes; Short-Term Memory; Synapses; System; Systems Biology; Techniques; Technology; Testing; Universities; Wisconsin; Work; electrical property; environmental enrichment for laboratory animals; experience; experimental study; frontal lobe; immunoreactivity; innovation; interdisciplinary approach; neural circuit; neural network; neurodevelopment; neuronal circuitry; neuronal excitability; neurophysiology; novel; novel strategies; patch clamp; relating to nervous system; response; sensor; transcriptome; translatome; voltage

Multi-PI: Xinyu Zhao, Meyer Jackson, University of Wisconsin-Madison. Title: Integration of Experience-Induced Gene Expression and Circuit Functions Understanding the complex relationships between cells, gene networks, neural circuits, and behavior requires techniques that can probe the molecular makeup of distinct types of neurons, evaluate their properties, and test their roles in higher level functions. Genes expressed within specific populations of neurons determine their electrical properties and these properties together with their synaptic connectivity collectively shape the electrical activity of neural circuits. This is especially well illustrated by a population of neurons defined by expression of the Ca2+ binding protein parvalbumin (PV). PV interneurons (PVIs) are sparsely distributed, fast-spiking cells that provide feedback and feedforward inhibition to principal neurons. One of the most well-defined network functions of PVIs is in the coordination of neuronal networks and their associated oscillations. PVIs entrain cortical networks to drive gamma oscillations (30-100 Hz) and control their frequency and strength. PVI-mediated gamma oscillations are known to have important roles in sensory processing, attention, working memory, and cognition. However, the gene networks that control PVI functions and their impact on gamma oscillations remain unclear. PVIs are readily modified by environmental conditions and experience. PV immunoreactivity increases after exploration of a novel environment, rearing under environmental enrichment (EE), and voluntary running (VR). These changes occur in brain regions associated with cognition, including hippocampus, prefrontal cortex, and amygdala. The molecular mechanisms underlying PVI changes during behavioral adaptation remain unknown. Although studies suggest that behavioral adaptions affect gamma oscillations, a role for PVIs in the link between behavioral adaption and gamma oscillations has not been established. This application takes a multidisciplinary approach to address the fundamental question of how PVIs contribute to behavioral adaptations. Our overarching hypothesis is that changes in gene expression that modify the cellular properties of PVIs will alter network oscillations, enabling PVIs to serve as a critical hub in behavioral adaptations. We will determine whether behavioral adaptation mobilizes networks of genes in PVIs, and assess the contributions of these networks to PVI physiology and gamma oscillations. This project combines the unique expertise of co-PIs Zhao (genetic regulation of neurodevelopment) and Jackson (neurophysiology and neural circuits) and co-Is Roy (system biology and machine learning) and Rosenberg (computational and system neuroscience). By integrating experimental data with gene network analysis and computational modeling of multicellular networks, this work will reveal how changes in molecular/cellular properties impact the emergent properties of neural circuits.

多PI：Xinyu Zhao，Meyer杰克逊，威斯康星大学麦迪逊分校。 题目：经验诱导的基因表达与回路功能的整合 理解细胞、基因网络、神经回路和行为之间的复杂关系需要 这些技术可以探测不同类型神经元的分子组成，评估它们的特性，并测试 在更高级别的职能中发挥作用。在特定神经元群体中表达的基因决定了它们的 电特性，这些特性与它们的突触连接一起共同塑造了电特性。 神经回路的活动。这特别好地通过由以下表达定义的神经元群体来说明： 钙结合蛋白小清蛋白（PV）。PV中间神经元（PVIs）是稀疏分布的快速尖峰细胞， 为主要神经元提供反馈和前馈抑制。定义最完善的网络功能之一 PVIs的作用是协调神经元网络及其相关振荡。PVI夹带皮质 网络驱动伽马振荡（30-100 Hz）并控制其频率和强度。PVI介导 已知伽马振荡在感觉处理、注意力、工作记忆和 认知.然而，控制PVI功能及其对伽马振荡影响的基因网络仍然存在 不清楚PVI很容易通过环境条件和经验进行修改。PV免疫反应性增加 经过探索新的环境，在环境丰富（EE）下饲养，并自愿运行 （VR）。这些变化发生在与认知相关的大脑区域，包括海马体、前额叶皮质， 和杏仁核行为适应过程中PVI变化的分子机制仍然存在 未知尽管研究表明行为适应影响伽马振荡，但PVI在 行为适应和伽马振荡之间的联系尚未建立。此应用程序需要一个 多学科的方法来解决PVIs如何有助于行为适应的基本问题。 我们的总体假设是，改变PVIs细胞特性的基因表达变化将导致PVIs的发生。 改变网络振荡，使PVIs成为行为适应的关键枢纽。我们将确定 行为适应是否调动了PVIs中的基因网络，并评估这些基因网络的贡献。 PVI生理学和伽马振荡的网络。这个项目结合了赵先生的独特专长 （神经发育的遗传调节）和杰克逊（神经生理学和神经回路）和共同是罗伊 （系统生物学和机器学习）和Rosenberg（计算和系统神经科学）。通过整合 实验数据与基因网络分析和计算建模的多细胞网络，这项工作 将揭示分子/细胞特性的变化如何影响神经回路的涌现特性。