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: 10132411
• 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/10132411
• 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; 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; rabies viral tracing; 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.

Multi-Pi：Xinyu Zhao，Meyer Jackson，威斯康星大学麦迪逊分校。 标题：经验诱导的基因表达和电路功能的整合 了解细胞，基因网络，神经回路和行为之间的复杂关系需要 可以探测不同类型神经元的分子构，评估其特性并测试的技术 它们在更高级别的功能中的作用。在特定神经元中表达的基因决定了它们 电气性能和这些特性及其突触连通性共同塑造电气 神经回路的活性。通过表达的表达定义的神经元种群，这一点尤其很好地说明了 Ca2+结合蛋白白蛋白（PV）。 PV中间神经元（PVI）是稀疏分布的快速刺激性细胞， 向主神经元提供反馈和喂养抑制。定义最明确的网络功能之一 PVIS是神经元网络及其相关振荡的协调。 PVIS夹带皮质 驱动γ振荡（30-100 Hz）并控制其频率和强度的网络。 PVI介导的 已知γ振荡在感觉处理，注意力，工作记忆和 认识。但是，控制PVI功能及其对γ振荡的影响仍然 不清楚。 PVI很容易通过环境条件和经验来修改。 PV免疫反应性增加 在探索了新的环境之后，在环境丰富（EE）下饲养和自愿跑步之后 （VR）。这些变化发生在与认知相关的大脑区域，包括海马，前额叶皮层， 和杏仁核。行为适应过程中PVI的基础机制仍然存在 未知。尽管研究表明行为适应会影响γ振荡，但PVI在 行为适应与γ振荡之间的联系尚未建立。该应用程序采用 多学科方法解决PVI如何促进行为适应的基本问题。 我们的总体假设是，基因表达的变化改变了PVI的细胞特性 改变网络振荡，使PVI成为行为适应的关键枢纽。我们将确定 行为适应是否动员PVI中的基因网络，并评估这些基因的贡献 PVI生理学和γ振荡的网络。该项目结合了Co-Pis Zhao的独特专业知识 （神经发育的遗传调节）和杰克逊（神经生理学和神经回路）和CO-IS ROY （系统生物学和机器学习）和罗森伯格（计算和系统神经科学）。通过集成 通过基因网络分析和多细胞网络的计算建模的实验数据，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新兴特性。