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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

基本信息

批准号：
10404503
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
项目类别：
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/10404503
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 gene network 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

项目摘要

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.

多圆周率：赵新宇，迈耶·杰克逊，威斯康星大学麦迪逊分校。