Learning-mediated plasticity in cortical feedback projections to the olfactory bulb

学习介导的皮质反馈投射到嗅球的可塑性

• 批准号: 10598602
• 负责人: Joseph Donald Zak
• 金额: $ 24.9万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10598602
• 关键词: Acute; Advisory Committees; Alzheimer' s Disease; Animals; Area; Award; Axon; Back; Behavioral; Brain; Cells; Central Nervous System; Classification; Complex; Complex Mixtures; Detection; Development; Diagnostic; Disease; Environment; Etiology; Feedback; Future; Genetic; Goals; Individual; Interneurons; Ion Channel Gating; Laboratories; Learning; Measurement; Measures; Mediating; Mentors; Modality; Modification; Mus; Neurodegenerative Disorders; Neurons; Neurosciences; Odors; Olfactory Pathways; Olfactory dysfunction; Optics; Outcome; Outcome Study; Output; Parkinson Disease; Pattern; Phase; Physiological; Play; Population; Positioning Attribute; Process; Property; Research Personnel; Rewards; Role; Scheme; Sensory; Shapes; Site; Stimulus; Symptoms; Synapses; Technical Expertise; Testing; Training; Universities; Update; Vision; Weight; Work; awake; calcium indicator; experience; experimental study; granule cell; in vivo; innovation; insight; light gated; multiphoton microscopy; nerve supply; neural circuit; novel; novel strategies; olfactory bulb; optogenetics; piriform cortex; postsynaptic; response; sensory input; sensory stimulus; sensory system

PROJECT SUMMARY/ABSTRACT To reliably encode information about the environment, neurons must modify their activity profiles and even connectivity to accurately interpret complex stimuli. Cortical feedback projections to the olfactory bulb are uniquely positioned at the interface between detection-based processing that is driven by sensory input and analytical processing occurring in the piriform cortex. This arrangement makes these projections an ideal target to study how learning reshapes neuronal activity profiles. I have developed an approach that will allow for a comprehensive analysis of the axonal activity of principal neurons in the piriform cortex, while mice learn a task requiring them to identify a specific odor embedded in complex mixtures, thereby providing unique insight into olfactory scene analysis. My approach will also provide a detailed analysis of the connectivity between cortical axons and their postsynaptic targets in the olfactory bulb, which will reveal how the olfactory bulb integrates processed information from the piriform cortex. The hypothesis I will test is that learning reshapes cortico-fugal input to the olfactory bulb, leading to enhanced odor-scene segmentation through the disambiguation of olfactory bulb output neuron activity profiles. The outcomes of these studies will provide novel insight to how the brain to updates its stimulus-encoding scheme from a synthetic to analytical representation of a stimulus environment. The studies proposed here are novel technically as well as conceptually, and the results will be broadly applicable to other sensory systems. In Aim 1, I will characterize how learning shapes the activity of cortical feedback projections to the olfactory bulb. Aim 2 will determine how the synaptic strength and number of cortical inputs to individual olfactory modules are updated during learning. Finally, Aim 3 will determine how cortical input shapes the activity profiles of bulbar output neurons. The training phase of this award will be conducted at Harvard University in the laboratories of Prof. Venkatesh Murthy and Prof. Naoshige Uchida. Together with my mentors and advisory committee, I have developed a comprehensive training plan that will provide me with new technical skills and provide professional development that will enable my successful transition to an independent investigator. The completion of this project will provide the basis for future experiments related to learning-mediated plasticity in the olfactory system and other sensory systems.

项目总结/摘要 为了可靠地编码有关环境的信息，神经元必须修改它们的活动轮廓，甚至 连接，以准确地解释复杂的刺激。大脑皮层对嗅球的反馈投射是 唯一定位在由感官输入驱动的基于检测的处理和 在梨状皮质中进行的分析处理。这种安排使这些投影成为理想的目标 来研究学习是如何重塑神经元活动的。我发明了一种方法 在小鼠学习任务时，梨状皮质中主要神经元的轴突活动的综合分析 要求他们识别复杂混合物中嵌入的特定气味，从而提供独特的见解， 嗅觉场景分析我的方法还将提供一个详细的分析， 轴突和它们在嗅球中的突触后靶点，这将揭示嗅球如何整合 处理来自梨状皮质的信息我将要检验的假设是，学习重塑了离皮质神经元 输入到嗅球，通过消除 嗅球输出神经元活动曲线。这些研究的结果将提供新的见解，如何 大脑将其刺激编码方案从刺激的合成表示更新为分析表示 环境这里提出的研究在技术上和概念上都是新颖的，其结果将是 广泛适用于其他感官系统。在目标1中，我将描述学习如何塑造 皮层反馈投射到嗅球。目标2将确定突触强度和数量 在学习过程中，皮层对各个嗅觉模块的输入会被更新。最后，目标3将确定如何 皮质输入塑造延髓输出神经元的活动轮廓。该奖项的培训阶段将是 在哈佛大学Venkatesh Murthy教授和Naoshige Uchida教授的实验室进行。 我与我的导师和咨询委员会一起制定了一个全面的培训计划， 为我提供新的技术技能，并提供专业发展，使我能够成功 过渡到独立调查员。该项目的完成将为今后的 与嗅觉系统和其他感觉系统中学习介导的可塑性相关的实验。