Generation and manipulation of combinatorial connectivity in olfactory perception

嗅觉感知中组合连接的生成和操纵

• 批准号: 10569889
• 负责人: Eleanor Josephine Clowney
• 金额: $ 3.16万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10569889
• 关键词: Acute; Adaptive Immune System; Address; Afferent Neurons; Anatomy; Animals; Antibodies; Architecture; Area; Arthropods; Axon; B-Lymphocytes; Behavior; Behavioral; Binding; Biological Models; Brain; Brain region; Cell surface; Cells; Cerebellum; Complex; Data; Development; Dimensions; Drosophila genus; Drosophila melanogaster; Environment; Generations; Genes; Genetic; Goals; Hippocampus (Brain); Human; Immunoglobulins; Individual; Instinct; Invertebrates; Investigation; Knowledge; Label; Learning; Memory; Methods; Modeling; Molecular Profiling; Mus; Mushroom Bodies; Neurons; Odors; Olfactory Cortex; Olfactory Learning; Olfactory Pathways; Partner in relationship; Pattern; Perception; Pharmacology; Property; Pyramidal Cells; Research Personnel; Sensory; Signal Transduction; Site; Smell Perception; Stimulus; Structure; Synapses; System; Techniques; Testing; Tweens; Variant; classical conditioning; combinatorial; density; entorhinal cortex; expectation; experience; experimental study; feature detection; flexibility; granule cell; neural circuit; novel; piriform cortex; postsynaptic; presynaptic; prevent; receptor; relating to nervous system; response; sensory input; sensory stimulus; theories; tool

ABSTRACT The central problem addressed by this proposal is how the brain represents almost limitless objects to “catego-rize an unlabeled world” (Edelman, 1976). This problem is particularly acute in olfaction, because physical odor signals are not obviously dimensional. While instinctual meanings are imparted through the structure of neural circuits, learning mechanisms can theoretically select experience-relevant representations from circuits lacking a priori structure. By analogy, the vertebrate adaptive immune system defends against novel invaders by se-lectively amplifying B cells carrying strongly binding antibodies from a randomly produced pool. How unstruc-tured, combinatorial connectivity forms during development is not understood in any system. The numerical complexity of vertebrate olfactory cortex and other associative learning centers including the cerebellum, hip-pocampus, and entorhinal cortex complicates developmental studies. Instead, we propose to address this question in the numerically simplified olfactory learning center of arthropods, the mushroom body. While this brain area performs a function similar to the cortex or cerebellum, representing objects as combinations of sen-sory stimuli, the fruit fly mushroom body has only 2000 intrinsic neurons. These intrinsic Kenyon cells receive 3-10 olfactory inputs, with each cell receiving different inputs. The sets of inputs to individual Kenyon cells are unpredictable—knowing one input to a particular cell does not illuminate which other inputs that cell receives. To ask how unstructured connectivity pattern forms during development, we are first using a variety of tech-niques to manipulate the ratio between Kenyon cells and their incoming olfactory inputs in order to identify mechanisms that set the number of inputs to individual Kenyon cells. Second, we are testing whether variation in expression of cell surface molecules across pre- and post-synaptic cells allows variation in connectivity be-tween them. The quantitative complexity and density of sensory inputs to associative brain areas are theorized to “optimize” representations of sensory objects, with alterations in these patterns expected to degrade neural and behavioral distinctions among stimuli. If successful, we will produce a model of the developmental mecha-nisms that generate neurons responding to complex sensory stimuli that can be applied to studying develop-ment and organization of sensory inputs to vertebrate associative learning areas; this study will also create techniques to manipulate the wiring parameters of the Drosophila mushroom body to explicitly test how wiring parameters dictate stimulus representation and separation, and how their alteration alters perception and learning.

摘要 这一提议所解决的核心问题是，大脑如何代表几乎无限的对象，以“catego-rize一个未标记的世界”（Edelman，1976）。这个问题在嗅觉中尤为严重，因为物理气味 信号不是明显的维度。虽然本能的意义是通过神经结构传递的， 理论上，学习机制可以从缺乏经验的回路中选择与经验相关的表征。 先验结构以此类推，脊椎动物的适应性免疫系统通过从随机产生的库中选择性扩增携带强结合抗体的B细胞来防御新的入侵者。在发育过程中，非结构化的组合连接性是如何形成的，在任何系统中都不清楚。数值 脊椎动物的嗅觉皮层和其他包括小脑、海马和内嗅皮层在内的联合学习中心的复杂性使发育研究复杂化。相反，我们建议解决这个问题， 问题的数字简化嗅觉学习中心的节肢动物，蘑菇体。虽然这 虽然果蝇的大脑区域执行类似于皮质或小脑的功能，将物体表示为感觉刺激的组合，但果蝇的蘑菇体只有2000个内在神经元。这些内在的凯尼恩细胞接受 3-10嗅觉输入，每个细胞接收不同的输入。单个凯尼恩细胞的输入集为 不可预测--知道对特定单元的一个输入并不说明该单元接收哪些其他输入。 为了探究非结构化连接模式在发育过程中是如何形成的，我们首先使用各种技术来操纵Kenyon细胞与其传入嗅觉输入之间的比率，以识别 设置输入到单个凯尼恩细胞的数量的机制。第二，我们正在测试变化是否 在突触前和突触后细胞中细胞表面分子的表达允许它们之间连接性的变化。定量的复杂性和密度的感觉输入联想脑区的理论 “优化”感官对象的表征，这些模式的改变预计会降低神经元的功能， 以及刺激之间的行为差异。如果成功，我们将建立一个产生神经元对复杂感觉刺激反应的发育机制模型，可用于研究脊椎动物联想学习区感觉输入的发育和组织;这项研究还将建立一个神经元对复杂感觉刺激反应的模型。 技术来操纵果蝇蘑菇体的布线参数，以明确测试布线如何 参数决定刺激的表示和分离，以及它们的改变如何改变感知， 学习