Using functionally-defined glomeruli to probe circuit function in the mammalian olfactory bulb

使用功能定义的肾小球探测哺乳动物嗅球的电路功能

• 批准号: 10468288
• 负责人: DALE M WACHOWIAK
• 金额: $ 38.47万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10468288
• 关键词: Adaptive Behaviors; Afferent Neurons; Animals; Behavior; Behavioral Assay; Biological Models; Brain; Cells; Code; Communities; Complex; Data; Detection; Diagnostic; Dorsal; Goals; Image; Individual; Interneurons; Knowledge; Lateral; Lead; Maps; Mediating; Modality; Modeling; Nature; Nervous system structure; Neurons; Neurosciences; Odorant Receptors; Odors; Olfactory Pathways; Organ; Output; Play; Population; Positioning Attribute; Problem Solving; Process; Property; Resources; Role; Sensory; Sensory Process; Shapes; Smell Perception; Specificity; Stimulus; System; Testing; Therapeutic; Time; behavioral response; cell type; driving behavior; experience; experimental study; glomerular function; improved; in vivo; information processing; innovation; insight; network models; neural circuit; novel; olfactory bulb; olfactory bulb glomeruli; olfactory sensory neurons; olfactory stimulus; operation; predictive modeling; relating to nervous system; response; sensory input; sensory prosthesis; sensory system; transmission process

PROJECT SUMMARY We seek to better understand how the brain processes olfactory information by focusing on how circuits of the olfactory bulb control two fundamental aspects of sensory processing: the relationship between sensory input and olfactory bulb output as a function of stimulus intensity, and tuning of response specificity by lateral inhibition. Models of how olfactory bulb circuits mediate these operations exist, but generating and testing rigorous predictions from them has been limited by a lack of understanding of how circuits are organized with respect to olfactory bulb glomeruli. Glomeruli represent individual odorant receptors and so constitute the fundamental unit of information processing at this stage. Our strategy is to overcome this gap by, first, better defining the functional map of odor 'space' across glomeruli of the dorsal olfactory bulb. To achieve this we will functionally define glomeruli in terms of the odorants to which they have maximal sensitivity as well as their relative sensitivities across a carefully-selected odorant panel, yielding the first `odor sensitivity' map of the dorsal olfactory bulb and allowing for the rapid and reliable identification of individual glomeruli across animals. We will use these data to uncover new insights into the organization of glomerular odor maps and to generate a public resource for further exploration by the neuroscience community. We will next use this knowledge to rigorously test alternative models for how specific circuits shape the input-output functions of the olfactory bulb by comparing intensity-response functions of sensory inputs and glomerular outputs and by selectively removing particular interneuron types from the olfactory bulb network. We will also test alternative models for how inhibitory connections between different glomeruli are organized and how they may be shaped by odor experience, using odorants that selectively activate different combinations of identified glomeruli. Our experimental strategy builds on innovative approaches that are key to achieving a new level of understanding of how odor representations are transformed by olfactory bulb circuits. First, we are able to repeatedly identify and target many glomeruli across the dorsal olfactory bulb using a small number of diagnostic odorants and to efficiently map responses to many odorants in a single experiment. Second, we are able to selectively image from sensory inputs to glomeruli, projection neuron outputs from glomeruli, or both simultaneously, allowing us to precisely characterize input-output transformations by olfactory circuits. Finally, we will develop an improved model of the olfactory bulb network that is highly constrained by experimental data and which should lead to new insights into how this network alters odor representations and enable new predictions that can be tested with further circuit manipulations or behavioral assays.

项目概要 我们试图通过关注电路如何处理嗅觉信息来更好地理解大脑如何处理嗅觉信息。 嗅球控制感觉处理的两个基本方面：感觉之间的关系 输入和嗅球输出作为刺激强度的函数，并通过横向调整响应特异性 抑制。嗅球电路如何介导这些操作的模型是存在的，但需要生成和测试 由于缺乏对电路如何组织的理解，他们的严格预测受到限制 关于嗅球肾小球。肾小球代表个体气味受体，因此构成 这一阶段信息处理的基本单位。 我们的策略是克服这一差距，首先，更好地定义气味“空间”的功能图 背侧嗅球的肾小球。为了实现这一目标，我们将在功能上定义肾小球 他们对其具有最大敏感性的气味剂以及在精心选择的范围内的相对敏感性 气味面板，产生第一个背侧嗅球的“气味敏感性”图，并允许快速和 可靠地识别动物个体肾小球。我们将利用这些数据来发现新的见解 组织肾小球气味图并生成公共资源以供进一步探索 神经科学界。接下来我们将利用这些知识来严格测试替代模型的具体效果 电路通过比较嗅球的强度响应函数来塑造嗅球的输入输出函数 感觉输入和肾小球输出，并通过选择性地从神经元中去除特定的中间神经元类型 嗅球网络。我们还将测试不同模型之间的抑制连接如何 肾小球的组织方式以及它们如何通过气味体验而形成，使用选择性的气味剂 激活已识别肾小球的不同组合。 我们的实验策略建立在创新方法的基础上，这些方法是实现新水平的关键 了解嗅球电路如何转换气味表征。首先，我们能够 使用少量的重复识别和瞄准背嗅球上的许多肾小球 诊断气味剂并在一次实验中有效绘制对多种气味剂的反应。其次，我们是 能够选择性地从肾小球的感觉输入、肾小球的投影神经元输出或两者进行成像 同时，使我们能够通过嗅觉电路精确地表征输入输出转换。 最后，我们将开发一个改进的嗅球网络模型，该模型受到以下因素的高度约束： 实验数据，这应该会带来关于该网络如何改变气味表征的新见解 实现新的预测，可以通过进一步的电路操作或行为分析进行测试。