Neural Circuit Mechanisms Underlying Dynamic Stimulus Selection

项目摘要/摘要 想象一下，一名棒球外野手在追踪一个飞球。为了成功接球，玩家不能得到 被一只飞过的鸟分散注意力，即使它的大小和明显的运动与球相似。这 是在干扰因素存在的情况下选择和维持刺激的一个具有挑战性的例子，但 我们每时每刻都在做这类任务。然而，大脑如何在内部代表多个对象和 协调不同神经群体的活动以执行选择过程 仍然难以捉摸。在哺乳动物的大脑中，神经元的绝对数量、复杂的投射和分布 参与刺激选择过程的神经元(例如，注意力)使其具有将所有 它们彼此之间的联系，并破译网络的动态。 果蝇黑腹果蝇会自然地定向(选择)和跟踪(保持选择 指)虚拟现实竞技场中众多物体中的一个，一种受苍蝇导航影响的行为 系统。在一个数字简单的大脑(大约150,000个神经元)中，这种明确的读数提供了 无与伦比的机会来研究多个不同的神经元群体如何调节刺激 选择和维护。此外，果蝇丰富的遗传工具使其成为可能 可重复地标记和操作相同数量的神经元，从动物到 生理学实验中的动物。 拟议的研究在微电路水平上建立了量化的理解，并最终 在多个神经种群中，(1)动物如何从许多刺激中选择 体现在多个水平的视觉处理上，(2)刺激选择如何决定 对上游视觉神经元的信息处理的影响，最后，(3)内部 饥饿和运动等大脑状态会调节刺激选择。 这项提议描述了一种新颖而强大的实验方法。我们将使用多色 双光子钙成像技术用于记录构成大脑的不同神经元群的活动 苍蝇的导航系统，同时在虚拟现实舞台上监控苍蝇的飞行行为。这个 我们将开发的技术还包括同步、高分辨率(空间和时间) 光遗传刺激，允许我们探索多种群神经动力学和相互作用 具有单细胞分辨率。我们将开发单细胞级别的计算模型，并测试 视觉(环)神经元的群体活动和标志性选择(COMPASS)神经元的反馈 它们相互作用，并相互作用于苍蝇的内部状态。该项目的成功实施将为 对刺激选择背后的多种群动态的第一个具体理解。

Project Summary/Abstract Imagine a baseball outfielder tracking a fly ball. To catch it successfully, the player must not get distracted by a passing bird, even if it has a similar size and apparent motion similar to the ball. This is a challenging example of stimulus selection and maintenance in the presence of distractors, but we all do this sort of task every moment. Yet how brains internally represent multiple objects and coordinate activities across diverse neural populations to perform the selection process has remained elusive. In mammalian brains, the sheer number, complex projections and distribution of neurons involved in stimulus selection processes (e.g., attention) make it challenging to visualize all their connections to one another and decipher the dynamics of the network. The fruit fly Drosophila melanogaster will naturally orient to (select) and track (maintain selection of) an object among many in a virtual reality arena, a behavior influenced by the fly’s navigation system. This unambiguous readout in a numerically simple brain (~150,000 neurons) provides an unparalleled opportunity to investigate how multiple distinct populations of neurons mediate stimulus selection and maintenance. Further, Drosophila’s rich genetic tools make it feasible and straightforward to reproducibly label and manipulate the same population of neurons from animal to animal in physiological experiments. The proposed studies build a quantitative understanding, at the microcircuit level and ultimately across multiple neural populations, of: (1) how an animal’s selection of a stimulus among many manifests across multiple levels of visual processing, (2) how the stimulus selection decision impinges on information processing in the upstream visual neurons, and, finally, (3) how internal brain states such as hunger and locomotion modulate stimulus selection. This proposal describes a novel and powerful experimental approach. We will use multi-color two-photon calcium imaging to record the activity of distinct neuronal populations that constitute the fly's navigation system while monitoring the fly’s flight behavior in a virtual reality arena. The technique we will develop also incorporates simultaneous, high resolution (spatial and temporal) optogenetic stimulation, which allows us to probe multi-population neural dynamics and interactions with single-cell resolution. We will develop single-cell level computational models and test how the population activity of visual (ring) neurons and feedback from landmark-selective (compass) neurons interact with each other and the fly’s internal states. This project's successful execution will provide the first concrete understanding of multi-population dynamics underlying stimulus selection.