Mechanisms of Active Sensing in Drosophila

项目摘要 这个项目的目标是研究主动感觉的细胞学基础。所有神经系统的重要功能 是区分来自外部世界的感觉刺激和由我们自己产生的感觉刺激 动静。这项任务依赖于将感觉信息与内部模型相结合的大脑回路，或者 期望，对自我产生的运动的期望。用于研究主动性的多种模型的复杂性和难解性 感知意味着将这些研究的洞察力转化为正常神经系统功能的故障 很有挑战性。果蝇(黑腹果蝇)主动移动触角，我最近的工作 阐明了处理来自天线的机械感觉信息的神经电路。鉴于……的力量 果蝇作为一种遗传模式生物，本项目旨在开发控制和感知的神经回路 天线运动作为研究主动感知原理的细胞模型。在K99(指导)部分 在这笔赠款中，我将确定自我和外部产生的机械感觉信号的蜂窝位置 在大脑中有不同的表现。我会做细胞内活动的电生理记录 从二阶和三阶机械感觉神经元，比较这两个群体如何编码被动和 触角的主动运动。我会用机器来区分这两种动作 同时记录的视频数据的学习分析。对于R00(独立)阶段，我将使用 光遗传学和免疫组织化学以确定控制触角运动的运动神经元。那我会的 询问来自运动神经元的输入在哪里影响感觉回路。最后，我将测试有源天线的作用 行为上的变化。通过干扰自由行走和飞行的苍蝇的主动触角运动，我将直接 测试这些动作如何实现不同的行为任务，如风向和避障。 总之，这些实验将确定果蝇主动感知的细胞基础，以及它们在目标- 定向行为。

Project Summary The goal of this project is to study the cellular basis of active sensation. A crucial function of all nervous systems is to distinguish between sensory stimuli originating from the external world and that generated by our own movements. This task relies on brain circuits that integrate sensory information with an internal model, or expectation, of self-generated movements. The complexity and intractability of many models used to study active sensing means that translating insights from these studies to failures of normal nervous system function remains challenging. Fruit flies (Drosophila melanogaster) actively move their antennae, and my recent work has elucidated a neural circuit that processes mechanosensory information from the antenna. Given the power of Drosophila as a genetic model organism, this project aims to develop the neural circuits controlling and sensing antennal movement as a cellular model for studying principles of active sensing. In the K99 (mentored) portion of this grant, I will identify the cellular location at which self- versus externally-generated mechanosensory signals become differentially represented in the brain. I will make electrophysiological recordings of intracellular activity from 2nd and 3rd order mechanosensory neurons and compare how these two populations encode passive and active movements of the antennae. I will distinguish between these two types of movements using machine learning analysis of simultaneously recorded video data. For the R00 (independent) phase, I will use optogenetics and immunohistochemistry to identify motor neurons that control antennal movement. I will then ask where input from motor neurons impinge on the sensory circuit. Finally, I will test the role of active antennal movements in behavior. By perturbing active antennal movements in freely walking and flying flies, I will directly test how these movements enable different behavioral tasks such as wind orientation and obstacle avoidance. Together, these experiments will identify the cellular basis for active sensing in Drosophila, and their role in goal- oriented behaviors.