Mechanisms of Active Sensing in Drosophila

这个项目的目标是研究活跃感觉的细胞基础。所有神经系统的一个关键功能是区分来自外部世界的感觉刺激和由我们自己的运动产生的感觉刺激。这项任务依赖于将感觉信息与自我产生的运动的内部模型或预期相结合的大脑回路。用于研究主动感知的许多模型的复杂性和难治性意味着将这些研究的见解转化为正常神经系统功能的失败仍然具有挑战性。果蝇（Drosophila melanogaster）主动移动它们的触角，我最近的工作已经阐明了处理来自触角的机械感觉信息的神经回路。鉴于果蝇作为遗传模式生物的能力，本项目旨在开发控制和感知触角运动的神经回路，作为研究主动感知原理的细胞模型。在这项资助的K99（指导）部分，我将确定自我和外部产生的机械感觉信号在大脑中表现不同的细胞位置。我将对二阶和三阶机械感觉神经元的细胞内活动进行电生理记录，并比较这两种神经元如何编码被动和主动的触角运动。我将使用机器学习分析同时录制的视频数据来区分这两种类型的动作。对于R00（独立）期，我将使用光遗传学和免疫组织化学来识别控制触角运动的运动神经元。然后我会问运动神经元的输入是在哪里冲击到感觉回路的。最后，我将测试主动触角运动在行为中的作用。通过干扰自由行走和飞行的苍蝇的主动触角运动，我将直接测试这些运动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，以及它们在目标导向行为中的作用。

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.