2022BBSRC-NSF/BIO Generating New Network Analysis Tools for Elucidating the Functional Logic of 3D Vision Circuits of the Drosophila Brain

2022BBSRC-NSF/BIO 生成新的网络分析工具来阐明果蝇大脑 3D 视觉电路的功能逻辑

• 批准号: BB/Y000234/1
• 负责人: Mikko Ilmari Juusola
• 金额: $ 107.95万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FY000234%2F1
• 关键词: 2022BBSRC; NSF; BIO; Generating; New

Human eyes constantly exert small-scale motions called microsaccades. The functional role of microsaccades in perceiving the visual world remains a mystery. The lack of suitable tools and methodologies has limited our understanding of how animals see the 3-dimensional visual world and control their movements. The primate eyes and brain have hindered simultaneous live imaging of large-scale clusters of neurons at cellular resolution. Conversely, approaches using small-brain model organisms, such as the fruit fly (Drosophila) and zebrafish, have focussed on assigning motion detection and colour discrimination tasks to single neurons and circuits. Recently, it has been discovered that the photoreceptors in the retina of the fruit fly are also subject to light-induced and muscle-induced retinal movements such as microsaccades. It was shown in the fruit fly that light-induced microsaccades play a key role in depth perception of stereo vision. In this proposal, we aim to generate novel tools to elucidate how Drosophila brain circuits work dynamically at subcellular resolution in the biochemical domain. These tools integrate activity recordings in the living eye and biological brain circuits with graph analysis, multiscale modelling, active visual sampling, and connectomics/synaptomics models of computation. Building on this integration, we will investigate how active sampling in the retina supports Drosophila visual networks to encode 3-dimensional object information. Our novel multidisciplinary approach will generate new open-source software tools that will be invaluable for the neuroscience community exploring how stereoscopic perception of 3D objects emerges from the complex synaptic interactions of the eyes' and brain's visual circuits. Individually and collectively, these tools will potentially have broad impact well beyond the immediate goal of elucidating the functional logic of 3D vision circuits in the Drosophila.

人眼不断地进行称为微扫视的小范围运动。微跳视在感知视觉世界中的功能作用仍然是一个谜。缺乏合适的工具和方法限制了我们对动物如何看待 3 维视觉世界并控制其运动的理解。灵长类动物的眼睛和大脑阻碍了以细胞分辨率对大规模神经元簇进行同步实时成像。相反，使用小脑模型生物（例如果蝇（果蝇）和斑马鱼）的方法侧重于将运动检测和颜色辨别任务分配给单个神经元和电路。最近，人们发现果蝇视网膜中的光感受器也会受到光诱导和肌肉诱导的视网膜运动（例如微跳视）的影响。在果蝇中，光诱导的微跳视在立体视觉的深度感知中发挥着关键作用。在本提案中，我们的目标是生成新的工具来阐明果蝇大脑回路如何在生化领域的亚细胞分辨率下动态工作。这些工具将活体眼睛和生物大脑回路中的活动记录与图形分析、多尺度建模、主动视觉采样和连接组学/突触组学模型相结合。在此集成的基础上，我们将研究视网膜中的主动采样如何支持果蝇视觉网络编码 3 维物体信息。我们新颖的多学科方法将产生新的开源软件工具，这对于神经科学界探索 3D 物体的立体感知如何从眼睛和大脑视觉回路的复杂突触相互作用中产生的过程来说非常宝贵。无论是单独还是集体，这些工具都可能产生广泛的影响，远远超出阐明果蝇 3D 视觉回路功能逻辑的直接目标。