美国霍华德休斯医学院Michael B. Reiser研究小组报道了连接体驱动的完整视觉系统的神经清查。相关论文于2025年3月26日发表于国际顶尖学术期刊《自然》杂志上。

在这里，该研究团队展示了雄性黑腹果蝇右视叶的连接体，获得了主题聚焦离子束铣削和扫描电子显微镜。该课题组人员建立了一个视觉神经元的综合清单，并开发了一个计算框架来量化它们的解剖结构。总之，这些数据为解释视觉神经元的形状与空间视觉的关系奠定了基础。通过将这种分析与连接信息、神经递质识别和专家管理相结合，该课题组人员将大约53,000个神经元分为732种类型。这些类型有系统的描述，大约一半是新命名的。最后，研究组分享了与它们的神经元类型目录相匹配的分裂-GAL4系的广泛收集。总的来说，这套全面的工具和数据为系统研究果蝇的视觉提供了新的可能性，并为更深入地理解感觉处理提供了基础。

研究人员表示，视觉为动物提供有关其周围环境的详细信息，并在视觉场景中传达各种特征，如颜色、形状和运动。计算这些平行的空间特征需要一个庞大而多样的神经元网络。因此，从苍蝇到人类，大脑中的视觉区域占其体积的一半。这些视觉区域通常具有明显的结构-功能关系，神经元沿着空间地图和形状组织，直接关系到它们在视觉处理中的作用。一个多世纪的解剖学研究已经详细地编目了苍蝇视觉系统中的细胞类型，平行的行为和生理实验也检验了苍蝇的视觉能力。为了揭示复杂视觉系统的多样性，必须仔细绘制神经结构的地图，并与有针对性地探索该电路的工具相匹配。

附：英文原文

Title: Connectome-driven neural inventory of a complete visual system

Author: Nern, Aljoscha, Loesche, Frank, Takemura, Shin-ya, Burnett, Laura E., Dreher, Marisa, Gruntman, Eyal, Hoeller, Judith, Huang, Gary B., Januszewski, Micha, Klapoetke, Nathan C., Koskela, Sanna, Longden, Kit D., Lu, Zhiyuan, Preibisch, Stephan, Qiu, Wei, Rogers, Edward M., Seenivasan, Pavithraa, Zhao, Arthur, Bogovic, John, Canino, Brandon S., Clements, Jody, Cook, Michael, Finley-May, Samantha, Flynn, Miriam A., Hameed, Imran, Fragniere, Alexandra M. C., Hayworth, Kenneth J., Hopkins, Gary Patrick, Hubbard, Philip M., Katz, William T., Kovalyak, Julie, Lauchie, Shirley A., Leonard, Meghan, Lohff, Alanna, Maldonado, Charli A., Mooney, Caroline, Okeoma, Nneoma, Olbris, Donald J., Ordish, Christopher, Paterson, Tyler, Phillips, Emily M., Pietzsch, Tobias, Salinas, Jennifer Rivas, Rivlin, Patricia K., Schlegel, Philipp, Scott, Ashley L., Scuderi, Louis A., Takemura, Satoko, Talebi, Iris, Thomson, Alexander, Trautman, Eric T., Umayam, Lowell, Walsh, Claire, Walsh, John J., Xu, C. Shan, Yakal, Emily A., Yang, Tansy, Zhao, Ting, Funke, Jan, George, Reed, Hess, Harald F., Jefferis, Gregory S. X. E., Knecht, Christopher, Korff, Wyatt, Plaza, Stephen M., Romani, Sandro, Saalfeld, Stephan, Scheffer, Louis K., Berg, Stuart, Rubin, Gerald M., Reiser, Michael B.

Issue&Volume: 2025-03-26

Abstract: Vision provides animals with detailed information about their surroundings and conveys diverse features such as colour, form and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons. Consequently, from flies to humans, visual regions in the brain constitute half its volume. These visual regions often have marked structure–function relationships, with neurons organized along spatial maps and with shapes that directly relate to their roles in visual processing. More than a century of anatomical studies have catalogued in detail cell types in fly visual systems1,2,3, and parallel behavioural and physiological experiments have examined the visual capabilities of flies. To unravel the diversity of a complex visual system, careful mapping of the neural architecture matched to tools for targeted exploration of this circuitry is essential. Here we present a connectome of the right optic lobe from a male Drosophila melanogaster acquired using focused ion beam milling and scanning electron microscopy. We established a comprehensive inventory of the visual neurons and developed a computational framework to quantify their anatomy. Together, these data establish a basis for interpreting how the shapes of visual neurons relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity and expert curation, we classified the approximately 53,000 neurons into 732 types. These types are systematically described and about half are newly named. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron-type catalogue. Overall, this comprehensive set of tools and data unlocks new possibilities for systematic investigations of vision in Drosophila and provides a foundation for a deeper understanding of sensory processing.

DOI: 10.1038/s41586-025-08746-0

Source: https://www.nature.com/articles/s41586-025-08746-0