研究人员绘制了整个昆虫大脑（果蝇幼虫）的突触分辨率连接组，包括学习、价值计算和行动选择，包括3016个神经元和548000个突触。研究人员描述了神经元类型、枢纽、前馈和反馈途径，以及跨半球和脑-神经线的相互作用。研究人员发现了普遍的多感官和半球间的整合、高度反复的结构、来自下行神经元的丰富反馈以及多个新的回路模体。大脑中最为反复的回路由学习中心的输入和输出神经元组成。一些结构特征，包括多层捷径和嵌套的反复回路，类似于最先进的深度学习架构。这个确定的大脑架构为未来的神经回路的实验和理论研究提供了基础。
据介绍，大脑包含相互连接的神经元网络，因此了解网络结构对于理解大脑功能至关重要。
附：英文原文
Title: The connectome of an insect brain
Author: Michael Winding, Benjamin D. Pedigo, Christopher L. Barnes, Heather G. Patsolic, Youngser Park, Tom Kazimiers, Akira Fushiki, Ingrid V. Andrade, Avinash Khandelwal, Javier Valdes-Aleman, Feng Li, Nadine Randel, Elizabeth Barsotti, Ana Correia, Richard D. Fetter, Volker Hartenstein, Carey E. Priebe, Joshua T. Vogelstein, Albert Cardona, Marta Zlatic
Issue&Volume: 2023-03-10
Abstract: Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain’s most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.
DOI: add9330
Source: https://www.science.org/doi/10.1126/science.add9330