连接体
神经科学
计算机科学
连接组学
神经元
生物神经网络
生物
功能连接
作者
Michael Winding,Benjamin D. Pedigo,Christopher L. Barnes,Heather G. Patsolic,Youngser Park,Tom Kazimiers,Akira Fushiki,Ingrid Andrade,Avinash Khandelwal,Javier Valdés-Alemán,Feng Li,Nadine Randel,Elizabeth Barsotti,Ana Correia,Richard D. Fetter,Volker Hartenstein,Carey E. Priebe,Joshua T Vogelstein,Albert Cardona,Marta Zlatic
出处
期刊:
[Cold Spring Harbor Laboratory]
日期:2022-11-28
被引量:8
标识
DOI:10.1101/2022.11.28.516756
摘要
Abstract Brains contain networks of interconnected neurons, so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an insect brain ( Drosophila larva) with rich behavior, including learning, value-computation, and action-selection, comprising 3,013 neurons and 544,000 synapses. We characterized neuron-types, hubs, feedforward and feedback pathways, and 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 powerful machine learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits. One-Sentence Summary We generated a synaptic-resolution brain connectome and characterized its connection types, neuron types, and circuit motifs.
科研通智能强力驱动
Strongly Powered by AbleSci AI