Functional connectomics reveals general wiring rule in mouse visual cortex

• 成果类型: Article
• 署名作者: Ding, Zhuokun; Fahey, Paul G.; Papadopoulos, Stelios; Wang, Eric Y.; Celii, Brendan; Papadopoulos, Christos; Chang, Andersen; Kunin, Alexander B.; Tran, Dat; Fu, Jiakun; Ding, Zhiwei; Patel, Saumil; Ntanavara, Lydia; Froebe, Rachel; Ponder, Kayla; Muhammad, Taliah; Bae, J. Alexander; Bodor, Agnes L.; Brittain, Derrick; Buchanan, Joann; Bumbarger, Daniel J.; Castro, Manuel A.; Cobos, Erick; Dorkenwald, Sven; Elabbady, Leila; Halageri, Akhilesh; Jia, Zhen; Jordan, Chris; Kapner, Dan; Kemnitz, Nico; Kinn, Sam; Lee, Kisuk; Li, Kai; Lu, Ran; Macrina, Thomas; Mahalingam, Gayathri; Mitchell, Eric; Mondal, Shanka Subhra; Mu, Shang; Nehoran, Barak; Popovych, Sergiy; Schneider-Mizell, Casey M.; Silversmith, William; Takeno, Marc; Torres, Russel; Turner, Nicholas L.; Wong, William; Wu, Jingpeng; Yin, Wenjing; Yu, Szi-chieh; Yatsenko, Dimitri; Froudarakis, Emmanouil; Sinz, Fabian; Josic, Kresimir; Rosenbaum, Robert; Seung, H. Sebastian; Collman, Forrest; da Costa, Nuno Macarico; Reid, R. Clay; Walker, Edgar Y.; Pitkow, Xaq; Reimer, Jacob; Tolias, Andreas S.
• 署名单位: Baylor College of Medicine; Baylor College of Medicine; Stanford University; Stanford University; Stanford University; Stanford University; Rice University; Creighton University; Salk Institute; Princeton University; Princeton University; Allen Institute for Brain Science; Princeton University; Massachusetts Institute of Technology (MIT); University of Crete; Foundation for Research & Technology - Hellas (FORTH); Eberhard Karls University of Tubingen; University of Gottingen; University of Gottingen; University of Houston System; University of Houston; University of Notre Dame; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; Rice University; Carnegie Mellon University; Carnegie Mellon University; Stanford University
• 刊物名称: Nature
• ISSN/ISSBN: 0028-3322
• DOI: 10.1038/s41586-025-08840-3
• 发表日期: 2025-04-10
• 关键词: organization; network; reconstruction; architecture; anatomy

摘要

Understanding the relationship between circuit connectivity and function is crucial for uncovering how the brain computes. In mouse primary visual cortex, excitatory neurons with similar response properties are more likely to be synaptically connected1, 2, 3, 4, 5, 6, 7-8; however, broader connectivity rules remain unknown. Here we leverage the millimetre-scale MICrONS dataset to analyse synaptic connectivity and functional properties of neurons across cortical layers and areas. Our results reveal that neurons with similar response properties are preferentially connected within and across layers and areas-including feedback connections-supporting the universality of 'like-to-like' connectivity across the visual hierarchy. Using a validated digital twin model, we separated neuronal tuning into feature (what neurons respond to) and spatial (receptive field location) components. We found that only the feature component predicts fine-scale synaptic connections beyond what could be explained by the proximity of axons and dendrites. We also discovered a higher-order rule whereby postsynaptic neuron cohorts downstream of presynaptic cells show greater functional similarity than predicted by a pairwise like-to-like rule. Recurrent neural networks trained on a simple classification task develop connectivity patterns that mirror both pairwise and higher-order rules, with magnitudes similar to those in MICrONS data. Ablation studies in these recurrent neural networks reveal that disrupting like-to-like connections impairs performance more than disrupting random connections. These findings suggest that these connectivity principles may have a functional role in sensory processing and learning, highlighting shared principles between biological and artificial systems.