Tian, XiaoguangChen, YuyanMajka, PiotrSzczupak, DiegoSanz Perl, YonatanYen, Cecil Chern-ChyiTong, ChuanjunFeng, FuruiJiang, HaitengGlen, DanielDeco, GustavoRosa, Marcello G. P.Silva, Afonso C.Liang, ZhifengLiu, Cirong2023-07-202023-07-202022Tian X, Chen Y, Majka P, Szczupak D, Sanz Perl Y, Yen CCC, Tong C, Feng F, Jiang H, Glen D, Deco G, Rosa MGP, Silva AC, Liang Z, Liu C. An integrated resource for functional and structural connectivity of the marmoset brain. Nat Commun. 2022;13:7416. DOI: 10.1038/s41467-022-35197-22041-1723http://hdl.handle.net/10230/57622Comprehensive integration of structural and functional connectivity data is required to model brain functions accurately. While resources for studying the structural connectivity of non-human primate brains already exist, their integration with functional connectivity data has remained unavailable. Here we present a comprehensive resource that integrates the most extensive awake marmoset resting-state fMRI data available to date (39 marmoset monkeys, 710 runs, 12117 mins) with previously published cellular-level neuronal tracing data (52 marmoset monkeys, 143 injections) and multi-resolution diffusion MRI datasets. The combination of these data allowed us to (1) map the fine-detailed functional brain networks and cortical parcellations, (2) develop a deep-learning-based parcellation generator that preserves the topographical organization of functional connectivity and reflects individual variabilities, and (3) investigate the structural basis underlying functional connectivity by computational modeling. This resource will enable modeling structure-function relationships and facilitate future comparative and translational studies of primate brains.application/pdfeng© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/articlehttp://dx.doi.org/10.1038/s41467-022-35197-2Network modelsNeural circuitsinfo:eu-repo/semantics/openAccess