@article{19765b428cac4f9fb950a775e9238872,
title = "An integrated resource for functional and structural connectivity of the marmoset brain",
abstract = "Comprehensive 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.",
author = "Xiaoguang Tian and Yuyan Chen and Piotr Majka and Diego Szczupak and Perl, {Yonatan Sanz} and Yen, {Cecil Chern Chyi} and Chuanjun Tong and Furui Feng and Haiteng Jiang and Daniel Glen and Gustavo Deco and Rosa, {Marcello G.P.} and Silva, {Afonso C.} and Zhifeng Liang and Cirong Liu",
note = "Funding Information: We thank Kaiwei Zhang and Binshi Bo at the 9.4T core facility (CEBSIT) for assistance in the data collection of the ION data, Lisa Zhang for the assistance in the data collection of the NIH 7T data, the Marmoset Animal Facility of CEBSIT for animal care, Xiaojia Zhu for the assistance in organizing MRI data in BIDS format, and the NIH Fellows Editorial Board for the editorial assistance on the early version of the manuscript. The study was supported by the grants from National Science and Technology Innovation 2030 Major Project of China (2022ZD0205000, 2021ZD0203900), the Pennsylvania Department of Health Commonwealth Universal Research Enhancement (CURE) Tobacco Settlement Appropriation – Phase 18 (Grant SAP4100083102 to ACS), the US National Institute on Aging (Grants R24AG073190 and U19AG074866 to ACS), the Shanghai Municipal Science and Technology Major Project (no. 2018SHZDZX05 to C.L. and Z.F.), the Lingang Laboratory (Grant no. LG-QS-202201-02 to C.L.), the National Natural Science Foundation of China (no. 32171088 to C.L.), the Australian Research Council (DP110101200, DP140101968, CE140100007) and National Health and Medical Research Council (APP1194206) to M.R., National Science Centre (2019/35/D/NZ4/03031 to P.M.), NIH Intramural Research Programs (ZIA NS003041 to A.S. and C.Y., ZICMH002888 to D.G.), International Neuroinformatics Coordinating Facility Seed Funding Grant (to P.M. and M.R.), a Spanish research project funded by the Spanish Ministry of Science, Innovation, and Universities (MCIU), State Research Agency (AEI), and European Regional Development Funds (FEDER) (ref. PID2019-105772GB-I00 AEI FEDER EU to G.D.), HBP SGA3 Human Brain Project Specific Grant Agreement 3 (grant agreement no. 945539 to G.D.), and the EU H2020 FET Flagship program and SGR Research Support Group support (ref. 2017 SGR 1545 to G.D.). Funding Information: We thank Kaiwei Zhang and Binshi Bo at the 9.4T core facility (CEBSIT) for assistance in the data collection of the ION data, Lisa Zhang for the assistance in the data collection of the NIH 7T data, the Marmoset Animal Facility of CEBSIT for animal care, Xiaojia Zhu for the assistance in organizing MRI data in BIDS format, and the NIH Fellows Editorial Board for the editorial assistance on the early version of the manuscript. The study was supported by the grants from National Science and Technology Innovation 2030 Major Project of China (2022ZD0205000, 2021ZD0203900), the Pennsylvania Department of Health Commonwealth Universal Research Enhancement (CURE) Tobacco Settlement Appropriation – Phase 18 (Grant SAP4100083102 to ACS), the US National Institute on Aging (Grants R24AG073190 and U19AG074866 to ACS), the Shanghai Municipal Science and Technology Major Project (no. 2018SHZDZX05 to C.L. and Z.F.), the Lingang Laboratory (Grant no. LG-QS-202201-02 to C.L.), the National Natural Science Foundation of China (no. 32171088 to C.L.), the Australian Research Council (DP110101200, DP140101968, CE140100007) and National Health and Medical Research Council (APP1194206) to M.R., National Science Centre (2019/35/D/NZ4/03031 to P.M.), NIH Intramural Research Programs (ZIA NS003041 to A.S. and C.Y., ZICMH002888 to D.G.), International Neuroinformatics Coordinating Facility Seed Funding Grant (to P.M. and M.R.), a Spanish research project funded by the Spanish Ministry of Science, Innovation, and Universities (MCIU), State Research Agency (AEI), and European Regional Development Funds (FEDER) (ref. PID2019-105772GB-I00 AEI FEDER EU to G.D.), HBP SGA3 Human Brain Project Specific Grant Agreement 3 (grant agreement no. 945539 to G.D.), and the EU H2020 FET Flagship program and SGR Research Support Group support (ref. 2017 SGR 1545 to G.D.). Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
month = dec,
doi = "10.1038/s41467-022-35197-2",
language = "English",
volume = "13",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",
}