An integrated resource for functional and structural connectivity of the marmoset brain

Xiaoguang Tian (), Yuyan Chen, Piotr Majka, Diego Szczupak, Yonatan Sanz Perl, Cecil Chern-Chyi Yen, Chuanjun Tong, Furui Feng, Haiteng Jiang, Daniel Glen, Gustavo Deco, Marcello G. P. Rosa (), Afonso C. Silva (), Zhifeng Liang () and Cirong Liu ()
Additional contact information
Xiaoguang Tian: University of Pittsburgh
Yuyan Chen: Chinese Academy of Sciences
Piotr Majka: Nencki Institute of Experimental Biology of the Polish Academy of Sciences
Diego Szczupak: University of Pittsburgh
Yonatan Sanz Perl: Universitat Pompeu Fabra
Cecil Chern-Chyi Yen: National Institutes of Health (NINDS/NIH)
Chuanjun Tong: Chinese Academy of Sciences
Furui Feng: Chinese Academy of Sciences
Haiteng Jiang: Zhejiang University School of Medicine
Daniel Glen: National Institutes of Health (NIMH/NIH)
Gustavo Deco: Universitat Pompeu Fabra
Marcello G. P. Rosa: Monash University
Afonso C. Silva: University of Pittsburgh
Zhifeng Liang: Chinese Academy of Sciences
Cirong Liu: Chinese Academy of Sciences

Nature Communications, 2022, vol. 13, issue 1, 1-17

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41467-022-35197-2

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