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

Author

Listed:
  • Xiaoguang Tian

    (University of Pittsburgh)

  • Yuyan Chen

    (Chinese Academy of Sciences)

  • Piotr Majka

    (Nencki Institute of Experimental Biology of the Polish Academy of Sciences
    Monash University)

  • Diego Szczupak

    (University of Pittsburgh)

  • Yonatan Sanz Perl

    (Universitat Pompeu Fabra
    Universidad de San Andrés)

  • 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
    Zhejiang University)

  • Daniel Glen

    (National Institutes of Health (NIMH/NIH))

  • Gustavo Deco

    (Universitat Pompeu Fabra
    Institució Catalana de la Recerca i Estudis Avançats (ICREA)
    Max Planck Institute for Human Cognitive and Brain Sciences
    Monash University, Melbourne)

  • Marcello G. P. Rosa

    (Monash University)

  • Afonso C. Silva

    (University of Pittsburgh)

  • Zhifeng Liang

    (Chinese Academy of Sciences
    Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai)

  • Cirong Liu

    (Chinese Academy of Sciences
    Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai
    Lingang Laboratory
    University of Chinese Academy of Sciences)

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.

Suggested Citation

  • 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 & , 2022. "An integrated resource for functional and structural connectivity of the marmoset brain," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35197-2
    DOI: 10.1038/s41467-022-35197-2
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    References listed on IDEAS

    as
    1. Adrián Ponce-Alvarez & Gustavo Deco & Patric Hagmann & Gian Luca Romani & Dante Mantini & Maurizio Corbetta, 2015. "Resting-State Temporal Synchronization Networks Emerge from Connectivity Topology and Heterogeneity," PLOS Computational Biology, Public Library of Science, vol. 11(2), pages 1-23, February.
    2. Matthew F. Glasser & Timothy S. Coalson & Emma C. Robinson & Carl D. Hacker & John Harwell & Essa Yacoub & Kamil Ugurbil & Jesper Andersson & Christian F. Beckmann & Mark Jenkinson & Stephen M. Smith , 2016. "A multi-modal parcellation of human cerebral cortex," Nature, Nature, vol. 536(7615), pages 171-178, August.
    3. Randy L. Buckner & Daniel S. Margulies, 2019. "Macroscale cortical organization and a default-like apex transmodal network in the marmoset monkey," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    4. Piotr Majka & Shi Bai & Sophia Bakola & Sylwia Bednarek & Jonathan M. Chan & Natalia Jermakow & Lauretta Passarelli & David H. Reser & Panagiota Theodoni & Katrina H. Worthy & Xiao-Jing Wang & Daniel , 2020. "Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
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    Cited by:

    1. Jie Xia & Cirong Liu & Jiao Li & Yao Meng & Siqi Yang & Huafu Chen & Wei Liao, 2024. "Decomposing cortical activity through neuronal tracing connectome-eigenmodes in marmosets," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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