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Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey

Author

Listed:
  • Piotr Majka

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

  • Shi Bai

    (Monash University Node
    Monash University)

  • Sophia Bakola

    (Monash University Node
    Monash University
    University of Bologna)

  • Sylwia Bednarek

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

  • Jonathan M. Chan

    (Monash University Node
    Monash University)

  • Natalia Jermakow

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

  • Lauretta Passarelli

    (University of Bologna)

  • David H. Reser

    (Monash University
    Monash University)

  • Panagiota Theodoni

    (New York University
    New York University - East China Normal University Institute of Brain and Cognitive Science
    New York University Shanghai)

  • Katrina H. Worthy

    (Monash University)

  • Xiao-Jing Wang

    (New York University)

  • Daniel K. Wójcik

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

  • Partha P. Mitra

    (Cold Spring Harbor)

  • Marcello G. P. Rosa

    (Monash University Node
    Monash University)

Abstract

Understanding the principles of neuronal connectivity requires tools for efficient quantification and visualization of large datasets. The primate cortex is particularly challenging due to its complex mosaic of areas, which in many cases lack clear boundaries. Here, we introduce a resource that allows exploration of results of 143 retrograde tracer injections in the marmoset neocortex. Data obtained in different animals are registered to a common stereotaxic space using an algorithm guided by expert delineation of histological borders, allowing accurate assignment of connections to areas despite interindividual variability. The resource incorporates tools for analyses relative to cytoarchitectural areas, including statistical properties such as the fraction of labeled neurons and the percentage of supragranular neurons. It also provides purely spatial (parcellation-free) data, based on the stereotaxic coordinates of 2 million labeled neurons. This resource helps bridge the gap between high-density cellular connectivity studies in rodents and imaging-based analyses of human brains.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14858-0
    DOI: 10.1038/s41467-020-14858-0
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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.
    2. Chuanjun Tong & Cirong Liu & Kaiwei Zhang & Binshi Bo & Ying Xia & Hao Yang & Yanqiu Feng & Zhifeng Liang, 2022. "Multimodal analysis demonstrating the shaping of functional gradients in the marmoset brain," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. 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.

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