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

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 K. Wójcik, Partha P. Mitra and Marcello G. P. Rosa ()
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Piotr Majka: Nencki Institute of Experimental Biology of the Polish Academy of Sciences
Shi Bai: Monash University Node
Sophia Bakola: Monash University Node
Sylwia Bednarek: Nencki Institute of Experimental Biology of the Polish Academy of Sciences
Jonathan M. Chan: Monash University Node
Natalia Jermakow: Nencki Institute of Experimental Biology of the Polish Academy of Sciences
Lauretta Passarelli: University of Bologna
David H. Reser: Monash University
Panagiota Theodoni: New York University
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

Nature Communications, 2020, vol. 11, issue 1, 1-14

Abstract: 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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14858-0

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DOI: 10.1038/s41467-020-14858-0

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