4.7 Article

Histology-Based Average Template of the Marmoset Cortex With Probabilistic Localization of Cytoarchitectural Areas

Journal

NEUROIMAGE
Volume 226, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2020.117625

Keywords

non-human primate; cortex; digital template; Nissl; cortical thickness; Callithrix jacchus

Funding

  1. International Neuroinformatics Coordinating Facility (INCF Seed Funding grant scheme)
  2. National Centre for Research and Development [ERA-NET-NEURON/17/2017]
  3. National Science Centre [2019/35/D/NZ4/03031]
  4. Australian Research Council [CE140100007]
  5. National Health and Medical Research Council [APP1122220]

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The rapid adoption of marmosets in neuroscience has led to a demand for 3D brain atlases, which has resulted in the creation of the Nencki-Monash template representing an average of 20 marmoset brains. This template allows for direct estimates of cortical areas, transformation to other marmoset brain templates, and integration with MRI and connectivity data. The combination of histology-based and MRI-based features makes this template valuable for future development of 3D brain atlases that consider variability in species.
The rapid adoption of marmosets in neuroscience has created a demand for three dimensional (3D) atlases of the brain of this species to facilitate data integration in a common reference space. We report on a new open access template of the marmoset cortex (the Nencki-Monash, or NM template), representing a morphological average of 20 brains of young adult individuals, obtained by 3D reconstructions generated from Nissl-stained serial sections. The method used to generate the template takes into account morphological features of the individual brains, as well as the borders of clearly defined cytoarchitectural areas. This has resulted in a resource which allows direct estimates of the most likely coordinates of each cortical area, as well as quantification of the margins of error involved in assigning voxels to areas, and preserves quantitative information about the laminar structure of the cortex. We provide spatial transformations between the NM and other available marmoset brain templates, thus enabling integration with magnetic resonance imaging (MRI) and tracer-based connectivity data. The NM template combines some of the main advantages of histology-based atlases (e.g. information about the cytoarchitectural structure) with features more commonly associated with MRI-based templates (isotropic nature of the dataset, and probabilistic analyses). The underlying workflow may be found useful in the future development of 3D brain atlases that incorporate information about the variability of areas in species for which it may be impractical to ensure homogeneity of the sample in terms of age, sex and genetic background.

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