Histology‐Based Average Template of the Marmoset Cortex With Probabilistic Localization of Cytoarchitectural Areas
Piotr Majka,
Sylwia Bednarek,
Jonathan M. Chan,
Natalia Jermakow,
Cirong Liu,
Gabriela Saworska,
Katrina H. Worthy,
Afonso C. Silva,
Daniel K. Wójcik,
Marcello G.P. Rosa
Affiliations
Piotr Majka
Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland; Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia; Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia; Corresponding authors: P. Majka: Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland; M.G.P. Rosa: Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia.
Sylwia Bednarek
Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland
Jonathan M. Chan
Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia; Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
Natalia Jermakow
Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland
Cirong Liu
Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA
Gabriela Saworska
Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland
Katrina H. Worthy
Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
Afonso C. Silva
Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA
Daniel K. Wójcik
Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland; Institute of Applied Psychology, Faculty of Management and Social Communication, Jagiellonian University, 30-348 Cracow, Poland
Marcello G.P. Rosa
Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia; Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia; Corresponding authors: P. Majka: Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland; M.G.P. Rosa: Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia.
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.
