BigBrain is a three-dimensional reconstruction of an individual human brain stained for cell bodies at ultra-high, nearly cellular, resolution. BigBrain is unique in its scale and an invaluable tool for brain mapping: it enables the spatial anchoring of multimodal data into an anatomically realistic standard space in a functionally relevant, microscoscopic dimension. BigBrain is also one of ten individual brains whose cytoarchitectonic maps contribute to the Julich Brain Atlas.
BigBrain has been developed within a collaboration between Forschungszentrum Jülich and McGill University in Montreal.
The German-Canadian Helmholtz International Lab HIBALL is a collaboration of neuroscientists and AI experts around Alan Evans at McGill University in Canada and Katrin Amunts at Forschungszentrum Jülich in Germany.
Within HIBALL, the next-generation multimodal 3D brain models will be developed at unmatched spatial resolution using novel deep learning methods and the latest supercomputing architectures to analyze neuroscientific data in the petabyte range.
To generate the BigBrain dataset, a complete paraffin-embedded human brain was cut into 7404 sections at 20-micrometer thickness and stained for cell bodies. The sections were digitized, resulting in images of up to 13,000 by 11,000 pixels and a data set of 1 TB. The images were downscaled to generate an isotropic resolution of 20 micrometers.
The full dataset of images, volumes, and surfaces are available for download on an ftp site. Additional files can be accessed via LORIS.
A three-dimensional atlas that integrates the different facets of human brain organisation at the millimeter and micrometer level
Explore BigBrain cortical layer segmentation online.
Explore probabilistic cytoarchitectonic maps registered to the BigBrain online in the NeHuBa viewer.
Head of the research group Architecture and Brain Function
Institute of Neurosciences and Medicine (INM-1)
C. u. O. Vogt-Institute for Brain Research
University Hospital Düsseldorf
Life Science Center
NeuroImage 240: 118327 (2021), ISSN 1053-8119, doi
Scientific Reports 10, 22039
PlosBiology 18(4): e3000678
27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP): 291-298
Science, 340(6139): 1472-1475