Julich Brain Atlas: BigBrain
Atlas

BigBrain

The BigBrain

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 in a functionally relevant microscopic dimension: 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 10 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.

HIBALL Brain Depiction

HIBALL

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.

brain section generated from BigBrain
The cytoarchitecture of the cortex of a human brain (the BigBrain)

The Method in a Nutshell

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.

Applications & Data

BigBrain Dataset

The full dataset of images, volumes, and surfaces are available for download on an ftp site. Additional files can be accessed via LORIS.

EBRAINS Multilevel Human Brain Atlas

A three-dimensional atlas that integrates the different facets of human brain organisation at the millimeter and micrometer level

Cortical Layer Maps

Explore BigBrain cortical layer segmentation online.

Cytoarchitectonic Maps

Explore probabilistic cytoarchitectonic maps registered to the BigBrain online in the NeHuBa viewer.

Contact

Prof. Dr. med.
Katrin Amunts

Head of the research group Architecture and Brain Function

Institute of Neurosciences and Medicine (INM-1)

Forschungszentrum Jülich
D-52425 Jülich
Germany

Tel.: +49-2461-61-4300
Fax: +49-2461-61-3483

k.amunts@fz-juelich.de

C. u. O. Vogt-Institute for Brain Research
Medical Faculty
University Hospital Düsseldorf

Life Science Center
Merowingerplatz 1A
D-40225 Düsseldorf
Germany

Tel: +49-211-81-06102
Fax: +49-211-81-06154

Key Publications

Schiffer C, Spitzer H, Kiwitz K, Unger N, Wagstyl K, Evans AC, Harmeling S, Amunts K, Dickscheid T (2022)

Convolutional Neural Networks for cytoarchitectonic brain mapping at large scale

NeuroImage 240: 118327 (2021), ISSN 1053-8119, doi

Paquola C, Royer J, Lewis LB, Lepage C, Glatard T, Wagstyl K, DeKraker J, Toussaint PJ, Valk SL, Collins L, Khan AR, Amunts K, Evans AC, Dickscheid T, Bernhardt B (2021)

The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging

eLife 10:e70119

Kiwitz K, Schiffer C, Spitzer H, Dickscheid T, Amunts K (2020)

Deep learning networks reflect cytoarchitectonic features used in brain mapping

Scientific Reports 10, 22039

Wagstyl K, Larocque S, Cucurull G, Lepage C, Cohen JP, Bludau S, Palomero-Gallagher N, Lewis LB, Funck T, Spitzer H, Dickscheid T, Fletcher PC, Romero A, Zilles K., Amunts K, Bengio Y, Evans AC (2020)

BigBrain 3D atlas of cortical layers: Cortical and laminar thickness gradients diverge in sensory and motor cortices

PlosBiology 18(4): e3000678

DeKraker J, Lau JC, Ferko KM, Khan AR, Kohler S (2019)

Hippocampal subfields revealed through unfolding and unsupervised clustering of laminar and morphological features in 3D BigBrain

NeuroImage 206(116328)

Oden L, Schiffer C, Spitzer H, Dickscheid T, Pleiter D (2019)

IO Challenges for Human Brain Atlasing Using Deep Learning Methods - An In-Depth Analysis

27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP): 291-298

Amunts K, Lepage C, Borgeat L, Mohlberg H, Dickscheid T, Rousseau ME, Bludau S, Bazin PL, Lewis LB, Oros-Peusquens AM, Shah NJ, Lippert T, Zilles K, Evans AC (2013)

BigBrain: An ultrahigh-resolution 3D human brain model

Science, 340(6139): 1472-1475