History of BigBrain

what is the BigBrain

BigBrain is a freely accessible high-resolution 3D digital atlas of the human brain, released in June 2013 by a team of researchers at the Montreal Neurological Institute (Canada) and the Forschungszentrum Jülich (Germany) and is part of the European Human Brain Project. The isotropic 3D spatial resolution of the BigBrain atlas is 20 µm, much finer than the typical 1 mm resolution of other existing 3D models of the human brain. In 2014, BigBrain was cited in the top 10 MIT Technology Review.


source brain

The 3D model was created from the brain of an unidentified 65-year-old man who died with no known brain pathology. His brain, after being removed from the skull, was first scanned using an MRI machine, then embedded in paraffin.


scanning at 20μm

In April 2004 the brain was sliced into 7,404 sections 20µm thick using a large-scale microtome. After each section was removed, the uncut face was photographed in order to provide an additional reference for removing distortion. The brain sections were placed on large glass slides and then stained for cell bodies using the Merker method, a process that causes the grey matter in the brain to be darkly stained while leaving the white matter uncolored. The stained sections were scanned and digitized using a flatbed scanner at 2400dpi, creating a one terabyte raw record. The acquisition process took about 1,000 hours of labor.


digitally repairing the images

The resulting digital images were then processed by human operators to remove artifacts, and by software to align them with the reference images and with neighboring sections, thereby correcting distortions that inevitably arise during histological processing. The corrected data were then assembled into a three-dimensional computer model with a spatial isotropic 3D resolution of 20 µm. The atlas took five years to complete.


rendering the BigBrain in 3D

In Summer 2017 the first version of the Human Brain Project’s web-based 3D atlas viewer was released. NeHuBa (neuroglancer for human brain atlas) is capable of displaying very large brain volumes, including oblique slicing, a whole brain overview, surface meshes, and maps. It allows to interactively choose difference template spaces and reference parcellations, find brain areas by name or visual selection, and browse additional region-specific multimodal data. The rendering of large volumetric data builds on the open source project Neuroglancer. BigBrain can be directly accessed at https://bigbrain.humanbrainproject.eu


segmentation of the BigBrain

Different approaches are currently being used to trace distinct areas on the BigBrain: manual delineation of brain cortical areas and subcortical structures based on existing atlases, and automatic methods derived from artificial intelligence (machine learning and deep learning) to extract cortical layers or count groups of cells.


sharing the atlas with the world

Users have access to all data: from the raw scanned sections (in order to develop new reconstruction and repair workflows and tools), to the derived data from our own analyses (to be used in different pipelines and analyses). Our online viewers are also available, and the data can be accessed and managed via our neuroinformatics platforms LORIS and CBRAIN.

We are building a community around the BigBrain, and everyone is welcome to join and contribute / collaborate.

BigBrain team

the people from the original paper

Prof. Katrin Amunts, PhD
Director of the Institute Structural and functional organisation of the brain (INM-1)
Forschungszentrum Jülich profile link
Prof. Alan Evans, PhD
James McGill Professor of Neurology, Psychiatry, Biomedical Eng.
McGill University mcin.ca
Sebastian Bludau
Observer-independent brain area definition
Forschungszentrum Jülich
Louis Borgeat
Volume data modeling and integration, development of the Atelier3D remote visualization and analysis tools
National Research Council of Canada
Timo Dickscheid
Data handling and pre-processing, platform manager
Forschungszentrum Jülich
Claude Lepage
Development and programming of image-processing tools for 3D reconstruction/alignment and automatic repair pipelines, manual repairs, registration, quality control and documentation
McGill Centre for Integrative Neuroscience
Lindsay B. Lewis
Manual repairs, quality control and documentation
McGill Centre for Integrative Neuroscience
Thomas Lippert
Realization of removal of artifacts and 3D reconstruction on Juropa
Forschungszentrum Jülich
Hartmut Mohlberg
Data acquisition, processing and platform manager
Forschungszentrum Jülich
Ana-Maria Oros-Peusquens
MR imaging
Forschungszentrum Jülich
Dr. Nicola Palomero-Gallagher
Forschungszentrum Jülich
Marc-Étienne Rousseau
Computing platform manager
McGill Centre for Integrative Neuroscience
Nadim J. Shah
MR imaging and supervision
Forschungszentrum Jülich
Dr. Karl Zilles
Principal investigator; project conceptualization and supervision
Forschungszentrum Jülich

Why create the BigBrain

a message from Dr. Zilles and Dr. Palomero-Gallagher

the major advantage of the BigBrain for our work is that the image data of the human brain are registered as a 3D volume at very high spatial resolution. Since the human brain is folded, any part of the cortical ribbon may be subjected to the geometrical effects of this folding, i.e. the cortex is obliquely or even tangentially sectioned at various sites in a 2D representation, e.g. in images of single microtome sections. This effect hampers the measurement of any cortical structure which is bound to the 3D columnar architecture of the cortex. In contrast, the BigBrain allows analyses in 3D, and thus has opened the door to many studies which would not be possible in 2D representations.