CONP Portal | Dataset


BigBrain dataset - 3D Classified Volumes (derived dataset)
Creators: BigBrain project
Contact: info@bigbrainproject.org
Licenses: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License
Version: 1.0
Modalities: histology
Formats: MINC NIfTI
Size: 633.0 MB
No of Files: 215
No of Subjects: 1
Input Datasets: bigbrain-datalad
Primary Publication: BigBrain: an ultrahigh-resolution 3D human brain model. Science.
Metadata file: DATS.json
Is About: Homo sapiens, adult
Description:
The BigBrain 3D classified volume dataset contains the 3D Classified volumes for basic tissue classes at multiple isotropic resolutions derived from the BigBrain dataset, a digitized reconstruction of high-resolution histological sections of the brain of a 65 years old man with no history of neurological or psychiatric diseases. The BigBrain dataset is the result of a collaborative effort between the teams of Dr. Katrin Amunts and Dr. Karl Zilles (Forschungszentrum Jülich) and Dr. Alan Evans (Montreal Neurological Institute). For more information please visit the BigBrain Project website [https://bigbrainproject.org]. This dataset contains the 3D classified volumes for basic tissue classes at multiple isotropic resolutions.

Dataset README information

README.md

BigBrain 3D Classified Volumes

BigBrain

The BigBrain is the brain of a 65 years old man with no neurological or psychiatric
diseases in clinical records at time of death. The brain was embedded in parafin and
sectioned in 7404 coronal histological sections (20 microns), stained for cell bodies.
The BigBrain is the digitized reconstruction of the hi-res histological sections
(20 microns isotropic).

Dataset content

This dataset contains 3D classified volumes from the BigBrain release 2015
published in the BigBrain Project website.

The volumes are available for several isotropic resolutions (100, 200, 300 and 400 microns) and classified for basic tissue classes:

  • 0: background
  • 1: CSF
  • 2: cortical gray
  • 3: white
  • 4: cerebellum
  • 5: layer 1 of cortex
  • 6: sub-cortical gray
  • 7: pineal gland
  • 8: cerebellum/brainstem gray
  • 9: cerebellum/brainstem white

Volumes are available in MINC and NIfTI formats.

Reference and more information

The BigBrain dataset is the result of a collaborative effort between the
teams of Dr. Katrin Amunts and Dr. Karl Zilles (Forschungszentrum Jülich)
and Dr. Alan Evans (Montreal Neurological Institute).

Amunts, K. et al.: "BigBrain: An Ultrahigh-Resolution 3D Human
Brain Model", Science (2013) 340 no. 6139 1472-1475, June 2013.
https://www.sciencemag.org/content/340/6139/1472.abstract

For more information please visit the BigBrain Project website.

Download Using DataLad

CircleCI status

The following instructions require a basic understanding of UNIX/LINUX command lines. Future portal functionality may include downloads directly from the web browser. Dataset download is currently enabled through DataLad.

Note: The conp-dataset requires version >=0.12.5 of DataLad and version >=8.20200309 of git-annex.

To install DataLad on your system, please refer to the install section of the DataLad Handbook (installation via miniconda is recommended in order to obtain the latest version of DataLad).

1) Initiate the CONP dataset

To initiate the CONP dataset (conp-dataset), run the following command in the directory where you want CONP datasets to be installed:

datalad install https://github.com/CONP-PCNO/conp-dataset.git

2) Install the BigBrain_3DClassifiedVolumes dataset

To install the dataset, go into the created conp-dataset directory and run datalad install on the dataset BigBrain_3DClassifiedVolumes:

cd conp-dataset
datalad install projects/BigBrain_3DClassifiedVolumes

3) Download the BigBrain_3DClassifiedVolumes dataset

Now that the DataLad dataset has been installed, go into the dataset directory under projects/BigBrain_3DClassifiedVolumes.

cd projects/BigBrain_3DClassifiedVolumes

Note that files visible in the dataset are symlinks and will need to be downloaded manually using the datalad get command in the dataset directory:

datalad get <filepath>

Note, if you run datalad get * command, all the files present in the dataset directory will be downloaded.

For more information on how DataLad works, please visit the DataLad Handbook documentation .