CONP Portal | Dataset


BigBrain dataset - Layer Segmentation (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 GIfTI OBJ STL PNG
Size: 10.4 GB
No of Files: 15002
No of Subjects: 1
Input Datasets: bigbrain-datalad
Primary Publications:
  • BigBrain: an ultrahigh-resolution 3D human brain model. Science.
  • Automated segmentation of cortical layers in BigBrain reveals divergent cortical and laminar thickness gradients in sensory and motor cortices. bioRxiv.
Project Landing Page: https://bigbrainproject.org
Metadata file: DATS.json
Is About: Homo sapiens, adult
Description:
The BigBrain Layer Segmentation dataset contains all layer segmentation files 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] and the paper From Konrad Wagtyl on the layer segmentation [https://www.biorxiv.org/content/10.1101/580597v1]

Dataset README information

README.md

BigBrain 3D ROIs

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 all layer segmentation files related to
Konrad Wagstyl's paper.
The layer segmentation files are derived from the BigBrain release 2015
published in the BigBrain Project website.

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. A subset of open datasets on the Portal are also available through a browser-based download button. The instructions below regard dataset download with the use of DataLad. To install DataLad on your system, please refer to the install section of the DataLad Handbook .

Note: For maximum compatibility with conp-dataset, the CONP recommends versions 3.12+ of Python, 10.20241202+ of git-annex, and 1.1.4+ of datalad.

1) Initiate the CONP dataset

Run the following command in the directory where you want the CONP dataset (conp-dataset) to be installed:

2) Install the BigBrain_Layer_Segmentation dataset

To install the BigBrain_Layer_Segmentation dataset, run the following commands to move into the "projects" subdirectory under the "conp-dataset" directory (created in the previous step) and run datalad install:

3) Download data from the BigBrain_Layer_Segmentation dataset

Now that the dataset has been installed, go into the BigBrain_Layer_Segmentation dataset directory.

The files visible after installing the dataset but before downloading (in the next step) are symbolic links and need to be downloaded manually using the datalad get command:

If you run datalad get * command, all the files available in the dataset directory will be downloaded.


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