CONP Portal | Dataset
The Cuban Human Brain Mapping Project (EEG, MRI, and Cognition dataset)
- Multimodal quantitative neuroimaging databases and methods: The Cuban human brain mapping project. Gertrudis Hernandez-Gonzalez et al. Clinical EEG and Neuroscience, Volume 42, Issue 3, 2011. https://doi.org/10.1177/155005941104200303
- Approximate average head models for EEG source imaging. Pedro A. Valdes-Hernandez et al. Journal of Neuroscience Methods, Volume 185, Issue 1, 2009. https://doi.org/10.1016/j.jneumeth.2009.09.005
- A quantitative EEG toolbox for the MNI Neuroinformatics ecosystem: normative SPM of EEG source spectra. Jorge F. Bosch-Bayard et al. Frontiers in Neuroinformatics (in press). 10.3389/fninf.2020.00033
- Crystallized and fluid intelligence are predicted by microstructure of specific white‐matter tracts. Daylin Gongora et al. Human Brain Mapping, Volume 41, Issue 4, 2020. https://doi.org/10.1002/hbm.24848
- Surface area and cortical thickness descriptors reveal different attributes of the structural human brain networks. Gretel Sanabria-Diaz et al. Neuroimage, Volume 50, Issue 4, 2010. https://doi.org/10.1016/j.neuroimage.2010.01.028
- White Matter Architecture Rather Than Cortical Surface Area Correlates With the EEG Alpha Rhythm. Pedro A. Valdes-Hernandez et al. Neuroimage, Volume 49, Issue 3, 2009. https://doi.org/10.1016/j.neuroimage.2009.10.030
- Characterizing Brain Anatomical Connections Using Diffusion Weighted MRI and Graph Theory. Yasser Iturria-Medina et al. Neuroimage, Volume 36, Issue 3, 2007. https://doi.org/10.1016/j.neuroimage.2007.02.012
- Studying the Human Brain Anatomical Network via Diffusion-Weighted MRI and Graph Theory. Yasser Iturria-Medina et al. Neuroimage, Volume 40, Issue 3, 2007. https://doi.org/10.1016/j.neuroimage.2007.10.060
- Tensor Analysis and Fusion of Multimodal Brain Images. Esin Karhan et al. IEEE, Volume 103, Issue 9, 2015. https://doi.org/10.1109/JPROC.2015.2455028
Acknowledges: | National Natural Science Foundation of China, CNS Program of UESTC |
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Description:
Dataset README information
The Cuban Human Brain Mapping Normative database
The Cuban Human Brain Mapping Project (CHBMP) repository is
an open multimodal neuroimaging and cognitive dataset from 282 healthy participants (31.9
± 9.3 years, age range 18–68 years).
This dataset was acquired from 2004 to 2008 as a subset
of a larger stratified random sample of 2,019 participants from La Lisa municipality in La
Habana, Cuba. The exclusion included presence of disease or brain dysfunctions.
The information made available for all participants comprises: high-density (64-120 channels)
resting state electroencephalograms (EEG), magnetic resonance images (MRI), psychological
tests (MMSE, Wechsler Adult Intelligence Scale -WAIS III, computerized reaction time tests
using a go no-go paradigm), as well as general information (age, gender, education, ethnicity,
handedness and weight).
- The EEG data contains recordings with at least 30 minutes duration including the following
conditions: eyes closed, eyes open, hyperventilation and subsequent recovery. - The MRI consisted in anatomical T1 as well as diffusion weighted (DWI)
images acquired on a 1.5 Tesla system.
The data is available for registered users on the LORIS
database which is part of the MNI neuroinformatics ecosystem (https://chbmp-open.loris.ca).
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 CHBMP dataset
To install the dataset, go into the created conp-dataset directory and run
datalad install
on the dataset CHBMP
:
cd conp-dataset
datalad install projects/CHBMP
3) Download the CHBMP dataset
Now that the DataLad dataset has been installed, go into the dataset directory under
projects/CHBMP
.
cd projects/CHBMP
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.