Download the data set from CRCNS

Download the data set from CRCNS#

In this script, we download the data set from CRCNS. A (free) account is required.

Warning

This script will download approximately 14GB of data, so it may take a while.

Cite this data set#

This tutorial is based on publicly available data published on CRCNS. If you publish any work using this data set, please cite the original publication [Nishimoto et al., 2011], and the data set [Nishimoto et al., 2014].

Download#

# path of the data directory
from voxelwise_tutorials.io import get_data_home
directory = get_data_home(dataset="vim-2")
print(directory)

We will only use the first subject in this tutorial, but you can run the same analysis on the two other subjects. Uncomment the lines in DATAFILES to download more subjects, or to download the anatomy files.

import getpass

from voxelwise_tutorials.io import download_crcns

DATAFILES = [
    'vim-2/Stimuli.tar.gz',
    'vim-2/VoxelResponses_subject1.tar.gz',
    # 'vim-2/VoxelResponses_subject2.tar.gz',
    # 'vim-2/VoxelResponses_subject3.tar.gz',
    # 'vim-2/anatomy.zip',
    # 'vim-2/checksums.md5',
    # 'vim-2/filelist.txt',
    # 'vim-2/docs/crcns-vim-2-data-description.pdf',
]

username = input("CRCNS username: ")
password = getpass.getpass("CRCNS password: ")

for datafile in DATAFILES:
    local_filename = download_crcns(datafile, username, password,
                                    destination=directory, unpack=True)

References#

[NVN+11]

S. Nishimoto, A. T. Vu, T. Naselaris, Y. Benjamini, B. Yu, and J. L. Gallant. Reconstructing visual experiences from brain activity evoked by natural movies. Current Biology, 21(19):1641–1646, 2011.

[NVN+14]

S. Nishimoto, A. T. Vu, T. Naselaris, Y. Benjamini, B. Yu, and J. L. Gallant. Gallant lab natural movie 4t fMRI data. 2014. doi:10.6080/K00Z715X.

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