CONP Portal | Dataset


dataset format
CONP status
308
11
Learning Naturalistic Structure: Processed fMRI dataset
  • Creators: DuPre, Elizabeth
  • Version: 0.1.0
  • Date Added: 2020-02-06
  • Date Updated: 2021-06-02
  • License: other-pd
  • Files: 240
  • Size: 13.9 GB
  • Formats: TSV, NIfTI, TXT
ARK ID : https://n2t.net/ark:/70798/d7g31prmz2wvt6tdw9
Learning Naturalistic Structure: Processed fMRI dataset
Creators: DuPre, Elizabeth
Licenses: other-pd
Version: 0.1.0
Formats: TSV NIfTI TXT
Size: 13.9 GB
No of Files: 240
Project Landing Page: https://zenodo.org/record/3647611
Metadata file: DATS.json
Description:

This data was obtained from OpenNeuro as ds001545. We would like to thank the authors for their generosity in sharing their data, and we point interested users towards their paper describing its acquisition:

Aly M, Chen J, Turk-Browne NB, & Hasson U (2018). Learning naturalistic temporal structure in the posterior medial network. Journal of Cognitive Neuroscience, 30(9): 1345-1365.


Experimental design

In this dataset, subjects were scanned while watching repeated presentations of intact and scrambled clips from Wes Anderson's 2014 film, The Grand Budapest Hotel. Scrambled clips were presented in either a 'fixed' (i.e., consistent scrambling from run to run) or 'random' (i.e., random scrambling from run to run) condition. An overview of the experimental design is shown in this figure from Aly and colleagues (2018)

Preprocessing

After downloading from OpenNeuro using DataLad, data was preprocessed using fMRIPrep 1.5.0rc1. A complete transcript of the fMRIPrep processing is available as a README file in the repository. Post-processing was performed using Nilearn. Briefly, functional files were masked with the fMRIPrep-derived brain mask and trimmed to discard non-steady state volumes. Please see the README for further details.

Dataset README information

README.md

Learning Naturalistic Structure: Processed fMRI dataset

DOI

Crawled from Zenodo

Description

This data was obtained from OpenNeuro as ds001545. We would like to thank the authors for their generosity in sharing their data, and we point interested users towards their paper describing its acquisition:

>
> Aly M, Chen J, Turk-Browne NB, & Hasson U (2018). Learning naturalistic temporal structure in the posterior medial network. Journal of Cognitive Neuroscience, 30(9): 1345-1365.
>


Experimental design

In this dataset, subjects were scanned while watching repeated presentations of intact and scrambled clips from Wes Anderson's 2014 film, The Grand Budapest Hotel. Scrambled clips were presented in either a 'fixed' (i.e., consistent scrambling from run to run) or 'random' (i.e., random scrambling from run to run) condition. An overview of the experimental design is shown in this figure from Aly and colleagues (2018)

Preprocessing

After downloading from OpenNeuro using DataLad, data was preprocessed using fMRIPrep 1.5.0rc1. A complete transcript of the fMRIPrep processing is available as a README file in the repository. Post-processing was performed using Nilearn. Briefly, functional files were masked with the fMRIPrep-derived brain mask and trimmed to discard non-steady state volumes. Please see the README for further details.

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:

datalad install https://github.com/CONP-PCNO/conp-dataset.git
2) Install the Learning_Naturalistic_Structure__Processed_fMRI_dataset dataset

To install the Learning_Naturalistic_Structure__Processed_fMRI_dataset 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:

cd conp-dataset/projects
datalad install Learning_Naturalistic_Structure__Processed_fMRI_dataset
3) Download data from the Learning_Naturalistic_Structure__Processed_fMRI_dataset dataset

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

cd Learning_Naturalistic_Structure__Processed_fMRI_dataset

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:

datalad get <filepath>

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.