The `mpib_sp_eeg` dataset.

Stefan Appelhoff 7d758ca026 carry over datacite.yml changes to actual file, not just conversion script 2 years ago
.datalad c83a484b79 [DATALAD] new dataset 2 years ago
code 7d758ca026 carry over datacite.yml changes to actual file, not just conversion script 2 years ago
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.bids-validator-config.json 41082ce33b run python source_to_bids 2 years ago
.bidsignore 41082ce33b run python source_to_bids 2 years ago
.gitattributes 8b532fc252 define what to track with git-annex 2 years ago
CHANGES 120a54ca6e change license to PDDL 2 years ago
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README.md 120a54ca6e change license to PDDL 2 years ago
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dataset_description.json 120a54ca6e change license to PDDL 2 years ago
participants.json 41082ce33b run python source_to_bids 2 years ago
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task-YokedFixed_eeg.json 41082ce33b run python source_to_bids 2 years ago
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README.md

The mpib_sp_eeg dataset

This is the readme of the mpib_sp_eeg dataset. The short dataset name results from these three facts:

  • the data was collected at the Max Planck Institute for Human Development (MPIB)
  • the behavioral task was the "Sampling Paradigm" (SP)
  • the dataset's main neuroimaging modality is electroencephalography data (EEG)

The data was collected in 2019 at the MPIB in Berlin by Stefan Appelhoff and colleagues.

The data is organized according to the Brain Imaging Data Structure, see: https://bids.neuroimaging.io

The dataset is managed with datalad, see: http://handbook.datalad.org/en/latest/index.html

Download

  1. Install datalad (http://handbook.datalad.org/en/latest/intro/installation.html)
  2. Run the code below from the shell:
    1. first "clone" the dataset
    2. then navigate to the root of the dataset
    3. then use datalad get <file you want> to get the file contents for each file you want (you can also use datalad get . -r to get everything at once, but this may take some time)
datalad clone https://gin.g-node.org/sappelhoff/mpib_sp_eeg
cd mpib_sp_eeg
datalad get participants.tsv

Preprint

A preprint is available on BioRxiv.

Experimental presentation code

The code used for the experimental presentation can be found on GitHub and Zenodo.

Analysis code

The code used for data analysis can be found on GitHub and on Zenodo.

Contact

License

The source_to_bids.py script in the code/ directory is licensed under the MIT license.

This data is made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://opendatacommons.org/licenses/pddl/1.0/

See also this human readable summary: https://opendatacommons.org/licenses/pddl/summary/

For details, please see the LICENSE file.

Using this dataset

If you use this dataset in your work, please consider citing it as well as the main references describing it.

Additional information

  • The eyetracking recording for sub-18 in the ActiveVariable task is broken ("sub-18/eeg/sub-18_task-ActiveVariable_recording-eyetracking_physio.tsv.gz").
  • The eyetracking recording for sub-15 in the YokedFixed task for unknown reasons has timing issues ("sub-15/eeg/sub-15_task-YokedFixed_recording-eyetracking_physio.tsv.gz").
  • All bipolar channels (ECG, HEOG, VEOG) were recorded with a ground electrode placed 10cm away from the navel on the participant's right side of the belly.
  • The following describes the approximate locations of the ECG, HEOG, and VEOG electrodes:
    • ECG- between the 5th and 6th rib on the left chest.
    • ECG+ in the middle of the upper chest
    • HEOG- 1cm from the left outer canthus
    • HEOG+ 1cm from the right outer canthus
    • VEOG- 2cm below the left eye
    • VEOG+ 1cm above the left eyebrow
datacite.yml
Title The mpib_sp_eeg dataset
Authors Appelhoff,Stefan;Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany;ORCID:0000-0001-8002-0877
Hertwig,Ralph;Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany;ORCID:0000-0002-9908-9556
Spitzer,Bernhard;Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany;ORCID:0000-0001-9752-932X
Description When acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does subjective control over sampling affect the quality of experience-based decisions? This resource contains behavioral, eyetracking, and EEG data of 40 human participants performing a numerical sampling task in which the level of subjective control over sampling was systematically varied. The dataset is organized according to the Brain Imaging Data Structure (BIDS).
License Open Data Commons Public Domain Dedication and License (PDDL) v1.0 (https://opendatacommons.org/licenses/pddl/1-0/)
References Control over sampling boosts numerical evidence processing in human decisions from experience Stefan Appelhoff, Ralph Hertwig, Bernhard Spitzer bioRxiv 2021.06.03.446960 [doi:10.1101/2021.06.03.446960] (IsSupplementTo)
Stefan Appelhoff. (2019, August 6). sappelhoff/sp_experiment: v1.0 (Version v1.0). Zenodo. http://doi.org/10.5281/zenodo.3361717 [doi:10.5281/zenodo.3361717] (IsReferencedBy)
Stefan Appelhoff. (2022). sappelhoff/sp_code: 1.0.0 (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.5929223 [doi:10.5281/zenodo.5929222] (IsReferencedBy)
Funding Max Planck Institute for Human Development
Keywords cognitive neuroscience
decisions from experience
DFE
sampling paradigm
sequential sampling
decision-making
control
EEG
electroencephalography
eyetracking
BIDS
Brain Imaging Data Structure
Resource Type Dataset