PenaltyKik.02 (ds003345)
PenaltyKik.02
Task fMRI and T1-weighted brain MRI of healthy young adults playing a real-time competitive penalty shot video game against human and computer opponents, collected to study the neural basis of dynamic strategic social behavior.
Overview
This OpenNeuro collection (ds003345), named PenaltyKik.02, holds brain MRI from a Duke University study of competitive decision-making. While in the scanner, participants steered a puck toward a goal with a joystick in a real-time video game, the Penalty Shot task, and a goalie controlled either by another person or by a computer algorithm tried to block them. The authors used the behavior and the fMRI to relate opponent sensitivity and action timing to activity in prefrontal cortex and the temporoparietal junction. Snapshot 1.0.0 appeared in October 2020; snapshots 1.0.1 and 1.0.2 from June 2021 added further defacing of the anatomical images. The data are released under CC0.
Composition
The snapshot has 75 subjects, which matches the analysed sample of the 2020 paper: 82 people were scanned and 7 were dropped for head motion over 3 mm. The paper reports 41 women, a mean age of 25.9 years (SD 6.8) and an age range of 18 to 48. All were right-handed and reported no neurological or psychiatric disorder. Every subject has one T1-weighted image and BOLD task runs, 223 runs in total: 73 subjects have three runs and two have two. No participants.tsv is shared, so per-subject age and sex are not available.
Acquisition
All images come from a GE Discovery MR750 at 3 T at Duke University Hospital. The BOLD runs use echo-planar imaging with a 2 s repetition time, 28 ms echo time and 3.0 x 3.0 x 3.8 mm voxels, and each run lasts about 12 minutes. The T1-weighted image is a 1 mm isotropic BRAVO scan. A 4-minute practice run was done before the three task runs but is not part of the release.
Annotations
There are no image labels. Each BOLD run has an events file with the trial timing of the game.
Known limitations
- Demographics exist only as group summaries in the paper.
- Seven high-motion participants are not included.
- Two subjects have only two of the three task runs.
- One site and one scanner.
Cohort
Aggregate numbers from the sources below. Bars are relative to the 75 subjects.
Sex
- Female 41 100%
Covers 41 of 75 subjects.
Methods: Participants in McDonald et al. 2020, Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior, Social Cognitive and Affective Neuroscience
Condition
Groups can overlap
- Healthy control 75 100%
Methods: Participants in McDonald et al. 2020, Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior, Social Cognitive and Affective Neuroscience
Country
- United States 75 100%
T1w sidecars: InstitutionName in File tree and JSON sidecars of ds003345 snapshot 1.0.2 (CC0), NIfTI files counted per subject folder, T1w sidecar fields Manufacturer, ManufacturersModelName, MagneticFieldStrength and InstitutionName
Contrast / sequence by field strength
ScansReported cross table. A dot marks a cell the source does not give.
| 3 T | |
|---|---|
| T1-weighted | 75 |
T1w sidecars: MagneticFieldStrength in File tree and JSON sidecars of ds003345 snapshot 1.0.2 (CC0), NIfTI files counted per subject folder, T1w sidecar fields Manufacturer, ManufacturersModelName, MagneticFieldStrength and InstitutionName
Age
mean 25.9 ± 6.8, range 18 to 48
No age bins reported.
Methods: Participants in McDonald et al. 2020, Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior, Social Cognitive and Affective Neuroscience
Contrast / sequence
Groups can overlap
- T1-weighted 75 100%
- BOLD fMRI 75 100%
anat folders, func folders in File tree and JSON sidecars of ds003345 snapshot 1.0.2 (CC0), NIfTI files counted per subject folder, T1w sidecar fields Manufacturer, ManufacturersModelName, MagneticFieldStrength and InstitutionName
Contrast / sequence by scanner vendor
ScansReported cross table. A dot marks a cell the source does not give.
| GE HealthCare | |
|---|---|
| T1-weighted | 75 |
T1w sidecars: Manufacturer in File tree and JSON sidecars of ds003345 snapshot 1.0.2 (CC0), NIfTI files counted per subject folder, T1w sidecar fields Manufacturer, ManufacturersModelName, MagneticFieldStrength and InstitutionName
Contrast combinations
How many subjects have exactly each set of contrasts.
| T1w | bold | Subjects with exactly this set |
|---|---|---|
75 |
License and access
Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer
Download without an account
Creative Commons Zero 1.0 Universal
Public domain dedication. Do anything with the data, including commercial use, without asking and without having to give credit.
dataset_description.json of snapshot 1.0.2 states "License" CC0.
What you can do
- Yes
- Yes
- Yes
- Yes
- Yes
What you can share
- Yes
- Yes
- Yes
What you must do
- No
- Share alike No
- No
- No
- Manuscript review No
- Release code No
- Return results No
- Delete after use No
Limits
- No
- Location limits No
Citation
McDonald KR, Broderick WF, Huettel SA, Pearson JM. Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior. Social Cognitive and Affective Neuroscience 15(4):383-393 (2020).
Sources
Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.
- OpenNeuro ds003345 snapshot 1.0.2 (dataset_description.json, README, CHANGES and snapshot summary) website
- File tree and JSON sidecars of ds003345 snapshot 1.0.2 (CC0), NIfTI files counted per subject folder, T1w sidecar fields Manufacturer, ManufacturersModelName, MagneticFieldStrength and InstitutionName computed
- McDonald et al. 2020, Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior, Social Cognitive and Affective Neuroscience paper
- McDonald et al. 2019, Bayesian nonparametric models characterize instantaneous strategies in a competitive dynamic game, Nature Communications paper