Moral judgments of intentional and accidental moral violations across Harm and Purity domains
The purpose of this data is to investigate neural differences within regions associated with Theory of Mind across a) intentional vs accidental moral acts; b) across moral domains (harmful vs impure acts); c) across moral subdomains; d) between morally relevant and nonmoral scenarios. Subjects were scanned while completing a Theory of Mind localizer task, and while completing the moral judgment task. For each scenario, subjects saw a text-based version of the scenario, and rated its moral wrongness on a 1-4 scale. Each scenario text was presented in 4 serial segments, comprising Background, Action, Outcome, and Intent.
For representational similarity analysis scripts: https://github.com/lypsychlab/RSA
- Amelia Brown
- James Dungan
- Jorie Koster-Hale
- Emily Wasserman
- Alek Chakroff
- Rebecca Saxe
- Liane Young
Contact Information:Name: Liane Young (Contact only after 7/2017)
Acknowledgements and Funding:
Alfred P. Sloan Foundation, Simons Foundation, NIH Grant 1R01 MH096914-01A1. Thanks to the members of the Morality Lab and Saxelab for helpful comments on manuscripts and data analyses.
External Publication Links:Decoding moral judgments from neural representations of intentions
When minds matter for moral judgment: intent information is neurally encoded for harmful but not impure acts
Siemens 3T Trio
How to cite this dataset:
In addition to any citation requirements in the dataset summary please use the following to cite this dataset:
This data was obtained from the OpenfMRI database. Its accession number is ds000212
Direct Links to data:
Revision: 1.0.1 Date Set: Oct. 11, 2017, 10:27 p.m.
- Added BIDSVersion to dataset_description.json
Revision: 1.0.0 Date Set: Dec. 1, 2016, 6:11 p.m.
- Initial release