Shared states: using MVPA to test neural overlap between self-focused emotion imagery and other-focused emotion understanding

Description: The unthresholded maps in this collection are from the "Shared States" project, which testedwhether the neural patterns that support imagining ‘performing an action’, ‘feeling a bodily sensation’ or ‘being in a situation’ are directly involved in understanding other people’s actions, bodily sensations and situations. Subjects imagined the content of short sentences describing emotional actions, interoceptive sensations and situations (self-focused task), and processed scenes and focused on how the target person was expressing an emotion, what this person was feeling, and why this person was feeling an emotion (other-focused task). Using a linear support vector machine classifier on brain-wide multi-voxel patterns, we accurately decoded each individual class in the self-focused task. When generalizing the classifier from the self-focused task to the other-focused task, we also accurately decoded whether subjects focused on the emotional actions, interoceptive sensations and situations of others. These results show that the neural patterns that underlie self-imagined experience are involved in understanding the experience of other people. This supports the theoretical assumption that the basic components of emotion experience and understanding share resources in the brain. Data were preprocessed and analyzed using FSL 5.0.10.

Related article: http://doi.org/10.1093/scan/nsx037

View ID Name Type
Field Value
Compact Identifierhttps://identifiers.org/neurovault.collection:4743
Add DateJan. 17, 2019, 10:02 a.m.
Uploaded bylukassnoek
Contributors
Related article DOI10.1093/scan/nsx037
Related article authorsSuzanne Oosterwijk, Lukas Snoek, Mark Rotteveel, Lisa Feldman Barrett and H. Steven Scholte
Citation guidelines

If you use the data from this collection please include the following persistent identifier in the text of your manuscript:

https://identifiers.org/neurovault.collection:4743

This will help to track the use of this data in the literature. In addition, consider also citing the paper related to this collection.