Neural bases of emotion reactivity and emotion regulation
Abstract/Contents
- Abstract
- Both our emotions and our efforts to regulate our emotions play a crucial role in our everyday lives. However, much remains to be learned about the brain processes that underlie emotion and emotion regulation. In this research, we seek to better understand the neural bases of emotion and emotion regulation by conducting theory- and data-driven analyses on human functional magnetic resonance imaging (fMRI) data recorded during emotion reactivity and emotion regulation. In the first study, using multiple samples and both univariate and multivariate analyses, we tested the commonly held the neural separability hypothesis, which holds that emotion reactivity and emotion regulation are associated with spatially separable macro-scale neural processes. Our fMRI results did not support the neural separability hypothesis. Both presumptive "reactivity" and "regulation" brain regions demonstrated equal or greater activation associated with the reactivity condition than the regulation condition, and both their multivoxel data could be used to decode reactivity trials more accurately than regulation trials. In the second study, we explored the predictions of individual differences in emotion reactivity and emotion regulation from whole-brain functional connectivity using a machine-learning approach. With exploratory analyses, we found that brain functional connectivity could predict unobserved individuals' emotion regulation but not emotion reactivity. Particularly, functional connectivity within and with the subcortical-cerebellum brain network was found to be most predictive of emotion regulation compared to other brain networks. Taken together, our studies advance our understanding of the neural bases of emotion reactivity and emotion regulation, moving us away from a spatially separated locationist account and towards a more integrated network-based multivariate model.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Zhang, Jinxiao |
|---|---|
| Degree supervisor | Gross, James J, (Professor of psychology) |
| Thesis advisor | Gross, James J, (Professor of psychology) |
| Thesis advisor | Poldrack, Russell A |
| Thesis advisor | Ram, Nilam |
| Thesis advisor | Zaki, Jamil, 1980- |
| Degree committee member | Poldrack, Russell A |
| Degree committee member | Ram, Nilam |
| Degree committee member | Zaki, Jamil, 1980- |
| Associated with | Stanford University, School of Humanities and Sciences |
| Associated with | Stanford University, Department of Psychology |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Jinxiao Zhang. |
|---|---|
| Note | Submitted to the Department of Psychology. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/qz794fq9513 |
Access conditions
- Copyright
- © 2023 by Jinxiao Zhang
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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