Abstract
Cognitive self-regulation can shape pain experience, but its effects on autonomic responses to painful events are unclear. In this study, participants (N = 41) deployed a cognitive strategy based on reappraisal and imagination to regulate pain up or down on different trials while skin conductance responses (SCRs) and electrocardiogram activity were recorded. Using a machine learning approach, we first developed stimulus-locked SCR and electrocardiogram physiological markers predictive of pain ratings. The physiological markers demonstrated high sensitivity and moderate specificity in predicting pain across 2 data sets, including an independent test data set (N = 84). When we tested the markers on the cognitive self-regulation data, we found that cognitive self-regulation had significant impacts on both pain ratings and pain-related physiology in accordance with regulatory goals. These findings suggest that self-regulation can impact autonomic nervous system responses to painful stimuli and provide pain-related autonomic profiles for future studies.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2338-2349 |
| Number of pages | 12 |
| Journal | Pain |
| Volume | 160 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 1 2019 |
| Externally published | Yes |
Keywords
- Autonomic nervous system
- ECG
- Pain
- SCR
- Self-regulation
ASJC Scopus subject areas
- Neurology
- Clinical Neurology
- Anesthesiology and Pain Medicine
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