Functional connectivity of the amygdala is linked to individual differences in emotional pain facilitation
Bibliographic record
Abstract
The amygdala is central to emotional processing of sensory stimuli, including pain. Because recent findings suggest that individual differences in emotional processes play a part in the development of chronic pain, a better understanding of the individual patterns of functional connectivity that makes individuals susceptible to emotionally modulated facilitation of pain is needed. We therefore investigated the neural correlates of individual differences in emotional pain facilitation using resting-state functional magnetic resonance imaging (rs-fMRI) with an amygdala seed. Thirty-seven participants took part in 3 separate sessions, during which pain sensitivity was tested (session 1), participants underwent rs-fMRI (session 2), and emotional pain modulation was assessed (session 3). The amygdala served as seed for the rs-fMRI analysis, and whole-brain voxel-wise connectivity was tested. Pain modulatory scores were entered as regressor for the group analysis. Stronger connectivity of the amygdala to S1/M1, S2/operculum, and posterior parietal cortex at rest characterized individuals who showed greater pain facilitation by negative emotions. When comparing the amygdala networks associated with pain unpleasantness and with pain-intensity modulation, most of the identified areas were equally related to either pain rating type; only amygdala connectivity to S1/M1 was found to predict pain-intensity modulation specifically. We demonstrate that trait-like patterns of functional connectivity between amygdala and cortical regions involved in sensory and motor responses are associated with the individual amplitude of pain facilitation by negative emotional states. Our results are an early step toward improved understanding of the mechanisms that give rise to individual differences in emotional pain modulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".