Emotional memory bias in adolescents with chronic pain: examining the relationship with neural, stress, and psychological factors
Bibliographic record
Abstract
ABSTRACT: Memory biases for pain-related information may contribute to the development and maintenance of chronic pain; however, evidence for when (and for whom) these biases occur is mixed. Therefore, we examined neural, stress, and psychological factors that could influence memory bias, focusing on memories that motivate disabling behaviors: pain perception, conditioned responses to threat-and-safety cues, and responses to aversive nonnoxious stimuli. Two studies were conducted with adolescents with and without chronic pain. Data from 58 participants were included in study 1 (chronic pain n = 34, pain free n = 24, mean age = 16 years), and 39 participants were included in study 2 (chronic pain n = 26, pain free n = 13, mean age = 16 years). Both studies used a threat-safety learning paradigm with memory recall (≈1 month later). Participants completed structural and functional (resting-state) magnetic resonance imaging, salivary cortisol measurements, and self-report measures. Adolescents with pain and pain-free peers consistently recalled being more afraid of safety cues (CS-) and, during heightened stress at encoding (higher cortisol levels), also reported being more afraid of threat cues (CS+). However, no memory bias was present for the emotional response to an aversive stimulus (US; loud scream) or for the recall of pain intensity. Functional connectivity of the amygdala and hippocampus with memory circuits related to the degree of memory bias, but the specific connections varied between the studies, and we observed no relationship between memory bias and brain morphology. Our findings highlight the value of considering the interaction between implicit and explicit memory systems, contributing to a more comprehensive understanding of emotional memory biases in the context of chronic pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".