Modulation of auditory sensory memory by chronic clinical pain and acute experimental pain: a mismatch negativity study
Bibliographic record
Abstract
Pain, especially chronic pain, can lead to cognitive deficits. Mismatch negativity (MMN) is a change-specific component of the auditory event-related brain potential (ERP) that is thought to provide a unique window into sensory memory processes. The present study was designed to determine how chronic and acute pain affects auditory sensory memory. In experiment 1, MMNs elicited by standard and deviant auditory stimuli at short and long inter-stimulus intervals (ISIs) were compared between trigeminal neuralgia (TN) patients and demographically matched healthy controls (HCs). The TN patients were found to have stronger attenuation of the MMN at longer ISIs than HCs. Correlation analysis revealed a significant positive correlation between the sensory subscale of McGill Pain Questionnaire and MMN amplitude reduction across ISI conditions. In experiment 2, MMNs recorded before, during, and after the cold pressor test were compared in healthy subjects. MMN amplitude was significantly reduced during pain exposure and recovered immediately thereafter. These results suggest that both chronic pain and acute pain can interfere with automatic change detection processes in the brain. This study provides the first evidence that chronic pain patients have a faster auditory memory trace decay than HCs.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".