Effects of Experimentally Induced Pain on Mismatch Negativity
Bibliographic record
Abstract
Abstract: Previous research has found that pain can exert a disruptive effect on cognitive processing. This experiment was conducted to extend previous research with participants with chronic pain. This report examines pain's effects on early processing of auditory stimulus differences using the Mismatch Negativity (MMN) in healthy participants while they experienced experimentally induced pain. Event-related potentials (ERPs) were recorded using target and standard tones whose pitch differences were easy- or difficult-to-detect in conditions where participants attended to (active attention) or ignored (passive attention) the stimuli. Both attention manipulations were conducted in no pain and pain conditions. Experimentally induced ischemic pain did not disrupt the MMN. However, MMN amplitudes were larger to difficult-to-detect deviant tones during painful stimulation when they were attended than when they were ignored. Also, MMN amplitudes were larger to the difficult- than to the easy-to-detect tones in the active attention condition regardless of pain condition. It appears that rather than exerting a disruptive effect, the presence of experimentally induced pain enhanced early processing of small stimulus differences in these healthy participants.
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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) | 0.003 | 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".