Mechanical pain sensitivity is associated with hippocampal structural integrity
Bibliographic record
Abstract
ABSTRACT: Rodents and human studies indicate that the hippocampus, a brain region necessary for memory processing, responds to noxious stimuli. However, the hippocampus has yet to be considered a key brain region directly involved in the human pain experience. One approach to answer this question is to perform quantitative sensory testing on patients with hippocampal damage-ie, medial temporal lobe epilepsy. Some case studies and case series have performed such tests in a handful of patients with various types of epilepsy and have reported mixed results. Here, we aimed to determine whether mechanical pain sensitivity was altered in patients diagnosed with temporal lobe epilepsy. We first investigated whether mechanical pain sensitivity in patients with temporal lobe epilepsy differs from that of healthy individuals. Next, in patients with temporal lobe epilepsy, we evaluated whether the degree of pain sensitivity is associated with the degree of hippocampal integrity. Structural integrity was based on hippocampal volume, and functional integrity was based on verbal and visuospatial memory scores. Our findings show that patients with temporal lobe epilepsy have lower mechanical pain sensitivity than healthy individuals. Only left hippocampal volume was positively associated with mechanical pain sensitivity-the greater the hippocampal damage, the lower the sensitivity to mechanical pain. Hippocampal measures of functional integrity were not significantly associated with mechanical pain sensitivity, suggesting that the mechanisms of hippocampal pain processing may be different than its memory functions. Future studies are necessary to determine the mechanisms of pain processing in the hippocampus.
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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 | 0.001 | 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".