The medial temporal lobe in nociception: a meta-analytic and functional connectivity study
Bibliographic record
Abstract
Recent neuroimaging studies implicate the medial temporal lobe (MTL) in nociception and pain modulation. Here, we aim to identify which subregions of the MTL are involved in human pain and to test its connectivity in a cohort of chronic low-back pain patients (CBP). We conducted 2 coordinate-based meta-analyses to determine which regions within the MTL showed consistent spatial patterns of functional activation (1) in response to experimental pain in healthy participants and (2) in chronic pain compared with healthy participants. We followed PRISMA guidelines and performed activation likelihood estimate (ALE) meta-analyses. The first meta-analysis revealed consistent activation in the right anterior hippocampus (right antHC), parahippocampal gyrus, and amygdala. The second meta-analysis revealed consistently less activation in patients' right antHC, compared with healthy participants. We then conducted a seed-to-voxel resting state functional connectivity of the right antHC seed with the rest of the brain in 77 CBP and 79 age-matched healthy participants. We found that CBP had significantly weaker antHC functional connectivity to the medial prefrontal cortex compared with healthy participants. Taken together, these data indicate that the antHC has abnormally lower activity in chronic pain and reduced connectivity to the medial prefrontal cortex in CBP. Future studies should investigate the specific role of the antHC in the development and management 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".