Dysregulated neuromodulation in the anterior cingulate cortex in chronic pain
Bibliographic record
Abstract
Chronic pain is a significant global socioeconomic burden with limited long-term treatment options. The intractable nature of chronic pain stems from two primary factors: the multifaceted nature of pain itself and an insufficient understanding of the diverse physiological mechanisms that underlie its initiation and maintenance, in both the peripheral and central nervous systems. The development of novel non-opioidergic analgesic approaches is contingent on our ability to normalize the dysregulated nociceptive pathways involved in pathological pain processing. The anterior cingulate cortex (ACC) stands out due to its involvement in top-down modulation of pain perception, its abnormal activity in chronic pain conditions, and its contribution to cognitive functions frequently impaired in chronic pain states. Here, we review the roles of the monoamines dopamine (DA), norepinephrine (NE), serotonin (5-HT), and other neuromodulators in controlling the activity of the ACC and how chronic pain alters their signaling in ACC circuits to promote pathological hyperexcitability. Additionally, we discuss the potential of targeting these monoaminergic pathways as a therapeutic strategy for treating the cognitive and affective symptoms associated with 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".