Claustrum projections to the anterior cingulate modulate nociceptive and pain-associated behavior
Bibliographic record
Abstract
The anterior cingulate cortex (ACC) is critical for the perception and unpleasantness of pain. 1 , 2 , 3 , 4 , 5 , 6 It receives nociceptive information from regions such as the thalamus and amygdala and projects to several cortical and subcortical regions of the pain neuromatrix. 7 , 8 ACC hyperexcitability is one of many functional changes associated with chronic pain, and experimental activation of ACC pyramidal cells produces hypersensitivity to innocuous stimuli (i.e., allodynia). 9 , 10 , 11 , 12 , 13 , 14 A less-well-studied projection to the ACC arises from a small forebrain region, the claustrum. 15 , 16 , 17 , 18 , 19 , 20 Stimulation of excitatory claustrum projection neurons preferentially activates GABAergic interneurons, generating feed-forward inhibition onto excitatory cortical networks. 21 , 22 , 23 , 24 Previous work has shown that claustrocingulate projections display altered activity in prolonged pain 25 , 26 , 27 ; however, it remains unclear whether and how the claustrum participates in nociceptive processing and high-order pain behaviors. Inhibition of ACC activity reverses mechanical allodynia in animal models of persistent and neuropathic pain, 1 , 9 , 28 suggesting claustrum inputs may function to attenuate pain processing. In this study, we sought to define claustrum function in acute and chronic pain. We found enhanced claustrum activity after a painful stimulus that was attenuated in chronic inflammatory pain. Selective inhibition of claustrocingulate projection neurons enhanced acute nociception but blocked pain learning. Inversely, chemogenetic activation of claustrocingulate neurons had no effect on basal nociception but rescued inflammation-induced mechanical allodynia. Together, these results suggest that claustrocingulate neurons are a critical component of the pain neuromatrix, and dysregulation of this connection may contribute to 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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".