Hyperactivity of Anterior Cingulate Cortex Areas 24a/24b Drives Chronic Pain-Induced Anxiodepressive-like Consequences
Bibliographic record
Abstract
Pain associates both sensory and emotional aversive components, and often leads to anxiety and depression when it becomes chronic. Here, we characterized, in a mouse model, the long-term development of these sensory and aversive components as well as anxiodepressive-like consequences of neuropathic pain and determined their electrophysiological impact on the anterior cingulate cortex (ACC, cortical areas 24a/24b). We show that these symptoms of neuropathic pain evolve and recover in different time courses following nerve injury in male mice. In vivo electrophysiological recordings evidence an increased firing rate and bursting activity within the ACC when anxiodepressive-like consequences developed, and this hyperactivity persists beyond the period of mechanical hypersensitivity. Whole-cell patch-clamp recordings also support ACC hyperactivity, as shown by increased excitatory postsynaptic transmission and contribution of NMDA receptors. Optogenetic inhibition of the ACC hyperactivity was sufficient to alleviate the aversive and anxiodepressive-like consequences of neuropathic pain, indicating that these consequences are underpinned by ACC hyperactivity. SIGNIFICANCE STATEMENT Chronic pain is frequently comorbid with mood disorders, such as anxiety and depression. It has been shown that it is possible to model this comorbidity in animal models by taking into consideration the time factor. In this study, we aimed at determining the dynamic of different components and consequences of chronic pain, and correlated them with electrophysiological alterations. By combining electrophysiological, optogenetic, and behavioral analyses in a mouse model of neuropathic pain, we show that the mechanical hypersensitivity, ongoing pain, anxiodepressive consequences, and their recoveries do not necessarily exhibit temporal synchrony during chronic pain processing, and that the hyperactivity of the anterior cingulate cortex is essential for driving the emotional impact of neuropathic 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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".