Metabotropic Glutamate Receptor Dependent Cortical Plasticity in Chronic Pain
Bibliographic record
Abstract
Many cortical areas play crucial roles in higher order brain functions such as pain and emotion-processing, decision-making, and cognition. Among them, anterior cingulate cortex (ACC) and insular cortex (IC) are two key areas. Glutamate mediates major excitatory transmission during long-term plasticity in both physiological and pathological conditions. Specifically related to nociceptive or pain behaviors, metabotropic glutamate subtype receptors (mGluRs) have been involved in different types of synaptic modulation and plasticity from periphery to the spinal cord. However, less is known about their functional roles in plasticity related to pain and its related behaviors within cortical regions. In this review, we first summarized previous studies of synaptic plasticity in both the ACC and IC, and discussed how mGluRs may be involved in both cortical long-term potentiation (LTP) and long-term depression (LTD)-especially in LTD. The activation of mGluRs contributes to the induction of LTD in both ACC and IC areas. The loss of LTD caused by peripheral amputation or nerve injury can be rescued by priming ACC or IC with activations of mGluR1 receptors. We also discussed the potential functional roles of mGluRs for pain-related behaviors. We propose that targeting mGluRs in the cortical areas including the ACC and IC may provide a new therapeutic strategy for the treatment of chronic pain, phantom pain or anxiety.
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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 | 0.002 |
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".