Plasticity of Metabotropic Glutamate Receptor-Dependent Long-Term Depression in the Anterior Cingulate Cortex after Amputation
Bibliographic record
Abstract
Long-term depression (LTD) is a key form of synaptic plasticity important in learning and information storage in the brain. It has been studied in various cortical regions, including the anterior cingulate cortex (ACC). ACC is a crucial cortical region involved in such emotion-related physiological and pathological conditions as fear memory and chronic pain. In the present study, we used a multielectrode array system to map cingulate LTD in a spatiotemporal manner within the ACC. We found that low-frequency stimulation (1 Hz, 15 min) applied onto deep layer V induced LTD in layers II/III and layers V/VI. Cingulate LTD requires activation of metabotropic glutamate receptors (mGluRs), while L-type voltage-gated calcium channels and NMDA receptors also contribute to its induction. Peripheral amputation of the distal tail impaired ACC LTD, an effect that persisted for at least 2 weeks. The loss of LTD was rescued by priming ACC slices with activation of mGluR1 receptors by coapplying (RS)-3,5-dihydroxyphenylglycine and MPEP, a form of metaplasticity that involved the activation of protein kinase C. Our results provide in vitro evidence of the spatiotemporal properties of ACC LTD in adult mice. We demonstrate that tail amputation causes LTD impairment within the ACC circuit and that this can be rescued by activation of mGluR1.
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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) | 0.000 | 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) | 0.001 | 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".