Cortical Tagged Synaptic Long-Term Depression in the Anterior Cingulate Cortex of Adult Mice
Bibliographic record
Abstract
The anterior cingulate cortex (ACC) is a key cortical region for pain perception and emotion. Different forms of synaptic plasticity, including long-term potentiation (LTP) and long-term depression (LTD), have been reported in the ACC. Synaptic tagging of LTP plays an important role in hippocampus-related associative memory. In this study, we demonstrate that synaptic tagging of LTD is detected in the ACC of adult male and female mice. This form of tagged LTD requires the activation of metabotropic glutamate receptor subtype 1 (mGluR1). The induction of tagged LTD is time-related with the strongest tagged LTD appearing when the interval between two independent stimuli is 30 min. Inhibitors of mGluR1 blocked the induction of tagged LTD; however, blocking N-methyl-d-aspartate receptors did not affect the induction of tagged LTD. Nimodipine, an inhibitor of L-type voltage-gated calcium channels, also blocked tagged LTD. In an animal model of amputation, we found that tagged LTD was either reduced or completely blocked. Together with our previous report of tagged LTP in the ACC, this study strongly suggests that excitatory synapses in the adult ACC are highly plastic. The biphasic tagging of synaptic transmission provides a new form of heterosynaptic plasticity in the ACC which has functional and pathophysiological significance in phantom 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".