Homosynaptic and Heterosynaptic Inhibition of Synaptic Tagging and Capture of Long-Term Potentiation by Previous Synaptic Activity
Bibliographic record
Abstract
Long-term potentiation (LTP) is an enhancement of synaptic strength that may contribute to information storage in the mammalian brain. LTP expression can be regulated by previous synaptic activity, a process known as "metaplasticity." Cell-wide occurrence of metaplasticity may regulate synaptic strength. However, few reports have demonstrated metaplasticity at synapses that are silent during activity at converging synaptic inputs. We describe a novel form of cell-wide metaplasticity in hippocampal area CA1. Low-frequency stimulation (LFS) decreased the stability of long-lasting LTP ["late" LTP (L-LTP)] induced later at the same inputs (homosynaptic inhibition) and at other inputs converging on the same postsynaptic cells (heterosynaptic inhibition). Significantly, heterosynaptic inhibition of L-LTP also occurred across basal and apical dendrites ("heterodendritic" inhibition). Because transient early LTP (E-LTP) was not affected by previous LFS, we examined the effects of LFS on the consolidation of E-LTP to L-LTP. The duration of E-LTP induced at one set of inputs can be extended by capturing L-LTP-associated gene products generated by previous activity at other inputs to the same postsynaptic neurons. LFS applied homosynaptically or heterosynaptically before L-LTP induction did not impair synaptic capture by subsequent E-LTP stimulation, suggesting that LFS does not impair L-LTP-associated transcription. In contrast, LFS applied just before E-LTP (homosynaptically or heterosynaptically) prevented synaptic tagging, and capture of L-LTP expression. Thus, LFS inhibits synaptic tagging to impair expression of subsequent L-LTP. Such anterograde inhibition represents a novel way in which synaptic activity can regulate the expression of future long-lasting synaptic plasticity in a cell-wide manner.
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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".