“Silent” Metaplasticity of the Late Phase of Long-Term Potentiation Requires Protein Phosphatases
Bibliographic record
Abstract
The late phase of long-term potentiation (L-LTP) is correlated with some types of long-term memory, but the mechanisms by which L-LTP is modulated by prior synaptic activity are undefined. Activation of protein phosphatases by low-frequency stimulation (LFS) given before induction of L-LTP may significantly modify L-LTP. Using cellular electrophysiological recording methods in mouse hippocampal slices, we show that LFS given before induction of L-LTP inhibited L-LTP in an activity-dependent manner without affecting either basal synaptic strength or the early phase of LTP (E-LTP). This anterograde inhibitory effect of LFS was persistent, required N-methyl-D-aspartate (NMDA) receptor activation, and was blocked by inhibitors of protein phosphatase 1 (PP1) and protein phosphatase 2A (PP2A). These data indicate that certain patterns of LFS can activate PP1 and/or PP2A, and that long-lasting activation of these phosphatases by prior LFS can suppress the subsequent expression of L-LTP without affecting E-LTP. Because this inhibition of L-LTP is caused by prior synaptic activity that, alone, produced no net effect on synaptic efficacy, we suggest that this is a "silent" form of metaplasticity that may influence long-term information storage by modulating the capacity of synapses to express L-LTP after repeated bouts of activity.
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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 | 0.001 | 0.001 |
| 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".