Protein Synthesis Is Required for the Enhancement of Long-Term Potentiation and Long-Term Memory by Spaced Training
Bibliographic record
Abstract
Spaced training is generally more effective than massed training for learning and memory, but the molecular mechanisms underlying this trial spacing effect remain poorly characterized. One potential molecular basis for the trial spacing effect is the differential modulation, by distinct temporal patterns of neuronal activity, of protein synthesis-dependent processes that contribute to the expression of specific forms of synaptic plasticity in the mammalian brain. Long-term potentiation (LTP) is a type of synaptic modification that may be important for certain forms of memory storage in the mammalian brain. To explore the role of protein synthesis in the trial spacing effect, we assessed the protein synthesis dependence of hippocampal LTP induced by 100-Hz tetraburst stimulation delivered to mouse hippocampal slices in either a temporally massed (20-s interburst interval) or spaced (5-min interburst interval) fashion. To extend our studies to the behavioral level, we trained mice in fear conditioning using either a massed or spaced training protocol and examined the sensitivity of long-term memory to protein synthesis inhibition. Larger LTP was induced by spaced stimulation in hippocampal slices. This improvement of synaptic potentiation following temporally spaced synaptic stimulation in slices was attenuated by bath application of an inhibitor of protein synthesis. Further, the maintenance of LTP induced by spaced synaptic stimulation was more sensitive to disruption by anisomycin than the maintenance of LTP elicited following massed stimulation. Temporally spaced behavioral training improved long-term memory for contextual but not for cued fear conditioning, and this enhancement of memory for contextual fear was also protein synthesis dependent. Our data reveal that altering the temporal spacing of synaptic stimulation and behavioral training improved hippocampal LTP and enhanced contextual long-term memory. From a broad perspective, these results suggest that the recruitment of protein synthesis-dependent processes important for long-term memory and for long-lasting forms of LTP can be modulated by the temporal profiles of behavioral training and synaptic stimulation.
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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".