Enhancing Prefrontal Neuron Activity Enables Associative Learning of Temporally Disparate Events
Bibliographic record
Abstract
The ability to link events that are separated in time is important for extracting meaning from experiences and guiding behavior in the future. This ability likely requires the brain to continue representing events even after they have passed, a process that may involve the prefrontal cortex and takes the form of sustained, event-specific neuron activity. Here, we show that experimentally increasing the activity of excitatory neurons in the medial prefrontal cortex (mPFC) enables rats to associate two stimuli separated by a 750-ms long temporal gap. Learning is accompanied by ramping increases in prefrontal theta and beta rhythms during the interval between stimuli. This ramping activity predicts memory-related behavioral responses on a trial-by-trial basis but is not correlated with the same muscular activity during non-memory conditions. Thus, the enhancement of prefrontal neuron excitability extends the time course of evoked prefrontal network activation and facilitates the formation of associations of temporally disparate, but correlated, events.
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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 | 0.000 |
| 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".