Bibliographic record
Abstract
In humans and other mammals, event memories are imprecise until the emergence of episodic or episodic-like memory during childhood. The onset of episodic-like memory has historically been associated with maturation of the hippocampus, yet the specific neurobiological mechanisms underlying episodic-like memory development are poorly understood. Using mice, we identified a series of cellular and molecular events in the neurodevelopment of the hippocampus that underlies the ontogeny of precise, episodic-like memories. We found that hippocampus-dependent memories increase in precision at the beginning of the fourth postnatal week (i.e., between postnatal days 20 and 24), following a transient period of elevated neuronal activity in hippocampal subfield CA1. The emergence of precise, episodic-like memories during the fourth postnatal week involves a shift in excitatory-inhibitory balance in CA1 that is initiated by the formation of the extracellular matrix around parvalbumin (PV+)-expressing interneurons. The maturation of CA1 PV+ interneurons by extracellular perineuronal nets (PNNs) subsequently allows experiences encoded by older mice to be allocated to sparse neuronal engram ensembles that support precise, episodic-like memories. Lastly, we found that the development of CA1 PNNs and episodic-like memory precision is regulated by early-life experiences, rather than chronological age alone. Specifically, episodic-like memory development can be decelerated by adverse experiences or accelerated by enriching experiences occurring during the early postnatal period. In summary, the research contained in this thesis demonstrates that the development of episodic-like memory requires adult-like neuronal allocation mechanisms that are controlled by the maturation of the extracellular matrix surrounding inhibitory circuitry in CA1. The timing of this shift in hippocampal function is shaped by early-life experiences, suggesting that the hippocampus undergoes a sensitive period for the emergence of episodic-like memories.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".