A role for adult hippocampal neurogenesis at multiple time scales: A study of recent and remote memory in humans.
Bibliographic record
Abstract
Adult hippocampal neurogenesis (AHN) is downregulated by numerous lifestyle factors including chronic stress. While the functional significance of AHN remains elusive, computational models and empirical evidence implicate immature neurons in minimizing interference between similar memories-a process termed pattern separation. The role of neurogenesis in remote memory is less clear. Some have proposed that neurogenesis promotes the clearance of old memories from the hippocampus, while others have proposed that neurogenesis promotes long-term retention of memories within the hippocampus. We used a modified version of the behavioral pattern separation task originally described by Kirwan and Stark (2007). In this task, some objects are repeated across trials, some are similar lures and the rest are novel. Participants are asked to classify each object as old, new, or similar. The correct classification of lures as similar may tax pattern separation processes in the hippocampus and AHN. To investigate the potential role of AHN in remote memory, we introduced a 2-week delay between the presentation and recognition of certain stimuli. As in previous studies, we found that those with higher depression scores made significantly more errors at identifying lures as similar when presentation and recognition were separated by a brief delay. When presentation and recognition trials were separated by a longer delay, the correct classification of lures dropped to chance levels for all groups, but now lower stress and depression scores were associated with superior identification of exact repetitions. Our data suggest a role for AHN in the stabilization of remote 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".