Hippocampal Dynamics Predict Interindividual Cognitive Differences in Rats
Bibliographic record
Abstract
There are important and sustained interindividual differences in cognition during aging. Here, we investigated hippocampal spatial representations in a rat model of cognitive aging characterized by individual differences in a mnemonic task. Individual cognitive capabilities in old rats were assessed in a delayed non-matching-to-position task. We recorded hippocampal CA1 place cells as the rats explored a familiar environment. Unlike the usual place cells commonly described in the literature, we found that a significant fraction of pyramidal neurons recorded in our study showed a substantial delayed onset of their place field activity. We established that this firing onset delay naturally occurs under basal conditions in old rats and is positively correlated with the remapping status of the animals. The lack of firing during the first few hundred seconds after the animals were introduced into a familiar environment was also associated with an increased locomotion in the remapping rats. This delayed activity is central to understanding the individual basis of age-related cognitive impairment and to resolving numerous discrepancies in the literature on the place cell contribution to the etiology of aged-related decline. Finally, we also found a positive correlation between the degree of firing variability of place cells ("overdispersion") and performance during the long delays in the delayed non-matching-to-position task. Place cell overdispersion might provide the functional basis for interindividual differences in behavior and cognition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".