Dorsal hippocampal function in unreinforced spatial learning
Bibliographic record
Abstract
This study examined learning about the spatial environment by rats during a single 10 min period of exploration on an eight-arm radial maze. Because no specific behaviors were learned during this procedure, the existence of learned spatial information was inferred from its retarding effect on subsequent conditioned cue preference (CCP) learning on the same maze. Previous experiments have shown that this form of spatial learning, measured in this way, requires an intact fimbriafornix and functional N-methyl-D-aspartate receptors. However, in the present experiments, large neurotoxic lesions of the dorsal hippocampus that impaired win-shift learning failed to eliminate the retarding effect of exploration on CCP learning. This result was obtained in three independent replications. These findings fail to confirm the hypothesis that the hippocampus is involved in spatial learning when that learning occurs in the absence of reinforcers and does not produce any specific learned behaviors. Previous work showed that this form of "pure" spatial learning requires an intact fimbria-fornix for acquisition but not for expression; the present findings suggest that the hippocampus is not required for either of these processes. The fimbria-fornix may interact with other temporal lobe structures in mediating this form of learning. The function of the hippocampus may be limited in some way to situations that involve reinforcers and/or situations in which specific behaviors are learned.
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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".