Spatial Reference Memory is Associated with Modulation of Theta–Gamma Coupling in the Dentate Gyrus
Bibliographic record
Abstract
Spatial reference memory in rodents represents a unique opportunity to study brain mechanisms responsible for encoding, storage and retrieval of a memory. Even though its reliance on hippocampal networks has long been established, the precise computations performed by different hippocampal subfields during spatial learning are still not clear. To study the evolution of electrophysiological activity in the CA1-dentate gyrus axis of the dorsal hippocampus over an iterative spatial learning paradigm, we recorded local field potentials in behaving mice using a newly designed appetitive version of the Barnes maze. We first showed that theta and gamma oscillations as well as theta-gamma coupling are differentially modulated in particular hippocampal subfields during the task. In addition, we show that dentate gyrus networks, but not CA1 networks, exhibit a transient learning-dependent increase in theta-gamma coupling specifically at the vicinity of the target area in the maze. In contrast to previous immediate early-gene studies, our results point to a long-lasting involvement of dentate networks in navigational memory in the Barnes maze. Based on these findings, we propose that theta-gamma coupling might represent a mechanism by which hippocampal areas compute relevant information.
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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) | 0.000 | 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".