Coordinated activities of retrosplenial ensembles during resting-state encode spatial landmarks
Bibliographic record
Abstract
The brain likely uses offline periods to consolidate recent memories. One hypothesis holds that the hippocampal output provides a unique, global linking or ‘index’ code for each memory, and that this code is stored in the cortex in association with locally encoded attributes of each memory. Activation of the index code is hypothesized to evoke coordinated memory trace reactivation thus facilitating consolidation. Retrosplenial cortex (RSC) is a major recipient of hippocampal outflow and we have described populations of neurons there with sparse and orthogonal coding characteristics that resemble hippocampal ‘place’ cells, and whose expression depends on an intact hippocampus. Using two-photon Ca 2+ imaging, we recorded ensembles of neurons in the RSC during periods of immobility before and after active running on a familiar linear treadmill track. Synchronous bursting of distinct groups of neurons occurred during rest both prior to and after running. In the second rest epoch, these patterns were associated with the locations of tactile landmarks and reward. Complementing established views on the functions of the RSC, our findings indicate that the structure is involved with processing landmark information during rest. This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.
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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".