Hippocampal gamma and sharp wave/ripples mediate bidirectional interactions with cortical networks during sleep
Bibliographic record
Abstract
Summary Hippocampus-neocortex interactions during sleep are critical for memory processes: hippocampally-initiated replay contributes to memory consolidation in the neocortex and hippocampal sharp wave/ripples are linked to generalized increases in neocortical cell activity and DOWN-UP state transitions. Yet, the spatial and temporal patterns of this exchange are unknown. With voltage imaging, electrocorticography, and laminarly-resolved hippocampal potentials, we characterized cortico-hippocampal interactions during anesthesia and NREM sleep. We observed neocortical activation transients spanning multiple spatial scales hinting at a quasi-critical regime. Transients were organized in a small number of functional networks matching known anatomical connectivity. A network overlapping with the default mode network and centered on retrosplenial cortex was the most associated with the hippocampus. Interestingly, hippocampal slow gamma was the oscillation that best correlated with this neocortical network, outpacing ripples. In fact, neocortical activity predicted hippocampal slow gamma and followed ripples, suggesting that consolidation processes rely on bi-directional exchanges between hippocampus and neocortex.
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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".