Attention modulates hippocampal sharp-wave ripples in humans
Bibliographic record
Abstract
Abstract Hippocampal sharp-wave ripples (SWRs) are high-frequency events critical for memory consolidation, typically studied during sleep and quiet wakefulness. Emerging evidence suggests that SWRs also occur during active behavior, yet their role in awake cognition remains unclear. Here, we demonstrate that changes in sustained attention modulate both the occurrence of SWRs and their temporal alignment to ongoing hippocampal oscillations. Using intracranial EEG recordings from epilepsy patients performing a sustained attention to response task (SART), we first identified attentional states based on behavioral variability and subjective reports. Next, we observed that SWRs were more frequent during high-attention periods, despite the absence of memory demands. Importantly, SWRs during low-attention periods showed higher phase synchrony with low-frequency oscillations (theta to lower beta) indicating increased endogenous coordination of SWRs under low attentional focus. These findings show that SWRs are dynamically regulated by attentional engagement, supporting a broader role for ripples in active cognitive processing.
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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".