Modality-Specific Consolidation Shapes Long-Term Retention in Statistical Learning
Bibliographic record
Abstract
Everyday learning unfolds across multiple senses, yet the long-term retention of multisensory statistical learning (SL) remains poorly understood. SL—the implicit detection and extraction of regularities from continuous input—has been documented across sensory modalities, but most work has focused on immediate learning in unisensory contexts. This study, using a within-subject design, directly compared 24-hour consolidation trajectories of auditory, visual, and audiovisual SL in young adults. Twenty-six participants completed familiarization and an immediate test phase in all three modalities, followed by delayed testing after 24 hours. Multisensory input yielded higher recognition accuracy than unisensory input at both immediate and delayed tests, demonstrating a robust performance advantage. However, only auditory SL showed overnight gains, while visual and multisensory SL remained stable across the retention interval. Cross-task correlations—both within each testing timepoint and for consolidation magnitudes—were weak, suggesting that modality-specific processes make a substantial contribution to SL. These findings provide the first direct evidence on the long-term retention of multisensory SL. While multisensory input boosts overall performance, consolidation trajectories remain constrained by modality-specific mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| 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 teacher head, 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".