Prediction Without Generalization: A Reanalysis of EEG Dream Recall Models in the DREAM Database
Mehdi Belafekir
Zenodo (CERN European Organization for Nuclear Research) June 8, 2026 preprint DOI: 10.5281/zenodo.20597471 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Validation analyses |
|---|---|
| Sample size | 148 |
| Population | Subjects in sleep and wakefulness research |
| Topics | Dreaming |
| Keywords | Recall Generalization Dream Variance accounting Code set theory Identity music Artificial intelligence Natural language processing Database Electroencephalography |
| Key points | No dataset-stage combination showed evidence of above-chance generalization after bootstrap testing, and dataset identity dominated predictive variance (74.5%). |
Abstract
52 validation analyses across 6 datasets, 148 subjects, and 1,267 awakenings. No dataset-stage combination showed evidence of above-chance generalization after bootstrap testing. Dataset identity dominates predictive variance (74.5%). All code and data publicly available.