Rapid Eye Movements (REMs) and visual dream recall in both congenitally blind and sighted subjects
Bibliographic record
Abstract
Our objective was to evaluate rapid eye movements (REMs) associated with visual dream recall in sighted subjects and congenital blind. During two consecutive nights polysomnographic recordings were performed at subjects home. REMs were detected by visual inspection on both EOG channels (EOG-H, EOG-V) and further classified as occurring isolated or in bursts. Dream recall was defined by the existence of a dream report. The two groups were compared using t-test and also the two-way ANOVA and a post-hoc Fisher test (for the features diagnosis (blind vs. sighted) and dream recall (yes or no) as a function of time). The average of REM awakenings per subject and the recall ability were identical in both groups. CB had a lower REM density than CS; the same applied to REM bursts and isolated eye movements. In the two-way ANOVA, REM bursts and REM density were significantly different for positive dream recall, mainly for the CB group and for diagnosis; furthermore for both features significant results were obtained for the interaction of time, recall and diagnosis; the interaction of recall and time was however, stronger. In line with previous findings the data show that blind have lower REMs density. However the ability of dream recall in congenitally blind and sighted controls is identical. In both groups visual dream recall is associated with an increase in REM bursts and density. REM bursts also show differences in the temporal profile. REM visual dream recall is associated with increased REMs activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".