Poor sleep quality affects spatial orientation in virtual environments
Bibliographic record
Abstract
Sleep is well known to have a significant impact on learning and memory. Specifically, studies adopting an experimentally induced sleep loss protocol in healthy individuals have provided evidence that the consolidation of spatial memories, as acquired through navigating and orienteering in spatial surroundings, is negatively affected by total sleep loss. Here, we used both objective and subjective measures to characterize individuals' quality of sleep, and grouped participants into either a poor (insomnia-like) or normal (control) sleep quality group. We asked participants to solve a wayfinding task in a virtual environment, and scored their performance by measuring the time spent to reach a target location and the number of wayfinding errors made while navigating. We found that participants with poor sleep quality were slower and more error-prone than controls in solving the task. These findings provide novel evidence that pre-existing sleep deficiencies in otherwise healthy individuals affects negatively the ability to learn novel routes, and suggest that sleep quality should be accounted for among healthy individuals performing experimental spatial orientation tasks in virtual environments.
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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 | 0.000 | 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".