Thirty minutes of daily artificial gravity does not mitigate head down tilt induced brain activity changes during cognitive task performance
Bibliographic record
Abstract
Introduction: Studies have shown that microgravity results in high dual task costs when crewmembers perform cognitive-motor dual tasking. Head-down tilt bedrest (HDBR) has been widely used as a spaceflight analog environment, recreating some of the sensorimotor and cognitive changes, headward fluid shifts, and unloading of bones and muscles. Here, we examined whether artificial gravity (AG) mitigates changes in cognitive performance and associated brain activity that occur in the HDBR environment. Methods: = 8 controls) during the course of 60 days HDBR. Participants performed spatial working memory and cognitive-motor dual tasking prior to entering HDBR, during HDBR and post-HDBR. Results: Brain activation patterns associated with these two tasks changed with HDBR, but there was no difference between the AG and control groups. Compensatory brain-behavioral change-change correlations were observed, where those who increased activation the most had the least decrease in motor tapping accuracy from pre-HDBR to late-HDBR. Discussion: These results suggest that AG does not reduce the need for compensatory brain responses that occur with HDBR, but longer duration and/or more optimal AG phasing may be required.
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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) | 0.002 | 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".