Artificial gravity during a spaceflight analog alters brain sensory connectivity
Bibliographic record
Abstract
Spaceflight has numerous untoward effects on human physiology. Various countermeasures are under investigation including artificial gravity (AG). Here, we investigated whether AG alters resting-state brain functional connectivity changes during head-down tilt bed rest (HDBR), a spaceflight analog. Participants underwent 60 days of HDBR. Two groups received daily AG administered either continuously (cAG) or intermittently (iAG). A control group received no AG. We assessed resting-state functional connectivity before, during, and after HDBR. We also measured balance and mobility changes from pre- to post-HDBR. We examined how functional connectivity changes throughout HDBR and whether AG is associated with differential effects. We found differential connectivity changes by group between posterior parietal cortex and multiple somatosensory regions. The control group exhibited increased functional connectivity between these regions throughout HDBR whereas the cAG group showed decreased functional connectivity. This finding suggests that AG alters somatosensory reweighting during HDBR. We also observed brain-behavioral correlations that differed significantly by group. Control group participants who showed increased connectivity between the putamen and somatosensory cortex exhibited greater mobility declines post-HDBR. For the cAG group, increased connectivity between these regions was associated with little to no mobility declines post-HDBR. This suggests that when somatosensory stimulation is provided via AG, functional connectivity increases between the putamen and somatosensory cortex are compensatory in nature, resulting in reduced mobility declines. Given these findings, AG may be an effective countermeasure for the reduced somatosensory stimulation that occurs in both microgravity and HDBR.
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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) | 0.001 | 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".