Brain and Behavioral Evidence for Reweighting of Vestibular Inputs with Long-Duration Spaceflight
Bibliographic record
Abstract
Microgravity alters vestibular signaling. In-flight adaptation to altered vestibular afferents is reflected in post-spaceflight aftereffects, evidenced by declines in vestibularly mediated behaviors (e.g., walking/standing balance), until readaptation to Earth's 1G environment occurs. Here we examine how spaceflight affects neural processing of applied vestibular stimulation. We used fMRI to measure brain activity in response to vestibular stimulation in 15 astronauts pre- and post-spaceflight. We also measured vestibularly-mediated behaviors, including balance, mobility, and rod-and-frame test performance. Data were collected twice preflight and four times postflight. As expected, vestibular stimulation at the preflight sessions elicited activation of the parietal opercular area ("vestibular cortex") and deactivation of somatosensory and visual cortices. Pre- to postflight, we found widespread reductions in this somatosensory and visual cortical deactivation, supporting sensory compensation and reweighting with spaceflight. These pre- to postflight changes in brain activity correlated with changes in eyes closed standing balance, and greater pre- to postflight reductions in deactivation of the visual cortices associated with less postflight balance decline. The observed brain changes recovered to baseline values by 3 months postflight. Together, these findings provide evidence for sensory reweighting and adaptive cortical neuroplasticity with spaceflight. These results have implications for better understanding compensation and adaptation to vestibular functional disruption.
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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".