The microgravity environment affects sensorimotor adaptation and its neural correlates
Bibliographic record
Abstract
The microgravity environment results in transient changes in sensorimotor behavior upon astronauts' return to Earth; the effects on behavior inflight are less understood. We examined whether adaptation to sensory conflict is disrupted in microgravity, suggesting competition for adaptive resources. We evaluated sensorimotor adaptation pre-, in-, and post-flight, as well as functional brain changes at pre- and post-flight, in astronauts participating in International Space Station missions. Astronauts (n = 13) performed this task pre- and four times post-flight within an MRI scanner and performed the task three times in microgravity during a 6-mo mission. We collected behavioral data from Earth-bound controls (n = 13) along the same timeline. Astronauts displayed no change in adaptation from pre- to inflight or following their return to Earth. They showed greater aftereffects of adaptation inflight; controls did not. Astronauts also displayed increased brain activity from pre- to post-flight. These increases did not return to baseline levels until 90 d post-flight. This pattern of brain activity may reflect compensation, allowing astronauts to maintain pre-flight performance levels. These findings indicate that microgravity does not alter short-term visuomotor adaptation; however, it does affect de-adaptation, and post-flight sensorimotor neural activation can take up to 90 d to return to pre-flight levels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".