Hippocampal Volumetric Changes in Astronauts Following a Mission in the International Space Station
Bibliographic record
Abstract
(1) Background: Evidence from non-human animal and spaceflight analog studies have suggested that traveling to outer space could have a significant impact on the structural properties of the hippocampus, a brain region within the medial temporal lobe that is critical for learning and memory. Here, we tested this hypothesis in a group of astronauts who participated in a six-month mission in the International Space Station (ISS). (2) Methods: We collected magnetic resonance imaging (MRI) scans from a sample of 17 (9 males, 8 females) astronauts before and after the ISS mission, and calculated percent gray matter volume changes in the whole hippocampus and its (anterior, body, and posterior) subregions in both hemispheres. (3) Following the six-month mission in the ISS, we found a significantly decreased volume in the whole left hippocampus; in addition, when looking at subregions separately, we detected a significantly decreased volume in the anterior subregion of the left hippocampus and the body subregion of the right hippocampus. We also found a significantly decreased volume in the whole right hippocampus of male astronauts as compared to female astronauts. (4) Conclusions: This study, providing the very first evidence of hippocampal volumetric changes in astronauts following a six-month mission to the ISS, could have significant implications for cognitive performance during future long-duration spaceflights.
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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 | 0.001 | 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".