THE EFFECTS OF EXERCISE ON BRAIN FUNCTIONAL CONNECTIVITY IN ADULTS AGED 55–65 EXPOSED TO EXPERIMENTAL BED REST
Bibliographic record
Abstract
Abstract Bed rest can occur because of chronic conditions, injury, or hospitalization and initiate a downward spiral of deleterious changes in several body systems. Exercise is a countermeasure to many of these changes. However, its impact on middle-aged and older adults’ brain functional connectivity (FC) during bed rest remains unexplored. We examined the effects of exercise on brain resting-state FC in adults exposed to 14 days of experimental 6° head-down bed rest (HDBR). We conducted a non-blinded, parallel-group, randomized controlled trial with 23 healthy adults aged 55-65. Participants were randomized to either 14 days of HDBR (CON) or 14 days of HDBR with daily aerobic and strength exercise training (EX). At baseline and HDBR completion, participants underwent brain structural and resting-state functional magnetic resonance (MRI). Resting-state MRI preprocessing was performed using the FMRIPREP version 20.2.3. We extracted preprocessed resting-state time-series from a priori networks of interest based on Yeo’s 7-network parcellation. We conducted complete-case data analysis (NEX=11; NCON=8). Analysis of covariance explored EX effects on resting-state FC after controlling for baseline resting-state FC and baseline physical activity assessed by the Physical Activity Scale for the Elderly. Changes in EX resting-state FC within- and between- the Visual, Sensorimotor, Dorsal Attention, Ventral Attention, Fronto-Executive, Frontoparietal, and Default Mode Networks were not statistically significant compared with CON (all ps > 0.05). Exposure to 14 days of experimental HDBR or 14 days of daily aerobic and strength exercise training in HDBR did not elicit changes in brain resting-state FC of healthy middle-aged and older adults.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".