Not Just for Joints: The Associations of Moderate-to-Vigorous Physical Activity and Sedentary Behavior with Brain Cortical Thickness
Bibliographic record
Abstract
INTRODUCTION: Cortical thinning is associated with aging; however, lifestyle factors can moderate this relationship. Two distinct lifestyle behaviors associated with brain health are regular moderate-to-vigorous physical activity (MVPA) and limited sedentary behavior (SB). However, it is unclear whether MVPA and SB levels contribute to cortical thickness independent of each other. We therefore investigated the independent relationships of MVPA and SB with cortical thickness using baseline data from a randomized controlled trial. METHODS: At baseline, we measured MVPA and SB for 7 d using the SenseWear Mini. A subset of the randomized controlled trial participants (n = 30) underwent a 3T magnetic resonance imaging scan, wherein region-specific cortical surface morphometric analyses were performed using T1-weighted structural magnetic resonance imaging. We conducted regression analyses using a surface-based cluster size exclusion method for multiple comparisons within FreeSurfer neuroimaging software to determine if MVPA and SB are independently correlated with region-specific cortical thickness. RESULTS: This subset of participants had a mean age of 61 yr (SD = 9 yr), and 80% were female. Higher MVPA was associated with greater cortical thickness in the temporal pole (cluster size, 855 mm; cortical thickness range, 2.59-3.72 mm; P < 0.05) and superior frontal gyrus (cluster size, 1204 mm; cortical thickness range, 2.41-3.15 mm; P < 0.05) of the left hemisphere, independent of SB. Sedentary behavior was not associated with greater cortical thickness in any region, independent of MVPA. CONCLUSIONS: Our results indicate that adults with greater MVPA-independent of SB-are associated with greater cortical thickness in regions, which are susceptible to age-associated atrophy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".