Improved Frontoparietal White Matter Integrity in Overweight Children Is Associated with Attendance at an After-School Exercise Program
Bibliographic record
Abstract
Aerobic fitness is associated with white matter integrity (WMI) in adults as measured by diffusion tensor imaging (DTI). This study examined the effect of an 8-month exercise intervention on WMI in children. Participants were 18 sedentary, overweight (BMI≥85th percentile) 8- to 11-year-old children (94% Black), randomly assigned to either an aerobic exercise (n=10) or sedentary attention control group (n=8). Each group was offered an instructor-led after-school program every school day for approximately 8 months. Before and after the program, all subjects participated in DTI scans. Tractography was conducted to isolate the superior longitudinal fasciculus and investigate whether the exercise intervention affected WMI in this region. There was no group by time interaction for WMI in the superior longitudinal fasciculus. There was a group by time by attendance interaction, however, such that higher attendance at the exercise intervention, but not the control intervention, was associated with increased WMI. Heart rate and the total dose of exercise correlated with WMI changes in the exercise group. In the overall sample, increased WMI was associated with improved scores on a measure of attention and improved teacher ratings of executive function. This study indicates that participating in an exercise intervention improves WMI in children as compared to a sedentary after-school program.
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 | 0.001 |
| 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".