Exploring the relationship between resting state intra-network connectivity and accelerometer-measured physical activity in pediatric concussion: A cohort study
Bibliographic record
Abstract
ABSTRACT Objectives To explore the association between resting state functional connectivity and accelerometer-measured physical activity in pediatric concussion. Methods Fourteen children with concussion (aged 14.54 ± 2.39 years, 8 female) were included in this secondary data-analysis. Participants had neuroimaging at 15.3 ± 6.7 days post-injury and subsequently a mean of 11.1 ± 5.0 days of accelerometer data. Intra-network connectivity of the default mode network (DMN), sensorimotor network (SMN), salience network (SN), and fronto-parietal network (FPN) was computed. Results Per general linear models, only intra-network connectivity of the DMN was associated with habitual physical activity levels. More specifically, increased intra-network connectivity of the DMN was significantly associated with higher levels of subsequent accelerometer-measured light physical activity (F (2,11) = 7.053, p = 0.011, R a 2 = 0.562; β = 0.469), moderate physical activity (F (2,11) = 7.053, p = 0.011, R a 2 = 0.562; β = 0.725), and vigorous physical activity (F (2,11) = 10.855, p = 0.002, R a 2 = 0.664; β = 0.79). Intra-network connectivity of the DMN did not significantly predict sedentary time. Likewise, the SMN, SA, and FPN were not significantly associated with either sedentary time or physical activity. Conclusion These findings suggest that there is a positive association between the intra-network connectivity of the DMN and device-measured physical activity in children with concussion. Given that DMN impairment can be commonplace following concussion, this may be associated with lower levels of habitual physical activity, which can preclude children from experiencing the symptom-improving benefits of sub-maximal physical activity. KEY FINDINGS What are the new findings? Intra-network connectivity of the default mode network is associated with subsequent accelerometer-measured light, moderate, and vigorous physical activity within the first-month of pediatric concussion Similar associations with physical activity are not observed when examining the intra-network connectivity of the sensorimotor network, salience network, or fronto-parietal network Improved connectivity within the default mode network may lead to increased participation in light to vigorous physical activity in pediatric concussion How might it impact on clinical practice in the future? Default mode network impairment is commonplace in concussion, and this may limit children from experiencing the symptom-improving benefits of physical activity Adjunctive interventions (e.g., mindfulness) that improve the health of the default mode network should be further studied in pediatric concussion
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".