An Acute Bout of Soccer Heading Subtly Alters Neurovascular Coupling Metrics
Bibliographic record
Abstract
Objective: The current investigation examined how a bout of soccer heading may impact brain function. Design: Semi-randomized crossover cohort. Setting: Controlled soccer heading. Participants: Seven male soccer players (24.1 ± 1.5 years). Intervention: 40 successful soccer headers were performed in 20 minutes (25m, launch velocity ~80 km/hr). X2 xPatch recorded linear and rotational head accelerations during each impact. A contact control ‘sham’ condition – ball made body contact, but not by the head; and a no activity time ‘control’ condition were also completed. Main Outcome Measures: Posterior and middle cerebral artery (PCA and MCA, respectively) cerebral blood velocity (CBV) was recorded during a visual task (neurovascular coupling: NVC) alongside SCAT3 symptoms scores pre/post a controlled bout of soccer heading. Results: Cumulative linear and rotational accelerations were 1,57497.9 g and 313,761±23,966 rads/s2, respectively during heading and changes in SCAT3 symptom number (pre: 2.6±3.0; post: 6.7±6.2, p=0.13) and severity (pre: 3.7±3.6, post: 9.4±7.6, p=0.11) were unchanged. In the PCA, no NVC differences were observed, including: relative CBV increase (28.0±7.6%, p=0.71) and total activation (188.7±68.1 cm, p=0.93). However, MCA-derived NVC metrics were blunted following heading, demonstrating decreased relative CBV increase (7.8±3.1 %, p=0.03) and decreased total activation (26.7±45.3 cm, p=0.04). Conclusion: Although an acute bout of soccer heading did not result in an increase of concussion-like symptoms, there were alterations in NVC responses within the MCA during a visual task. This suggests an acute bout of repetitive soccer heading can alter CBV regulation within the region of the brain associated with the header impacts.
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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 | 0.000 | 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) | 0.003 | 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".