Repeated Subconcussive Head Impacts Compromise White Matter Integrity and Bimanual Coordination in Collegiate Football Players
Bibliographic record
Abstract
Abstract Objectives To determine whether repetitive subconcussive impacts in collegiate football are associated with altered white matter microstructure, motor control deficits, and changes in concussion symptoms across a single season. Design Cohort study with non-contact controls and stratification of contact athletes by head-impact exposure. Method Twenty-two male varsity football players and 27 non-contact controls underwent pre-season diffusion tensor imaging. Tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were derived from commissural and association tracts using probabilistic tractography. Helmet-mounted accelerometers quantified head-impact frequency and gForce over the season, classifying athletes into high (HE) and low-exposure (LE) groups. Football players completed the Kinarm Ball-on-Bar bimanual coordination task and SCAT3 symptom checklist pre- and post-season. Results At pre-season, contact athletes showed altered white matter microstructure versus controls, with higher FA and predominantly lower MD across most tracts. Over the season, HE athletes sustained more total impacts and gForce than LE athletes and showed declining bimanual coordination on the Ball-on-Bar motor task. SCAT3 symptom and severity scores were low and showed no differences in change. Conclusions Repetitive subconcussive exposure in collegiate football is associated with persisting white matter differences and subtle bimanual motor coordination deficits that are not detected by routine symptom-based tools, supporting the use of advanced neuroimaging and robotic motor assessment to monitor athlete brain health.
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 | 0.001 | 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) | 0.002 | 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".