Decreased Number of Self-Paced Saccades in Post-Concussion Syndrome Associated with Higher Symptom Burden and Reduced White Matter Integrity
Bibliographic record
Abstract
The aim of this study was to examine the potential utility of a self-paced saccadic eye movement as a marker of post-concussion syndrome (PCS) and monitoring the recovery from PCS. Fifty-nine persistently symptomatic participants with at least two concussions performed the self-paced saccade (SPS) task. We evaluated the relationships between the number of SPSs and 1) number of self-reported concussion symptoms, and 2) integrity of major white matter (WM) tracts (as measured by fractional anisotropy [FA] and mean diffusivity) that are directly or indirectly involved in saccadic eye movements and often affected by concussion. These tracts included the uncinate fasciculus (UF), cingulum (Cg) and its three subcomponents (subgenual, retrosplenial, and parahippocampal), superior longitudinal fasciculus, and corpus callosum. Mediation analyses were carried out to examine whether specific WM tracts (left UF and left subgenual Cg) mediated the relationship between the number of SPSs and 1) interval from last concussion or 2) total number of self-reported symptoms. The number of SPSs was negatively correlated with the total number of self-reported symptoms (r = -0.419, p = 0.026). The number of SPSs were positively correlated with FA of left UF and left Cg (r = 0.421, p = 0.013 and r = 0.452, p = 0.008; respectively). FA of the subgenual subcomponent of the left Cg partially mediated the relationship between the total number of symptoms and the number of SPSs, while FA of the left UF mediated the relationship between interval from last concussion and the number of SPSs. In conclusion, SPS testing as a fast and objective assessment may reflect symptom burden in patients with PCS. In addition, since the number of SPSs is associated with the integrity of some WM tracts, it may be useful as a diagnostic biomarker in patients with PCS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".