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Smooth Pursuit And Saccadic Eye Movements Following Years Of Contact Collision Sports: A Pilot Study

2020· article· en· W3041539471 on OpenAlexaboutno aff
Nicholas G. Murray, Brian Székely, Arthur Islas, Cameron Kissick, Philip Pavilonis, Sushma Alphonsa, Madison R. Taylor, Nora Constantino

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2020
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsSaccadic maskingConcussionEye movementPsychologySaccadic eye movementMidbrainVisual fieldSmooth pursuitSaccadePhysical medicine and rehabilitationAudiologyMedicineOphthalmologyPoison controlInjury preventionNeuroscience

Abstract

fetched live from OpenAlex

Repetitive head impacts (RHI) are the result of a blow to the head that does not elicit clinical signs or symptoms of a concussion. Recent evidence suggests that RHI from a single season of collegiate football can lead to a reduction in midbrain white matter integrity. The midbrain carries projecting fibers to the trochlear and oculomotor nerves, which if damaged may impair oculomotor control. PURPOSE: The purpose of this study was to evaluate oculomotor function following multiple years of Division I contact sports during a dynamic visual acuity (DVA) task. METHODS: Two NCAA Division I football defensive backs with no diagnosed concussion history (a first-year freshmen [F1; age=18 years], senior [S1; age=21 years]) and a healthy control (CON; age=23 years), all with lower than 20/20 vision, completed a DVA task at pre-season. For the DVA task (optotype spatial range=1.0 to -0.3), participants were asked to complete 60 randomized trials of smooth pursuit (30°/s) and saccades (150°/s). Participants head were stabilized in a chin rest at a distance of 154cm away from the 26° visual field monitor (165Hz, 2560 x 1440 pixel resolution, 300 cd/m2 luminance) while wearing a head-mounted binocular video oculography eye tracker (Eyelink SR research, 500 Hz, Ottawa, CN). Using a 2-up-1-down staircase method, participants tracked a Landolt-C ring that moved across the screen (horizontally left to right) where the size of the gap in the C along with the orientation (left, right, up or down) adjusted based on the correct/incorrect responses during both smooth pursuit and saccadic trials. Smooth pursuit eye movement (SPEM) velocity gain and saccadic peak velocity were calculated using ternary eye movement classification from the transformed spherical coordinates via a custom MATLAB code (MATLAB 2019a, Natick, MA, USA). No statistical analysis were performed given the single-subject design. RESULTS: SPEMs gain is lower for S1 (0.88) when compared to F1 (0.82) and CON (0.92). Similarly, during the saccadic trials, S1 had slower average saccadic peak velocity (S1=279.75°/s; F1 =392.34°/s; CON=491.96°/s). CONCLUSIONS: These results may indicate that engaging in contact collision sport for 2+ years at the Division 1 level may result in less accurate (lower SPEMs gain) and slower saccadic eye movements. Supported by NIH P20GM103650

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.056
GPT teacher head0.350
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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