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Record W4400279263 · doi:10.1089/neur.2024.0018

Assessment of Oculomotor Functions as a Biomarker in Mild Traumatic Brain Injury

2024· article· en· W4400279263 on OpenAlexafffund
Ekaterina Lunkova, Jen‐Kai Chen, Rajeet Singh Saluja, Alain Ptito

Bibliographic record

VenueNeurotrauma Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University Health CentreMcGill University
FundersMitacsMcGill University
KeywordsTraumatic brain injuryBiomarkerMedicineNeurosciencePsychologyPhysical medicine and rehabilitationBiologyPsychiatry

Abstract

fetched live from OpenAlex

Mild traumatic brain injury (mTBI), or concussion, is a major public health problem, and ambiguity still exists regarding its diagnosis. While functional magnetic resonance imaging (fMRI) has been identified as a helpful screening tool for concussion, its limited accessibility in clinical or field settings necessitates a more efficient alternative. Oculomotor function deficit is an often-reported pathology in mTBI. Due to the neuroanatomical overlap between eye-movement circuitry and mTBI pathophysiology, visual deficits are expected. In this study, we investigate the possibility of using an oculomotor assessment tool for finding biomarkers in concussion. We used fMRI with tasks evaluating oculomotor functions: smooth pursuit (SP), saccades, anti-saccades, and optokinetic nystagmus (OKN). Before the scanning, the testing with a system of virtual reality goggles with integrated eye- and head-tracking was used where subjects performed the same tasks as those used in fMRI. Twenty-nine concussed symptomatic adults (CSA) within 1-month postconcussion and 29 age- and sex-matched healthy controls (HCS) were tested to examine blood oxygen level-dependent (BOLD) fMRI alterations associated with performances in oculomotor function after mTBI and evaluate the efficacy of the oculomotor assessment in detecting oculomotor and gaze deficits following mTBI. Comparing CSA with HCS, significant differences were observed in anti-saccades and OKN performance. CSA group exhibited elevated %BOLD signal change on each task compared with HCS: in the superior frontal gyrus during the smooth pursuit, inferior frontal gyrus during the saccades, putamen and dorsolateral prefrontal cortex (DLPFC) during the anti-saccades, and lingual gyrus and IFG during the OKN. Key findings include the following: (1) oculomotor deficits in concussed subjects compared with controls, (2) abnormal activation patterns in areas related to the regulation and control of oculomotor movements, suggesting concussion-induced disruptions, and (3) the potential of oculomotor assessment as a promising approach for mTBI biomarkers, with anti-saccades and OKN identified as the most sensitive tasks.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.365
Teacher spread0.305 · 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 teacher head, 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

Citations3
Published2024
Admission routes2
Has abstractyes

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