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Record W4390511726 · doi:10.1167/iovs.65.1.2

Measuring the Interocular Delay and its Link to Visual Acuity in Amblyopia

2024· article· en· W4390511726 on OpenAlexaff
Daniel Gurman, Alexandre Reynaud

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2024
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsVisual acuityAudiologyMedicineOphthalmology

Abstract

fetched live from OpenAlex

Purpose: Research on interocular synchronicity in amblyopia has demonstrated a deficit in synchronization (i.e., a neural processing delay) between the two eyes. Current methods for assessing interocular delay are either costly or ineffective for assessments in severe amblyopia. In this study, we adapted a novel protocol developed by Burge and Cormack based on continuous target tracking to measure the interocular delay on a wide range of amblyopes. Our main aims were to assess the accessibility of this protocol and to investigate the relationship between interocular delay and visual acuity. Methods: This protocol, which consists of tracking a target undergoing random lateral motion with the mouse cursor, is performed both binocularly and monocularly. The processing speed of a given eye is computed by comparing the changes in velocity of the target and mouse via cross-correlation. The difference in processing speed between the eyes defines the interocular delay. Results: Cross-correlations revealed that the amblyopic eye tends to be delayed in time compared with the fellow eye. Interocular delays fell in the range of 0.6 to 114.0 ms. The magnitude of the delay was positively correlated with differences in interocular visual acuity (R2 = 0.484; P = 0.0002). Conclusions: These results demonstrate the accessibility of this new protocol and further support the link between interocular synchronicity and amblyopia. Furthermore, we determine that the interocular delay in amblyopia is best explained by a deficit in the temporal integration of the amblyopic eye.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.120
GPT teacher head0.386
Teacher spread0.266 · 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 designBench or experimental
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

Citations15
Published2024
Admission routes1
Has abstractyes

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