A Comparison of Electrophysiological and Behavioral Measures of Visual Acuity
Bibliographic record
Abstract
Unlike behavioral techniques, the measurement of visual evoked potentials (VEPs) provides an objective electrophysiological measure of vision directly from the visual cortex. The purpose of the present study is to provide the first comparison of visual acuity scores obtained using a new VEP system and those obtained using behavioral tests. Grating acuity was estimated in 27 participants (M = 21.2±1.5 years) using the VeriSci Neucodia VEP system following the sweep VEP (sVEP) procedure. During each 10 second sweep, participants were presented with 8 horizontal square wave gratings ranging from 5.3 to 35.6 cpd (0.75 to -0.07 logMAR). Each participant completed 8 sweeps. Grating acuity was also measured using the Teller Acuity Cards II (TAC) and optotype acuity was estimated using the Early Treatment Diabetic Retinopathy Study (ETDRS) visual acuity test. Scores from the three tests were compared. In addition, coefficients of repeatability (COR) were determined for all possible test pairs in order to determine level of agreement. Friedman analyses revealed a significant test effect (p< 0.0001). Specifically, ETDRS scores were significantly finer than scores obtained with sVEP (-0.04 v. 0.12 logMAR, p< 0.0001) and the TAC (-0.04 v. 0.11 logMAR, p< 0.0001). TAC and sVEP scores did not differ (TAC=0.11 logMAR; VEP=0.12 logMAR; p=0.52). COR analyses indicated that the level of agreement between all test pairs was poor and virtually identical (TAC and sVEP COR=0.30 logMAR; sVEP and ETDRS COR=0.30 logMAR; TAC and ETDRS COR=0.31 logMAR). The poor agreement between tests is not surprising given that they assess different visual abilities (i.e., TAC and sVEP: resolution acuity; ETDRS: recognition acuity). Furthermore, the tests likely tap different underlying neural mechanisms as VEPs are recorded directly from the visual cortex, whereas the TAC and the ETDRS require a behavioural response and therefore, likely tap mechanisms further upstream within the visual system and beyond. Meeting abstract presented at VSS 2017
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".