Pattern visual evoked potentials for identifying malingering

Sun, I-Ting; Lee, Jong‐Jer; Huang, Huei-Jean; Kuo, Hsi-Kung

doi:10.1007/s10633-015-9483-0

Cited by 7 publications

(6 citation statements)

References 29 publications

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“…This value of the VEP spatial frequency limit is likely to have the closest association with a clinical measurement of visual acuity since both are estimates of spatial threshold, although they have different physiological bases. 20,21 Our findings confirm this. The differences in maturation of the two measures can help forecast behavioural outcomes based on confirmation of some degree of visual pathway function in infancy using VEPs that mature early in comparison to behavioural acuity, which continues to develop later in preschool years.…”

Section: Discussionsupporting

confidence: 88%

“…The smallest check width to produce a PRVEP may be termed the VEP spatial frequency limit. This value of the VEP spatial frequency limit is likely to have the closest association with a clinical measurement of visual acuity since both are estimates of spatial threshold, although they have different physiological bases 20,21 . Our findings confirm this.…”

Section: Discussionsupporting

confidence: 79%

“…21 [adjusted R 2 =0.18]). When presence/absence of a 25 0 PRVEP response was added to a multivariate linear regression model, both factors were significantly associated with the logMAR-equivalent visual acuity at T2 (preferential looking presence/absence, p=0.02; 25 0 PRVEP response, p=0.01; R 2 =0.40 [adjusted R 2 =0.35]).…”

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confidence: 99%

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Prognostic value of transient pattern visual evoked potentials in children with cerebral visual impairment

Howes

Thompson

Liasis

et al. 2021

Develop Med Child Neuro

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To investigate whether pattern reversal visual evoked potentials (PRVEPs) could predict future visual acuity in infants with cerebral visual impairment (CVI).METHOD Fifty-five children (27 males, 28 females) with severe CVI seen in the ophthalmology department of a specialist children's hospital were identified retrospectively. Behavioural visual acuity and visual evoked potentials (VEPs) at presentation (time 1, T1) were compared with final visual acuity at late preschool/early school age (time 2, T2). Predictors of visual acuity at T2 were identified using univariate and multivariate logistic and linear regression analysis. RESULTSMedian age was 14 months at T1 (range: 6-44mo) and 63 months at T2 (range: 29-150mo). The presence of a PRVEP produced by a check width of 50 0 (minutes of arc) or smaller (T1) predicted (p=0.05) the presence of measurable preferential looking acuity at T2. The presence of PRVEP to check widths of 25 0 or smaller (T1) predicted (p=0.02) better preferential looking acuity (logMAR-equivalent) scores at T2. The latter association was independent of presenting acuity at T1. INTERPRETATIONThe presence of PRVEPs to check widths of 50 0 and 25 0 in infancy provided useful information. VEPs in young children with CVI may have prognostic value regarding future acuity.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 79%

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Prognostic value of transient pattern visual evoked potentials in children with cerebral visual impairment

Howes

Thompson

Liasis

et al. 2021

Develop Med Child Neuro

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“…It includes peak time and amplitude evaluation elements, with low variability across subjects and a strong relationship with VA. PRVEPs are mainly applied in patients who are unable or unwilling to complete a subjective VA examination and those with cognitive deficits. They are widely used in the assessment of optic neuropathy [ 1 – 3 ] and functional visual loss [ 4 ], in the identification of malingering [ 5 ], and in the early diagnosis and prognostication of multiple sclerosis [ 6 – 8 ]. Over the years, several reports have demonstrated that using the visual-evoked potential technique to detect the completeness of visual pathways has been widely recognized in ophthalmology [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

A feasibility study for objective evaluation of visual acuity based on pattern-reversal visual evoked potentials and other related visual parameters with machine learning algorithm

Chen

et al. 2023

BMC Ophthalmol

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Background To develop machine learning models for objectively evaluating visual acuity (VA) based on pattern-reversal visual evoked potentials (PRVEPs) and other related visual parameters. Methods Twenty-four volunteers were recruited and forty-eight eyes were divided into four groups of 1.0, 0.8, 0.6, and 0.4 (decimal vision). The relationship between VA, peak time, or amplitude of P100 recorded at 5.7°, 2.6°, 1°, 34′, 15′, and 7′ check sizes were analyzed using repeated-measures analysis of variance. Correlations between VA and P100, contrast sensitivity (CS), refractive error, wavefront aberrations, and visual field were analyzed by rank correlation. Based on meaningful P100 peak time, P100 amplitude, and other related visual parameters, four machine learning algorithms and an ensemble classification algorithm were used to construct objective assessment models for VA. Receiver operating characteristic (ROC) curves were used to compare the efficacy of different models by repeated sampling comparisons and ten-fold cross-validation. Results The main effects of P100 peak time and amplitude between different VA and check sizes were statistically significant (all P < 0.05). Except amplitude at 2.6° and 5.7°, VA was negatively correlated with peak time and positively correlated with amplitude. The peak time initially shortened with increasing check size and gradually lengthened after the minimum value was reached at 1°. At the 1° check size, there were statistically significant differences when comparing the peak times between the vision groups with each other (all P < 0.05), and the amplitudes of the vision reduction groups were significantly lower than that of the 1.0 vision group (all P < 0.01). The correlations between peak time, amplitude, and visual acuity were all highest at 1° (rs = − 0.740, 0.438). VA positively correlated with CS and spherical equivalent (all P < 0.001). There was a negative correlation between VA and coma aberrations (P < 0.05). For different binarization classifications of VA, the classifier models with the best assessment efficacy all had the mean area under the ROC curves (AUC) above 0.95 for 500 replicate samples and above 0.84 for ten-fold cross-validation. Conclusions Machine learning models established by meaning visual parameters related to visual acuity can assist in the objective evaluation of VA.

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“…As far as we know, using AO to bypass the optical limits in VEP measurement is a new technique. It has been found that using the VEP measurements in visual performance tests appears to improve diagnostic power [9,10] . It prompts us to consider the new technique of integrating VEP measurements into an AO system.…”

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confidence: 99%

Objective visual performance evaluation with visual evoked potential measurements based on an adaptive optics system

Yang

Zhao

et al. 2018

Chin. Opt. Lett.

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An objective visual performance evaluation with visual evoked potential (VEP) measurements was first integrated into an adaptive optics (AO) system. The optical and neural limits to vision can be bypassed through this system. Visual performance can be measured electrophysiologically with VEP, which reflects the objective function from the retina to the primary visual cortex. The VEP measurements without and with AO correction were preliminarily carried out using this system, demonstrating the great potential of this system in the objective visual performance evaluation. The new system will provide the necessary technique and equipment support for the further study of human visual function.

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Pattern visual evoked potentials for identifying malingering

Abstract: The pattern VEP amplitude of 50' checkerboard size was useful to assess VA and can be helpful in discriminating malingering from real disability.

Cited by 7 publications

References 29 publications

Prognostic value of transient pattern visual evoked potentials in children with cerebral visual impairment

Prognostic value of transient pattern visual evoked potentials in children with cerebral visual impairment

A feasibility study for objective evaluation of visual acuity based on pattern-reversal visual evoked potentials and other related visual parameters with machine learning algorithm

Objective visual performance evaluation with visual evoked potential measurements based on an adaptive optics system

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