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Exploring the methods of data analysis in multifocal visual evoked potentials

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PURPOSE: The multifocal visual evoked potential (mfVEP) provides a topographical assessment of visual function, which has already shown potential for use in patients with glaucoma and multiple sclerosis. However, the variability in mfVEP measurements has limited its broader application. The purpose of this study was to compare several methods of data analysis to decrease mfVEP variability.

METHODS: Twenty-three normal subjects underwent mfVEP testing. Monocular and interocular asymmetry data were analyzed. Coefficients of variability in amplitude were examined using peak-to-peak, root mean square (RMS), signal-to-noise ratio (SNR) and logSNR techniques. Coefficients of variability in latency were examined using second peak and cross-correlation methods.

RESULTS: LogSNR and peak-to-peak methods had significantly lower intra-subject variability when compared with RMS and SNR methods. LogSNR had the lowest inter-subject amplitude variability when compared with peak-to-peak, RMS and SNR. Average latency asymmetry values for the cross-correlation analysis were 1.7 ms (CI 95 % 1.2-2.3 ms) and for the second peak analysis 2.5 ms (CI 95 % 1.7-3.3 ms). A significant difference was found between cross-correlation and second peak analysis for both intra-subject variability (p < 0.001) and inter-subject variability (p < 0.001).

CONCLUSIONS: For a comparison of amplitude data between groups of patients, the logSNR or SNR methods are preferred because of the smaller inter-subject variability. LogSNR or peak-to-peak methods have lower intra-subject variability, so are recommended for comparing an individual mfVEP to previous published normative data. This study establishes that the choice of mfVEP data analysis method can be used to decrease variability of the mfVEP results.

Original languageEnglish
JournalDocumenta ophthalmologica. Advances in ophthalmology
Volume133
Issue number1
Pages (from-to)41-8
Number of pages8
ISSN0012-4486
DOIs
Publication statusPublished - Aug 2016

    Research areas

  • Journal Article

ID: 49838930