Documenta Ophthalmologica

, Volume 133, Issue 1, pp 41–48 | Cite as

Exploring the methods of data analysis in multifocal visual evoked potentials

  • L. Malmqvist
  • L. De Santiago
  • C. Fraser
  • A. Klistorner
  • S. Hamann
Original Research Article



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.


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.


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).


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.


Multifocal visual evoked potentials Inter-subject variability Intra-subject variability Coefficient of variability Data analysis 



This research was partially supported by Værn om Synet, Synoptik-Fonden, Kleinsmed Svend Helge Arvid Schröder og Hustrus Fond and by the Spanish government Grant: TEC2011-26066.

Compliance with ethical standards

Conflict of interest

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership or other equity interest; and expert testimony or patent-licensing arrangements) or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.


This research was partially supported by Værn om Synet, Synoptik-Fonden, Kleinsmed Svend Helge Arvid Schröder og Hustrus Fond and by the Spanish government Grant: TEC2011-26066 in the form of Ph.D. salary. The sponsors had no role in the design or conduct of this research.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Statement of human rights

The study was performed in accordance with Universal Declaration of Human Rights.

Statement on the welfare of animals

This article does not contain any studies with animals.


  1. 1.
    Blanco R, Perez-Rico C, Puertas-Munoz I, Ayuso-Peralta L, Boquete L, Arevalo-Serrano J (2014) Functional assessment of the visual pathway with multifocal visual evoked potentials, and their relationship with disability in patients with multiple sclerosis. Mult Scler 20(2):183–191. doi: 10.1177/1352458513493683 CrossRefPubMedGoogle Scholar
  2. 2.
    Wolff BE, Bearse MA Jr, Schneck ME, Barez S, Adams AJ (2010) Multifocal VEP (mfVEP) reveals abnormal neuronal delays in diabetes. Doc Ophthalmol Adv Ophthalmol 121(3):189–196. doi: 10.1007/s10633-010-9245-y CrossRefGoogle Scholar
  3. 3.
    Fraser CL, Klistorner A, Graham SL, Garrick R, Billson FA, Grigg JR (2006) Multifocal visual evoked potential analysis of inflammatory or demyelinating optic neuritis. Ophthalmology 113(2):323e321–323e322. doi: 10.1016/j.ophtha.2005.10.017 CrossRefGoogle Scholar
  4. 4.
    Klistorner A, Arvind H, Nguyen T, Garrick R, Paine M, Graham S, O’Day J, Yiannikas C (2009) Multifocal VEP and OCT in optic neuritis: a topographical study of the structure-function relationship. Doc Ophthalmol Adv Ophthalmol 118(2):129–137. doi: 10.1007/s10633-008-9147-4 CrossRefGoogle Scholar
  5. 5.
    Hood DC, Zhang X, Greenstein VC, Kangovi S, Odel JG, Liebmann JM, Ritch R (2000) An interocular comparison of the multifocal VEP: a possible technique for detecting local damage to the optic nerve. Investig Ophthalmol Vis Sci 41(6):1580–1587Google Scholar
  6. 6.
    Semela L, Yang EB, Hedges TR, Vuong L, Odel JG, Hood DC (2007) Multifocal visual-evoked potential in unilateral compressive optic neuropathy. Br J Ophthalmol 91(4):445–448. doi: 10.1136/bjo.2006.097980 CrossRefPubMedGoogle Scholar
  7. 7.
    Rodarte C, Hood DC, Yang EB, Grippo T, Greenstein VC, Liebmann JM, Ritch R (2006) The effects of glaucoma on the latency of the multifocal visual evoked potential. Br J Ophthalmol 90(9):1132–1136. doi: 10.1136/bjo.2006.095158 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Moschos MM, Georgopoulos G, Chatziralli IP, Koutsandrea C (2012) Multifocal VEP and OCT findings in patients with primary open angle glaucoma: a cross-sectional study. BMC Ophthalmol 12:34. doi: 10.1186/1471-2415-12-34 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Grippo TM, Ezon I, Kanadani FN, Wangsupadilok B, Tello C, Liebmann JM, Ritch R, Hood DC (2009) The effects of optic disc drusen on the latency of the pattern-reversal checkerboard and multifocal visual evoked potentials. Investig Ophthalmol Vis Sci 50(9):4199–4204. doi: 10.1167/iovs.08-2887 CrossRefGoogle Scholar
  10. 10.
    Klistorner AI, Graham SL (2001) Electroencephalogram-based scaling of multifocal visual evoked potentials: effect on intersubject amplitude variability. Investig Ophthalmol Vis Sci 42(9):2145–2152Google Scholar
  11. 11.
    Zhang X, Hood DC, Chen CS, Hong JE (2002) A signal-to-noise analysis of multifocal VEP responses: an objective definition for poor records. Doc Ophthalmol Adv Ophthalmol 104(3):287–302CrossRefGoogle Scholar
  12. 12.
    Mazinani BA, Waberski TD, Weinberger AW, Walter P, Roessler GF (2011) Improving the quality of multifocal visual evoked potential results by calculating multiple virtual channels. Jpn J Ophthalmol 55(4):396–400. doi: 10.1007/s10384-011-0040-4 CrossRefPubMedGoogle Scholar
  13. 13.
    Hood DC, Zhang X, Hong JE, Chen CS (2002) Quantifying the benefits of additional channels of multifocal VEP recording. Doc Ophthalmol Adv Ophthalmol 104(3):303–320CrossRefGoogle Scholar
  14. 14.
    Sabeti F, James AC, Essex RW, Maddess T (2013) Dichoptic multifocal visual evoked potentials identify local retinal dysfunction in age-related macular degeneration. Doc Ophthalmol Adv Ophthalmol 126(2):125–136. doi: 10.1007/s10633-012-9366-6 CrossRefGoogle Scholar
  15. 15.
    Klistorner A, Fraser C, Garrick R, Graham S, Arvind H (2008) Correlation between full-field and multifocal VEPs in optic neuritis. Doc Ophthalmol Adv Ophthalmol 116(1):19–27. doi: 10.1007/s10633-007-9072-y CrossRefGoogle Scholar
  16. 16.
    Alshowaeir D, Yannikas C, Garrick R, Van Der Walt A, Graham SL, Fraser C, Klistorner A (2014) Multifocal VEP assessment of optic neuritis evolution. Clin Neurophysiol. doi: 10.1016/j.clinph.2014.11.010 PubMedGoogle Scholar
  17. 17.
    Bengtsson M, Andreasson S, Andersson G (2005) Multifocal visual evoked potentials—a method study of responses from small sectors of the visual field. Clin Neurophysiol 116(8):1975–1983. doi: 10.1016/j.clinph.2005.04.009 CrossRefPubMedGoogle Scholar
  18. 18.
    Hood DC, Greenstein VC, Odel JG, Zhang X, Ritch R, Liebmann JM, Hong JE, Chen CS, Thienprasiddhi P (2002) Visual field defects and multifocal visual evoked potentials: evidence of a linear relationship. Arch Ophthalmol 120(12):1672–1681CrossRefPubMedGoogle Scholar
  19. 19.
    Fortune B, Zhang X, Hood DC, Demirel S, Johnson CA (2004) Normative ranges and specificity of the multifocal VEP. Doc Ophthalmol Adv Ophthalmol 109(1):87–100CrossRefGoogle Scholar
  20. 20.
    Nakamura M, Ishikawa K, Nagai T, Negi A (2011) Receiver-operating characteristic analysis of multifocal VEPs to diagnose and quantify glaucomatous functional damage. Doc Ophthalmol Adv Ophthalmol 123(2):93–108. doi: 10.1007/s10633-011-9285-y CrossRefGoogle Scholar
  21. 21.
    Jayaraman M, Gandhi RA, Ravi P, Sen P (2014) Multifocal visual evoked potential in optic neuritis, ischemic optic neuropathy and compressive optic neuropathy. Indian J Ophthalmol 62(3):299–304. doi: 10.4103/0301-4738.118452 CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Hood DC, Greenstein VC (2003) Multifocal VEP and ganglion cell damage: applications and limitations for the study of glaucoma. Progr Retinal Eye Res 22(2):201–251CrossRefGoogle Scholar
  23. 23.
    Sutter EE (1992) A deterministic approach to nonlinear system analysis. In: RB Pinter, B Nabet (eds) Nonlinear vision: determination of neural receptive fields, function, and networks. CRC press, Boca Raton, pp 171–220Google Scholar
  24. 24.
    Hood DC, Ohri N, Yang EB, Rodarte C, Zhang X, Fortune B, Johnson CA (2004) Determining abnormal latencies of multifocal visual evoked potentials: a monocular analysis. Doc Ophthalmol Adv Ophthalmol 109(2):189–199CrossRefGoogle Scholar
  25. 25.
    Hood DC, Zhang X, Rodarte C, Yang EB, Ohri N, Fortune B, Johnson CA (2004) Determining abnormal interocular latencies of multifocal visual evoked potentials. Doc Ophthalmol Adv Ophthalmol 109(2):177–187CrossRefGoogle Scholar
  26. 26.
    de Santiago L, Klistorner A, Ortiz M, Fernandez-Rodriguez AJ, Rodriguez Ascariz JM, Barea R, Miguel-Jimenez JM, Boquete L (2015) Software for analysing multifocal visual evoked potential signal latency progression. Comput Biol Med 59:134–141. doi: 10.1016/j.compbiomed.2015.02.004 CrossRefPubMedGoogle Scholar
  27. 27.
    De Santiago L, Fernandez A, Blanco R, Perez-Rico C, Rodriguez-Ascariz JM, Barea R, Miguel-Jimenez JM, Amo C, Sanchez-Morla EM, Boquete L (2014) Improved measurement of intersession latency in mfVEPs. Doc Ophthalmol Adv Ophthalmol 129(1):65–69. doi: 10.1007/s10633-014-9438-x CrossRefGoogle Scholar
  28. 28.
    Thie J, Sriram P, Klistorner A, Graham SL (2012) Gaussian wavelet transform and classifier to reliably estimate latency of multifocal visual evoked potentials (mfVEP). Vis Res 52(1):79–87. doi: 10.1016/j.visres.2011.11.002 CrossRefPubMedGoogle Scholar
  29. 29.
    Pipper CB, Ritz C, Bisgaard H (2012) A versatile method for confirmatory evaluation of the effects of a covariate in multiple models. J R Stat Soc C-Appl 61:315–326. doi: 10.1111/j.1467-9876.2011.01005.x CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • L. Malmqvist
    • 1
  • L. De Santiago
    • 2
  • C. Fraser
    • 3
  • A. Klistorner
    • 3
  • S. Hamann
    • 1
  1. 1.Department of Ophthalmology, RigshospitaletUniversity of CopenhagenGlostrupDenmark
  2. 2.Department of ElectronicsUniversity of AlcaláAlcalá de HenaresSpain
  3. 3.Department of Ophthalmology, Sydney Eye HospitalUniversity of SydneySydneyAustralia

Personalised recommendations