Hostname: page-component-7b7567c8c-7pwfn Total loading time: 0 Render date: 2026-11-13T21:26:14.848Z Has data issue: false hasContentIssue false
  • English
  • Français

Effect of temporal sparseness and dichoptic presentation on multifocal visual evoked potentials

Published online by Cambridge University Press:  05 April 2005

ANDREW C. JAMES,
RASA RUSECKAITE and
TED MADDESS
ANDREW C. JAMES
Affiliation:
Centre for Visual Sciences, Research School of Biological Sciences, Australian National University, Canberra, Australia
RASA RUSECKAITE
Affiliation:
Centre for Visual Sciences, Research School of Biological Sciences, Australian National University, Canberra, Australia
TED MADDESS
Affiliation:
Centre for Visual Sciences, Research School of Biological Sciences, Australian National University, Canberra, Australia
Get accessRights & Permissions [Opens in a new window]

Abstract

Multifocal VEP (mfVEP) responses were obtained from 13 normal human subjects for nine test conditions, covering three viewing conditions (dichoptic and left and right monocular), and three different temporal stimulation forms (rapid contrast reversal, rapid pattern pulse presentation, and slow pattern pulse presentation). The rapid contrast reversal stimulus had pseudorandomized reversals of checkerboards in each visual field region at a mean rate of 25 reversals/s, similar to most mfVEP studies to date. The rapid pattern pulse presentation had pseudorandomized presentations of a checkerboard for one frame, interspersed with uniform grey frames, with a mean rate of 25 presentations/s per region per eye. The slow pattern pulse stimulus had six presentations/s per region per eye. Recording time was 5.3 min/condition. For dichoptic presentation slow pattern pulse responses were 4.6 times larger in amplitude than the contrast reversal responses. Binocular suppression was greatest for the contrast reversal stimulus. Consideration of the signal-to-noise ratios indicated that to achieve a given level of reliability, slow pattern pulse stimuli would require half the recording time of contrast reversal stimuli for monocular viewing, and 0.4 times the recording time for dichoptically presented stimuli. About half the responses to the slow pattern pulse stimuli had peak value exceeding five times their estimated standard error. Responses were about 20% smaller in the upper visual field locations. Space–time decomposition showed that responses to slow pattern pulse were more consistent across visual field locations. We conclude that the pattern pulse stimuli, which we term temporally sparse, maintain the visual system in a high contrast gain state. This more than compensates for the smaller number of presentations in the run, and provides signal-to-noise advantages that may be valuable in clinical application.

Keywords

MultifocalVisual evoked potentialsmfVEPPattern pulseSparseDichopticBinocular suppressionSystem identification

Information

Type
Research Article
Information
Visual Neuroscience , Volume 22 , Issue 1 , January 2005, pp. 45 - 54
Copyright
© 2005 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

REFERENCES

Artes, P.H., Iwase, A., Ohno, Y., Kitazawa, Y., & Chauhan, B.C. (2002). Properties of perimetric threshold estimates from Full Threshold, SITA Standard, and SITA Fast strategies. Investigative Ophthalmology and Visual Science 43, 2654–2659.Google Scholar
Atkin, A., Wolkstein, M., Bodis-Wollner, I., Anders, M., Kels, B., & Podos, S.M. (1980). Interocular comparison of contrast sensitivities in glaucoma patients and suspects. British Journal of Ophthalmology 64, 858–862.CrossRefGoogle Scholar
Baseler, H.A., Sutter, E.E., Klein, S.A., & Carney, T. (1994). The topography of visual evoked response properties across the visual field. Electroencephalography and Clinical Neurophysiology 90, 65–81.CrossRefGoogle Scholar
Benardete, E.A. & Kaplan, E. (1999). The dynamics of primate retinal ganglion cells. Visual Neuroscience 16, 344–368.CrossRefGoogle Scholar
Benardete, E.A., Kaplan, E., & Knight, B.W. (1992). Contrast gain control in the primate retina: P cells are not X-like,some M cells are. Visual Neuroscience 8, 483–486.CrossRefGoogle Scholar
Draper, N.R. & Smith, H. (1998). Applied Regression Analysis. New York: Wiley.
Fortune, B. & Hood, D.C. (2003). Conventional pattern-reversal VEPs are not equivalent to summed multifocal VEPs. Investigative Ophthalmology & Visual Science 44, 1364–1375.CrossRefGoogle Scholar
Fortune, B., Johnson, C.A., & Cioffi, G.A. (2001). The topographic relationship between multifocal electroretinographic and behavioral perimetric measures of function in glaucoma. Optometry and Vision Science 78, 206–214.CrossRefGoogle Scholar
Fortune, B., Schneck, M.E., & Adams, A.J. (1999). Multifocal electroretinogram delays reveal local retinal dysfunction in early diabetic retinopathy. Investigative Ophthalmology & Visual Science 40, 2638–2651.Google Scholar
Goldberg, I., Graham, S.L., & Klistorner, A.I. (2002). Multifocal objective perimetry in the detection of glaucomatous field loss. American Journal of Ophthalmology 133, 29–39.CrossRefGoogle Scholar
Greenstein, V.C., Holopigian, K., Hood, D.C., Seiple, W., & Carr, R.E. (2000). The nature and extent of retinal dysfunction associated with diabetic macular edema. Investigative Ophthalmology & Visual Science 41, 3643–3654.Google Scholar
Hoffmann, M.B., Straube, S., & Bach, B. (2003). Pattern-onset stimulation boosts central multifocal VEP responses. Journal of Vision 3, 432–439.Google Scholar
Hood, D. & Zhang, X. (2000). Multifocal ERG and VEP responses and visual fields: Comparing disease—related changes. Documenta Ophthalmologica 100, 115–137.CrossRefGoogle Scholar
Hood, D.C., Odel, J.G., & Zhang, X. (2000a). Tracking the recovery of local optic nerve function after optic neuritis: A multifocal VEP study. Investigative Ophthalmology & Visual Science 41, 4032–4038.Google Scholar
Hood, D.C., Zhang, X., Greenstein, V.C., Kangovi, S., Odel, J.G., Liebmann, M.J., & Ritch, R. (2000b). An interocular comparison of the multifocal VEP: A possible technique for detecting local damage to the optic nerve. Investigative Ophthalmology & Visual Science 41, 1580–1587.Google Scholar
James, A.C. (2003). The pattern pulse multifocal visual evoked potential. Investigative Opthalmology & Visual Science 44, 879–890.CrossRefGoogle Scholar
James, A.C. & Maddess, T. (2000). Method and apparatus for assessing neural function by sparse stimuli; Australia Patent No. PQ 6465-00.
James, A.C., Maddess, T., Price, N., & Ye, N. (2000). Dichoptic multiregion VEP kernels from short binary and ternary sequences. In ARVO, Vol. 41, pp. S490. Ft. Lauderdale, Florida: Investigative Opthalmology & Visual Science.
Jeffreys, D.A. (1971). Cortical source locations of pattern-related visual evoked potentials recorded from the human scalp. Nature 229, 502–504.CrossRefGoogle Scholar
Jeffreys, D.A. & Axford, J.G. (1972). Source locations of pattern-specific components of human visual evoked potentials. I. Component of striate cortical origin. Experimental Brain Research 16, 1–21.Google Scholar
Klistorner, A.I. & Graham, S.L. (1999). Multifocal pattern VEP perimetry: Analysis of sectoral waveform. Documenta Ophthalmologica 98, 183–196.CrossRefGoogle Scholar
Klistorner, A.I., Graham, S.L., Grigg, J.R., & Billson, F.A. (1998a). Electrode position and the multi-focal visual-evoked potential: Role in objective visual field assesement. Australian and New Zealand Journal of Ophthalmology 26, 91–94.Google Scholar
Klistorner, A.I., Graham, S.L., Grigg, J.R., & Billson, F.A. (1998b). Multifocal topographic visual evoked potential: Improving objective detection of local visual field defects. Investigative Ophthalmology & Visual Science 39, 937–950.Google Scholar
Maddess, T. & James, A.C. (1998). Simultaneous binocular assessment of multiple optic nerve and cortical regions in diseases affecting nerve conduction. USA Patent No. 6,315,414.
Maddess, T., James, A.C., Goldberg, I., Wine, S., & Dobinson, J. (2000a). Comparing a parallel PERG, automated perimetry, and frequency-doubling thresholds. Investigative Ophthalmology & Visual Science 41, 3827–3832.Google Scholar
Maddess, T., James, A.C., Goldberg, I., Wine, S., & Dobinson, J. (2000b). A spatial frequency-doubling illusion-based pattern electroretinogram for glaucoma. Investigative Ophthalmology & Visual Science 41, 3818–3826.Google Scholar
Maddess, T. & Severt, W.L. (1999). Testing for glaucoma with the frequency-doubling illusion in the whole, macular and eccentric visual fields. Australian and New Zealand Journal of Ophthalmology 27, 194–196.CrossRefGoogle Scholar
Palmowski, A.M., Sutter, E.E., Bearse, M.A., Jr., & Fung, W. (1997). Mapping of retinal function in diabetic retinopathy using the multifocal electroretinogram. Investigative Ophthalmology & Visual Science 38, 2586–2596.Google Scholar
Palmowski, A.M., Sutter, E.E., Bearse, M.A., Jr., & Fung, W. (1999). Multifocal electroretinogram (MF-ERG) in diagnosis of macular changes. Example: Senile macular degeneration. Ophthalmologe 96, 166–173.Google Scholar
Press, W.H., Teukolsky, S.A., Vetterling, W.T., & Flannery, B.P. (1992). Numerical Recipes in C—The Art of Scientific Computing. Cambridge: Cambridge University Press.
Regan, M.P. & Regan, D. (1989). Objective investigation of visual function using a nondestructive zoom-FFT technique for evoked potential analysis. Canadian Journal of Neurological Sciences 16, 168–179.CrossRefGoogle Scholar
Sutter, E. (1992). A deterministic approach to nonlinear systems analysis. In Nonlinear Vision: Determination of Neural Receptive Fields, Function, and Networks, ed. Pinter, R. B. & Nabet, B., pp. 31–74. Ann Arbor, Michigan: CRC Press.
Sutter, E. & Tran, D. (1992). The field topography of ERG components in man—I. The photopic luminance response. Vision Research 32, 433–446.CrossRefGoogle Scholar
Victor, J.D. & Shapley, R.M. (1979a). The nonlinear pathway of Y ganglion cells in the cat retina. Journal of General Physiology 74, 671–689.Google Scholar
Victor, J.D. & Shapley, R.M. (1979b). Receptive field mechanism of cat X and Y retinal ganglion cells. Journal of General Physiology 74, 275–298.Google Scholar
Victor, J.D., Shapley, R.M., & Knight, B.W. (1977). Nonlinear analysis of cat retinal ganglion cells in the frequency domain. Proceedings of the National Academy of Sciences of the U.S.A. 74, 3068–3072.CrossRefGoogle Scholar
Walsh, T. (1990). The fields of vision. In Visual Fields, Examination and Interpretation, ed. Walsh, T., pp. 1–29. La Jolla, California: American Academy of Ophthalmology.