Nonlinear Characteristics of Visual Evoked Potential and Their Correlation with the Visual Responses on Magnocellular and Parvocellular Pathways

K. Momose*, S. Kasahara

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

Abstract

Purpose was to investigate the nonlinear characteristics of visual evoked potentials (VEPs), and their correlation with the visual responses on parvocellular and magnocellular pathways. The VEPs elicited by checkerboard pattern alternating based on pseudorandom binary sequence were measured, and their nonlinear parameters (binary kernels) were calculated. VEPs to checkerboard with 0.5, 1.0, 2.0 and 4.0 [c/d] were measured. First and second-order binary kernels were compared with steadystate VEPs (S-VEPs) to pattern reversal stimulation with a constant temporal frequency (4, 8, 12, 16, and 32 Hz). Positive peak latency at 150 ms of second-order first slice was correlated with S-VEP amplitude for 32 Hz (r = - 0.71). Amplitudes of second slice were well correlated with S-VEPs to 4, 8, 12, and 16 Hz stimuli (r = 0.62, 0.77, 0.61, and 0.72). These results support the previously reported observations that the first and second slice response functions reflect the response of the parvocellular and magnocellular pathways, respectively.

Original languageEnglish
Pages (from-to)2331-2334
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume3
Publication statusPublished - 2003
Externally publishedYes
EventA New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico
Duration: 2003 Sept 172003 Sept 21

Keywords

  • Binary kernel
  • Magnocellular
  • Parvocellular
  • Pseudorandom binary sequence
  • Spatial frequency
  • Temporal frequency
  • VEP

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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