Relationship between the binary kernels of visually evoked potentials and the visual responses on the magnocellular and parvocellular pathways

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4 Citations (Scopus)

Abstract

Objectives: To investigate the nonlinear characteristics of visual evoked potentials (VEPs), and their correlation with the visual responses on parvocellular and magnocellular pathways. First and second-order kernels of the VEPs elicited by several checkerboard patterns were estimated, and their relations to the visual pathway responses were investigated. Methods: VEPs elicited by checkerboard pattern (0.5, 1.0, 2.0 and 4.0 c/d) alternating based on pseudorandom binary sequence were measured, and their binary kernels were calculated. First and second-order binary kernels were compared with amplitudes of the steady-state VEPs (S-VEPs) to pattern reversal stimulation with a constant temporal frequency (4, 8, 12, 16, and 32 Hz). Results: Positive peak latencies at 150 ms (P150) of second-order first and second slices were correlated with S-VEP amplitude for higher temporal frequencies, indicating that the first and second slices reflect the response of the magnocellular. However, for second and third slices, their amplitudes were partially correlated with 4-16 Hz S-VEP, and this indicated that the second slice contains both magno- and parvocellular pathway responses. P150 latencies of third slices were correlated with S-VEP for lower temporal frequencies, indicating that third slice reflects the response of the parvocellular pathway. Conclusions: The lower slices of second-order binary kernels reflect the response of the magnocellular pathway and the higher slices reflect those on the parvocellular pathway in the human visual system of VEPs.

Original languageEnglish
Pages (from-to)169-173
Number of pages5
JournalMethods of Information in Medicine
Volume46
Issue number2
Publication statusPublished - 2007 Mar 28

Keywords

  • Binary kernel
  • Magnocellular
  • PRBS
  • Parvocellular
  • Visual pathway
  • Visually evoked potentials

ASJC Scopus subject areas

  • Health Informatics
  • Advanced and Specialised Nursing
  • Health Information Management

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