Steady-state PERG adaptation: a conspicuous component of response variability with clinical significance

P. Monsalve, S. Ren, G. Triolo, Luis E Vazquez, A. D. Henderson, M. Kostic, P. Gordon, William J Feuer, Vittorio Porciatti

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Purpose: To investigate within-test variability of the steady-state PERG (SS-PERG). Methods: SS-PERGs were recorded in response to black–white horizontal gratings (1.6 cycles/deg, 98% contrast, 15.63 reversals/s, LED display, 25 deg square field, 800 cd/sqm mean luminance) using skin electrodes. PERG and noise (± reference) signals were averaged over 1024 epochs (~ 2.2 min) and Fourier analyzed to retrieve SS-PERG amplitude and phase. SS-PERGs were split into 16 partial averages (samples) of 64 epochs each, and corresponding amplitudes and phases combined in polar coordinates to assess their dispersion (within-test variability). To assess time-dependent variability, samples were clustered in four successive time segments of ~ 33 s each. Amplitude adaptation was defined as amplitude difference between initial and final clusters, and PERG phase adaptation as the corresponding phase difference. To determine the dynamic range of SS-PERG adaptation, recording was performed in normal controls of different age (n = 32) and patients with different severity of optic nerve dysfunction (early manifest glaucoma, EMG, n = 7; non-arteritic ischemic optic neuropathy, NAION, n = 5). Results: Amplitude adaptation was largest in younger controls (amplitude adaptation ÷ noise, SNR = 9.5, 95% CI 13.1, 5.9) and progressively decreased with increasing age (older subjects, SNR = 5.5, 95% CI 9.2, 1.8) and presence of disease (EMG: SNR = 2.4, 95% CI 3.5, 1.4; NAION: SNR = 1.9, 95% CI 6.5,-2.2). In 11 young subjects, amplitude adaptation was repeatable (test–retest in two sessions a week apart; intraclass correlation coefficient = 0.59). Phase adaptation was not significantly different from zero in all groups. Conclusions: SS-PERG adaptation accounts for a sizeable portion of the within-test variability. As it has robust SNR, sufficient test–retest variability, and is altered in disease, it may have physiological and clinical significance. This study suggests that SS-PERG protocols should include adaptation in addition to SS-PERG amplitude and phase/latency.

Original languageEnglish (US)
Pages (from-to)1-8
Number of pages8
JournalDocumenta Ophthalmologica
DOIs
StateAccepted/In press - May 19 2018

Fingerprint

Noise
Ischemic Optic Neuropathy
Optic Nerve
Glaucoma
Electrodes
Skin

Keywords

  • Glaucoma
  • Neural adaptation
  • Non-arteritic ischemic optic neuropathy
  • Pattern electroretinogram
  • Variability

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Physiology (medical)

Cite this

Steady-state PERG adaptation : a conspicuous component of response variability with clinical significance. / Monsalve, P.; Ren, S.; Triolo, G.; Vazquez, Luis E; Henderson, A. D.; Kostic, M.; Gordon, P.; Feuer, William J; Porciatti, Vittorio.

In: Documenta Ophthalmologica, 19.05.2018, p. 1-8.

Research output: Contribution to journalArticle

Monsalve, P. ; Ren, S. ; Triolo, G. ; Vazquez, Luis E ; Henderson, A. D. ; Kostic, M. ; Gordon, P. ; Feuer, William J ; Porciatti, Vittorio. / Steady-state PERG adaptation : a conspicuous component of response variability with clinical significance. In: Documenta Ophthalmologica. 2018 ; pp. 1-8.
@article{59f2ffe69ff1436fa3f5ca7574ca4f97,
title = "Steady-state PERG adaptation: a conspicuous component of response variability with clinical significance",
abstract = "Purpose: To investigate within-test variability of the steady-state PERG (SS-PERG). Methods: SS-PERGs were recorded in response to black–white horizontal gratings (1.6 cycles/deg, 98{\%} contrast, 15.63 reversals/s, LED display, 25 deg square field, 800 cd/sqm mean luminance) using skin electrodes. PERG and noise (± reference) signals were averaged over 1024 epochs (~ 2.2 min) and Fourier analyzed to retrieve SS-PERG amplitude and phase. SS-PERGs were split into 16 partial averages (samples) of 64 epochs each, and corresponding amplitudes and phases combined in polar coordinates to assess their dispersion (within-test variability). To assess time-dependent variability, samples were clustered in four successive time segments of ~ 33 s each. Amplitude adaptation was defined as amplitude difference between initial and final clusters, and PERG phase adaptation as the corresponding phase difference. To determine the dynamic range of SS-PERG adaptation, recording was performed in normal controls of different age (n = 32) and patients with different severity of optic nerve dysfunction (early manifest glaucoma, EMG, n = 7; non-arteritic ischemic optic neuropathy, NAION, n = 5). Results: Amplitude adaptation was largest in younger controls (amplitude adaptation ÷ noise, SNR = 9.5, 95{\%} CI 13.1, 5.9) and progressively decreased with increasing age (older subjects, SNR = 5.5, 95{\%} CI 9.2, 1.8) and presence of disease (EMG: SNR = 2.4, 95{\%} CI 3.5, 1.4; NAION: SNR = 1.9, 95{\%} CI 6.5,-2.2). In 11 young subjects, amplitude adaptation was repeatable (test–retest in two sessions a week apart; intraclass correlation coefficient = 0.59). Phase adaptation was not significantly different from zero in all groups. Conclusions: SS-PERG adaptation accounts for a sizeable portion of the within-test variability. As it has robust SNR, sufficient test–retest variability, and is altered in disease, it may have physiological and clinical significance. This study suggests that SS-PERG protocols should include adaptation in addition to SS-PERG amplitude and phase/latency.",
keywords = "Glaucoma, Neural adaptation, Non-arteritic ischemic optic neuropathy, Pattern electroretinogram, Variability",
author = "P. Monsalve and S. Ren and G. Triolo and Vazquez, {Luis E} and Henderson, {A. D.} and M. Kostic and P. Gordon and Feuer, {William J} and Vittorio Porciatti",
year = "2018",
month = "5",
day = "19",
doi = "10.1007/s10633-018-9633-2",
language = "English (US)",
pages = "1--8",
journal = "Documenta Ophthalmologica",
issn = "0012-4486",
publisher = "Springer Netherlands",

}

TY - JOUR

T1 - Steady-state PERG adaptation

T2 - a conspicuous component of response variability with clinical significance

AU - Monsalve, P.

AU - Ren, S.

AU - Triolo, G.

AU - Vazquez, Luis E

AU - Henderson, A. D.

AU - Kostic, M.

AU - Gordon, P.

AU - Feuer, William J

AU - Porciatti, Vittorio

PY - 2018/5/19

Y1 - 2018/5/19

N2 - Purpose: To investigate within-test variability of the steady-state PERG (SS-PERG). Methods: SS-PERGs were recorded in response to black–white horizontal gratings (1.6 cycles/deg, 98% contrast, 15.63 reversals/s, LED display, 25 deg square field, 800 cd/sqm mean luminance) using skin electrodes. PERG and noise (± reference) signals were averaged over 1024 epochs (~ 2.2 min) and Fourier analyzed to retrieve SS-PERG amplitude and phase. SS-PERGs were split into 16 partial averages (samples) of 64 epochs each, and corresponding amplitudes and phases combined in polar coordinates to assess their dispersion (within-test variability). To assess time-dependent variability, samples were clustered in four successive time segments of ~ 33 s each. Amplitude adaptation was defined as amplitude difference between initial and final clusters, and PERG phase adaptation as the corresponding phase difference. To determine the dynamic range of SS-PERG adaptation, recording was performed in normal controls of different age (n = 32) and patients with different severity of optic nerve dysfunction (early manifest glaucoma, EMG, n = 7; non-arteritic ischemic optic neuropathy, NAION, n = 5). Results: Amplitude adaptation was largest in younger controls (amplitude adaptation ÷ noise, SNR = 9.5, 95% CI 13.1, 5.9) and progressively decreased with increasing age (older subjects, SNR = 5.5, 95% CI 9.2, 1.8) and presence of disease (EMG: SNR = 2.4, 95% CI 3.5, 1.4; NAION: SNR = 1.9, 95% CI 6.5,-2.2). In 11 young subjects, amplitude adaptation was repeatable (test–retest in two sessions a week apart; intraclass correlation coefficient = 0.59). Phase adaptation was not significantly different from zero in all groups. Conclusions: SS-PERG adaptation accounts for a sizeable portion of the within-test variability. As it has robust SNR, sufficient test–retest variability, and is altered in disease, it may have physiological and clinical significance. This study suggests that SS-PERG protocols should include adaptation in addition to SS-PERG amplitude and phase/latency.

AB - Purpose: To investigate within-test variability of the steady-state PERG (SS-PERG). Methods: SS-PERGs were recorded in response to black–white horizontal gratings (1.6 cycles/deg, 98% contrast, 15.63 reversals/s, LED display, 25 deg square field, 800 cd/sqm mean luminance) using skin electrodes. PERG and noise (± reference) signals were averaged over 1024 epochs (~ 2.2 min) and Fourier analyzed to retrieve SS-PERG amplitude and phase. SS-PERGs were split into 16 partial averages (samples) of 64 epochs each, and corresponding amplitudes and phases combined in polar coordinates to assess their dispersion (within-test variability). To assess time-dependent variability, samples were clustered in four successive time segments of ~ 33 s each. Amplitude adaptation was defined as amplitude difference between initial and final clusters, and PERG phase adaptation as the corresponding phase difference. To determine the dynamic range of SS-PERG adaptation, recording was performed in normal controls of different age (n = 32) and patients with different severity of optic nerve dysfunction (early manifest glaucoma, EMG, n = 7; non-arteritic ischemic optic neuropathy, NAION, n = 5). Results: Amplitude adaptation was largest in younger controls (amplitude adaptation ÷ noise, SNR = 9.5, 95% CI 13.1, 5.9) and progressively decreased with increasing age (older subjects, SNR = 5.5, 95% CI 9.2, 1.8) and presence of disease (EMG: SNR = 2.4, 95% CI 3.5, 1.4; NAION: SNR = 1.9, 95% CI 6.5,-2.2). In 11 young subjects, amplitude adaptation was repeatable (test–retest in two sessions a week apart; intraclass correlation coefficient = 0.59). Phase adaptation was not significantly different from zero in all groups. Conclusions: SS-PERG adaptation accounts for a sizeable portion of the within-test variability. As it has robust SNR, sufficient test–retest variability, and is altered in disease, it may have physiological and clinical significance. This study suggests that SS-PERG protocols should include adaptation in addition to SS-PERG amplitude and phase/latency.

KW - Glaucoma

KW - Neural adaptation

KW - Non-arteritic ischemic optic neuropathy

KW - Pattern electroretinogram

KW - Variability

UR - http://www.scopus.com/inward/record.url?scp=85047135058&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85047135058&partnerID=8YFLogxK

U2 - 10.1007/s10633-018-9633-2

DO - 10.1007/s10633-018-9633-2

M3 - Article

C2 - 29779071

AN - SCOPUS:85047135058

SP - 1

EP - 8

JO - Documenta Ophthalmologica

JF - Documenta Ophthalmologica

SN - 0012-4486

ER -