Comparison of photopic negative response measurements in the time and time–frequency domains

Abstract

Purpose To compare measurements of the full-field photopic negative response (PhNR), as well as intra-subject variation in the PhNR, using time and time-frequency domain analyses. Methods Full-field ERGs were recorded from 20 normally-sighted subjects (ages 24 to 65 years) elicited by a long-wavelength pulse (3 cd s m−2) presented against a short wavelength adapting field (12.5 cd m−2). Three to 10 waveforms were obtained from each subject and each waveform was analyzed using standard time domain analyses of the PhNR, as well as a discrete wavelet transform (DWT) to extract time-frequency components that correspond to the PhNR. Three different measures of the PhNR were derived and compared: 1) amplitude at the PhNR trough; 2) amplitude at 72 ms following stimulus onset; 3) energy in the 11 Hz, 60 to 120 ms DWT frequency bin that corresponds to the PhNR. In addition, the effect of normalizing the PhNR by the b-wave was evaluated for each of the measures. Coefficients of variation (CVs) were computed for each definition to evaluate intra-subject variation. Results PhNR amplitudes measured at the trough and at 72 ms were significantly correlated (r = 0.88, p < 0.001). Additionally, PhNR energy derived by DWT was significantly correlated with the amplitude measured at the trough (r = 0.64, p = 0.002) and at 72 ms (r = 0.60, p = 0.005). Mean (± SD) intra-subject CVs were 26% (15%), 49% (26%), and 30% (15%), for measures at the trough, 72 ms, and DWT, respectively. Normalization by the b-wave amplitude (i.e. PhNR/b) had minimal effect on the intra-subject CVs, whereas normalization by the sum of the b-wave and PhNR amplitudes (i.e. PhNR/[b+PhNR]) substantially reduced the CVs for all three measures (mean CVs were less than 17% for all conditions). Conclusions Although each PhNR definition has advantages and disadvantages, all three metrics provide similar estimates of the PhNR. Intra-subject CVs, however, were relatively high for measurements made at 72 ms, indicating that definitions based on a fixed time-point may introduce variability. The substantial decrease in intra-subject variation after normalization by the sum of the PhNR and b-wave amplitudes may be advantageous under some conditions.

Wavelet decomposition analysis in the two-flash multifocal ERG in early glaucoma: a comparison to ganglion cell analysis and visual field

“…In electrophysiology of vision, this method has been introduced a decade ago [ 20 , 21 ]. It has been used to analyze the photopic negative response in the full-field ERG of healthy subjects [ 22 ]. Barraco et al [ 23 ] compared different analytical approaches (including application of the continuous wavelet transform, CWT) to analyze the a -wave of the full-field ERG, demonstrating consistently altered photoreceptor behavior in various diseases.…”

Assessing the Contribution of the Oscillatory Potentials to the Genesis of the Photopic ERG with the Discrete Wavelet Transform

“…The DWT generates scalograms (Figure 1(a)) which display the energy ( z -axis) of the signal (maximal values are shown in red; lowest values in blue) as a function of time ( x -axis) and frequency ( y -axis). As previously demonstrated by us and others [10, 13, 15–18], this time-frequency approach allows for the identification of energy descriptors, each defined with their respective time and frequency coordinates. The DWT yields measurements of the photopic b-wave (found in the 20 and 40 Hz bands) and OPs (found in the 80 and 160 Hz bands) through the quantification of their respective associated wavelet coefficients [10, 16, 17].…”

“…Unfortunately, given that the FFT quantifies the power level of all the frequency components contained within a signal (such as the ERG), whether they are time-locked to the stimulus or not (i.e., no temporal resolution), its use can lead to erroneous interpretations [10, 13–15]. Fortunately, the latter limitation can be easily overcome with the use of the discrete wavelet transform (DWT), which is somewhat of an improved FFT since it includes both temporal and frequency resolutions [10, 13–18]. …”

Baseline Detrending for the Photopic Negative Response

“…Baseline trend correction requires a compromise between trend removal, which improves signal repeatability, and waveform distortion which reduces discriminatory ability. Using discrete wavelet analysis, Kundra et al 22 showed that the PhNR was characterized by components located near the 11 Hz band (approximate range, 8–16 Hz), with minor contribution from lower frequencies (approximate range, 2–8 Hz). Thus, setting a high pass above 2 Hz attenuated the PhNR by removing these lower frequencies ( Fig.…”

“…The PhNR was shown to contain low temporal frequencies near approximately 11 Hz with smaller contributions from frequencies in the 2 to 8 Hz range. 22 Therefore, a comparison of increasing the high-pass cutoff from 1 to 10 Hz (in 1 Hz increments) was evaluated. The ISCEV low-pass cutoff of 300 Hz was retained.…”