The 103 K1 and K2 mfERG waveforms were each averaged within 35 retinal zones
(Fig. 1B)to improve the signal-to-noise ratio (SNR). P1 peak implicit time (K1-IT) and N1-P1 amplitude (K1-AMP) of each of the 35 resultant first-order components were measured using a template-scaling method
27 in which the template for each zone was the mean component waveform (0–60 ms postflash) of the 30 control subjects at that location
(Fig. 1C K1) . In this method, the K1 template at each location was multiplicatively scaled in amplitude and time to minimize the least-squares difference between it and the response measured. K1-AMP was the voltage difference between the scaled N1 trough and P1 peak
(Fig. 1C K1-AMP) , and the K1-IT was the time from the local flash to the scaled P1 peak
(Fig. 1C K1-IT) . A major advantage of this method is that it was less affected by noise than by direct peak-to-peak amplitude and peak implicit time measurements. In addition, it provided an index of how well the scaled template characterized the measured waveform. A complete description of this method is presented in Hood and Li.
27
The SNR of each K2 (K2-SNR) was calculated by dividing the root mean square (RMS) amplitude of the signal epoch (8.3 − 70.5 ms postflash) by the mean of the RMS amplitude of the 35 noise epochs (120.8 − 183.3 ms postflash) for that subject
(Fig. 1C K2) . The mean of the 35 noise RMS amplitudes was used because noise varies among different epochs, and, therefore, the mean is the best estimate of the “true” noise within a response kernel. The SNR was then converted to decibels (dB = 10 × log
10 [SNR]).
K1-IT, K1-AMP, and K2-SNR normally vary with retinal location. To compensate for this when combining or comparing measurements across locations, median values for each of the 35 zones were calculated for the 30 control subjects, and deviations from these normative median values were calculated for each location or subject. The criterion for response abnormality for each zone was defined as K1-IT values beyond the 95th percentile of the control group and K1-AMP and K2-SNR values below the 5th percentile.
To visualize potential associations between K2-SNR deviations and K1-IT deviations, scatterplots were constructed. To establish whether an association between K2-SNR and K1-IT was statistically significant, a 2 × 2 cell χ2 test was performed. This test does not assume a specific type of association (e.g., linear) but instead tests for a significant trend. When setting up a 2 × 2 table, it is important that all cells have an adequate number of observations. Therefore, before χ2 analyses were performed, the data within each subject group were transformed (shifted) by subtracting the group’s median K1-IT and K2-SNR deviations so that there were adequate frequencies in each cell, allowing for a valid χ2. Values equal to one median, (x,0) or (0,y), were equally assigned to the neighboring cells. (For example, if four values were equal to the K1-IT median, two were assigned to the cell below the median, and two were assigned to the cell above the median.) Values equal to both median deviations (0,0) were excluded from the χ2 analysis because they could not be unambiguously assigned to a cell. This transformation does not significantly affect a potential association between the variables. Instead, it simply shifts the cell borders so that approximately equal numbers of observations occur in the column and row totals.