Second-order kernels were extracted using VERIS 4.8 (EDI, Inc.). Spatial smoothing and artifact rejection features available in VERIS were not used. All subsequent analysis was performed with IGOR 5.0 (WaveMetrics, Inc., Lake Oswego, OR). The traces were digitally low-pass filtered with a high-frequency cutoff of 30 Hz.
To assess signal presence we evaluated the signal-to-noise ratio (SNR), as described by Zhang et al.
28 using a “mean noise-window SNR.” First, the records from the two blocks for each stimulus were averaged. Then the SNR for each
ith sector (of the
n = 60 total sectors) of subject
j was defined as
\[\mathrm{SNR}ij{=}\mathrm{RMS}_{ij}(45{\mbox{--}}150\ \mathrm{ms})/{[}{\Sigma}_{i}\ \mathrm{RMS}_{ij}(325{\mbox{--}}430\ \mathrm{ms})/n{]}{-}1.\]
The denominator in
(equation 1)is the average of the individual root mean squares (RMSs) of
n = 60 sectors in the noise window (325–430 ms after stimulus onset). An estimate of false-positive rates was obtained from the distribution of SNRs in the noise window for each
ith sector,
jth subject,
mth electrode pair, and
qth condition, according to Hood et al.
24 :
\[\mathrm{SNR}_{ijmq}{=}\mathrm{RMS}_{ijmq}(325{\mbox{--}}430\ \mathrm{ms})/{[}{\Sigma}_{i}\ \mathrm{RMS}_{ijmq}(325{\mbox{--}}430\ \mathrm{ms})/n{]}{-}1.\]
Thus, we calculated
i ×
j ×
m ×
q SNRs (i.e., 10,080 ratios;
i = 60 locations;
j = 28 subjects;
m = 3 electrode pairs;
q = 2 conditions [left- and right-eye stimulation]). An analysis of the distribution of these SNRs showed that SNRs ≥ 0.75 are part of the noise distribution, with a probability of <3%. We therefore applied an SNR threshold of 0.75 to exclude “silent” visual field locations (i.e., without recordable signals) from our analyses. Thus, we included visual field locations with super-threshold responses (i.e., with recordable signals, which we will refer to as “responsive” locations). In our quantitative analyses we compared two stimulus conditions (i.e., left- and right-eye stimulation). Each stimulus location had to evoke superthreshold responses in at least one of the two conditions to enter the analysis (logical OR-operator). Thus, a bias of the results to one of these two conditions due to the thresholding procedure was avoided—for example, an AND operator would lead to an
exclusion of stimulus locations that are suppressed below the SNR threshold in only one of the two stimulus conditions and would, as a consequence, cause an underestimation of possible interocular differences of the responses.
To assess the lateralization of the responses, we calculated the difference potentials for each of the three electrodes on one hemisphere and its corresponding electrode on the other hemisphere. We then selected for each visual field location the electrode pair with the greatest SNR during stimulation of either eye for further analysis.
24 This procedure ensured that the same electrode pair was selected for left- and right-eye stimulation. Next, the difference VEPs obtained for each eye were correlated with each other to obtain Pearson’s correlation coefficient (
r ranging between −1 and 1). For this correlation the “signal time window” (45–150 ms) was used. The correlation allows for the distinction of normal and abnormal projections of the optic nerves. Positively correlated traces indicate that both eyes project to the same cortical regions, whereas negatively correlated traces indicate that both eyes project to opposite hemispheres.
10 16 It should be noted that the correlation approach is a more objective approach than a single peak analysis and therefore allows one to deal with small signal amplitudes.