## 3 Results
### Seasonality Effects in the EEG during Learning of Emotional Pictures  
Figure 2 shows the wavelet plot of participants with low seasonality scores on electrode O1 for negative pictures, and an exemplary time-frequency intersection (10 Hz/100 ms), where the data were compared to the group with high seasonality scores. Table 1 lists the significant results of the semi-parametric ANOVA. \begin{table}
\begin{tabular}{l c c c} \hline  & \(F\) & \(df\) & \(p\) \\ \hline seasonality & 4.44 & 1, 513.27 & 0.043 \\ lobe & 9.66 & 1.97, Inf & \textless{}0.001 \\ seasonality \(\times\) lobe & 5.50 & 1.97, Inf & 0.003 \\ valence & 5.02 & 1.93, Inf & 0.011 \\ seasonality \(\times\) valence & 3.31 & 1.923, Inf & 0.037 \\ lobe \(\times\) valence & 6.85 & 3.34, Inf & \textless{}0.001 \\ frequency & 16.88 & 1, Inf & \textless{}0.001 \\ lobe \(\times\) frequency & 153.74 & 1.77, Inf & \textless{}0.001 \\ lobe \(\times\) valence \(\times\) frequency & 11.75 & 2.74, Inf & \textless{}0.001 \\ lobe \(\times\) valence \(\times\) hemisphere & 2.85 & 3.68, Inf & 0.027 \\ time-window & 11.94 & 1, Inf & \textless{}0.001 \\ lobe \(\times\) time-window & 5.51 & 1.36, Inf & 0.011 \\ seasonality \(\times\) valence \(\times\) frequency \(\times\) & 4.35 & 1.95, Inf & 0.018 \\ time-window & 3.62 & 1.96, Inf & 0.032 \\ \hline \end{tabular} 1  
\end{table} 
Table 1: Significant results of the semi-parametric ANOVA-type statistics for the grouping factors seasonality (low vs. high), lobe (frontal, temporal, occipital), hemisphere (left, right), valence (negative, neutral, positive), frequency (alpha, gamma), and time-window (50–150 ms, 300–400 ms) 1. Figure 1: Boxplots of number of remembered pictures (\(y\)-axis) per emotional valence category (\(x\)-axis), grouped by seasonality group (SAD low vs. high, colors red and blue). Boxes indicate the interquartile range; the center line indicates the median. Whiskers indicate the range from the minimum (0) to the largest value that does not exceed 1.5\(\times\) the interquartile range above the upper quartile. Values outside that range are considered outliers and represented as circles. Following the significant results from the semi-parametric ANOVA, post hoc tests were conducted for those effects that involved the grouping factor seasonality since these were the important interactions with respect to our hypotheses. The many post hoc tests called for a correction for multiple comparisons, which we conducted by interpreting the resulting p-values at the Bonferroni-Holm corrected level of significance. Overall, the main effect of seasonality indicated that EEG power was higher for participants with low as compared to high seasonality. This effect was particularly evident over the temporal lobe (F(1,24) = 114.11; \(p\) =0.001). The main effect for valence indicated that EEG power was lower for neutral pictures than for negative (V = 2,046,729; \(p<0.001\)) and positive pictures (V = 1,567,998; \(p<0.001\)), and higher for positive than negative pictures (V = 1,727,382; \(p\) =0.006). There was higher EEG power for participants with low as compared to high seasonality scores while learning negative (F(1,24) = 49.21; \(p\) = 0.014) and positive valence pictures (F(1,24) = 68.59; \(p=0.012\)), whereas no such difference was found for neutral valence pictures. Regarding the interaction between seasonality, valence, frequency range, and time-window, there was higher power for participants with low seasonality scores as compared to high seasonality scores in the alpha range while learning positive valence pictures in the early time-window of 50-150 ms (F(1,6) = 25.88 \(p\) = 0.003) and also for negative valence pictures in the late time-window of 300-400 ms (F(1,6) = 21.92; \(p\) = 0.003).