Figure 3: Display of the results of the analysis of the within-subject factors in the sample dataset. The left part of the display shows the significance of the TANOVA’s main effects (expectancy and day) and their interaction as line graphs showing the probability 𝑃 ( 𝑦 -axis) of the null hypothesis as a function of time ( 𝑥 -axis). Significant time points ( 𝑃 < . 0 5 ) are marked in white. By clicking in a graph, a cursor is set, the 𝑃 value of the respective time point is displayed besides the graph title, and the effect is mapped on the right side of the display. In the current figure, the main effect of expectancy (correct versus false sentence endings) at 400 ms is displayed. The upper right part of the display shows the mean topographic maps of all factor levels from the graph where the cursor has been set. In the present display of the main effect of expectancy, these are the mean maps across subjects and days of correct and false sentence endings at 400 ms. For the figure in the lower right part, these two mean maps have been fed into an MDS analysis. For this purpose, all mean maps were submitted to a spatial PCA. The 𝑥 -axis of the figure represents the projection of mean maps onto the first eigenvector. The spatial distribution of the eigenvector is represented by two topographic maps below the 𝑥 -axis. The graph indicates that the “false” condition is more negative and the correct condition is more positive at parietal electrodes.