EEG: Contours in multiple topoplots
It is commonly accepted that axes of plots should align if data needs to be compared between subplots. But the default way on how multiple topoplots are plotted violates this principle. While usually the limits of the colormap are kept constant for all colormaps, the contours rarely are. This default plot looks similar to this one:
It is simple, keep the contours constant!
In eeglab this is done using the topoplot function with the argument
'numcontours', linspace(-scale,scale,n_contours) or similar. You can also use my new plotting script available here on github
So if we would keep the values constant at which contours are generated it looks like this:
Each topoplot has its individual color-limits. While the local (in a single topoplot) extremata a clearly visible, not much to compare between topoplots
Individual contours improve the readability of each map, but they do not add anything that eases the comparison.
Forcing the same color-limits in the colormap allows for direct comparison between topoplots. But whether the white of the 9th’s or the 12th’s topoplot is bigger is hard to tell.
Going back to individual colormaps, but keeping the same contours: This helps already a lot, I seem to abstract the colormap away a bit and use the contours for comparison
The opposite way, same color-limits but individual contours. Again I seem to rely more on the contours, in this case this is more confusing than before.
In the final plot colormap and contour are aligned. This enhances comparison between topoplots.
One problem with the same color-limits or the same contour lines between topoplots is, that large deflections could hide small ones. As in many cases, it depends on what features of the data you want to highlight. I recommend the final plot where contour and colormap align as the default.
If you are plotting multiple topoplots, try to keep the color-limits of the colormap as well as the contour levels constant