C_manual_check
In this script each subject's data gets loaded, externals get deleted and the data gets plotted in the EEGlab GUI. Make sure you always set the scale to the same number, since EEGLAB bases it on the noise level of the data. In the GUI set the scale to 5, so you can see if there are flat channels. to clarify, this is not an optional script, the pipeline does not work without it. This is on purpose since looking at the data is a very (or maybe the most) important step in pre-processing the data.
(example)
After that Change the scale to 50 (this value will be automatically set
and different for each data set). It is important to always set it to
the same scale, so that you can compare noise between data sets.
When looking at 160 channel data, be sure to check in settings how many channels you want to see. Because it is clear that there are bad channels, but their label is hard to spot.
After figuring out which channels to delete, type their labels in the command window of Matlab. They need to be entered in the following structure:
{'FC1' 'P1' 'po3'}Be critical, but if you delete too many channels (>10) you should consider whether that data set should be included.
This function uses the locations of the deleted channels and creates a scalp map with these locations so one can see if too many channels close to each other are deleted.
This function plot on a group level how often a channel is deleted. This means that if a channel is deleted, on the location of that channel in the headmap you will see a number. That number indicates how often that channel is deleted. This is saved as one figure.
This is a variable that will store the ID, % deleted data, seconds of
data left and N - deleted channels of each participants. When all the
individual subjects are run, we load participant_info and include this
variable and save it again.
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