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Drop outs

Nodes containing no information need to be removed prior to running any type of graph analyses. Luckily, the parcellate.sh script will also output a set of error files for nodes that have no signal. These error files can be easily incorporated in your graph pipeline, and even easier with this wrapper rb_checkErrors.m. This will given you a mask file that you can use to filter out erroneous nodes across all your subjects or plot using BrainNet. It also give you a figure with missing nodes by subjects and overall percentage of missing nodes.

NB: At the moment it doesn't include a check for outliers on nodes that do contain information (e.g. check whether the signal variability in one node is ±3 stdevs from the mean for example).

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