How can I anonymize or deidentify a CTF dataset?
Using the CTF command line tool “newDs” with the “-anon” option. To keep all other aspects of the dataset as it is, you should specify some options:
newDs -anon -includeBadChannels -includeBadSegments -includeBad <dataset> <savePath>".
Otherwise, bad channels, bad segments (in the continuous data) and bad trials (in segmented data) will be thrown away.
Make sure the savePath has an unambiguous name, so that you don't mix up your data.
Fields that are blanked out: purpose, site, institute, operator name, run title and description, collection description. The subject ID is set to Anon-1. The collection date and time are changed to 11/11/1911, 11:11.
It is advisable to also convert the headlocalizer datasets, which are inside the SubjectXX.ds and are named hz.ds, hz2.ds, etc.
An example use is (note that this should all be on a single line)
newDs -anon -includeBadChannels -includeBadSegments -includeBad /home/common/matlab/fieldtrip/data/Subject01.ds ~/anon/Subject01.ds newDs -anon -includeBadChannels -includeBadSegments -includeBad /home/common/matlab/fieldtrip/data/Subject01.ds/hz.ds ~/anon/Subject01.ds/hz.ds newDs -anon -includeBadChannels -includeBadSegments -includeBad /home/common/matlab/fieldtrip/data/Subject01.ds/hz2.ds ~/anon/Subject01.ds/hz2.ds
rm ~/anon/Subject01.ds/defaults.de rm ~/anon/Subject01.ds/hz.ds/defaults.de rm ~/anon/Subject01.ds/hz2.ds/defaults.de
See also this frequently asked question on how to anonimize an anatomical MRI.