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in brief, it means defining a dictionary for each filter field. This dictionary then
contains a filter-name, which again links to a dictionary ... this dictionary then
contains the key value pairs of the filter parameters.
I agree that it sounds a bit complicated and nested at first glance, but it allows for a
very exhaustive documentation of the filters. For example two different kinds of
hardware filters with different sets of parameters
feedback is welcome, since this is not very fixed in EEG.
The text was updated successfully, but these errors were encountered:
I think the ieeg examples have quite a good coverage by now. Should we merge the branch into master, like we will do with the EEG branch? @choldgraf@dorahermes
The following is a list of example datasets that would be particularly useful to highlight the iEEG specification for BIDS:
multiple runs of clinical observation data
Clinical recordings during no task
Seizure recordings
We could maybe add the dataset we use for the Brainstorm SEEG tutorial?
https://neuroimage.usc.edu/brainstorm/Tutorials/Epileptogenicity
An example showing how to properly format hardware/software filters:
I am linking to an EEG example on how the filter fields could be formatted:
https://github.com/bids-standard/bids-starter-kit/wiki/FAQ#how-to-format-hardware-and-software-filter-fields-in-a-json
in brief, it means defining a dictionary for each filter field. This dictionary then
contains a filter-name, which again links to a dictionary ... this dictionary then
contains the key value pairs of the filter parameters.
I agree that it sounds a bit complicated and nested at first glance, but it allows for a
very exhaustive documentation of the filters. For example two different kinds of
hardware filters with different sets of parameters
feedback is welcome, since this is not very fixed in EEG.
The text was updated successfully, but these errors were encountered: