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Neuronal-Oscillations / FLUX

The FLUX pipeline for analysis of MEG data using MNE Python
https://neuosc.com/flux/
BSD 3-Clause "New" or "Revised" License
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"Publications and preregistration" provides different suggestions in the two tutorials #12

Open oscfer88 opened 2 years ago

oscfer88 commented 2 years ago

An example from the ICA part:

MNE: Example text "The data were down sampled to 200Hz prior to Independent Component Analysis (ICA) and bandpass filtered at 1 – 40 Hz. Next the fastICA algorithm (Hyvärinen and Oja, 2000) was applied to the segmented data as implemented in MNE Python. Clear components containing cardiac artefacts and eyeblinks (identified in time course and topographies of the ICA components) were removed in each subject (3 – 5 over subjects) in the raw unfiltered data. "

FieldTrip: Pre-registration: ICA will be used to 'project out' artefacts. Prior to the ICA, downsampling will be performed to 200 Hz. The runica algorithm will be applied. Ocular, cardiac and muscle artefacts will be identified in the components based on time-course and topography. These components will be projected out in the non-downsampled data. Publications: beyond the details above report the mean number of ICA components (incl. standard deviation) rejected in each subject. EXAMPLE: "The data were downsampled to 200Hz prior to Independet Component Analysis (ICA). Next the 'runica' ICA algorithm (see Bell & Sejnowski, 1995, Amari, Cichocki & Yang, 1996) was applied on the segmented data as implemented in Fieldtrip. Clear components containing cardiac artifacts and eyeblinks were removed in each subject (XX+/-YY over subjects)."

olejen commented 2 years ago

@TamasMinarik Please update FieldTrip FLUX tutorial from MNE FLUX scripts