Apply MNE preprocessing

When using run_unfold on your BIDS dataset it is usually assumed that your data is already preprocessed (or you want to have a look at the raw data). However, you also have the option to apply some further processing to your data. This is done by providing a custom function as extract_data keyword to run_unfold.

I.e. run_unfold(dataDF, bfDict; extract_data = your_custom_function)

By default raw_to_data is used.

function raw_to_data(raw; channels::AbstractVector{<:Union{String,Integer}}=[])
  return pyconvert(Array, raw.get_data(picks=pylist(channels), units="uV"))
end

You can exchange this function through an arbitrary function (applying MNE processing as needed), as long as it takes the raw MNE data object and returns a pyconverted Julia Array containing the data stream. For example

function raw_to_filtered_data(raw; channels::AbstractVector{<:Union{String,Integer}}=[], l_freq=0.5, h_freq=45)

  # Load data into memory
  raw.load_data()

  # Re-reference to mastoids and add Cz back in
  UnfoldBIDS.PyMNE.add_reference_channels(raw, ref_channels=UnfoldBIDS.pylist(["Cz"]), copy=false)
  raw.set_eeg_reference(ref_channels=UnfoldBIDS.pylist(["RM", "LM"]))

  # Filter data
  raw.filter(l_freq, h_freq, picks="eeg")

  return UnfoldBIDS.pyconvert(Array, raw.get_data(picks=UnfoldBIDS.pylist(channels), units="uV"))
end

However, including a preprocessing step right before fitting your model can often be a bottleneck in performance. If you think you will more likely only apply some preprocessing and then play around with the model, it's often more advisable to preprocess the raw objects in the dataframe before fitting.

function ref_and_filter_data!(raw; l_freq=0.5, h_freq=45)
  raw.load_data()

  # Re-reference to mastoids and add Cz back in
  UnfoldBIDS.PyMNE.add_reference_channels(raw, ref_channels=UnfoldBIDS.pylist(["Cz"]), copy=false)
  raw.set_eeg_reference(ref_channels=UnfoldBIDS.pylist(["RM", "LM"]))

  # Filter data
  raw.filter(l_freq, h_freq, picks="eeg")

end

for row in eachrow(loaded_data_df)
  ref_and_filter_data!(row.raw)
end

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