ArtifactReject¶

Bases: BaseClass

Class for rejecting or correcting bad channels in EEG epochs.

Identifies bad channels per epoch and either interpolates them using MNE's built-in functionality, or replaces them with NaNs.

MNE-functions used: mne.pick_types, mne.Epochs.interpolate_bads

Parameters:

Name	Type	Description	Default
`raw`	`Epochs`	Input data.	required
`mode`	`(interpolation, nan_replacement)`	Method for dealing with bad channels.	`'interpolation'`
`max_gradient_uv`	`int`	Maximal allowed voltage step in µV/ms.	`50`
`max_amplitude_uv`	`int`	Maximal allowed amplitude in µV.	`75`
`min_activity_uv`	`int`	Lowest allowed activity in intervals in µV.	`0.5`
`interval_ms`		Interval length in milliseconds for checking activity.	`100`
`**kwargs`		Additional keyword arguments passed to the underlying `Epochs.pick_types()` and `Epochs.interpolate_bads()` methods. Pass arguments for the different functions by using a dictionary with `pick_types`, and `interpolate_bads` as keys. Example: {'pick_types' : {'stim': False, 'eog': True}, 'interpolate_bads': {'mode': 'fast'}}	`{}`

Attributes:

Name	Type	Description
`processed`	`Epochs`	Output data.

Example settings for config file¶

Example settings in correct format for the config file.

ArtifactReject: 
  _biopap_module: <class 'biopap.modules.artifact_reject.ArtifactReject'>
  mode: 'interpolation'
  max_gradient_uv: 50
  max_amplitude_uv: 75
  min_activity_uv: 0.5
  interval_ms: 100