Actions¶

Actions serve as the primary analytical tools within Meggie. Upon establishing an experiment and incorporating the raw data files for each subject, these actions are systematically employed to progressively convert the raw magnetic or electric signals into meaningful behavioral outcomes. Below is a catalog of the available actions along with their respective descriptions.

Preprocessing¶

Events from annotations (raw_events_from_annotations)¶

Create events from annotations for further analysis.

The following MNE functions are used:
- mne.utils.config._get_stim_channel
- raw.load_data
- raw.save

Filter (raw_filter)¶

Apply low-pass, high-pass, band-pass, and band-stop filters to raw data to isolate specific frequency ranges or remove unwanted frequencies.

The following MNE functions are used:
- raw.filter
- raw.load_data
- raw.save

Artifact removal (raw_ica)¶

Apply Independent Component Analysis (ICA) to raw data to identify and remove artifacts such as heartbeats and eye blinks.

The following MNE functions are used:
- ica.apply
- ica.fit
- ica.get_sources
- ica.plot_components
- ica.plot_properties
- mne.create_info
- mne.io.RawArray
- mne.io.pick.channel_type
- mne.preprocessing.ICA
- raw.drop_channels
- raw.load_data
- raw.plot
- raw.save

Montage (raw_montage)¶

Apply a montage to the EEG dataset, enabling the creation of topographical plots.

The following MNE functions are used:
- mne.channels.make_standard_montage
- montage.save
- raw.load_data
- raw.save

Plot raw (raw_plot)¶

Produce a time series plot of the raw data.

The following MNE functions are used:
- mne.find_events
- mne.utils.config._get_stim_channel
- raw.load_data
- raw.plot

Plot projections (raw_plot_projections)¶

Generate a plot to visualize the projection vectors contained within the raw data.

The following MNE functions are used:
- raw.load_data
- raw.plot_projs_topomap

Rereference (raw_rereference)¶

Re-reference the raw data to an average reference, which can be computed from one or more selected channels or all channels.

The following MNE functions are used:
- mne.pick_types
- raw.load_data
- raw.save

Resample (raw_resample)¶

Adjust the dataset by resampling it to a different sampling frequency.

The following MNE functions are used:
- raw.load_data
- raw.resample
- raw.save

Continuous data¶

Create spectrum (spectrum_create)¶

Calculate the spectral data at specified time intervals for the current subject.

The following MNE functions are used:
- mne.io.write_info
- mne.pick_info
- mne.pick_types
- mne_spectrum.get_data
- raw.compute_psd
- raw.load_data

Delete (spectrum_delete)¶

Permanently remove the selected spectrum object from the current subject.

Delete from all (spectrum_delete_from_all)¶

Permanently remove the selected spectrum object from all matching subjects.

Average over subjects (spectrum_group_average)¶

Calculate the average of the selected spectrum object across subjects, with options to group subjects before averaging.

The following MNE functions are used:
- mne.io.write_info
- mne.pick_info

Plot (spectrum_plot)¶

Generate a plot for the selected spectrum object. The spectrum object may be visualized for all channels individually or as an average across specified channel groups.

The following MNE functions are used:
- mne.channels._divide_to_regions
- mne.pick_info
- mne.pick_types
- mne.viz.iter_topography
- raw.load_data

Save to csv (spectrum_save)¶

Export the numerical data from the spectrum object for all matching subjects into a CSV file.

The following MNE functions are used:
- mne.channels._divide_to_regions
- mne.pick_info
- mne.pick_types

Epochs¶

Create epochs (epochs_create)¶

Create a new epoch collection for the current subject.

The following MNE functions are used:
- epochs.get_data
- epochs.save
- mne.Epochs
- mne.find_events
- mne.pick_types
- mne.utils.config._get_stim_channel
- raw.load_data

Delete (epochs_delete)¶

Permanently remove the selected epoch collection from the current subject.

Delete from all (epochs_delete_from_all)¶

Permanently remove the selected epoch collection from all matching subjects.

Plot (epochs_plot)¶

Generate a simple plot for the selected epoch collection.

The following MNE functions are used:
- epochs.plot

Plot image (epochs_plot_image)¶

Generate an image plot for the selected epoch collection.

The following MNE functions are used:
- epochs.plot_image

Evoked responses¶

Create evoked (evoked_create)¶

Compute the average of selected epoch collections independently. Each collection is averaged separately, resulting in a distinct average curve for each.

The following MNE functions are used:
- epochs.average
- mne.write_evokeds

Delete (evoked_delete)¶

Permanently remove the selected evoked response object from the current subject.

Delete from all (evoked_delete_from_all)¶

Permanently remove the selected evoked response object from all matching subjects.

Average over subjects (evoked_group_average)¶

Calculate the average of the selected evoked response object across subjects, with options to group subjects before averaging.

The following MNE functions are used:
- mne.grand_average
- mne.pick_types
- mne.write_evokeds

Plot (evoked_plot)¶

Generate a plot for the selected evoked response object. The response may be visualized for all channels individually or as an average across specified channel groups.

The following MNE functions are used:
- mne.channels._divide_to_regions
- mne.pick_info
- mne.pick_types
- mne.viz.plot_evoked_topo

Plot topomaps (evoked_plot_topomap)¶

Produce a series of topographical maps at specified time intervals for the selected evoked response object.

The following MNE functions are used:
- evoked.plot_topomap
- mne.pick_types

Save to csv (evoked_save)¶

Export the numerical data from the evoked response object for all matching subjects into a CSV file.

The following MNE functions are used:
- mne.channels._divide_to_regions
- mne.pick_info
- mne.pick_types

Induced responses (TFR)¶

Create TFR (tfr_create)¶

Calculate time-frequency representations (TFRs) for selected epoch collections independently, with each collection yielding a unique TFR.

The following MNE functions are used:
- mne.time_frequency.tfr.tfr_morlet
- tfr.save

Delete (tfr_delete)¶

Permanently remove the selected TFR object from the current subject.

Delete from all (tfr_delete_from_all)¶

Permanently remove the selected TFR object from all matching subjects.

Average over subjects (tfr_group_average)¶

Calculate the average of the selected TFR object across subjects, with options to group subjects before averaging.

The following MNE functions are used:
- mne.grand_average
- tfr.save

Plot TFR (tfr_plot)¶

Visualize the selected TFR object as a heatmap, with options for individual channel visualization or averaging across channel groups.

The following MNE functions are used:
- mne.baseline.rescale
- mne.channels._divide_to_regions
- mne.create_info
- mne.pick_info
- mne.pick_types
- mne.time_frequency.tfr.AverageTFR
- tfr.apply_baseline
- tfr.plot
- tfr.plot_topo

Plot TSE (tfr_plot_tse)¶

Visualize the Temporal Spectral Evolution (TSE) of the selected TFR object, collapsing the frequency dimension over a specified interval, for individual channels or averaged across channel groups.

The following MNE functions are used:
- mne.baseline.rescale
- mne.channels._divide_to_regions
- mne.pick_info
- mne.pick_types
- mne.viz.iter_topography

Save TFR to csv (tfr_save)¶

Export the numerical data from the TFR object for all matching subjects into a CSV file.

The following MNE functions are used:
- mne.baseline.rescale
- mne.channels._divide_to_regions
- mne.pick_info
- mne.pick_types

Save TSE to csv (tfr_save_tse)¶

Export the TSE data from the TFR object, collapsing the frequency dimension over a specified interval, into a CSV file for all matching subjects.

The following MNE functions are used:
- mne.baseline.rescale
- mne.channels._divide_to_regions
- mne.pick_info
- mne.pick_types