pyavs.add_fix_event_trigger

pyavs.add_fix_event_trigger(raw: mne.io.Raw, blocks: List[int], et_events: DataFrame, session: int, block_trigger_offset: int = 1000, stim_channel: str = 'STI101', verbose: bool = True, event_types: List[str] = ['fixation', 'saccade', 'blink'], recording: str = 'scene') → Tuple[mne.io.Raw, List[Tuple[int, int]]][source]

Adds eye movement based event triggers (fixation, saccade) to the raw neuro data.

Parameters:

  • raw (mne.io.Raw) – Raw neuro data

  • blocks (list of int) – List of blocks

  • et_events (pandas.DataFrame) – Events structure of the eye tracker data

  • session (int) – Session number

  • block_trigger_offset (int, optional) – Offset of the block trigger in the MEG data as used in repair_events function (default: 1000)

  • stim_channel (str, optional) – Name of the stim channel in the raw data (default: ‘STI101’)

  • verbose (bool, optional) – Print some output (default: True)

  • event_types (list of str, optional) – List of event types to add (default: [‘fixation’, ‘saccade’]) Valid options: [‘fixation’, ‘saccade’, ‘blink’]

  • recording (str, optional) – Recording context to filter events by (default: ‘scene’) Valid options: [‘scene’, ‘caption’, ‘microphone’]

Returns:

(raw_with_annotations, missing_trials) - Raw with added eye movement based event annotations and list of missing trials

Return type:

tuple