neuralset.extractors.neuro.IeegExtractor

pydantic model neuralset.extractors.neuro.IeegExtractor[source][source]

Intracranial EEG feature extractor.

Parameters:
  • picks (default = ("seeg", "ecog", )) – pick “seeg” and “ecog” channels by default.

  • reference ("bipolar" or None, default=None) – If “bipolar”, applies a bipolar reference to the data, i.e., uses neighboring electrode as reference. Uses mne.set_bipolar_reference under the hood. [ieeg1]

Notes

Bipolar reference currently can only be applied to sEEG. It expects that the channels in raw.ch_names are ordered by probe, and with ascending order for each probe, and the names consists of the probe name followed by the position on the probe. eg: [‘OF1’, ‘OF2’, ‘OF3’, … , ‘OF12’, ‘OF13’, ‘OF14’, ‘H1’, ‘H2’, ‘H3’, … , ‘H13’, ‘H14’, ‘H15’, …]

WATCH-OUT: this will take the closest electrode on the probe, meaning that if the neighboring electrode is missing for some reason (eg: rejected before applying the reference) then the next electrode will be used for referencing.

References

Fields:
field event_types: Literal['Ieeg'] = 'Ieeg'[source]
field picks: tuple[str, ...] = ('seeg', 'ecog')[source]
field reference: Literal['bipolar'] | None = None[source]
requirements: tp.ClassVar[tuple[str, ...]] = ()[source]