Intracranial Electrode Location and Analysis in MNE-Python

Abstract

Intracranial electrophysiology analysis requires precise location and anatomical labeling of electrode recording contacts before a signal processing analysis of the data can be interpreted. Signal processing techniques are common to other electrophysiology modalities, such as magnetoencephalography (MEG) and electroencephalography (EEG), so ideally locating and labeling intracranial electrodes would be an integrated part of a single analysis software package. This work covers the addition of intracranial electrode localization and intracranial-specific analyses to MNE-Python (Gramfort et al., 2013) including aligning a computed tomography (CT) image to a magnetic resonance (MR) image, locating electrode contacts in the CT image using a graphical user interface (GUI), warping the positions of contacts from the brain of an individual to a template brain and the visualizations that accompany these steps. This allows MNE-Python’s suite of signal processing and analysis tools to be used more easily by intracranial electrophysiology researchers.