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iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization

Published version
Peer-reviewed

Type

Article

Change log

Authors

Blenkmann, AO 
Phillips, HN 
Princich, JP 
Rowe, JB 
Bekinschtein, TA 

Abstract

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.

Description

Keywords

SEEG, ECoG, intracranial EEG, MRI, CT, atlas, epilepsy

Journal Title

Frontiers in Neuroinformatics

Conference Name

Journal ISSN

1662-5196
1662-5196

Volume Title

11

Publisher

Frontiers
Sponsorship
Wellcome Trust (103838/Z/14/Z)
James S McDonnell Foundation (220020289)
Medical Research Council (MC_U105597119)
MRC (1233633)
Medical Research Council (MC_UU_00005/12)
This work was supported by Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) to AB and SK, Agencia Nacional de Promoción Científica y Tecnológica (PIDC 53/2012 and PICT 0775/2012 to AB, JP, SK, and PICT 1232/2014 to CM), Universidad Nacional Arturo Jauretche Investiga 2014 to AB and SK, Comisión de Investigaciones Científicas (CIC) to CHM, Medical Research Council (MC-A060-5PQ30 to JR and a Doctoral Training award to HP), Wellcome Trust (103838 Senior Research Fellowship to JR, Biomedical Research Fellowship; WT093811MA to TB), the James F. McDonnell Foundation 21st Century Science Initiative: Understanding Human Cognition to JR.