ALICE: A tool for automatic localization of intra-cranial electrodes for clinical and high-density grids

Journal of Neuroscience Methods
Mariana P BrancoNick F Ramsey

Abstract

Electrocorticographic (ECoG) measurements require the accurate localization of implanted electrodes with respect to the subject's neuroanatomy. Electrode localization is particularly relevant to associate structure with function. Several procedures have attempted to solve this problem, namely by co-registering a post-operative computed tomography (CT) scan, with a pre-operative magnetic resonance imaging (MRI) anatomy scan. However, this type of procedure requires a manual and time-consuming detection and transcription of the electrode coordinates from the CT volume scan and restricts the extraction of smaller high-resolution ECoG grid electrodes due to the downsampling of the CT. ALICE automatically detects electrodes on the post-operative high-resolution CT scan, visualizes them in a combined 2D and 3D volume space using AFNI and SUMA software and then projects the electrodes on the individual's cortical surface rendering. The pipeline integrates the multiple-step method into a user-friendly GUI in Matlab®, thus providing an easy, automated and standard tool for ECoG electrode localization. ALICE was validated in 13 subjects implanted with clinical ECoG grids by comparing the calculated electrode center-of-mass coordinates wi...Continue Reading

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Citations

Jul 13, 2019·Journal of Neural Engineering·Mariana P BrancoNick F Ramsey
Jul 3, 2020·PLoS Computational Biology·Julia BerezutskayaNick F Ramsey
Jul 15, 2020·Brain Topography·Anna GaglianeseNick F Ramsey
Jul 11, 2018·Nature Protocols·Arjen StolkRobert Oostenveld
Mar 10, 2021·International Journal of Computer Assisted Radiology and Surgery·Jessica CentracchioPaolo Bifulco
Aug 10, 2021·NeuroImage·Giovanni PiantoniNatalia Petridou

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