Abstract
AbstractIntracranial electroencephalography (iEEG) provides a unique opportunity to measure human brain function with implanted electrodes. A key step in neuroscience inference from iEEG is localizing the electrodes relative to individual subject anatomy and identified regions in brain atlases. While there are number of workflows for electrode localization, most suffer from one or more limitations. The first limitation is a lack of integration: scientists must install and use different software packages for each localization step. Second, they are inefficient: while most iEEG analysis steps can be automated, electrode localization is still largely a manual process. Third, most current tools are limited to the localization process itself, leaving users without the ability to create high-quality visualizations for clinical and research purposes. We developed YAEL (Your Advanced Electrode Localizer) to overcome these limitations. First, YAEL is completely integrated: a single easy-to-use graphical user interface (GUI) controls every step of the localization process. Second, YAEL uses a flexible 3D viewer and automation tools to make accurate localization of electrodes quick and easy. Third, after localization is complete, YAEL leverages the same viewer to create high-quality visualizations of electrode data including identified brain areas from atlases; the response to experimental tasks measured with iEEG; and clinical measures such as epileptiform activity or the results of electrical stimulation mapping. YAEL contains more than 30,000 lines of code, is free and open source, and can be installed in minutes on Mac, Windows and Linux platforms fromhttps://yael.wiki. User interactions with YAEL occur through a web browser ensuring a familiar user experience and consistent operation across platforms and whether YAEL is used locally or deployed in the cloud.
Publisher
Cold Spring Harbor Laboratory
Reference38 articles.
1. iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization;Front Neuroinform,2017
2. ALICE: A tool for automatic localization of intra-cranial electrodes for clinical and high-density grids;J Neurosci Methods,2018
3. Chang, W. , Cheng, J. , Allaire, J.J. , Sievert, C. , Schloerke, B. , Xie, Y. , Allen, J. , McPherson, J. , Dipert, A. , Borges, B. , 2023. shiny: Web Application Framework for R.
4. Cortical Surface-Based Analysis
5. LeGUI: A Fast and Accurate Graphical User Interface for Automated Detection and Anatomical Localization of Intracranial Electrodes;Front Neurosci,2021