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Published December 4, 2017 | Version getting_started
Software Open

pelednoam/ieil: The electrode labelling algorithm (ELA) main purpose is to estimate the probability that a particular brain region contributes to the source of the signal at each electrode using purely anatomical approaches. Even through electrodes in the brain, whether placed in either white or grey matter, receives signal from multiple sources, current thought is that the signal is generated from the local field potentials from grey matter (whether cortical or subcortical). We developed a simple and approachable ELA to identify this source by identifying the overlap of an expanding area (cylinder) around each electrode with identified brain structure labels. We are mapping these electrodes to regions in a given location which can be flexibly chosen within Freesurfer. Here we used the DKT atlas in combination with a subcortical mapping enabled through Freesurfer (Desikan et al., 2006; Fischl et al., 2004).

Creators

  • 1. MGH/HST Martinos Center for Biomedical Imaging

Description

The electrode lablling algorithm (ELA) main purpose is to estimate the probability that a particular brain region contributes to the source of the signal at each electrode using purely anatomical approaches. Even through electrodes in the brain, whether placed in either white or grey matter, receives signal from multiple sources, current thought is that the signal is generated from the local field potentials from grey matter (whether cortical or subcortical). We developed a simple and approachable ELA to identify this source by identifying the overlap of an expanding area (cylinder) around each electrode with identified brain structure labels. We are mapping these electrodes to regions in a given location which can be flexibly chosen within Freesurfer. Here we used the DKT atlas in combination with a subcortical mapping enabled through Freesurfer (Desikan et al., 2006; Fischl et al., 2004).

Files

pelednoam/ieil-getting_started.zip

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