Liberty S. Hamilton, David L. Chang, Morgan B. Lee, Edward F. Chang
Abstract
In this article, we introduce img_pipe, our open source python package for preprocessing of imaging data for use in intracranial electrocorticography (ECoG) and intracranial stereo-EEG analyses. The process of electrode localization, labeling, and warping for use in ECoG currently varies widely across laboratories, and it is usually performed with custom, lab-specific code. This python package aims to provide a standardized interface for these procedures, as well as code to plot and display results on 3D cortical surface meshes. It gives the user an easy interface to create anatomically labeled electrodes that can also be warped to an atlas brain, starting with only a preoperative T1 MRI scan and a postoperative CT scan. We describe the full capabilities of our imaging pipeline and present a step-by-step protocol for users.
This research output has an Altmetric Attention Score of 24. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 January 2018.
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#1,647,585
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#32,026
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Outputs of similar age from Frontiers in Neuroinformatics
#3
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Altmetric has tracked 26,194,269 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 850 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done particularly well, scoring higher than 95% of its peers.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.
