1,2, David L. Chang 1,2, 1,2 and Edward F. Chang 1,2 * • 1Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, United States • 2Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA, United States 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.

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We describe the full capabilities of our imaging pipeline and present a step-by-step protocol for users. Introduction High-density electrocorticography (ECoG) is an invasive method where recordings are obtained directly from the surface of the brain in patients with medically intractable epilepsy. This approach provides millimeter spatial and millisecond temporal resolution neurophysiological data from awake, behaving humans, which complements the information obtained from noninvasive approaches such as, fMRI, EEG, and MEG (). Preprocessing of ECoG data typically relies on aligning a preoperative MRI scan to a postoperative CT scan or postoperative MRI, then electrodes are localized either manually or in a semi-automated fashion (;;;;;;;; ).

Once electrodes are localized in the MRI, they are assigned anatomical labels, and then potentially warped to a common MNI atlas space for comparisons across subjects. While many labs that perform ECoG research have their own methods for performing these steps, to our knowledge there exists no software package that incorporates all steps of image processing necessary for ECoG electrode localization and warping from start to finish.

Buddha In Daily Life Pdf Viewer. Here, we present a protocol to perform all of these steps, from pial surface reconstruction to CT coregistration, electrode identification and anatomical labeling, and warping to a common atlas space. We take advantage of tools provided in the nipy software package (), dural surface reconstruction from ielu (), 3D plotting in mayavi (; ), and extend on functions available in the MATLAB-based CTMR package (). This protocol has been used to localize and label electrodes in our previously published work (;;;;; ). In an effort to promote open and affordable access to these tools, all requirements to run the pipeline (aside from physical hardware) are freely available for download at no cost to the user. We hope that this software will facilitate more efficient workflows within ECoG research labs and will aid in reproducibility across studies. Materials and Methods Subjects Here, we present electrode localizations from human subjects undergoing surgical treatment for intractable epilepsy.

Subjects were implanted with high-density subdural intracranial electrode grids (AdTech 256 channels, 4 mm center-to-center spacing and 1.17 mm diameter), subdural electrode strips (1 cm spacing), and/or depth electrodes (5 mm spacing) as part of their clinical evaluation for epilepsy surgery. This study was carried out in accordance with the recommendations of the University of California, San Francisco Institutional Review Board with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. This protocol was approved by the University of California, San Francisco Institutional Review Board.

Example Data We include sample data for use with this pipeline so that the user may follow along with each of these steps and check their results. Sample data is available at and includes an AC-PC aligned T1 MRI scan, CT scan, and all intermediate and final files from the execution of img_pipe. This subject's data is shown in Figure. Other figures include data from this subject and others to illustrate a wide variety of scenarios that could be encountered when using our software. We suggest that users who wish to follow along download this data set, then copy the files from the acpc and CT directories to a new Freesurfer subject directory. The user can then start from the prep_recon() step.