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Code for detecting and classifying epileptiform activity (EA)

Heining, Katharina


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{
  "description": "<p><strong>Code for detecting and classifying epileptiform activity (EA)</strong><br>\nWritten by Katharina Heining, last modified 2020/10/20 &nbsp;<br>\nInstitution: University of Freiburg, Germany<br>\nAccompanying Paschen et al. (2020), eLife</p>\n\n<p>The subdirectory <strong>core</strong> contains the main code: &nbsp;</p>\n\n<ul>\n\t<li>&nbsp;<em>ed_detection.py</em>:&nbsp;&nbsp;&nbsp; wrapper for preprocessing, spike detection and spike sorting &nbsp;</li>\n\t<li>&nbsp;<em>artisfaction.py</em>:&nbsp;&nbsp; &nbsp;semiautomatic identification of artifacts</li>\n\t<li>&nbsp;<em>blipS.py</em>:&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; spike detection* blipsort.py:&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp; spike sorting</li>\n\t<li>&nbsp;<em>ea_analysis.py</em>:&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp; wrapper for burst detection and classification</li>\n\t<li>&nbsp;<em>somify.py</em>:&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; projecting data on a SOM and SOM plotting</li>\n\t<li>&nbsp;<em>helpers.py</em>:&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; supportive functions for the other scripts</li>\n\t<li>&nbsp;<em>ea_management.py</em>:&nbsp;&nbsp; &nbsp;reading data, handling results, recording-class functions</li>\n</ul>\n\n<p><em>configAnalysis.yml</em> contains parameters used for analyses &nbsp;<br>\n<em>som.h5</em> holds the SOM obtained from reference dataset -- see Heining et al. (2019), referenced below.* &nbsp;</p>\n\n<p>The subdirectory <strong>code_for_figures</strong> contains the code used for illustration (Supplementary Figure 1).<br>\n&nbsp;<br>\nThe code contained in this folder is &copy; K. Heining, 2020, developed at the University of Freiburg. &nbsp;<br>\nThis code is made available under the BSD license enclosed with the software (see licence.txt).<br>\nOver and above the legal restrictions imposed by this license, if you use this software for an academic publication then you are obliged to provide proper attribution.<br>\nFor this, you need to cite the paper that describes the code: &nbsp;<br>\n* Heining, K., Kilias, A., Janz, P., H&auml;ussler, U., Kumar, A., Haas, C. A., and Egert, U.<br>\n(2019). Bursts with high and low load of epileptiform spikes show context-dependent<br>\ncorrelations in epileptic mice. eNeuro, 6(5).</p>", 
  "license": "https://opensource.org/licenses/MIT", 
  "creator": [
    {
      "affiliation": "Biomicrotechnology, Department of Microsystems Engineering \u2013 IMTEK, Faculty of Engineering, University of Freiburg, 79110 Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, 79104 Freiburg, Germany; Faculty of Biology, University of Freiburg, 79104 Freiburg, Germany", 
      "@id": "https://orcid.org/0000-0003-1976-3764", 
      "@type": "Person", 
      "name": "Heining, Katharina"
    }
  ], 
  "url": "https://zenodo.org/record/4110614", 
  "datePublished": "2020-10-20", 
  "keywords": [
    "epileptiform activity", 
    "local field potential", 
    "detection of epileptiform spikes"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.4110614", 
  "@id": "https://doi.org/10.5281/zenodo.4110614", 
  "@type": "SoftwareSourceCode", 
  "name": "Code for detecting and classifying epileptiform activity (EA)"
}
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