Work Description

Title: A taxonomy of seizure dynamotypes - Code & Data Open Access Deposited

h
Attribute Value
Methodology
  • Human data were collected from seven international epilepsy centers: University of Michigan, Mayo Clinic, Hospital of the University of Pennsylvania, Children’s Hospital of Philadelphia, University of Melbourne, University of Freiburg, and Kyoto University Hospital. All patients consented to share their data according to the local institution’s review board policy. Data were de-identified EEG collected with each institution’s clinical EEG equipment. All EEG data used in this work were from either grid or depth intracranial electrodes. All sampling rates were > 200 Hz and antialiasing filters > 100 Hz, but there was variability between centers (XLTek, Nicolet, Natus, Nihon Kohden, NeuroVista). The Melbourne patients had ambulatory devices that recorded data for several months, while all the others were acquired during acute inpatient recording sessions. There were only two centers (Kyoto, Michigan) that had amplifiers that recorded low enough frequency content (high pass filter 0.016 Hz) to allow analysis of direct current (DC, i.e. very low frequency) shifts, and so only those centers were included in the analyses that involved DC coupling. Simulated data were generated to validate the visual classification scheme. Depending on the analysis in question, data was either highpass filtered, median filtered, or left raw before features were extracted.
Description
  • This data and scripts are meant to test and show seizure differentiation based on bifurcation theory. A zip file is included which contains real and simulated seizure waveforms, Matlab scripts, and metadata. The matlab scripts allow for visual review validation and objective feature analysis. The file “README.txt” provides more detail about each individual file within the zip file.

  • Data citation: Crisp, D.N., Saggio, M.L., Scott, J., Stacey, W.C., Nakatani, M., Gliske, S.F., Lin, J. (2019). Epidynamics: Navigating the map of seizure dynamics - Code & Data [Data set]. University of Michigan Deep Blue Data Repository.  https://doi.org/10.7302/ejhy-5h41
Creator
Depositor
  • dncrisp@umich.edu
Contact information
Discipline
Funding agency
  • National Institutes of Health (NIH)
ORSP grant number
  • AWD002118
Keyword
Citations to related material
  • Saggio, M.L., Crisp, D., Scott, J., Karoly, P.J., Kuhlmann, L., Nakatani, M., Murai, T., Dümpelmann, M., Schulze-Bonhage, A., Ikeda, A., Cook, M., Gliske, S.V., Lin, J., Bernard, C., Jirsa, V., Stacey, W., 2020. In pre-print. Epidynamics characterize and navigate the map of seizure dynamics. bioRxiv 2020.02.08.940072. https://doi.org/10.1101/2020.02.08.940072
Resource type
Curation notes
  • On May 31 and July 15, 2019, revised code and documentation were added to record, including enhanced context, minor corrections, and organization. See file "Epidynamics_UpdateLog_20190531.txt" for details.
Last modified
  • 05/14/2020
Published
  • 04/16/2019
Language
DOI
  • https://doi.org/10.7302/ejhy-5h41
License
To Cite this Work:
Crisp, D. N., Saggio, M. L., Scott, J., Stacey, W. C., Nakatani, M., Gliske, S. V., Lin, J. (2019). A taxonomy of seizure dynamotypes - Code & Data [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/ejhy-5h41

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Files (Count: 3; Size: 315 MB)

May 31, 2019

List of changes to Epidynamics repository:
1. Visual Classification -> Reviewer Widgets
a. Prompt instructions for reviewer widgets were clarified, and a warning was added
about the possibility of overwriting current data.
b. Reviewer widgets were changed so that the numbers in the bottom left corner
of the widget were not cut-off (i.e. display was slightly moved).
c. READMEs were changed to:
i. Use correct names
ii. Fix spelling errors
iii. Enhance readability
2. Visual Classification -> Reviewer Widgets -> Real Data
a. Explained different colors of waveforms
3. Visual Classification -> Reviewer Widgets -> Real Data -> No DC
a. Separated into two subfolders (Onset and Offset) to be equivalent to similar folders.
4. Visual Classification -> Reviewer Marking & Analysis
a. Code changed to automatically add the correct paths. (Users no longer need to change
paths for code to work.)
b. README added so users can better orient themselves to this part of the analysis.
i. The addition of this README was reflected in the top-level README which
details the location and purpose of all READMEs within the dataset
5. Data Analysis -> Code
a. README updated to call out the two most important functions in the folder.
b. All DRIVER files changed so path changes are now unnecessary.
c. A small portion from one of the DRIVER scripts that had been used for
debugging was removed. This section was a few lines that were not important to the
overall function, and was already commented out.
6. General
a. Fix spelling errors

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