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A predictive epilepsy index based on probabilistic classification of interictal spike waveforms.

Jesse A Pfammatter1, Rachel A Bergstrom2, Eli P Wallace1

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|November 7, 2018
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Summary

This study introduces an automated method to quantify interictal spikes in electroencephalography (EEG) data, offering a fast and unbiased measure of epilepsy burden in mice. The developed Hourly Epilepsy Index predicts epileptogenic treatment and tracks disease progression.

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Area of Science:

  • Neuroscience
  • Epilepsy Research
  • Computational Biology

Background:

  • Manual quantification of interictal spikes in electroencephalography (EEG) is laborious and prone to bias, hindering accurate assessment of epilepsy disease burden.
  • Existing methods lack the speed and objectivity required for comprehensive analysis of spike morphologies and their relation to disease progression.

Purpose of the Study:

  • To develop and validate a probability-based, automated method for classifying and quantifying interictal events in EEG data.
  • To establish an Hourly Epilepsy Index predictive of epileptogenic treatment and disease progression, even in the absence of observed seizures.

Main Methods:

  • Detection of high-amplitude events followed by Principal Component Analysis (PCA) projection of waveforms.
  • Clustering of spike morphologies using a Gaussian Mixture Model (GMM).
  • Calculation of P(kainate) probability scores and the Hourly Epilepsy Index based on event cluster probabilities and record duration.

Main Results:

  • The automated method successfully classified and quantified interictal events in EEG data from kainate-treated and saline-injected mice.
  • The Hourly Epilepsy Index was predictive of kainate treatment and showed increased magnitude over time in a subset of animals.
  • The Index correlated with electrographic seizures and revealed dynamic changes in epileptiform spike morphology prevalence.

Conclusions:

  • The developed automated analysis is fast, unbiased, and provides quantitative insights into spike morphologies relevant to epilepsy progression.
  • The Hourly Epilepsy Index serves as a valuable, objective biomarker for epilepsy research, facilitating a better understanding of interictal spikes.
  • Further refinement of this method promises to define interictal spikes in more quantitative and unambiguous terms.