Detection of Interictal Epileptiform Discharges Using Signal Envelope Distribution Modelling: Application to Epileptic and Non-Epileptic Intracranial Recordings

Radek Janca, Petr Jezdik, Roman Cmejla, Martin Tomasek, Gregory Alan Worrell, Squire Matthew Stead, Joost Wagenaar, John G R Jefferys, Pavel Krsek, Vladimir Komarek, Premysl Jiruska, Petr Marusic

Research output: Contribution to journalArticle

21 Scopus citations

Abstract

Interictal epileptiform discharges (spikes, IEDs) are electrographic markers of epileptic tissue and their quantification is utilized in planning of surgical resection. Visual analysis of long-term multi-channel intracranial recordings is extremely laborious and prone to bias. Development of new and reliable techniques of automatic spike detection represents a crucial step towards increasing the information yield of intracranial recordings and to improve surgical outcome. In this study, we designed a novel and robust detection algorithm that adaptively models statistical distributions of signal envelopes and enables discrimination of signals containing IEDs from signals with background activity. This detector demonstrates performance superior both to human readers and to an established detector. It is even capable of identifying low-amplitude IEDs which are often missed by experts and which may represent an important source of clinical information. Application of the detector to non-epileptic intracranial data from patients with intractable facial pain revealed the existence of sharp transients with waveforms reminiscent of interictal discharges that can represent biological sources of false positive detections. Identification of these transients enabled us to develop and propose secondary processing steps, which may exclude these transients, improving the detector’s specificity and having important implications for future development of spike detectors in general.

Original languageEnglish (US)
Pages (from-to)172-183
Number of pages12
JournalBrain Topography
Volume28
Issue number1
DOIs
StatePublished - 2014

Keywords

  • Automatic detection
  • Hilbert transform
  • Interictal epileptiform discharges
  • Intracranial recording
  • Principal component analysis
  • Spike detection

ASJC Scopus subject areas

  • Clinical Neurology
  • Anatomy
  • Neurology
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

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