Interictal high-frequency oscillations (HFOs) as predictors of high frequency and conventional seizure onset zones

Pradeep Modur, Svjetlana Miocinovic

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

we investigated the relationship between the interictal highfrequency oscillations (HFOs) and the seizure onset zones (SOZs) defined by the ictal HFOs or conventional frequency activity (CFA), and evaluated the usefulness of the interictalHFOsas spatialmarkers of the SOZs. We analysed seizures showing discrete HFOs at onset on intracranial EEGs acquired at ≥1000-Hz sampling rate in a training cohort of 10 patients with temporal and extratemporal epilepsy. We classified each ictal channel as: HFO+ (HFOs at onset with subsequent evolution), HFO- (HFOs at onset without evolution), CFA (1.6-70-Hz activity at onset with evolution), or non-ictal. We defined the SOZs as: hSOZ (HFO+ channels only), hfo+&-SOZ (HFO+ and HFO-channels), and cSOZ (CFA channels). Using automated methods, we detected the interictal HFOs and extracted five features: density, connectivity, peak frequency, log power, and amplitude. We created logistic regression models using these features, and tested their performance in a separate replication cohort of three patients. The models containing the five interictal HFO features reliably differentiated the channels located inside the SOZ from those outside in the training cohort (p0.5) but not the cSOZ. Our study shows that the interictal HFOs are useful in defining the spatial extent of the SOZ, and predicting whether or not a given channel in a novel patient would be involved in the seizure. The findings support the existence of an abnormal network of tightly-linked ictal and interictal HFOs in patients with intractable epilepsy.

Original languageEnglish (US)
Pages (from-to)413-424
Number of pages12
JournalEpileptic Disorders
Volume17
Issue number4
StatePublished - Dec 1 2015

Keywords

  • Epilepsy
  • High-frequency oscillations
  • Intracranial EEG
  • Seizure localization
  • Seizure prediction

ASJC Scopus subject areas

  • Clinical Neurology
  • Neurology

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