ArticleEpileptic disorders : international epilepsy journal with videotape2015
Interictal high-frequency oscillations (HFOs) as predictors of high frequency and conventional seizure onset zones.
Article in Epileptic disorders : international epilepsy journal with videotape, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 21 citations in OpenAlex.
- Noninvasive high-frequency oscillations riding spikes delineates epileptogenic sources.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- The Onset of Interictal Spike-Related Ripples Facilitates Detection of the Epileptogenic Zone.Frontiers in neurology · 2021Article
- Interictal spike connectivity in human epileptic neocortex.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2019Article
- A Stacked Sparse Autoencoder-Based Detector for Automatic Identification of Neuromagnetic High Frequency Oscillations in Epilepsy.IEEE transactions on medical imaging · 2018Article
- High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence.Computational intelligence and neuroscience · 2018Review
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Authors and funding
2 authors at 1 institution in 1 country.
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Abstract
We investigated the relationship between the interictal high-frequency oscillations (HFOs) and the seizure onset zones (SOZs) defined by the ictal HFOs or conventional frequency activity (CFA), and evaluated the usefulness of the interictal HFOs as spatial markers 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 (p<0.001), reaching the highest accuracy for the classification of hSOZ. Log power and connectivity had the highest odds ratios, both being higher for the channels inside the SOZ compared with those outside the SOZ. In the replication cohort of novel patients, the same models differentiated the HFO+ from HFO- channels, and predicted the extents of the hSOZ and hfo+&-SOZ (F1 measure >0.5) 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.
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