scholarly journals Publisher Correction: High-frequency oscillations in scalp EEG mirror seizure frequency in pediatric focal epilepsy

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ece Boran ◽  
Johannes Sarnthein ◽  
Niklaus Krayenbühl ◽  
Georgia Ramantani ◽  
Tommaso Fedele
Keyword(s):  
Seizure Frequency ◽  
High Frequency ◽  
Focal Epilepsy ◽  
Scalp Eeg ◽  
High Frequency Oscillations

scholarly journals High-frequency oscillations in scalp EEG mirror seizure frequency in pediatric focal epilepsy

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ece Boran ◽  
Johannes Sarnthein ◽  
Niklaus Krayenbühl ◽  
Georgia Ramantani ◽  
Tommaso Fedele
Keyword(s):  
Seizure Frequency ◽  
Epilepsy Surgery ◽  
High Frequency ◽  
Focal Epilepsy ◽  
Low Noise ◽  
Drug Resistant ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Custom Made ◽  
Active Epilepsy

Abstract High-frequency oscillations (HFO) are promising EEG biomarkers of epileptogenicity. While the evidence supporting their significance derives mainly from invasive recordings, recent studies have extended these observations to HFO recorded in the widely accessible scalp EEG. Here, we investigated whether scalp HFO in drug-resistant focal epilepsy correspond to epilepsy severity and how they are affected by surgical therapy. In eleven children with drug-resistant focal epilepsy that underwent epilepsy surgery, we prospectively recorded pre- and postsurgical scalp EEG with a custom-made low-noise amplifier (LNA). In four of these children, we also recorded intraoperative electrocorticography (ECoG). To detect clinically relevant HFO, we applied a previously validated automated detector. Scalp HFO rates showed a significant positive correlation with seizure frequency (R2 = 0.80, p < 0.001). Overall, scalp HFO rates were higher in patients with active epilepsy (19 recordings, p = 0.0066, PPV = 86%, NPV = 80%, accuracy = 84% CI [62% 94%]) and decreased following successful epilepsy surgery. The location of the highest HFO rates in scalp EEG matched the location of the highest HFO rates in ECoG. This study is the first step towards using non-invasively recorded scalp HFO to monitor disease severity in patients affected by epilepsy.

scholarly journals A Neuromorphic Spiking Neural Network Detects Epileptic High Frequency Oscillations in the Scalp EEG

2021 ◽  
Author(s):  
Karla Burelo ◽  
Georgia Ramantani ◽  
Giacomo Indiveri ◽  
Johannes Sarnthein
Keyword(s):  
Low Power ◽  
Seizure Frequency ◽  
High Frequency ◽  
Therapy Monitoring ◽  
Non Invasive ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Eeg Recordings ◽  
Active Epilepsy ◽  
Wearable Electronic Devices

Abstract Background: Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The demand for therapy monitoring in epilepsy has kindled interest in compact wearable electronic devices for long- term EEG recording. Spiking neural networks (SNN) have been shown to be optimal architectures for being embedded in compact low-power signal processing hardware. Methods: We analyzed 20 scalp EEG recordings from 11 patients with pediatric focal lesional epilepsy. We designed a custom SNN to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band. Results: We identified the optimal SNN parameters to automatically detect EoI and reject artifacts. The occurrence of HFO thus detected was associated with active epilepsy with 80% accuracy. The HFO rate mirrored the decrease in seizure frequency in 8 patients (p = 0.0047). Overall, the HFO rate correlated with seizure frequency (rho = 0.83, p < 0.0001, Spearman’s correlation).Conclusions: The fully automated SNN detected clinically relevant HFO in the scalp EEG. This is a further step towards non-invasive epilepsy monitoring with a low-power wearable device.

scholarly journals High frequency oscillations and seizure frequency in patients with focal epilepsy

2009 ◽  
Vol 85 (2-3) ◽  
pp. 287-292 ◽  
Author(s):  
Maeike Zijlmans ◽  
Julia Jacobs ◽  
Rina Zelmann ◽  
François Dubeau ◽  
Jean Gotman
Keyword(s):  
Seizure Frequency ◽  
High Frequency ◽  
Focal Epilepsy ◽  
High Frequency Oscillations

scholarly journals Interictal high frequency oscillations (HFOs) in patients with focal epilepsy and normal MRI

2012 ◽  
Vol 123 (1) ◽  
pp. 100-105 ◽  
Author(s):  
Luciana Andrade-Valença ◽  
Francesco Mari ◽  
Julia Jacobs ◽  
Maeike Zijlmans ◽  
André Olivier ◽  
...  
Keyword(s):  
High Frequency ◽  
Focal Epilepsy ◽  
High Frequency Oscillations

Evoked versus spontaneous high frequency oscillations in the chronic electrocorticogram in focal epilepsy

2017 ◽  
Vol 128 (5) ◽  
pp. 858-866 ◽  
Author(s):  
M.A. van 't Klooster ◽  
N.E.C. van Klink ◽  
D. van Blooijs ◽  
C.H. Ferrier ◽  
K.P.J. Braun ◽  
...  
Keyword(s):  
High Frequency ◽  
Focal Epilepsy ◽  
High Frequency Oscillations

scholarly journals Stereotyped high-frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy

Brain ◽  
2018 ◽  
Vol 141 (3) ◽  
pp. 713-730 ◽  
Author(s):  
Su Liu ◽  
Candan Gurses ◽  
Zhiyi Sha ◽  
Michael M Quach ◽  
Altay Sencer ◽  
...  
Keyword(s):  
High Frequency ◽  
Focal Epilepsy ◽  
Machine Learning Techniques ◽  
Seizure Onset ◽  
Functional Regions ◽  
Clinical Biomarkers ◽  
High Frequency Oscillations ◽  
Potential Association ◽  
Waveform Similarity ◽  
Seizure Onset Zones

Abstract High-frequency oscillations in local field potentials recorded with intracranial EEG are putative biomarkers of seizure onset zones in epileptic brain. However, localized 80–500 Hz oscillations can also be recorded from normal and non-epileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones, which limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a repetitive fashion with a similar waveform morphology that specifically indicates seizure onset zones. We investigated the waveform patterns of automatically detected high-frequency oscillations in 13 epilepsy patients and five control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The repetitive oscillatory waveforms were identified by using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random waveforms were found in the functional regions independent from the epileptogenic locations. The repetitive waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step towards the translation of these signature events into valid clinical biomarkers. 5721572971001 awx374media1 5721572971001

scholarly journals Spike-related haemodynamic responses overlap with high frequency oscillations in patients with focal epilepsy

Brain ◽  
2018 ◽  
Vol 141 (3) ◽  
pp. 731-743 ◽  
Author(s):  
Karina A González Otárula ◽  
Hui Ming Khoo ◽  
Nicolás von Ellenrieder ◽  
Jeffery A Hall ◽  
François Dubeau ◽  
...  
Keyword(s):  
High Frequency ◽  
Focal Epilepsy ◽  
High Frequency Oscillations

scholarly journals High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Peter Höller ◽  
Eugen Trinka ◽  
Yvonne Höller
Keyword(s):  
High Frequency ◽  
Visual Detection ◽  
Signal To Noise Ratio ◽  
Physiological Activity ◽  
Automated Detection ◽  
Detection Algorithms ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Scalp Electroencephalogram ◽  
Electroencephalogram Eeg

High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.

scholarly journals Ictal Occurrence of High-Frequency Oscillations Correlates With Seizure Severity in a Rat Model of Temporal Lobe Epilepsy

2021 ◽  
Vol 15 ◽  
Author(s):  
Nadja Birk ◽  
Jan Schönberger ◽  
Karin Helene Somerlik-Fuchs ◽  
Andreas Schulze-Bonhage ◽  
Julia Jacobs
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Rat Model ◽  
High Frequency ◽  
Focal Epilepsy ◽  
Epileptic Activity ◽  
Seizure Severity ◽  
Chronic Epilepsy ◽  
High Frequency Oscillations

High-frequency oscillations (HFOs, ripples 80–250 Hz, fast ripples 250–500 Hz) are biomarkers of epileptic tissue. They are most commonly observed over areas generating seizures and increase in occurrence during the ictal compared to the interictal period. It has been hypothesized that their rate correlates with the severity of epilepsy and seizure in affected individuals. In the present study, it was aimed to investigate whether the HFO count mirrors the observed behavioral seizure severity using a kainate rat model for temporal lobe epilepsy. Seizures were selected during the chronic epilepsy phase of this model and classified by behavioral severity according to the Racine scale. Seizures with Racine scale 5&amp;6 were considered generalized and severe. HFOs were marked in 24 seizures during a preictal, ictal, and postictal EEG segment. The duration covered by the HFO during these different segments was analyzed and compared between mild and severe seizures. HFOs were significantly increased during ictal periods (p &lt; 0.001) and significantly decreased during postictal periods (p &lt; 0.03) compared to the ictal segment. Ictal ripples (p = 0.04) as well as fast ripples (p = 0.02) were significantly higher in severe seizures compared to mild seizures. The present study demonstrates that ictal HFO occurrence mirrors seizure severity in a chronic focal epilepsy model in rats. This is similar to recent observations in patients with refractory mesio-temporal lobe epilepsy. Moreover, postictal HFO decrease might reflect postictal inhibition of epileptic activity. Overall results provide additional evidence that HFOs can be used as biomarkers for measuring seizure severity in epilepsy.

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