A comparison between automated detection methods of high-frequency oscillations (80–500Hz) during seizures

Salami, Pariya; Lévesque, Maxime; Gotman, Jean; Avoli, Massimo

doi:10.1016/j.jneumeth.2012.09.003

Cited by 38 publications

(24 citation statements)

References 16 publications

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“…To identify oscillations in each frequency range (80-200 Hz and 250-500 Hz), a multi-parametric algorithm was employed using routines based on standardized functions (Matlab Signal Processing Tool-box) as described in detail in Hamidi et al (2014) and Salami et al (2012).…”

Section: Methodsmentioning

confidence: 99%

KCC2 function modulates in vitro ictogenesis

Hamidi

Avoli

2015

Neurobiology of Disease

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GABA A receptor-mediated inhibition is active and may contribute to epileptiform synchronization. The efficacy of inhibition relies on low levels of intracellular Cl − , which are controlled by KCC2 activity. This evidence has led us to analyze with field potential recordings the effects induced by the KCC2 blockers VU0240551 (10 μM) or bumetanide (50 μM) and by the KCC2 enhancer CLP257 (100 μM) on the epileptiform discharges generated by piriform and entorhinal cortices (PC and EC, respectively) in an in vitro brain slice preparation. Ictal-and interictal-like discharges along with high-frequency oscillations (HFOs, ripples: 80-200 Hz, fast ripples: 250-500 Hz) were recorded from these two regions during application of 4-aminopyridine (4AP, 50 μM). Blocking KCC2 activity with either VU024055 or high doses of bumetanide abolished ictal discharge in both PC and EC; in addition, these experimental procedures decreased the interval of occurrence and duration of interictal discharges. In contrast, enhancing KCC2 activity with CLP257 increased ictal discharge duration in both regions. Finally, blocking KCC2 activity decreased the duration and amplitude of pharmacologically isolated synchronous GABAergic events whereas enhancing KCC2 activity led to an increase in their duration. Our data demonstrate that in vitro ictogenesis is abolished or facilitated by inhibiting or enhancing KCC2 activity, respectively. We propose that these effects may result from the reduction of GABA A receptor-dependent increases in extracellular K + that are known to rest on KCC2 function.

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Section: Methodsmentioning

confidence: 99%

KCC2 function modulates in vitro ictogenesis

Hamidi

Avoli

2015

Neurobiology of Disease

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“…To be considered as an HFO candidate, oscillatory events in each frequency band had to show at least four consecutive cycles having amplitude of 3 SD above the mean. The time lag between two consecutive cycles had to be between 5 and 12.5 ms for ripples and between 2 and 4 ms for fast ripples (Lévesque et al, 2011Salami et al, 2012). HFOs were considered as co-occurring with a spike if they occurred within a time window of ±500 ms from the peak of an interictal spike.…”

Section: Analysis Of High-frequency Oscillationsmentioning

confidence: 99%

Dynamics of interictal spikes and high-frequency oscillations during epileptogenesis in temporal lobe epilepsy

Salami

Lévesque

Benini

et al. 2014

Neurobiology of Disease

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Mesial temporal lobe epilepsy (MTLE) is characterized in humans and in animal models by a seizure-free latent phase that follows an initial brain insult; this period is presumably associated to plastic changes in temporal lobe excitability and connectivity. Here, we analyzed the occurrence of interictal spikes and high frequency oscillations (HFOs; ripples: 80-200 Hz and fast ripples: 250-500 Hz) from 48 h before to 96 h after the first seizure in the rat pilocarpine model of MTLE.Interictal spikes recorded with depth EEG electrodes from the hippocampus CA3 area and entorhinal cortex (EC) were classified as type 1 (characterized by a spike followed by a wave) or type 2 (characterized by a spike with no wave). We found that: (i) there was a switch in the distribution of both types of interictal spikes before and after the occurrence of the first seizure; during the latent phase both types of interictal spikes predominated in the EC whereas during the chronic phase both types of spikes predominated in CA3; (ii) type 2 spike duration decreased in both regions from the latent to the chronic phase; (iii) type 2 spikes associated to fast ripples occurred at higher rates in EC compared to CA3 during the latent phase while they occurred at similar rates in both regions in the chronic phase; and (iv) rates of fast ripples outside of spikes were higher in EC compared to CA3 during the latent phase. Our findings demonstrate that the transition from the latent to the chronic phase is paralleled by dynamic changes in interictal spike and HFO expression in EC and CA3. We propose that these changes may represent biomarkers of epileptogenicity in MTLE.

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“…Since visual marking of HFOs is highly time-consuming, several algorithms for automatic or semi-automatic detection of HFOs have been proposed [11][12][13][14][15][16][17][18][19]. While earlier detectors rely rather on thresholds in the time domain, a number of recent detectors also incorporate the frequency domain, which is computationally more demanding.…”

Section: Introductionmentioning

confidence: 99%

Human Intracranial High Frequency Oscillations (HFOs) Detected by Automatic Time-Frequency Analysis

Burnos¹,

Hilfiker²,

Sürücü³

et al. 2014

J Neurol Surg A Cent Eur Neurosurg

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Objectives: High frequency oscillations (HFOs) have been proposed as a new biomarker for epileptogenic tissue. The exact characteristics of clinically relevant HFOs and their detection are still to be defined. Methods:We propose a new method for HFO detection, which we have applied to six patient iEEGs. In a first stage, events of interest (EoIs) in the iEEG were defined by thresholds of energy and duration. To recognize HFOs among the EoIs, in a second stage the iEEG was Stockwell-transformed into the time-frequency domain, and the instantaneous power spectrum was parameterized. The parameters were optimized for HFO detection in patient 1 and tested in patients 2-5. Channels were ranked by HFO rate and those with rate above half maximum constituted the HFO area. The seizure onset zone (SOZ) served as gold standard. Results:The detector distinguished HFOs from artifacts and other EEG activity such as interictal epileptiform spikes. Computation took few minutes. We found HFOs with relevant power at frequencies also below the 80-500 Hz band, which is conventionally associated with HFOs. The HFO area overlapped with the SOZ with good specificity . 90% for five patients and one patient was re-operated. The performance of the detector was compared to two well-known detectors.Conclusions: Compared to methods detecting energy changes in filtered signals, our second stage -analysis in the timefrequency domain -discards spurious detections caused by artifacts or sharp epileptic activity and improves the detection of HFOs. The fast computation and reasonable accuracy hold promise for the diagnostic value of the detector.

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A comparison between automated detection methods of high-frequency oscillations (80–500Hz) during seizures

Cited by 38 publications

References 16 publications

KCC2 function modulates in vitro ictogenesis

KCC2 function modulates in vitro ictogenesis

Dynamics of interictal spikes and high-frequency oscillations during epileptogenesis in temporal lobe epilepsy

Human Intracranial High Frequency Oscillations (HFOs) Detected by Automatic Time-Frequency Analysis

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