Ictal and interictal high frequency oscillations in patients with focal epilepsy

Zijlmans, Maeike; Jacobs, Julia; Kahn, Yusuf U.; Zelmann, Rina; Dubeau, François; Gotman, Jean

doi:10.1016/j.clinph.2010.09.021

Cited by 158 publications

(139 citation statements)

References 34 publications

Supporting

Mentioning

128

Contrasting

Unclassified

Order By: Relevance

“…Bragin et al (2005) also found that HFOs increase in amplitude, duration, and frequency in the dentate gyrus at the onset of seizures occurring spontaneously in vivo in epileptic rats that have received a unilateral hippocampal injection of kainic acid. In keeping with these experimental data, Zijlmans et al (2011) recently observed an increase in the percentage of time occupied by HFOs during the transition from preictal to ictal activity in epileptic patients, using time windows of 10 s before and 5 s after seizure onset; however, no significant increase in HFOs could be identified 1, 5, and 15 min before seizure onset in another clinical study (Jacobs et al, 2009).…”

Section: Introductionmentioning

confidence: 63%

Two Seizure-Onset Types Reveal Specific Patterns of High-Frequency Oscillations in a Model of Temporal Lobe Epilepsy

2012

View full text Add to dashboard Cite

High-frequencyoscillations(HFOs;80 -500Hz)arethoughttomirrorthepathophysiologicalchangesoccurringinepilepticbrains.However,the distribution of HFOs during seizures remains undefined. Here, we recorded from the hippocampal CA3 subfield, subiculum, entorhinal cortex, and dentate gyrus to quantify the occurrence of ripples (80 -200 Hz) and fast ripples (250 -500 Hz) during low-voltage fast-onset (LVF) and hypersynchronous-onset (HYP) seizures in the rat pilocarpine model of temporal lobe epilepsy. We discovered in LVF seizures that (1) progressionfrompreictaltoictalactivitywascharacterizedinseizure-onsetzonesbyanincreaseofrippleratesthatwerehigherwhencomparedwithfast ripple rates and (2) ripple rates during the ictal period were higher compared with fast ripple rates in seizure-onset zones and later in regions of secondary spread. In contrast, we found in HYP seizures that (1) fast ripple rates increased during the preictal period and were higher compared with ripple rates in both seizure-onset zones and in regions of secondary spread and (2) they were still higher compared with ripple rates in both seizure-onset zones and regions of secondary spread during the ictal period. Our findings demonstrate that ripples and fast ripples show distinct time-and region-specific patterns during LVF and HYP seizures, thus suggesting that they play specific roles in ictogenesis.

show abstract

Section: Introductionmentioning

confidence: 63%

Two Seizure-Onset Types Reveal Specific Patterns of High-Frequency Oscillations in a Model of Temporal Lobe Epilepsy

2012

View full text Add to dashboard Cite

show abstract

“…Several studies have examined the pre-ictal and ictal changes of HFOs [4,35,36]. The rate of HFOs has been found to increase a few seconds before seizure onset [35] and its distribution remains largely confined to the same epileptogenic area during both the interictal and ictal periods, whereas spikes are more widespread during seizures than in the interictal period [35]. An increase in HFO rate or power has been found in many other studies [4,37,38].…”

Section: High-frequency Oscillationsmentioning

confidence: 99%

“…Fast ripples have also been proposed to emerge from outof-phase firing within small groups of neurons, perhaps through coupling via axonal gap junctions [34]. Several studies have examined the pre-ictal and ictal changes of HFOs [4,35,36]. The rate of HFOs has been found to increase a few seconds before seizure onset [35] and its distribution remains largely confined to the same epileptogenic area during both the interictal and ictal periods, whereas spikes are more widespread during seizures than in the interictal period [35].…”

Section: High-frequency Oscillationsmentioning

confidence: 99%

Advances of Intracranial Electroencephalography in Localizing the Epileptogenic Zone

Jin

Wang

2016

Neurosci. Bull.

View full text Add to dashboard Cite

Intracranial electroencephalography (iEEG) provides the best precision in estimating the location and boundary of an epileptogenic zone. Analysis of iEEG in the routine EEG frequency range (0.5-70 Hz) remains the basis in clinical practice. Low-voltage fast activity is the most commonly reported ictal onset pattern in neocortical epilepsy, and low-frequency high-amplitude repetitive spiking is the most commonly reported ictal onset pattern in mesial temporal lobe epilepsy. Recent studies using wideband EEG recording have demonstrated that examining higher (80-1000 Hz) and lower (0.016-0.5 Hz) EEG frequencies can provide additional diagnostic information and help to improve the surgical outcome. In addition, novel computational techniques of iEEG signal analysis have provided new insights into the epileptic network. Here, we review some of these recent advances. Although these sophisticated and advanced techniques of iEEG analysis show promise in localizing the epileptogenic zone, their utility needs to be further validated in larger studies.

show abstract

“…It has been suggested that HFOs increase preictally and the number of HFOs increases a few seconds before seizure onset [6,12]. The number of HFOs during the ictal period is higher than the preictal period and is longer in duration [7]. It is important to note that the HFO oscillations are subgroup of HF activities and the intention of this work is to exploit automatic seizure detection through HF activities.…”

Section: Introductionmentioning

confidence: 99%

“…High Frequency (HF) activities which consist of high frequency oscillations (HFOs) and other activities above 80 Hz are visible in many seizures and occur from the very onset [6,7]. HFOs are grouped into ripples (80-250 Hz) and fast ripple (250-500 Hz) and have been associated to seizure genesis [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Automatic seizure detection in SEEG using high frequency activities in wavelet domain

Ayoubian¹,

Lacoma²,

Gotman³

2013

Medical Engineering & Physics

View full text Add to dashboard Cite

Existing automatic detection techniques show high sensitivity and moderate specificity, and detect seizures a relatively long time after onset. High frequency (80-500 Hz) activity has recently been shown to be prominent in the intracranial EEG of epileptic patients but has not been used in seizure detection. The purpose of this study is to investigate if these frequencies can contribute to seizure detection. The system was designed using 30 h of intracranial EEG, including 15 seizures in 15 patients. Wavelet decomposition, feature extraction, adaptive thresholding and artifact removal were employed in training data. An EMG removal algorithm was developed based on two features: Lack of correlation between frequency bands and energy-spread in frequency. Results based on the analysis of testing data (36 h of intracranial EEG, including 18 seizures) show a sensitivity of 72%, a false detection of 0.7/h and a median delay of 5.7 s. Missed seizures originated mainly from seizures with subtle or absent high frequencies or from EMG removal procedures. False detections were mainly due to weak EMG or interictal high frequency activities. The system performed sufficiently well to be considered for clinical use, despite the exclusive use of frequencies not usually considered in clinical interpretation. High frequencies have the potential to contribute significantly to the detection of epileptic seizures.

show abstract

Ictal and interictal high frequency oscillations in patients with focal epilepsy

Cited by 158 publications

References 34 publications

Two Seizure-Onset Types Reveal Specific Patterns of High-Frequency Oscillations in a Model of Temporal Lobe Epilepsy

Two Seizure-Onset Types Reveal Specific Patterns of High-Frequency Oscillations in a Model of Temporal Lobe Epilepsy

Advances of Intracranial Electroencephalography in Localizing the Epileptogenic Zone

Automatic seizure detection in SEEG using high frequency activities in wavelet domain

Contact Info

Product

Resources

About