High‐frequency oscillations mirror severity of human temporal lobe seizures (original) (raw)
Related papers
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Studies on intracranial electroencephalography (icEEG) recordings of patients with drug resistant epilepsy (DRE) show that epilepsy biomarkers propagate in time across brain areas. Here, we propose a novel method that estimates critical features of these propagations for different epilepsy biomarkers (spikes, ripples, and fast ripples), and assess their common onset as a reliable biomarker of the epileptogenic zone (EZ). For each biomarker, an automatic algorithm ranked the icEEG electrodes according to their timing occurrence in propagations and finally dichotomized them as onset or spread. We validated our algorithm on icEEG recordings of 8 children with DRE having a good surgical outcome (Engel score = 1). We estimated the overlap of the onset, spread, and entire zone of propagation with the resection (RZ) and the seizure onset zone (SOZ). Spike and ripple propagations were seen in all patients, whereas fast ripple propagations were seen in 6 patients. Spike, ripple, and fast ripple propagations had a mean duration of 28.3 ± 24.3 ms, 38.7 ± 37 ms, and 25 ± 14 ms respectively. Onset electrodes predicted the RZ and SOZ with higher specificity compared to the entire zone for all three biomarkers (p<0.05). Overlap of spike and ripple onsets presented a higher specificity than each separate biomarker onset: for the SOZ, the onsets overlap was more specific (97.89 ± 2.36) than the ripple onset (p=0.031); for the RZ, the onsets overlap was more specific (98.48 ± 1.5) than the spike onset (p=0.016). Yet, the entire zone for spike and ripple propagations predicted the RZ with higher sensitivity compared to each biomarker's onset (or spread) (p<0.05). We present, for the first time, preliminary evidence from icEEG data that fast ripples propagate in time across large areas of the brain. The onsets overlap of spike and ripple propagations constitutes an extremely specific (but not sensitive) biomarker of the EZ, compared to areas of spread (and entire areas) in propagation. Clinical Relevance-Our novel method can identify propagation events of epilepsy biomarkers, quantify their features, and delineate their overlapping onset, which constitutes an extremely specific biomarker of the EZ and may benefit children with DRE undergoing epilepsy neurosurgery.
Interictal scalp fast oscillations as a marker of the seizure onset zone
Neurology, 2011
Objective: This study aims to identify if oscillations at frequencies higher than the traditional EEG can be recorded on the scalp EEG of patients with focal epilepsy and to analyze the association of these oscillations with interictal discharges and the seizure onset zone (SOZ).
Seizure-european Journal of Epilepsy, 2020
Efforts to improve epilepsy surgery outcomes have led to increased interest in the study of electroencephalographic oscillations outside the conventional EEG bands. These include fast activity above the gamma band, known as high frequency oscillations (HFOs), and infraslow activity (ISA) below the delta band, sometimes referred to as direct current (DC) or ictal baseline shifts (IBS). HFOs in particular have been extensively studied as potential biomarkers for epileptogenic tissue in light of evidence showing that resection of brain tissue containing HFOs is associated with good surgical outcomes. Not all HFOs are conclusively pathological, however, as they can be recorded in nonepileptic tissue and induced by cognitive, visual, or motor tasks. Consequently, efforts to distinguish between pathological and physiological HFOs have identified several traits specific to pathological HFOs, such as coupling with interictal spikes, association with delta waves, and stereotypical morphologies. On the opposite end of the EEG spectrum, sub-delta oscillations have been shown to colocalize with the seizure onset zones (SOZ) and appear in a narrower spatial distribution than activity in the conventional EEG frequency bands. In this report, we review studies that implicate HFOs and ISA in ictogenesis and discuss current limitations such as inter-observer variability and poor standardization of recording techniques. Furthermore, we propose that HFOs and ISA should be analyzed in addition to activity in the conventional EEG band during intracranial presurgical EEG monitoring to identify the best possible surgical margin. 2. Physiological and pathological HFOs HFOs are commonly divided into high gamma (80-150 Hz), ripples (80-250 Hz), fast ripples (FRs, 250-500 Hz), and very high-frequency oscillations (VHFOs, 500 Hz to 2 kHz). These ranges are somewhat
Epilepsia, 2016
Ripples (80-150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathologic ripple (pRipple) event. We quantified phase amplitude coupling (PAC) between epileptiform electroencephalography (EEG) spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by (1) a phasor transform that corresponds to the strength and rate of ripples coupled with spikes, and a (2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure-onset zone (SOZ). Both the phasor transform and ripple-triggered averaging methods s...
The Journal of neuroscience : the official journal of the Society for Neuroscience, 2012
High-frequency oscillations (HFOs; 80-500 Hz) are thought to mirror the pathophysiological changes occurring in epileptic brains. 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) progression from preictal to ictal activity was characterized in seizure-onset zones by an increase of ripple rates that were higher when compared with fast 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 co...
The Onset of Interictal Spike-Related Ripples Facilitates Detection of the Epileptogenic Zone
Frontiers in Neurology, 2021
Objective: Accurate estimation of the epileptogenic zone (EZ) is essential for favorable outcomes in epilepsy surgery. Conventional ictal electrocorticography (ECoG) onset is generally used to detect the EZ but is insufficient in achieving seizure-free outcomes. By contrast, high-frequency oscillations (HFOs) could be useful markers of the EZ. Hence, we aimed to detect the EZ using interictal spikes and investigated whether the onset area of interictal spike-related HFOs was within the EZ.Methods: The EZ is considered to be included in the resection area among patients with seizure-free outcomes after surgery. Using a complex demodulation technique, we developed a method to determine the onset channels of interictal spike-related ripples (HFOs of 80–200 Hz) and investigated whether they are within the resection area.Results: We retrospectively examined 12 serial patients who achieved seizure-free status after focal resection surgery. Using the method that we developed, we determined...
Local Generation of Fast Ripples in Epileptic Brain
The Journal of Neuroscience, 2002
Aperiodic high-frequency oscillations (Ͼ100 Hz) reflect a shortterm synchronization of neuronal electrical activity. It has been shown in the epileptic brain that spontaneous oscillations in the frequency range of 250-600 Hz reflect action potential population bursts of synchronously discharging neuronal clusters. These oscillations occur in the early stages of epileptogenesis in areas adjacent to the brain lesion and may trigger the formation of seizure-generating neuronal networks. We studied the extent of the area generating oscillations in the frequency range of 250-600 Hz [fast ripples (FRs)] in intrahippocampal kainic acid-treated rats with spontaneous seizures, by analyzing voltage versus depth profiles of FRs in hippocampal and parahippocampal areas in freely moving animals and by spatial mapping in hippocampal slice preparations in vitro. The strength of inhibition was compared in areas with and without FRs using a paired-pulse paradigm. The extent of the areas generating FRs did not exceed 1 mm 3. The areas generating FRs became broader after the application of the GABA A receptor antagonist bicuculline. Paired-pulse fast inhibition at 15-30 msec intervals was similar in areas generating FRs and areas not generating FRs. Our data illustrate that hypothesized clusters of highly interconnected neurons are capable of overcoming interneuron feedback inhibition, resulting in generation of epileptiform bursts, eventually leading to seizure activity.
Simultaneous MEG and EEG to detect ripples in people with focal epilepsy
Clinical Neurophysiology, 2019
h i g h l i g h t s Ripples in MEG and EEG provide complementary information. Ripples in MEG are less frequent but more specific for the region of interest than ripples in EEG. In sufficient numbers, ripples in EEG and MEG are (partially) concordant with the epileptic region. a b s t r a c t Objective: We studied ripples (80-250 Hz) simultaneously recorded in electroencephalography (EEG) and magnetoencephalography (MEG) to evaluate the differences. Methods: Simultaneous EEG and MEG were recorded in 30 patients with drug resistant focal epilepsy. Ripples were automatically detected and visually checked in virtual channels throughout the cortex. The number and location of ripples in EEG and MEG were compared to each other and to a region of interest (ROI) defined by clinically available information. Results: Eleven patients showed ripples in both MEG and EEG, 11 only in EEG and one only in MEG. Twenty-four percent of the ripples occurred simultaneously in EEG and MEG, 71% only in EEG, and 5% only in MEG. Three patients without spikes in EEG showed EEG ripples. Ripple localization was concordant with the ROI in 80% of patients with MEG ripples, as opposed to 62% full or partial concordance for EEG ripples. With the optimal threshold for localizing the ROI, sensitivity and specificity were more than 80%. Conclusions: Ripples in MEG are less frequent but more specific and sensitive for the region of interest than ripples in EEG. Ripples in EEG can exist without spikes in the EEG. Significance: Ripples in MEG and EEG provide complementary information.
Epilepsia, 2007
Purpose: To determine whether hippocampal sclerosis might form an anatomical substrate for pathological high-frequency oscillations in patients with temporal lobe epilepsy (TLE). Methods: Intracerebral wide bandwidth electroencephalogram was recorded in patients with medically intractable complex partial seizures. A computer-automated program detected interictal normal ripples (80-150 Hz) and pathologic fast ripples (FR, 151-500 Hz) from microelectrodes within hippocampus, entorhinal, and subicular cortices. Hippocampal MRI volumetric analysis and cell density measurements were correlated with rates of FR and ripple discharge. Results: In all 13 patients, higher rates of FR (p = 0.03) and ratios of FR to ripple discharges (p = 0.02) were observed in sites ipsilateral to seizure onset compared with rates within contralateral nonictal sites. Higher ratios of FR to ripple discharge were associated with smaller ipsilateral hippocampal volumes (p = 0.02) and lower fascia dentata (FD; p = 0.02) and Ammon's horn (p = 0.0005) neuron densities. While reduced FD and Ammon's horn neuron densities correlated with higher ratios of discharges, stepwise multiple regression analysis revealed that decreased neuron densities within CA1 and prosubiculum regions most strongly predicted ratios of FR to ripples (r 2 = 0.78, p = 0.008). Conclusions: In surgical patients with TLE, higher ratios of FR to ripple discharges are associated with histopathologic changes found in hippocampal sclerosis. These findings support the hypothesis that pathological alterations linked with hippocampal cell loss and synaptic reorganization promote FR and reduce ripple generation. KEY WORDS: Hippocampus-Atrophy-Ripple-Fast ripples. A number of studies in patients with medically intractable temporal lobe epilepsy (TLE) have reported the presence of interictal high-frequency oscillations within brain areas where seizures arise (Bragin et al., 1999a;
Alterations in Areas Generating Fast Ripples in an Animal Model of Temporal Lobe Epilepsy
2015
The molecular basis of epileptogenesis is poorly characterized. Studies in humans and animal models have identified an electrophysiological signature that precedes the onset of epilepsy, which has been termed fast ripples (FRs) based on its frequency. Multiple lines of evidence implicate regions generating FRs in epileptogenesis, and FRs appear to demarcate the seizure onset zone, suggesting a role in ictogenesis as well. We performed gene expression analysis comparing areas of the dentate gyrus that generate FRs to those that do not generate FRs in a well-characterized rat model of epilepsy. We identified a small cohort of genes that are differentially expressed in FR versus non-FR brain tissue and used quantitative PCR to validate some of those that modulate neuronal excitability. Gene expression network analysis demonstrated conservation of gene co-expression between non-FR and FR samples, but examination of gene connectivity revealed changes that were most pronounced in the cm-40 module, which contains several genes associated with synaptic function and the differentially expressed genes Kcna4, Kcnv1, and Npy1r that are down-regulated in FRs. We then demonstrate that the genes within the cm-40 module are regulated by seizure activity and enriched for the targets of the RNA binding protein Elavl4. Our data suggest that seizure activity induces co-expression of genes associated with synaptic transmission and that this pattern is attenuated in areas displaying FRs, implicating the failure of this mechanism in the generation of FRs.