Amplitude of high frequency oscillations as a biomarker of the seizure onset zone

ObjectiveStudies of high frequency oscillations (HFOs) in epilepsy have primarily tested the HFO rate as a biomarker of the seizure onset zone (SOZ), but the rate varies over time and is not robust for all individual subjects. As an alternative, we tested the performance of HFO amplitude as a potential SOZ biomarker using two automated detection algorithms.MethodHFOs were detected in intracranial electroencephalogram (iEEG) from 11 patients using a machine learning algorithm and a standard amplitude-based algorithm. For each detector, SOZ and non-SOZ channels were classified using the rate and amplitude of high frequency events, and performance was compared using receiver operating characteristic curves.ResultsThe amplitude of detected events was significantly higher in SOZ. Across subjects, amplitude more accurately classified SOZ/non-SOZ than rate (higher values of area under the ROC curve and sensitivity, and lower false positive rates). Moreover, amplitude was more consistent across segments of data, indicated by lower coefficient of variation.ConclusionAs an SOZ biomarker, HFO amplitude offers advantages over HFO rate: it exhibits higher classification accuracy, more consistency over time, and robustness to parameter changes.SignificanceThis biomarker has the potential to increase the generalizability of HFOs and facilitate clinical implementation as a tool for SOZ localization.     

Automatic 80-250Hz "ripple" high frequency oscillation detection in invasive subdural grid and strip recordings in epilepsy by a radial basis function neural network

ObjectiveRecent studies give evidence that high frequency oscillations (HFOs) in the range between 80 Hz and 500 Hz in invasive recordings of epilepsy patients have the potential to serve as reliable markers of epileptogenicity. This study presents an algorithm for automatic HFO detection.MethodsThe presented HFO detector uses a radial basis function neural network. Input features of the detector were energy, line length and instantaneous frequency. Visual marked “ripple” HFOs (80–250 Hz) of 3 patients were used to train the neural network, and a further 8 patients served for the detector evaluation.ResultsDetector sensitivity and specificity were 49.1% and 36.3%. The linear and rank correlation between visual and automatic marked “ripple” HFO counts over the channels were significant for all recordings. A reference detector based on the line length achieved a sensitivity of 35.4% and a specificity of 46.8%.ConclusionsAutomatic detections corresponded only partly to visual markings for single events but the relative distribution of brain regions displaying “ripple” HFO activity is reflected by the automated system.SignificanceThe detector allows the automatic evaluation of brain areas with high HFO frequency, which is of high relevance for the demarcation of the epileptogenic zone.     

Redaction of false high frequency oscillations due to muscle artifact improves specificity to epileptic tissue

ObjectiveHigh Frequency Oscillations (HFOs) are a promising biomarker of epilepsy. HFOs are typically acquired on intracranial electrodes, but contamination from muscle artifacts is still problematic in HFO analysis. This paper evaluates the effect of myogenic artifacts on intracranial HFO detection and how to remove them.MethodsIntracranial EEG was recorded in 31 patients. HFOs were detected for the entire recording using an automated algorithm. When available, simultaneous scalp EEG was used to identify periods of muscle artifact. Those markings were used to train an automated scalp EMG detector and an intracranial EMG detector. Specificity to epileptic tissue was evaluated by comparison with seizure onset zone and resected volume in patients with good outcome.ResultsEMG artifacts are frequent and produce large numbers of false HFOs, especially in the anterior temporal lobe. The scalp and intracranial EMG detectors both had high accuracy. Removing false HFOs improved specificity to epileptic tissue.ConclusionsEvaluation of HFOs requires accounting for the effect of muscle artifact. We present two tools that effectively mitigate the effect of muscle artifact on HFOs.SignificanceRemoving muscle artifacts improves the specificity of HFOs to epileptic tissue. Future HFO work should account for this effect, especially when using automated algorithms or when scalp electrodes are not present.     

High‐frequency oscillations: The state of clinical research

Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal high‐frequency oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It highlights the growing literature on the association between HFOs and postsurgical seizure outcome. A recent meta‐analysis confirmed a higher resection ratio for HFOs in seizure‐free versus non–seizure‐free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show high scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure frequency. The time‐consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer‐assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.     

Clinical Utility of Interictal High-Frequency Oscillations Recorded with Subdural Macroelectrodes in Partial Epilepsy

Background and Purpose

There is growing interest in high-frequency oscillations (HFO) as electrophysiological biomarkers of the epileptic brain. We evaluated the clinical utility of interictal HFO events, especially their occurrence rates, by comparing the spatial distribution with a clinically determined epileptogenic zone by using subdural macroelectrodes.

Methods

We obtained intracranial electroencephalogram data with a high temporal resolution (2000 Hz sampling rate, 0.05-500 Hz band-pass filter) from seven patients with medically refractory epilepsy. Three epochs of 5-minute, artifact-free data were selected randomly from the interictal period. HFO candidates were first detected by an automated algorithm and subsequently screened to discard false detections. Validated events were further categorized as fast ripple (FR) and ripple (R) according to their spectral profiles. The occurrence rate of HFOs was calculated for each electrode contact. An HFO events distribution map (EDM) was constructed for each patient to allow visualization of the spatial distribution of their HFO events.

Results

The subdural macroelectrodes were capable of detecting both R and FR events from the epileptic neocortex. The occurrence rate of HFO events, both FR and R, was significantly higher in the seizure onset zone (SOZ) than in other brain regions. Patient-specific HFO EDMs can facilitate the identification of the location of HFO-generating tissue, and comparison with findings from ictal recordings can provide additional useful information regarding the epileptogenic zone.

Conclusions

The distribution of interictal HFOs was reasonably consistent with the SOZ. The detection of HFO events and construction of spatial distribution maps appears to be useful for the presurgical mapping of the epileptogenic zone.     

Human and automated detection of high-frequency oscillations in clinical intracranial EEG recordings.

OBJECTIVE: Recent studies indicate that pathologic high-frequency oscillations (HFOs) are signatures of epileptogenic brain. Automated tools are required to characterize these events. We present a new algorithm tuned to detect HFOs from 30 to 85 Hz, and validate it against human expert electroencephalographers. METHODS: We randomly selected 28 3-min single-channel epochs of intracranial EEG (IEEG) from two patients. Three human reviewers and three automated detectors marked all records to identify candidate HFOs. Subsequently, human reviewers verified all markings. RESULTS: A total of 1330 events were collectively identified. The new method presented here achieved 89.7% accuracy against a consensus set of human expert markings. A one-way ANOVA determined no difference between the mean F-measures of the human reviewers and automated algorithm. Human kappa statistics (mean kappa=0.38) demonstrated marginal identification consistency, primarily due to false negative errors. CONCLUSIONS: We present an HFO detector that improves upon existing algorithms, and performs as well as human experts on our test data set. Validation of detector performance must be compared to more than one expert because of interrater variability. SIGNIFICANCE: This algorithm will be useful for analyzing large EEG databases to determine the pathophysiological significance of HFO events in human epileptic networks.     

Simultaneously recorded intracranial and scalp high frequency oscillations help identify patients with poor postsurgical seizure outcome

ObjectiveHigh frequency oscillations (HFO) between 80–500 Hz are markers of epileptic areas in intracranial and maybe also scalp EEG. We investigate simultaneous recordings of scalp and intracranial EEG and hypothesize that scalp HFOs provide important additional clinical information in the presurgical setting.MethodsSpikes and HFOs were visually identified in all intracranial scalp EEG channels. Analysis of correlation of event location between intracranial and scalp EEG as well as relationship between events and the SOZ and zone of surgical removal was performed.Results24 patients could be included, 23 showed spikes and 19 HFOs on scalp recordings. In 15/19 patients highest scalp HFO rate was located over the implantation side, with 13 patients having the highest scalp and intracranial HFO rate over the same region. 17 patients underwent surgery, 7 became seizure free. Patients with poor post-operative outcome showed significantly more regions with HFO than those with seizure free outcome.ConclusionsScalp HFOs are mostly located over the SOZ. Widespread scalp HFOs are indicative of a larger epileptic network and associated with poor postsurgical outcome.SignificanceAnalysis of scalp HFO add clinically important information about the extent of epileptic areas during presurgical simultaneous scalp and intracranial EEG recordings.     

Interictal high‐frequency oscillations (HFOs) as predictors of high frequency and conventional seizure onset zones

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.     

Update on the mechanisms and roles of high‐frequency oscillations in seizures and epileptic disorders

High‐frequency oscillations (HFOs) are a type of brain activity that is recorded from brain regions capable of generating seizures. Because of the close association of HFOs with epileptogenic tissue and ictogenesis, understanding their cellular and network mechanisms could provide valuable information about the organization of epileptogenic networks and how seizures emerge from the abnormal activity of these networks. In this review, we summarize the most recent advances in the field of HFOs and provide a critical evaluation of new observations within the context of already established knowledge. Recent improvements in recording technology and the introduction of optogenetics into epilepsy research have intensified experimental work on HFOs. Using advanced computer models, new cellular substrates of epileptic HFOs were identified and the role of specific neuronal subtypes in HFO genesis was determined. Traditionally, the pathogenesis of HFOs was explored mainly in patients with temporal lobe epilepsy and in animal models mimicking this condition. HFOs have also been reported to occur in other epileptic disorders and models such as neocortical epilepsy, genetically determined epilepsies, and infantile spasms, which further support the significance of HFOs in the pathophysiology of epilepsy. It is increasingly recognized that HFOs are generated by multiple mechanisms at both the cellular and network levels. Future studies on HFOs combining novel high‐resolution in vivo imaging techniques and precise control of neuronal behavior using optogenetics or chemogenetics will provide evidence about the causal role of HFOs in seizures and epileptogenesis. Detailed understanding of the pathophysiology of HFOs will propel better HFO classification and increase their information yield for clinical and diagnostic purposes.     

Interictal high-frequency oscillations (80-500 Hz) are an indicator of seizure onset areas independent of spikes in the human epileptic brain

Purpose: High‐frequency oscillations (HFOs) known as ripples (80–250 Hz) and fast ripples (250–500 Hz) can be recorded from macroelectrodes inserted in patients with intractable focal epilepsy. They are most likely linked to epileptogenesis and have been found in the seizure onset zone (SOZ) of human ictal and interictal recordings. HFOs occur frequently at the time of interictal spikes, but were also found independently. This study analyses the relationship between spikes and HFOs and the occurrence of HFOs in nonspiking channels. Methods: Intracerebral EEGs of 10 patients with intractable focal epilepsy were studied using macroelectrodes. Rates of HFOs within and outside spikes, the overlap between events, event durations, and the percentage of spikes carrying HFOs were calculated and compared according to anatomical localization, spiking activity, and relationship to the SOZ. Results: HFOs were found in all patients, significantly more within mesial temporal lobe structures than in neocortex. HFOs could be seen in spiking as well as nonspiking channels in all structures. Rates and durations of HFOs were significantly higher in the SOZ than outside. It was possible to establish a rate of HFOs to identify the SOZ with better sensitivity and specificity than with the rate of spikes. Discussion: HFOs occurred to a large extent independently of spikes. They are most frequent in mesial temporal structures. They are prominent in the SOZ and provide additional information on epileptogenicity independently of spikes. It was possible to identify the SOZ with a high specificity by looking at only 10 min of HFO activity.     

Dynamic changes of ictal high-frequency oscillations in neocortical epilepsy: using multiple band frequency analysis

PURPOSE: To characterize the spatial and temporal course of ictal high-frequency oscillations (HFOs) recorded by subdural EEG in children with intractable neocortical epilepsy. METHODS: We retrospectively studied nine children (four girls, five boys; 4-17 yr) who presented with intractable extrahippocampal localization-related epilepsy and who underwent extraoperative video subdural EEG (1000 Hz sampling rate) and cortical resection. We performed multiple band frequency analysis (MBFA) to evaluate the frequency, time course, and distribution of ictal HFOs. We compared ictal HFO changes before and after clinical onset and postsurgical seizure outcomes. RESULTS: Seventy-eight of 79 seizures showed HFOs. We observed wide-band HFOs ( approximately 250 Hz, approximately 120 electrodes) in six patients either with partial seizures alone (three patients) or with epileptic spasms (three patients). Three patients with partial seizures that secondarily generalized had wide-band HFOs ( approximately 170 Hz) before clinical onset and sustained narrow-band HFOs (60-164 Hz) with electrodecremental events after clinical onset ( approximately 28 electrodes). In four postoperatively seizure-free patients, more electrodes recorded higher-frequency HFOs inside the resection area than outside before and after clinical seizure onset. In five patients with residual seizures, electrodes recorded more HFOs that were of higher or equal frequency outside the surgical area than inside after clinical onset. CONCLUSION: For partial seizures alone and epileptic spasms, more electrodes recorded only wide-band HFOs; for partial seizures that secondarily generalized, fewer electrodes recorded wide-band HFOs, but in these seizures electrodes also recorded subsequent sustained narrow-band ictal HFOs. Resection of those brain regions having electrodes with ictal, higher HFOs resulted in postsurgical seizure-free outcomes.     

MEG detection of high frequency oscillations and intracranial-EEG validation in pediatric epilepsy surgery

ObjectiveTo assess the feasibility of automatically detecting high frequency oscillations (HFOs) in magnetoencephalography (MEG) recordings in a group of ten paediatric epilepsy surgery patients who had undergone intracranial electroencephalography (iEEG).MethodsA beamforming source-analysis method was used to construct virtual sensors and an automatic algorithm was applied to detect HFOs (80–250 Hz). We evaluated the concordance of MEG findings with the sources of iEEG HFOs, the clinically defined seizure onset zone (SOZ), the location of resected brain structures, and with post-operative outcome.ResultsIn 8/9 patients there was good concordance between the sources of MEG HFOs and iEEG HFOs and the SOZ. Significantly more HFOs were detected in iEEG relative to MEG t(71) = 2.85, p < .05. There was good concordance between sources of MEG HFOs and the resected area in patients with good and poor outcome, however HFOs were also detected outside of the resected area in patients with poor outcome.ConclusionOur findings demonstrate the feasibility of automatically detecting HFOs non-invasively in MEG recordings in paediatric patients, and confirm compatibility of results with invasive recordings.SignificanceThis approach provides support for the non-invasive detection of HFOs to aid surgical planning and potentially reduce the need for invasive monitoring, which is pertinent to paediatric patients.     

MEG correlates of epileptic high gamma oscillations in invasive EEG

In patients with pharmacoresistant focal epilepsy, we demonstrate that magnetoencephalography (MEG) detects spike‐locked and spike‐independent epileptic high gamma oscillations (HGOs) using combined MEG and invasive electroencephalography (iEEG) from subdural macroelectrodes. Six patients, who underwent presurgical workup for epilepsy surgery with preoperative simultaneous MEG and subdural iEEG recordings, were investigated. HGOs in iEEG were detected automatically and served as triggers for averaging and localization of simultaneous MEG data. iEEG‐HGOs were detected in all patients and MEG‐HGOs in five patients. HGOs were highly associated with epileptic networks and correctly identified seizure‐onset zones in five (MEG) and six patients (iEEG). Minimum‐norm source analysis of MEG data yielded concordant localizations. Noninvasive analysis of HGOs may allow investigation of epileptic networks independent of spikes and seizures. Determination of sensitivity and specificity, as well as development of MEG‐HGO analysis without the need of iEEG should be addressed in a larger study.     

Extrahippocampal high‐frequency oscillations during epileptogenesis

The current study aimed to investigate the spatial and temporal patterns of high‐frequency oscillations (HFOs) in the intra‐/extrahippocampal areas during epileptogenesis. Local field potentials were bilaterally recorded from hippocampus (CA1), thalamus, motor cortex, and prefrontal cortex in 13 rats before and after intrahippocampal kainic acid (KA) lesions. HFOs in the ripple (100‐200 Hz) and fast ripple (250‐500 Hz) ranges were detected and their rates were computed during different time periods (1‐5 weeks) after KA‐induced status epilepticus (SE). Recurrent spontaneous seizures were observed in 7 rats after SE, and the other 6 rats did not develop epilepsy. During the latent period, the rate of hippocampal HFOs increased at the ipsilateral site of the KA lesion in both groups, and the HFO rate was significantly higher in the animals that later developed epilepsy. Animals that later developed epilepsy also demonstrated widespread appearance of HFOs, in both the ripple and the fast ripple range, whereas animals that did not develop epilepsy only exhibited changes in the ipsilateral intrahippocampal HFO rate. This study demonstrates an association between an increased rate of widespread HFOs and the later development of epilepsy, suggesting the formation of large‐scale distributed pathological networks during epileptogenesis.     

Scalp EEG interictal high frequency oscillations as an objective biomarker of infantile spasms

ObjectiveTo investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms.MethodsWe retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80–500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3–4 Hz and 0.5–1 Hz as quantified with modulation indices (MIs).ResultsTwenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p < 0.001 by HFO rate; p < 0.01 by MIs at 3–4 Hz; p = 0.02 by MIs at 0.5–1 Hz). The presence of active spasms was predicted by the logistic regression models incorporating HFO-related metrics (AUC: 0.80–0.98) better than that incorporating hypsarrhythmia (AUC: 0.61). The predictive performance of the best model remained favorable (87.5% accuracy) after a cross-validation procedure.ConclusionsIncreased rate of HFOs and coupling between HFOs and SWA are associated with active epileptic spasms.SignificanceScalp-recorded HFOs may serve as an objective EEG biomarker for active epileptic spasms.     

Topographic movie of ictal high-frequency oscillations on the brain surface using subdural EEG in neocortical epilepsy

PURPOSE: To understand the rapid dynamic changes of ictal intracranial high-frequency oscillations (HFOs) in neocortical epilepsy. METHODS: We integrated multiple band frequency analysis and brain-surface topographic maps of HFOs from ictal subdural EEG (SDEEG) recordings. We used SDEEG to record partial seizures consisting of right-arm jerks with secondary generalization in a 17-year-old right-handed girl. We selected 20-s EEG sections that included preclinical seizure recordings. We averaged the HFO power between 60 and 120 Hz for 25 selected electrodes, made topographic maps from these averaged powers, and superimposed the maps on the brain-surface image. We filmed consecutive HFO maps at a 10-ms frame rate. RESULTS: Before clinical seizure onset, high-power HFOs emerged at the superior portion of the left precentral gyrus, then appeared in the middle of the left postcentral gyrus, and subsequently reverberated between both regions as well as the posterior portion of the left postcentral gyrus. Right-arm extension and facial grimacing started as the HFO power decreased. As generalized tonic-clonic seizures evolved, HFO power increased but remained within the central region. CONCLUSIONS: Topographic movies of intracranial HFOs on the brain surface allow visualization of the dynamic ictal changes in neocortical epilepsy.     

L-Type calcium channel blockade reduces network activity in human epileptic hypothalamic hamartoma tissue

Purpose: Human hypothalamic hamartomas (HHs) are associated with gelastic seizures, intrinsically epileptogenic, and notoriously refractory to medical therapy. We previously reported that the L‐type calcium channel antagonist nifedipine blocks spontaneous firing and γ‐aminobutyric acid (GABA)_A–induced depolarization of single cells in HH tissue slices. In this study, we examined whether blocking L‐type calcium channels attenuates emergent activity of HH neuronal networks. Methods: A high‐density multielectrode array was used to record extracellular signals from surgically resected HH tissue slices. High‐frequency oscillations (HFOs, ripples and fast ripples), field potentials, and multiunit activity (MUA) were studied (1) under normal and provoked [4‐aminopyridine (4‐AP)] conditions; and (2) following nifedipine treatment. Key Findings: Spontaneous activity occurred during normal artificial cerebrospinal fluid (aCSF) conditions. Nifedipine reduced the total number and duration of HFOs, abolished the association of HFOs with field potentials, and increased the inter‐HFO burst intervals. Notably, the number of active regions was decreased by 45 ± 9% (mean ± SEM) after nifedipine treatment. When considering electrodes that detected activity, nifedipine increased MUA in 58% of electrodes and reduced the number of field potentials in 67% of electrodes. Provocation with 4‐AP increased the number of events and, as the number of electrodes that detected activity increased 248 ± 62%, promoted tissue‐wide propagation of activity. During provocation with 4‐AP, nifedipine effectively reduced HFOs, the association of HFOs with field potentials, field potentials, MUA, and the number of active regions, and limited propagation. Significance: This is the first study to report (1) the presence of HFOs in human subcortical epileptic brain tissue in vitro; (2) the modulation of “pathologic” high‐frequency oscillations (i.e., fast ripples) in human epileptic tissue by L‐type calcium channel blockers; and (3) the modulation of network physiology and synchrony of emergent activity in human epileptic tissue following blockade of L‐type calcium channels. Attenuation of activity in HH tissue during normal and provoked conditions supports a potential therapeutic usefulness of L‐type calcium channel blockers in epileptic patients with HH.     

Topographic movie of intracranial ictal high-frequency oscillations with seizure semiology: epileptic network in Jacksonian seizures

Purpose: We developed a technique to produce images of dynamic changes in ictal high‐frequency oscillations (HFOs) >40 Hz recorded on subdural electroencephalography (EEG) that are time‐locked to the ictal EEG and ictal semiology video. We applied this technique to Jacksonian seizures to demonstrate ictal HFO propagation along the homunculus in the primary sensory‐motor cortex to visualize the underlying epileptic network. Methods: We analyzed intracranial ictal EEGs from two patients with intractable Jacksonian seizures who underwent epilepsy surgery. We calculated the degrees of increase in amplitude within 40–80, 80–200, and 200–300 Hz frequency bands compared to the interictal period and converted them into topographic movies projected onto the brain surface picture. We combined these data with the ictal EEGs and video of the patient demonstrating ictal semiology. Key Findings: The ictal HFOs began in the sensory cortex and appeared concomitantly with the sensory aura. They then propagated to the motor cortex at the same time that focal motor symptoms evolved. As the seizure progressed, the ictal HFOs spread or reverberated in the rolandic region. However, even when the seizure became secondarily generalized, the ictal HFOs were confined to the rolandic region. In both cases, there was increased amplitude of higher frequency bands during seizure initiation compared to seizure progression. Significance: This combined movie showed the ictal HFO propagation corresponding to the ictal semiology in Jacksonian seizures and revealed the epileptic network involved in seizure initiation and progression. This method may advance understanding of neural network activities relating to clinical seizure generation and propagation.     

Hippocampal high frequency oscillations in unilateral and bilateral mesial temporal lobe epilepsy

ObjectiveThe main aim of this study was to investigate the potential differences in terms of interictal high frequency oscillations (HFOs) between both hippocampi in unilateral (U-MTLE) and bilateral mesial temporal lobe epilepsy (B-MTLE).MethodsSixteen patients with MTLE underwent bilateral hippocampal depth electrode implantation as part of epilepsy surgery evaluation. Interictal HFOs were detected automatically. The analyses entail comparisons of the rates and spatial distributions of ripples and fast ripples (FR) in hippocampi and amygdalae, with respect to the eventual finding of hippocampal sclerosis (HS).ResultsIn U-MTLE, higher ripple and FR rates were found in the hippocampi ipsilateral to the seizure onset than in the contralateral hippocampi. Non-epileptic hippocampi in U-MTLE were distinguished by significantly lower ripple rate than in the remaining analyzed hippocampi. There were not differences between the hippocampi in B-MTLE. In the hippocampi with proven HS, higher FR rates were observed in the ventral than in the dorsal parts.ConclusionsNon-epileptic hippocampi in U-MTLE demonstrated significantly lower ripple rates than those epileptic in U-MTLE and B-MTLE.SignificanceLow interictal HFO occurrence might be considered as a marker of the non-epileptic hippocampi in MTLE.     

Influence of contact size on the detection of HFOs in human intracerebral EEG recordings

ObjectiveHigh frequency oscillations (HFOs) are brief electroencephalographic events associated with epileptic activity, and likely representing biological markers of the epileptogenic zone. HFOs are usually detected with intracranial EEG and detection is influenced by contact size. The size of commercially available intracerebral electrodes varies widely. This study assesses HFO detection rates from adjacent electrode contacts in human intracerebral recordings.MethodsIntracerebral recordings were collected from 11 patients undergoing stereoelectroencephalographic investigation using hybrid depth electrodes containing adjacent large (0.8 or 5 mm²) and small (0.2 or 0.3 mm²) contacts. HFOs were marked manually during 5-min tracings in 131 pairs of adjacent large and small contacts. HFO rates per minute and mean event durations were compared between adjacent contacts.ResultsA minimal but statistically significant advantage in ripple detection was found in a subgroup of large contacts. Otherwise, HFO rates and mean event durations were not statistically different between groups.ConclusionThe size of clinical contacts within the studied range did not influence HFO detection in a clinically relevant manner. Larger contacts provide a minimal advantage for ripple detection.SignificanceOur findings suggest that commercially available intracerebral electrodes with contacts between 0.2 and 5 mm² likely possess similar HFO detection abilities.