Quantitative interictal subdural EEG analyses in children with neocortical epilepsy

Benchmarking signal quality and spatiotemporal distribution of interictal spikes in prolonged human iEEG recordings using CorTec wireless brain interchange

Neuromodulation through implantable pulse generators (IPGs) represents an important treatment approach for neurological disorders. While the field has observed the success of state-of-the-art interventions, such as deep brain stimulation (DBS) or responsive neurostimulation (RNS), implantable systems face various technical challenges, including the restriction of recording from a limited number of brain sites, power management, and limited external access to the assessed neural data in a continuous fashion. To the best of our knowledge, for the first time in this study, we investigated the feasibility of recording human intracranial EEG (iEEG) using a benchtop version of the Brain Interchange (BIC) unit of CorTec, which is a portable, wireless, and externally powered implant with sensing and stimulation capabilities. We developed a MATLAB/SIMULINK-based rapid prototyping environment and a graphical user interface (GUI) to acquire and visualize the iEEG captured from all 32 channels of the BIC unit. We recorded prolonged iEEG (~ 24 h) from three human subjects with externalized depth leads using the BIC and commercially available clinical amplifiers simultaneously in the epilepsy monitoring unit (EMU). The iEEG signal quality of both streams was compared, and the results demonstrated a comparable power spectral density (PSD) in all the systems in the low-frequency band (< 80 Hz). However, notable differences were primarily observed above 100 Hz, where the clinical amplifiers were associated with lower noise floor (BIC-17 dB vs. clinical amplifiers <  - 25 dB). We employed an established spike detector to assess and compare the spike rates in each iEEG stream. We observed over 90% conformity between the spikes rates and their spatial distribution captured with BIC and clinical systems. Additionally, we quantified the packet loss characteristic in the iEEG signal during the wireless data transfer and conducted a series of simulations to compare the performance of different interpolation methods for recovering the missing packets in signals at different frequency bands. We noted that simple linear interpolation has the potential to recover the signal and reduce the noise floor with modest packet loss levels reaching up to 10%. Overall, our results indicate that while tethered clinical amplifiers exhibited noticeably better noise floor above 80 Hz, epileptic spikes can still be detected successfully in the iEEG recorded with the externally powered wireless BIC unit opening the road for future closed-loop neuromodulation applications with continuous access to brain activity.

Identifying sources of human interictal discharges with travelling wave and white matter propagation

Interictal epileptiform discharges have been shown to propagate from focal epileptogenic sources as travelling waves or through more rapid white matter conduction. We hypothesize that both modes of propagation are necessary to explain interictal discharge timing delays. We propose a method that, for the first time, incorporates both propagation modes to identify unique potential sources of interictal activity. We retrospectively analysed 38 focal epilepsy patients who underwent intracranial EEG recordings and diffusion-weighted imaging for epilepsy surgery evaluation. Interictal discharges were detected and localized to the most likely source based on relative delays in time of arrival across electrodes, incorporating travelling waves and white matter propagation. We assessed the influence of white matter propagation on distance of spread, timing and clinical interpretation of interictal activity. To evaluate accuracy, we compared our source localization results to earliest spiking regions to predict seizure outcomes. White matter propagation helps to explain the timing delays observed in interictal discharge sequences, underlying rapid and distant propagation. Sources identified based on differences in time of receipt of interictal discharges are often distinct from the leading electrode location. Receipt of activity propagating rapidly via white matter can occur earlier than more local activity propagating via slower cortical travelling waves. In our cohort, our source localization approach was more accurate in predicting seizure outcomes than the leading electrode location. Inclusion of white matter in addition to travelling wave propagation in our model of discharge spread did not improve overall accuracy but allowed for identification of unique and at times distant potential sources of activity, particularly in patients with persistent postoperative seizures. Since distant white matter propagation can occur more rapidly than local travelling wave propagation, combined modes of propagation within an interictal discharge sequence can decouple the commonly assumed relationship between spike timing and distance from the source. Our findings thus highlight the clinical importance of recognizing the presence of dual modes of propagation during interictal discharges, as this may be a cause of clinical mislocalization.

Effect of Sevoflurane Anesthesia on Intraoperative Spikes, High-Frequency Oscillations, and Phase-Amplitude Coupling in MRI-Normal Hippocampus

INTRODUCTION

The purpose of this study was to determine the effect of sevoflurane anesthesia on spikes, high-frequency oscillations (HFOs), and phase-amplitude coupling using a modulation index in MRI-normal hippocampus, with the aim of evaluating the utility of intraoperative electrocorticography in identifying the epileptogenic hippocampus during sevoflurane administration.

METHODS

Eleven patients with intractable temporal lobe epilepsy with a normal hippocampus on MRI underwent extra-operative electrocorticography evaluation. Patients were assigned to the Ictal (+) or Ictal (-) group depending on whether the parahippocampal gyrus was included in the seizure onset zone. Intraoperative electrocorticography was performed under 0.5 and 1.5 minimum alveolar concentration of sevoflurane. The rates of spikes, ripples, fast ripples (FRs), ripples on spikes, FRs on spikes, and MI HFO(3-4 Hz) were evaluated.

RESULTS

During the intraoperative electrocorticography procedure, sevoflurane administration was found to significantly increase the rate of spikes, ripples on spikes, fast ripples on spikes, and MI HFO(3-4 Hz) in the Ictal (+) group (P < 0.01). By contrast, the Ictal (-) group exhibited a paradoxical increase in the rate of ripples and fast ripple (P < 0.05).

CONCLUSIONS

Our findings indicate that the administration of sevoflurane during intraoperative electrocorticography in patients with MRI-normal hippocampus can lead to a dose-dependent enhancement of epileptic biomarkers (spikes, ripples on spikes, fast ripples on spikes, and MI (HFO 3-4)) in the epileptogenic hippocampus, while paradoxically increasing the rate of ripples and fast ripple in the nonepileptogenic hippocampus. These results have significant implications for the identification of the MRI-normal hippocampus that requires surgical intervention and preservation of the nonepileptogenic hippocampus.

High-rate leading spikes in propagating spike sequences predict seizure outcome in surgical patients with temporal lobe epilepsy

Inter-ictal spikes aid in the diagnosis of epilepsy and in planning surgery of medication-resistant epilepsy. However, the localizing information from spikes can be unreliable because spikes can propagate, and the burden of spikes, often assessed as a rate, does not always correlate with the seizure onset zone or seizure outcome. Recent work indicates identifying where spikes regularly emerge and spread could localize the seizure network. Thus, the current study sought to better understand where and how rates of single and coupled spikes, and especially brain regions with high-rate and leading spike of a propagating sequence, informs the extent of the seizure network. In 37 patients with medication-resistant temporal lobe seizures, who had surgery to treat their seizure disorder, an algorithm detected spikes in the pre-surgical depth inter-ictal EEG. A separate algorithm detected spike propagation sequences and identified the location of leading and downstream spikes in each sequence. We analysed the rate and power of single spikes on each electrode and coupled spikes between pairs of electrodes, and the proportion of sites with high-rate, leading spikes in relation to the seizure onset zone of patients seizure free (n = 19) and those with continuing seizures (n = 18). We found increased rates of single spikes in mesial temporal seizure onset zone (ANOVA, P < 0.001, η2 = 0.138), and increased rates of coupled spikes within, but not between, mesial-, lateral- and extra-temporal seizure onset zone of patients with continuing seizures (P < 0.001; η2 = 0.195, 0.113 and 0.102, respectively). In these same patients, there was a higher proportion of brain regions with high-rate leaders, and each sequence contained a greater number of spikes that propagated with a higher efficiency over a longer distance outside the seizure onset zone than patients seizure free (Wilcoxon, P = 0.0172). The proportion of high-rate leaders in and outside the seizure onset zone could predict seizure outcome with area under curve = 0.699, but not rates of single or coupled spikes (0.514 and 0.566). Rates of coupled spikes to a greater extent than single spikes localize the seizure onset zone and provide evidence for inter-ictal functional segregation, which could be an adaptation to avert seizures. Spike rates, however, have little value in predicting seizure outcome. High-rate spike sites leading propagation could represent sources of spikes that are important components of an efficient seizure network beyond the clinical seizure onset zone, and like the seizure onset zone these, too, need to be removed, disconnected or stimulated to increase the likelihood for seizure control.

Interictal discharges in the human brain are travelling waves arising from an epileptogenic source

While seizure activity may be electrographically widespread, increasing evidence has suggested that ictal discharges may in fact represent travelling waves propagated from a focal seizure source. Interictal epileptiform discharges (IEDs) are an electrographic manifestation of excessive hypersynchronization of cortical activity that occur between seizures and are considered a marker of potentially epileptogenic tissue. The precise relationship between brain regions demonstrating IEDs and those involved in seizure onset, however, remains poorly understood. Here, we hypothesize that IEDs likewise reflect the receipt of travelling waves propagated from the same regions which give rise to seizures. Forty patients from our institution who underwent invasive monitoring for epilepsy, proceeded to surgery and had at least one year of follow-up were included in our study. Interictal epileptiform discharges were detected using custom software, validated by a clinical epileptologist. We show that IEDs reach electrodes in sequences with a consistent temporal ordering, and this ordering matches the timing of receipt of ictal discharges, suggesting that both types of discharges spread as travelling waves. We use a novel approach for localization of ictal discharges, in which time differences of discharge receipt at nearby electrodes are used to compute source location; similar algorithms have been used in acoustics and geophysics. We find that interictal discharges co-localize with ictal discharges. Moreover, interictal discharges tend to localize to the resection territory in patients with good surgical outcome and outside of the resection territory in patients with poor outcome. The seizure source may originate at, and also travel to, spatially distinct IED foci. Our data provide evidence that interictal discharges may represent travelling waves of pathological activity that are similar to their ictal counterparts, and that both ictal and interictal discharges emerge from common epileptogenic brain regions. Our findings have important clinical implications, as they suggest that seizure source localizations may be derived from interictal discharges, which are much more frequent than seizures.

Spike patterns surrounding sleep and seizures localize the seizure-onset zone in focal epilepsy

OBJECTIVE

Interictal spikes help localize seizure generators as part of surgical planning for drug-resistant epilepsy. However, there are often multiple spike populations whose frequencies change over time, influenced by brain state. Understanding state changes in spike rates will improve our ability to use spikes for surgical planning. Our goal was to determine the effect of sleep and seizures on interictal spikes, and to use sleep and seizure-related changes in spikes to localize the seizure-onset zone (SOZ).

METHODS

We performed a retrospective analysis of intracranial electroencephalography (EEG) data from patients with focal epilepsy. We automatically detected interictal spikes and we classified different time periods as awake or asleep based on the ratio of alpha to delta power, with a secondary analysis using the recently published SleepSEEG algorithm. We analyzed spike rates surrounding sleep and seizures. We developed a model to localize the SOZ using state-dependent spike rates.

RESULTS

We analyzed data from 101 patients (54 women, age range 16-69). The normalized alpha-delta power ratio accurately classified wake from sleep periods (area under the curve = .90). Spikes were more frequent in sleep than wakefulness and in the post-ictal compared to the pre-ictal state. Patients with temporal lobe epilepsy had a greater wake-to-sleep and pre- to post-ictal spike rate increase compared to patients with extra-temporal epilepsy. A machine-learning classifier incorporating state-dependent spike rates accurately identified the SOZ (area under the curve = .83). Spike rates tended to be higher and better localize the seizure-onset zone in non-rapid eye movement (NREM) sleep than in wake or REM sleep.

SIGNIFICANCE

The change in spike rates surrounding sleep and seizures differs between temporal and extra-temporal lobe epilepsy. Spikes are more frequent and better localize the SOZ in sleep, particularly in NREM sleep. Quantitative analysis of spikes may provide useful ancillary data to localize the SOZ and improve surgical planning.

Clinical Yield of Electromagnetic Source Imaging and Hemodynamic Responses in Epilepsy: Validation With Intracerebral Data

BACKGROUND AND OBJECTIVES

Accurate delineation of the seizure-onset zone (SOZ) in focal drug-resistant epilepsy often requires stereo-EEG (SEEG) recordings. Our aims were to propose a truly objective and quantitative comparison between EEG/magnetoencephalography (MEG) source imaging (EMSI), EEG/fMRI responses for similar spikes with primary irritative zone (PIZ) and SOZ defined by SEEG and to evaluate the value of EMSI and EEG/fMRI to predict postsurgical outcome.

METHODS

We identified patients with drug-resistant epilepsy who underwent EEG/MEG, EEG/fMRI, and subsequent SEEG at the Epilepsy Service from the Montreal Neurological Institute and Hospital. We quantified multimodal concordance within the SEEG channel space as spatial overlap with PIZ/SOZ and distances to the spike-onset, spike maximum amplitude and seizure core intracerebral channels by applying a new methodology consisting of converting EMSI results into SEEG electrical potentials (EMSIe-SEEG) and projecting the most significant fMRI response on the SEEG channels (fMRIp-SEEG). Spatial overlaps with PIZ/SOZ (AUCPIZ, AUCSOZ) were assessed by using the area under the receiver operating characteristic curve (AUC). Here, AUC represents the probability that a randomly picked active contact exhibited higher amplitude when located inside the spatial reference than outside.

RESULTS

Seventeen patients were included. Mean spatial overlaps with the PIZ and SOZ were 0.71 and 0.65 for EMSIe-SEEG and 0.57 and 0.62 for fMRIp-SEEG. Good EMSIe-SEEG spatial overlap with the PIZ was associated with smaller distance from the maximum EMSIe-SEEG contact to the spike maximum amplitude channel (median distance 14 mm). Conversely, good fMRIp-SEEG spatial overlap with the SOZ was associated with smaller distances from the maximum fMRIp-SEEG contact to the spike-onset and seizure core channels (median distances 10 and 5 mm, respectively). Surgical outcomes were correctly predicted by EEG/MEG in 12 of 15 (80%) patients and EEG/fMRI in 6 of 11(54%) patients.

DISCUSSION

With the use of a unique quantitative approach estimating EMSI and fMRI results in the reference SEEG channel space, EEG/MEG and EEG/fMRI accurately localized the SOZ and the PIZ. Precisely, EEG/MEG more accurately localized the PIZ, whereas EEG/fMRI was more sensitive to the SOZ. Both neuroimaging techniques provide complementary localization that can help guide SEEG implantation and select good candidates for surgery.

Sevoflurane-based enhancement of phase-amplitude coupling and localization of the epileptogenic zone

OBJECTIVE

Phase-amplitude coupling between high-frequency (≥150 Hz) and delta (3-4 Hz) oscillations - modulation index (MI) - is a promising, objective biomarker of epileptogenicity. We determined whether sevoflurane anesthesia preferentially enhances this metric within the epileptogenic zone.

METHODS

This is an observational study of intraoperative electrocorticography data from 621 electrodes chronically implanted into eight patients with drug-resistant, focal epilepsy. All patients were anesthetized with sevoflurane during resective surgery, which subsequently resulted in seizure control. We classified 'removed' and 'retained' brain sites as epileptogenic and non-epileptogenic, respectively. Mixed model analysis determined which anesthetic stage optimized MI-based classification of epileptogenic sites.

RESULTS

MI increased as a function of anesthetic stage, ranging from baseline (i.e., oxygen alone) to 2.0 minimum alveolar concentration (MAC) of sevoflurane, preferentially at sites showing higher initial MI values. This phenomenon was accentuated just prior to sevoflurane reaching 2.0 MAC, at which time, the odds of a site being classified as epileptogenic were enhanced by 86.6 times for every increase of 1.0 MI.

CONCLUSIONS

Intraoperative MI best localized the epileptogenic zone immediately before sevoflurane reaching 2.0 MAC in this small cohort of patients.

SIGNIFICANCE

Prospective, large cohort studies are warranted to determine whether sevoflurane anesthesia can reduce the need for extraoperative, invasive evaluation.

The Onset of Interictal Spike-Related Ripples Facilitates Detection of the Epileptogenic Zone

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 the onset channels of interictal spike-related ripples and found that for all 12 patients, they were among the resection channels. The onset frequencies of ripples were in the range of 80-150 Hz. However, the ictal onset channels (evaluated based on ictal ECoG patterns) and ripple onset channels coincided in only 3 of 12 patients. Conclusions: Determining the onset area of interictal spike-related ripples could facilitate EZ estimation. This simple method that utilizes interictal ECoG may aid in preoperative evaluation and improve epilepsy surgery outcomes.

Dynamic tractography-based localization of spike sources and animation of spike propagations

OBJECTIVE

This study was undertaken to build and validate a novel dynamic tractography-based model for localizing interictal spike sources and visualizing monosynaptic spike propagations through the white matter.

METHODS

This cross-sectional study investigated 1900 spike events recorded in 19 patients with drug-resistant temporal lobe epilepsy (TLE) who underwent extraoperative intracranial electroencephalography (iEEG) and resective surgery. Twelve patients had mesial TLE (mTLE) without a magnetic resonance imaging-visible mass lesion. The remaining seven had a mass lesion in the temporal lobe neocortex. We identified the leading and lagging sites, defined as those initially and subsequently (but within ≤50 ms) showing spike-related augmentation of broadband iEEG activity. In each patient, we estimated the sources of 100 spike discharges using the latencies at given electrode sites and diffusion-weighted imaging-based streamline length measures. We determined whether the spatial relationship between the estimated spike sources and resection was associated with postoperative seizure outcomes. We generated videos presenting the spatiotemporal change of spike-related fiber activation sites by estimating the propagation velocity using the streamline length and spike latency measures.

RESULTS

The spike propagation velocity from the source was 1.03 mm/ms on average (95% confidence interval = .91-1.15) across 133 tracts noted in the 19 patients. The estimated spike sources in mTLE patients with International League Against Epilepsy Class 1 outcome were more likely to be in the resected area (83.9% vs. 72.3%, φ = .137, p < .001) and in the medial temporal lobe region (80.5% vs. 72.5%, φ = .090, p = .002) than those associated with the Class ≥2 outcomes. The resulting video successfully animated spike propagations, which were confined within the temporal lobe in mTLE but involved extratemporal lobe areas in lesional TLE.

SIGNIFICANCE

We have, for the first time, provided dynamic tractography visualizing the spatiotemporal profiles of rapid propagations of interictal spikes through the white matter. Dynamic tractography has the potential to serve as a unique epilepsy biomarker.

Modulation of locomotor behaviors by location-specific epileptic spiking and seizures

INTRODUCTION

Epilepsy is a debilitating neurological condition characterized by spontaneous seizures as well as significant comorbid behavioral abnormalities. In addition to seizures, epileptic patients exhibit interictal spikes far more frequently than seizures, often, but not always observed in the same brain areas. The exact relationship between spiking and seizures as well as their respective effects on behavior are not well understood. In fact, spiking without overt seizures is seen in various psychiatric conditions including attention-deficit hyperactivity disorder.

METHODS

In order to study the effects of spiking and seizures on behavior in an epileptic animal model, we used long-term video-electroencephalography recordings at six cortical recording sites together with behavioral activity monitoring. Animals received unilateral injections of tetanus toxin into either the somatosensory or motor cortex.

RESULTS

Somatosensory cortex-injected animals developed progressive spiking ipsilateral to the injection site, while those receiving the injection into the motor cortex developed mostly contralateral spiking and spontaneous seizures. Animals with spiking but no seizures displayed a hyperactive phenotype, while animals with both spiking and seizures displayed a hypoactive phenotype. Not all spikes were equivalent as spike location strongly correlated with distinct locomotor behaviors including ambulatory distance, vertical movements, and rotatory movement.

CONCLUSIONS

Together, our results demonstrate relationships between brain region-specific spiking, seizures, and behaviors in rodents that could translate into a better understanding for patients with epileptic behavioral comorbidities and other neuropsychiatric disorders.

Quantitative EEG biomarkers for epilepsy and their relation to chemical biomarkers

The electroencephalogram (EEG) is the most important method to diagnose epilepsy. In clinical settings, it is evaluated by experts who identify patterns visually. Quantitative EEG is the application of digital signal processing to clinical recordings in order to automatize diagnostic procedures, and to make patterns visible that are hidden to the human eye. The EEG is related to chemical biomarkers, as electrical activity is based on chemical signals. The most well-known chemical biomarkers are blood laboratory tests to identify seizures after they have happened. However, research on chemical biomarkers is much less extensive than research on quantitative EEG, and combined studies are rarely published, but highly warranted. Quantitative EEG is as old as the EEG itself, but still, the methods are not yet standard in clinical practice. The most evident application is an automation of manual work, but also a quantitative description and localization of interictal epileptiform events as well as seizures can reveal important hints for diagnosis and contribute to presurgical evaluation. In addition, the assessment of network characteristics and entropy measures were found to reveal important insights into epileptic brain activity. Application scenarios of quantitative EEG in epilepsy include seizure prediction, pharmaco-EEG, treatment monitoring, evaluation of cognition, and neurofeedback. The main challenges to quantitative EEG are poor reliability and poor generalizability of measures, as well as the need for individualization of procedures. A main hindrance for quantitative EEG to enter clinical routine is also that training is not yet part of standard curricula for clinical neurophysiologists.

Dynamic analysis of fMRI activation during epileptic spikes can help identify the seizure origin

OBJECTIVE

We use the dynamic electroencephalography-functional magnetic resonance imaging (EEG-fMRI) method to incorporate variability in the amplitude and field of the interictal epileptic discharges (IEDs) into the fMRI analysis. We ask whether IED variability analysis can (a) identify additional activated brain regions during the course of IEDs, not seen in standard analysis; and (b) demonstrate the origin and spread of epileptic activity. We explore whether these functional changes recapitulate the structural connections and propagation of epileptic activity during seizures.

METHODS

Seventeen patients with focal epilepsy and at least 30 IEDs of a single type during simultaneous EEG-fMRI were studied. IED variability and EEG source imaging (ESI) analysis extracted time-varying dynamic changes. General linear modeling (GLM) generated static functional maps. Dynamic maps were compared to static functional maps. The dynamic sequence from IED variability was compared to the ESI results. In a subset of patients, we investigated structural connections between active brain regions using diffusion-based fiber tractography.

RESULTS

IED variability distinguished the origin of epileptic activity from its propagation in 15 of 17 (88%) patients. This included two cases where no result was obtained from the standard GLM analysis. In both of these cases, IED variability revealed activation in line with the presumed epileptic focus. Two cases showed no result from either method. Both had very high spike rates associated with dysplasia in the postcentral gyrus. In all 15 cases with dynamic activation, the observed dynamics were concordant with ESI. Fiber tractography identified specific white matter pathways between brain regions that were active at IED onset and propagation.

SIGNIFICANCE

Dynamic techniques involving IED variability can provide additional power for EEG-fMRI analysis, compared to standard analysis, revealing additional biologically plausible information in cases with no result from the standard analysis and gives insight into the origin and spread of IEDs.

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset

The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.

Interpretation of the Intracranial Stereoelectroencephalography Signal

The intracranial electroencephalogram (iEEG) is essential in decision making for epilepsy surgery. Although localization of epileptogenic brain regions by means of iEEG has been the gold standard for surgical decision-making for more than 70 years, established guidelines for what constitutes genuine iEEG epileptic activity and what is normal brain activity are not available. This review provides a summary of the current state of knowledge and understanding on normal iEEG entities and variants, the effects of sleep on regional and lobar iEEG, iEEG patterns of interictal and ictal epileptic activity and their relation to well-described epileptogenic pathologies and surgical outcome.

Patient phenotypes and clinical outcomes in invasive monitoring for epilepsy: An individual patient data meta-analysis

OBJECTIVE

Invasive monitoring provides valuable clinical information in patients with drug-resistant epilepsy (DRE). However, there is no clear evidence indicating either stereoelectroencephalography (SEEG) or subdural electrodes (SDE) as the optimal method. Our goal was to examine differences in postresection seizure freedom rates between SEEG- and SDE-informed resective epilepsy surgeries. Additionally, we aimed to determine potential clinical indicators for SEEG or SDE monitoring in patients with drug-resistant epilepsy.

METHODS

A systematic literature review was performed in which we searched for primary articles using keywords such as "electroencephalography", "intracranial grid", and "epilepsy." Only studies containing individual patient data (IPD) were included for analysis. A one-stage IPD meta-analysis was performed to determine differences in rates of seizure freedom (International League Against Epilepsy (ILAE) guidelines and Engel classification) and resection status between SEEG and SDE patients. A Cox proportional-hazards regression was performed to determine the effect of time on seizure freedom status. Additionally, a principal component analysis was performed to investigate primary drivers of variance between these two groups.

RESULTS

This IPD meta-analysis compared differences between SEEG and SDE invasive monitoring techniques in 595 patients from 33 studies. Our results demonstrate that while there was no difference in seizure freedom rates regardless of resection (p = 0.0565), SEEG was associated with a lower rate of resection compared with SDE (82.00% SEEG, 92.74% SDE, p = 0.0002). Additionally, while SDE was associated with a higher rate of postresection seizure freedom (54.04% SEEG, 64.32% SDE, p = 0.0247), the difference between seizure freedom rates following SEEG- or SDE-informed resection decreased with long-term follow-up. A principal component analysis showed that cases resulting in SEEG were associated with lower risk of morbidity than SDE cases, which were strongly collinear with multiple subpial transections, anterior temporal lobectomy, amygdalectomy, and hippocampectomy.

SIGNIFICANCE

In this IPD meta-analysis of SEEG and SDE invasive monitoring techniques, SEEG and SDE were associated with similar rates of seizure freedom at latest follow-up. The former was associated with lower rates of resection. Furthermore, the clinical phenotypes of patients undergoing SEEG monitoring was associated with lower rates of complications. Future long-term prospective registries of IPD are promising options for clarifying the differences in these intracranial monitoring techniques as well as the unique patient phenotypes that may be associated with their indication.

Method of invasive monitoring in epilepsy surgery and seizure freedom and morbidity: A systematic review

OBJECTIVE

Invasive monitoring is sometimes necessary to guide resective surgery in epilepsy patients, but the ideal method is unknown. In this systematic review, we assess the association of postresection seizure freedom and adverse events in stereoelectroencephalography (SEEG) and subdural electrodes (SDE).

METHODS

We searched three electronic databases (MEDLINE, Embase, and CENTRAL [Cochrane Central Register of Controlled Trials]) from their inception to January 2018 with the keywords "electroencephalography," "intracranial grid," and "epilepsy." Studies that presented primary quantitative patient data for postresection seizure freedom with at least 1 year of follow-up or complication rates of SEEG- or SDE-monitored patients were included. Two trained investigators independently collected data from eligible studies. Weighted mean differences (WMDs) with 95% confidence interval (CIs) were used as a measure of the association of SEEG or SDE with seizure freedom and with adverse event outcomes.

RESULTS

Of 11 462 screened records, 48 studies met inclusion criteria. These studies reported on 1973 SEEG patients and 2036 SDE patients. Our systematic review revealed SEEG was associated with 61.0% and SDE was associated with 56.4% seizure freedom after resection (WMD = +5.8%, 95% CI = 4.7-6.9%, P = .001). Furthermore, SEEG was associated with 4.8% and SDE was associated with 15.5% morbidity (WMD = -10.6%, 95% CI = -11.6 to -9.6%, P = .001). SEEG was associated with 0.2% mortality and SDE was associated with 0.4% mortality (WMD = -0.2%, 95% CI = -0.3 to -0.1%, P = .001).

SIGNIFICANCE

In this systematic review of SEEG and SDE invasive monitoring techniques, SEEG was associated with fewer surgical resections yet better seizure freedom outcomes in those undergoing resections. SEEG was also associated with lower mortality and morbidity than SDE. Clinical studies directly comparing these modalities are necessary to understand the relative rates of seizure freedom, morbidity, and mortality associated with these techniques.

The seizure onset zone drives state-dependent epileptiform activity in susceptible brain regions

OBJECTIVE

Due to variability in the patterns of propagation of interictal epileptiform discharges (IEDs), qualitative definition of the irritative zone has been challenging. Here, we introduce a quantitative approach toward exploration of the dynamics of IED propagation within the irritative zone.

METHODS

We examined intracranial EEG (iEEG) in nine participants undergoing invasive monitoring for seizure localization. We used an automated IED detector and a community detection algorithm to identify populations of electrodes exhibiting IED activity that co-occur in time, and to group these electrodes into communities.

RESULTS

Within our algorithmically-identified communities, IED activity in the seizure onset zone (SOZ) tended to lead IED activity in other functionally coupled brain regions. The tendency of pathological activity to arise in the SOZ, and to spread to non-SOZ tissues, was greater in the asleep state.

CONCLUSIONS

IED activity, and, by extension, the variability observed between the asleep and awake states, is propagated from a core seizure focus to nearby less pathological brain regions.

SIGNIFICANCE

Using an unsupervised, computational approach, we show that the spread of IED activity through the epilepsy network varies with physiologic state.

Reproducibility of interictal spike propagation in children with refractory epilepsy

OBJECTIVE

Interictal spikes are a characteristic feature of invasive electroencephalography (EEG) recordings in children with refractory epilepsy. Spikes frequently co-occur across multiple brain regions with discernable latencies, suggesting that spikes can propagate through distributed neural networks. The purpose of this study was to examine the long-term reproducibility of spike propagation patterns over hours to days of interictal recording.

METHODS

Twelve children (mean age 13.1 years) were retrospectively studied. A mean ± standard deviation (SD) of 47.2 ± 40.1 hours of interictal EEG recordings were examined per patient (range 17.5-166.5 hours). Interictal recordings were divided into 30-minute segments. Networks were extracted based on the frequency of spike coactivation between pairs of electrodes. For each 30-minute segment, electrodes were assigned a "Degree Preference (DP)" based on the tendency to appear upstream or downstream within propagation sequences. The consistency of DPs across segments ("DP-Stability") was quantified using the Spearman rank correlation.

RESULTS

Regions exhibited highly stable preferences to appear upstream, intermediate, or downstream in spike propagation sequences. Across networks, the mean ± SD DP-Stability was 0.88 ± 0.07, indicating that propagation patterns observed in 30-minute segments were representative of the patterns observed in the full interictal window. At the group level, regions involved in seizure generation appeared more upstream in spike propagation sequences.

SIGNIFICANCE

Interictal spike propagation is a highly reproducible output of epileptic networks. These findings shed new light on the spatiotemporal dynamics that may constrain the network mechanisms of refractory epilepsy.

Presurgical intracranial investigations in epilepsy surgery

Identification and localization of the "epileptogenic process" in the brain of patients with drug-resistant epilepsy for surgical cure is the goal of presurgical investigations. Intracranial recordings are required when conflicting data between seizure clinical semiology and EEG prevent precise localization within one hemisphere or lateralization, when a visible lesion on MRI seems unrelated to the electroclinical data, or in MRI-negative cases. Two methods are currently used. The objective of the subdural grid electrocorticography with or without depth electrodes (SDG/DE) is the best possible identification of the area of onset of spontaneous seizures and localization of the eloquent cortex. The objective of stereoelectroencephalography (SEEG) is to define the epileptogenic zone (configured as a network) and its relation to an unmasked lesion. Two-dimensional (SDG) and three-dimensional (SEEG) brain sampling dictate different strategies for noninvasive presurgical phase I goals as well as for data analysis. SEEG must resolve several potential localization hypotheses in a manner that cannot be achieved with SDG. SDG operates through brain surface coverage, unlike SEEG, which samples networks. SDG estimates the extent of cortical resection through a lobar or sublobar localization of ictal onset and constraints from functional mapping. SEEG defines a tailored resection according to the results of anatomo-electro-clinical correlations in stereotaxic space that will guide the ablation of the epileptogenic zone. SEEG is currently expanding faster than SDG. The prerequisites (especially in the preimplantation hypothetical strategy) and technical tools (especially stimulation and functional mapping) in the two methods are very different. This chapter presents a comparative review of the rationale, indications, electrode implantation strategies, interpretation, and surgical decision making of these two approaches of presurgical evaluation for epilepsy surgery.

Interictal spike connectivity in human epileptic neocortex

OBJECTIVE

Interictal spikes are a biomarker of epilepsy, yet their precise roles are poorly understood. Using long-term neocortical recordings from epileptic patients, we investigated the spatial-temporal propagation patterns of interictal spiking.

METHODS

Interictal spikes were detected in 10 epileptic patients. Short time direct directed transfer function was used to map the spatial-temporal patterns of interictal spike onset and propagation across different cortical topographies.

RESULTS

Each patient had unique interictal spike propagation pattern that was highly consistent across times, regardless of the frequency band. High spiking brain regions were often not spike onset regions. We observed frequent spike propagations to shorter distances and that the central sulcus forms a strong barrier to spike propagation. Spike onset and seizure onset seemed to be distinct networks in most cases.

CONCLUSIONS

Patients in epilepsy have distinct and unique network of causal propagation pattern which are very consistent revealing the underlying epileptic network. Although spike are epileptic biomarkers, spike origin and seizure onset seems to be distinct in most cases.

SIGNIFICANCE

Understanding patterns of interictal spike propagation could lead to the identification patient-specific epileptic networks amenable to surgical or other treatments.

Proteomic analysis of human epileptic neocortex predicts vascular and glial changes in epileptic regions

Epilepsy is a common neurological disorder, which is not well understood at the molecular level. Exactly why some brain regions produce epileptic discharges and others do not is not known. Patients who fail to respond to antiseizure medication (refractory epilepsy) can benefit from surgical removal of brain regions to reduce seizure frequency. The tissue removed in these surgeries offers an invaluable resource to uncover the molecular and cellular basis of human epilepsy. Here, we report a proteomic study to determine whether there are common proteomic patterns in human brain regions that produce epileptic discharges. We analyzed human brain samples, as part of the Systems Biology of Epilepsy Project (SBEP). These brain pieces are in vivo electrophysiologically characterized human brain samples withdrawn from the neocortex of six patients with refractory epilepsy. This study is unique in that for each of these six patients the comparison of protein expression was made within the same patient: a more epileptic region was compared to a less epileptic brain region. The amount of epileptic activity was defined for each patient as the frequency of their interictal spikes (electric activity between seizures that is a parameter strongly linked to epilepsy). Proteins were resolved from three subcellular fractions, using a 2D differential gel electrophoresis (2D-DIGE), revealing 31 identified protein spots that changed significantly. Interestingly, glial fibrillary acidic protein (GFAP) was found to be consistently down regulated in high spiking brain tissue and showed a strong negative correlation with spike frequency. We also developed a two-step analysis method to select for protein species that changed frequently among the patients and identified these proteins. A total of 397 protein spots of interest (SOI) were clustered by protein expression patterns across all samples. These clusters were used as markers and this analysis predicted proteomic changes due to both histological differences and molecular pathways, revealed by examination of gene ontology clusters. Our experimental design and proteomic data analysis predicts novel glial changes, increased angiogenesis, and changes in cytoskeleton and neuronal projections between high and low interictal spiking regions. Quantitative histological staining of these same tissues for both the vascular and glial changes confirmed these findings, which provide new insights into the structural and functional basis of neocortical epilepsy.

The Sub-Regional Functional Organization of Neocortical Irritative Epileptic Networks in Pediatric Epilepsy

Between seizures, irritative network generates frequent brief synchronous activity, which manifests on the EEG as interictal epileptiform discharges (IEDs). Recent insights into the mechanism of IEDs at the microscopic level have demonstrated a high variance in the recruitment of neuronal populations generating IEDs and a high variability in the trajectories through which IEDs propagate across the brain. These phenomena represent one of the major constraints for precise characterization of network organization and for the utilization of IEDs during presurgical evaluations. We have developed a new approach to dissect human neocortical irritative networks and quantify their properties. We have demonstrated that irritative network has modular nature and it is composed of multiple independent sub-regions, each with specific IED propagation trajectories and differing in the extent of IED activity generated. The global activity of the irritative network is determined by long-term and circadian fluctuations in sub-region spatiotemporal properties. Also, the most active sub-region co-localizes with the seizure onset zone in 12/14 cases. This study demonstrates that principles of recruitment variability and propagation are conserved at the macroscopic level and that they determine irritative network properties in humans. Functional stratification of the irritative network increases the diagnostic yield of intracranial investigations with the potential to improve the outcomes of surgical treatment of neocortical epilepsy.

Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone

The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.

Altered metabolomic-genomic signature: A potential noninvasive biomarker of epilepsy

OBJECTIVE

This study aimed to identify noninvasive biomarkers of human epilepsy that can reliably detect and localize epileptic brain regions. Having noninvasive biomarkers would greatly enhance patient diagnosis, patient monitoring, and novel therapy development. At the present time, only surgically invasive, direct brain recordings are capable of detecting these regions with precision, which severely limits the pace and scope of both clinical management and research progress in epilepsy.

METHODS

We compared high versus low or nonspiking regions in nine medically intractable epilepsy surgery patients by performing integrated metabolomic-genomic-histological analyses of electrically mapped human cortical regions using high-resolution magic angle spinning proton magnetic resonance spectroscopy, cDNA microarrays, and histological analysis.

RESULTS

We found a highly consistent and predictive metabolite logistic regression model with reduced lactate and increased creatine plus phosphocreatine and choline, suggestive of a chronically altered metabolic state in epileptic brain regions. Linking gene expression, cellular, and histological differences to these key metabolites using a hierarchical clustering approach predicted altered metabolic vascular coupling in the affected regions. Consistently, these predictions were validated histologically, showing both neovascularization and newly discovered, millimeter-sized microlesions.

SIGNIFICANCE

Using a systems biology approach on electrically mapped human cortex provides new evidence for spatially segregated, metabolic derangements in both neurovascular and synaptic architecture in human epileptic brain regions that could be a noninvasively detectable biomarker of epilepsy. These findings both highlight the immense power of a systems biology approach and identify a potentially important role that magnetic resonance spectroscopy can play in the research and clinical management of epilepsy.

Automated long-term EEG analysis to localize the epileptogenic zone

Objective

We investigated the performance of automatic spike detection and subsequent electroencephalogram (EEG) source imaging to localize the epileptogenic zone (EZ) from long-term EEG recorded during video-EEG monitoring.

Methods

In 32 patients, spikes were automatically detected in the EEG and clustered according to their morphology. The two spike clusters with most single events in each patient were averaged and localized in the brain at the half-rising time and peak of the spike using EEG source imaging. On the basis of the distance from the sources to the resection and the known patient outcome after surgery, the performance of the automated EEG analysis to localize the EZ was quantified.

Results

In 28 out of the 32 patients, the automatically detected spike clusters corresponded with the reported interictal findings. The median distance to the resection in patients with Engel class I outcome was 6.5 and 15 mm for spike cluster 1 and 27 and 26 mm for cluster 2, at the peak and the half-rising time of the spike, respectively. Spike occurrence (cluster 1 vs. cluster 2) and spike timing (peak vs. half-rising) significantly influenced the distance to the resection (p < 0.05). For patients with Engel class II, III, and IV outcomes, the median distance increased to 36 and 36 mm for cluster 1. Localizing spike cluster 1 at the peak resulted in a sensitivity of 70% and specificity of 100%, positive prediction value (PPV) of 100%, and negative predictive value (NPV) of 53%. Including the results of spike cluster 2 led to an increased sensitivity of 79% NPV of 55% and diagnostic OR of 11.4, while the specificity dropped to 75% and the PPV to 90%.

Significance

We showed that automated analysis of long-term EEG recordings results in a high sensitivity and specificity to localize the epileptogenic focus.

A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers

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We created a validation method for the evaluation of automated classification of interictal spikes.

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We used a modified version of Wave_clus (WC) to automatically classify the data of 5 patients.

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WC classification was similar to EEG reviewers providing an unbiased evaluation of the clinical data.

Objective

To validate the application of an automated neuronal spike classification algorithm, Wave_clus (WC), on interictal epileptiform discharges (IED) obtained from human intracranial EEG (icEEG) data.

Method

Five 10-min segments of icEEG recorded in 5 patients were used. WC and three expert EEG reviewers independently classified one hundred IED events into IED classes or non-IEDs. First, we determined whether WC-human agreement variability falls within inter-reviewer agreement variability by calculating the variation of information for each classifier pair and quantifying the overlap between all WC-reviewer and all reviewer-reviewer pairs. Second, we compared WC and EEG reviewers’ spike identification and individual spike class labels visually and quantitatively.

Results

The overlap between all WC-human pairs and all human pairs was >80% for 3/5 patients and >58% for the other 2 patients demonstrating WC falling within inter-human variation. The average sensitivity of spike marking for WC was 91% and >87% for all three EEG reviewers. Finally, there was a strong visual and quantitative similarity between WC and EEG reviewers.

Conclusions

WC performance is indistinguishable to that of EEG reviewers’ suggesting it could be a valid clinical tool for the assessment of IEDs.

Significance

WC can be used to provide quantitative analysis of epileptic spikes.

Detection of Epileptic Seizures Using Phase-Amplitude Coupling in Intracranial Electroencephalography

Seizure detection using intracranial electroencephalography (iEEG) contributes to improved treatment of patients with refractory epilepsy. For that purpose, a feature of iEEG to characterize the ictal state with high specificity and sensitivity is necessary. We evaluated the use of phase–amplitude coupling (PAC) of iEEG signals over a period of 24 h to detect the ictal and interictal states. PAC was estimated by using a synchronisation index (SI) for iEEG signals from seven patients with refractory temporal lobe epilepsy. iEEG signals of the ictal state was characterised by a strong PAC between the phase of β and the amplitude of high γ. Furthermore, using SI values, the ictal state was successfully detected with significantly higher accuracy than by using the amplitude of high γ alone. In conclusion, PAC accurately distinguished the ictal state from the interictal state.

Interictal high-frequency oscillations generated by seizure onset and eloquent areas may be differentially coupled with different slow waves

OBJECTIVE

High-frequency oscillations (HFOs) can be spontaneously generated by seizure-onset and functionally-important areas. We determined if consideration of the spectral frequency bands of coupled slow-waves could distinguish between epileptogenic and physiological HFOs.

METHODS

We studied a consecutive series of 13 children with focal epilepsy who underwent extraoperative electrocorticography. We measured the occurrence rate of HFOs during slow-wave sleep at each electrode site. We subsequently determined the performance of HFO rate for localization of seizure-onset sites and undesirable detection of nonepileptic sensorimotor-visual sites defined by neurostimulation. We likewise determined the predictive performance of modulation index: MI(XHz)&(YHz), reflecting the strength of coupling between amplitude of HFOsXHz and phase of slow-waveYHz. The predictive accuracy was quantified using the area under the curve (AUC) on receiver-operating characteristics analysis.

RESULTS

Increase in HFO rate localized seizure-onset sites (AUC⩾0.72; p<0.001), but also undesirably detected nonepileptic sensorimotor-visual sites (AUC⩾0.58; p<0.001). Increase in MI(HFOs)&(3-4Hz) also detected both seizure-onset (AUC⩾0.74; p<0.001) and nonepileptic sensorimotor-visual sites (AUC⩾0.59; p<0.001). Increase in subtraction-MIHFOs [defined as subtraction of MI(HFOs)&(0.5-1Hz) from MI(HFOs)&(3-4Hz)] localized seizure-onset sites (AUC⩾0.71; p<0.001), but rather avoided detection of nonepileptic sensorimotor-visual sites (AUC⩽0.42; p<0.001).

CONCLUSION

Our data suggest that epileptogenic HFOs may be coupled with slow-wave3-4Hz more preferentially than slow-wave0.5-1Hz, whereas physiologic HFOs with slow-wave0.5-1Hz more preferentially than slow-wave3-4Hz during slow-wave sleep.

SIGNIFICANCE

Further studies in larger samples are warranted to determine if consideration of the spectral frequency bands of slow-waves coupled with HFOs can positively contribute to presurgical evaluation of patients with focal epilepsy.

Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization

Electrical source imaging of interictal spikes observed in EEG recordings of patients with refractory epilepsy provides useful information to localize the epileptogenic focus during the presurgical evaluation. However, the selection of the time points or time epochs of the spikes in order to estimate the origin of the activity remains a challenge. In this study, we consider a Bayesian EEG source imaging technique for distributed sources, i.e. the multiple volumetric sparse priors (MSVP) approach. The approach allows to estimate the time courses of the intensity of the sources corresponding with a specific time epoch of the spike. Based on presurgical averaged interictal spikes in six patients who were successfully treated with surgery, we estimated the time courses of the source intensities for three different time epochs: (i) an epoch starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii) an epoch starting 50 ms before the spike peak and ending at the spike peak and (iii) an epoch containing the full spike time period starting 50 ms before the spike peak and ending 230 ms after the spike peak. To identify the primary source of the spike activity, the source with the maximum energy from 50 ms before the spike peak till 50% of the spike peak was subsequently selected for each of the time windows. For comparison, the activity at the spike peaks and at 50% of the peaks was localized using the LORETA inversion technique and an ECD approach. Both patient-specific spherical forward models and patient-specific 5-layered finite difference models were considered to evaluate the influence of the forward model. Based on the resected zones in each of the patients, extracted from post-operative MR images, we compared the distances to the resection border of the estimated activity. Using the spherical models, the distances to the resection border for the MSVP approach and each of the different time epochs were in the same range as the LORETA and ECD techniques. We found distances smaller than 23 mm, with robust results for all the patients. For the finite difference models, we found that the distances to the resection border for the MSVP inversions of the full spike time epochs were generally smaller compared to the MSVP inversions of the time epochs before the spike peak. The results also suggest that the inversions using the finite difference models resulted in slightly smaller distances to the resection border compared to the spherical models. The results we obtained are promising because the MSVP approach allows to study the network of the estimated source-intensities and allows to characterize the spatial extent of the underlying sources.

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A Bayesian ESI technique is evaluated to localize interictal spike activity.

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Averaged spikes in six patients were used that were seizure free after surgery.

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We compared the technique with the LORETA an ECD technique.

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We evaluated both spherical and 5-layered finite difference forward models.

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Our approach is potentially useful to delineate the irritative zone.

Spatial-temporal patterns of electrocorticographic spectral changes during midazolam sedation

OBJECTIVE

To better understand 'when' and 'where' wideband electrophysiological signals are altered by sedation.

METHODS

We generated animation movies showing electrocorticography (ECoG) amplitudes at eight spectral frequency bands across 1.0-116 Hz, every 0.1s, on three-dimensional surface images of 10 children who underwent epilepsy surgery. We measured the onset, intensity, and variance of each band amplitude change at given nonepileptic regions separately from those at affected regions. We also determined the presence of differential ECoG changes depending on the brain anatomy.

RESULTS

Within 20s following injection of midazolam, beta (16-31.5 Hz) and sigma (12-15.5 Hz) activities began to be multifocally augmented with increased variance in amplitude at each site. Beta-sigma augmentation was most prominent within the association neocortex. Augmentation of low-delta activity (1.0-1.5 Hz) was relatively modest and confined to the somatosensory-motor region. Conversely, injection of midazolam induced attenuation of theta (4.0-7.5 Hz) and high-gamma (64-116 Hz) activities.

CONCLUSIONS

Our observations support the notion that augmentation beta-sigma and delta activities reflects cortical deactivation or inactivation, whereas theta and high-gamma activities contribute to maintenance of consciousness. The effects of midazolam on the dynamics of cortical oscillations differed across regions.

SIGNIFICANCE

Sedation, at least partially, reflects a multi-local phenomenon at the cortical level rather than global brain alteration homogeneously driven by the common central control structure.

Intracranial EEG analysis in tumor-related epilepsy: Evidence of distant epileptic abnormalities

OBJECTIVE

In patients with tumor-related epilepsy (TRE), surgery traditionally focuses on tumor resection; but identification and removal of associated epileptogenic zone may improve seizure outcome. Here, we study spatial relationship of tumor and seizure onset and early spread zone (SOSz). We also perform quantitative analysis of interictal epileptiform activities in patients with both TRE and non-lesional epilepsy in order to better understand the electrophysiological basis of epileptogenesis.

METHODS

Twenty-five patients (11 with TRE and 14 with non-lesional epilepsy) underwent staged surgery using intracranial electrodes. Tumors were outlined on MRI and images were coregistered with post-implantation CT images. For each electrode, distance to the nearest tumor margin was measured. Electrodes were categorized based on distance from tumor and involvement in seizure. Quantitative EEG analysis studying frequency, amplitude, power, duration and slope of interictal spikes was performed.

RESULTS

At least part of the SOSz was located beyond 1.5 cm from the tumor margin in 10/11 patients. Interictally, spike frequency and power were higher in the SOSz and spikes near tumor were smaller and less sharp. Interestingly, peritumoral electrodes had the highest spike frequencies and sharpest spikes, indicating greatest degree of epileptic synchrony. A complete resection of the SOSz resulted in excellent seizure outcome.

CONCLUSIONS

Seizure onset and early spread often involves brain areas distant from the tumor.

SIGNIFICANCE

Utilization of epilepsy surgery approach for TRE may provide better seizure outcome and study of the intracranial EEG may provide insight into pathophysiology of TRE.

Predicting novel histopathological microlesions in human epileptic brain through transcriptional clustering

Although epilepsy is associated with a variety of abnormalities, exactly why some brain regions produce seizures and others do not is not known. We developed a method to identify cellular changes in human epileptic neocortex using transcriptional clustering. A paired analysis of high and low spiking tissues recorded in vivo from 15 patients predicted 11 cell-specific changes together with their 'cellular interactome'. These predictions were validated histologically revealing millimetre-sized 'microlesions' together with a global increase in vascularity and microglia. Microlesions were easily identified in deeper cortical layers using the neuronal marker NeuN, showed a marked reduction in neuronal processes, and were associated with nearby activation of MAPK/CREB signalling, a marker of epileptic activity, in superficial layers. Microlesions constitute a common, undiscovered layer-specific abnormality of neuronal connectivity in human neocortex that may be responsible for many 'non-lesional' forms of epilepsy. The transcriptional clustering approach used here could be applied more broadly to predict cellular differences in other brain and complex tissue disorders.

Effect of subthalamic nucleus stimulation on penicillin induced focal motor seizures in primate

BACKGROUND

Drug-resistant motor epilepsies are particularly incapacitating for the patients. In a primate model of focal motor seizures induced by intracortical injection of penicillin, we recently showed that seizures propagated from the motor cortex towards the basal ganglia.

OBJECTIVE

Using the same animal model here, we hypothesized that disruption of subthalamic nucleus (STN) activity by chronic high frequency stimulation (HFS) could modify pathological excessive cortical synchronisation occurring during focal motor seizures, and therefore could reduce seizure activity.

METHODS

Two monkeys were chronically implanted with one electrode positioned into the STN. In each experiment, seizures were induced during 6 hours by injecting penicillin into the motor cortex. During stimulation sessions, HFS-STN was applied at the beginning of penicillin injection.

RESULTS

Our results indicate that HFS-STN improved focal motor seizures by delaying the occurrence of the first seizure, by decreasing the number of seizures by 47% and therefore the total time spent seizing by 53% compared to control. These results argue for a therapeutic use of HFS-STN in motor seizures because they were obtained in a very severe primate model of motor status similar to that seen in human. Furthermore, HFS-STN was much more efficient than direct cortical HFS of the epileptic focus, which we already tested in the same primate model.

CONCLUSIONS

The present study suggests that HFS-STN could be used as an experimental therapy when other therapeutic strategies are not possible or have failed in humans suffering from motor epilepsy but the present study still warrants controlled studies in humans.

Detection of interictal epileptiform discharges using signal envelope distribution modelling: application to epileptic and non-epileptic intracranial recordings

Interictal epileptiform discharges (spikes, IEDs) are electrographic markers of epileptic tissue and their quantification is utilized in planning of surgical resection. Visual analysis of long-term multi-channel intracranial recordings is extremely laborious and prone to bias. Development of new and reliable techniques of automatic spike detection represents a crucial step towards increasing the information yield of intracranial recordings and to improve surgical outcome. In this study, we designed a novel and robust detection algorithm that adaptively models statistical distributions of signal envelopes and enables discrimination of signals containing IEDs from signals with background activity. This detector demonstrates performance superior both to human readers and to an established detector. It is even capable of identifying low-amplitude IEDs which are often missed by experts and which may represent an important source of clinical information. Application of the detector to non-epileptic intracranial data from patients with intractable facial pain revealed the existence of sharp transients with waveforms reminiscent of interictal discharges that can represent biological sources of false positive detections. Identification of these transients enabled us to develop and propose secondary processing steps, which may exclude these transients, improving the detector's specificity and having important implications for future development of spike detectors in general.

Electric source imaging of interictal activity accurately localises the seizure onset zone

OBJECTIVE

It remains controversial whether interictal spikes are a surrogate of the seizure onset zone (SOZ). Electric source imaging (ESI) is an increasingly validated non-invasive approach for localising the epileptogenic focus in patients with drug-resistant epilepsy undergoing evaluation for surgery, using high-density scalp EEG and advanced source localisation algorithms that include the patient's own MRI. Here we investigate whether localisation of interictal spikes by ESI provides valuable information on the SOZ.

METHODS

In 38 patients with focal epilepsy who later underwent intracranial EEG monitoring, we performed ESI of interictal spikes recorded with 128-256-channel EEG. We measured the distance between the ESI maximum and the nearest intracranial electrodes in the SOZ and irritative zone (IZ, the source of interictal spikes). The resection of the region harbouring the ESI maximum was correlated to surgical outcome.

RESULTS

The median distance from the ESI maximum to the nearest electrode involved in the SOZ was 17 mm (IQR 8-27). The IZ and SOZ colocalised in most patients (median distance 0 mm, IQR 0-14), supporting the notion that localising interictal spikes is a valid surrogate for the SOZ. There was no difference in accuracy among patients with temporal or extratemporal epilepsy. In the 32 patients who underwent resective surgery, including the ESI maximum in the resection correlated with favourable outcome (p=0.03).

CONCLUSIONS

Localisation of interictal spikes provides an excellent estimate of the SOZ in the majority of patients. ESI should be taken into account for the management of patients undergoing intracranial recordings.

Usefulness of interictal spike source localization in temporal lobe epilepsy: electrocorticographic study

The success of epilepsy surgery depends on delineation of the suspected epileptogenic zone. The gold standard to delineate it is to use the ictal onset zone from an electrocorticography (ECoG). Although interictal spikes are also associated with the epileptogenic zone, their clinical significance has been under-evaluated. The aim of this study was to evaluate the source localization of interictal spikes in terms of the association with epileptogenic zone in surgical temporal lobe epilepsy patients. The proposition is that the resection volume in patients with favorable outcomes includes the epileptogenic zone. The association with the epileptogenic zone was assessed as follows: (1) how many of the interictal spike sources are within the resection volume in patients with favorable outcomes and (2) how many of the interictal spike sources are outside the resection volume in patients with unfavorable outcomes. Thirty-eight temporal lobe epilepsy (TLE) patients who underwent both ECoG monitoring and epilepsy surgery were recruited and their 10min of ECoG recordings were analyzed. Six tumor-related TLE patients were excluded in the analysis. Of the remaining 32 patients, 20 patients achieved favorable surgical outcomes (Engel I and II), while the surgical outcomes of 12 patients were unfavorable (Engel III and IV). In each patient, interictal spike sources were localized using sLORETA and co-registered into a reconstructed brain model. The correspondence rate with the resection volume was estimated by counting the percentage of interictal spike sources in the resection volume. The correspondence rate in patients with favorable outcomes was 72.8±22.1, which was significantly higher than that (41.2±28.8) of the patients with unfavorable outcomes (p=0.002). Nine out of twelve patients (75%) with unfavorable outcomes had multiple interictal spike source clusters both interior and exterior to the resection volume, while 4 of the 20 patients with favorable outcomes (20%) had such multiple clusters (p=0.021). In conclusion, interictal spike sources are highly associated with the epileptogenic zone. ECoG interictal spike source localization could help in the delineation of the potential resection volume.

Automatic detection of prominent interictal spikes in intracranial EEG: validation of an algorithm and relationsip to the seizure onset zone

OBJECTIVE

To develop an algorithm for the automatic quantitative description and detection of spikes in the intracranial EEG and quantify the relationship between prominent spikes and the seizure onset zone.

METHODS

An algorithm was developed for the quantification of time-frequency properties of spikes (upslope, instantaneous energy, downslope) and their statistical representation in a univariate generalized extreme value distribution. Its performance was evaluated in comparison to expert detection of spikes in intracranial EEG recordings from 10 patients. It was subsequently used in 18 patients to detect prominent spikes and quantify their spatial relationship to the seizure onset area.

RESULTS

The algorithm displayed an average sensitivity of 63.4% with a false detection rate of 3.2 per minute for the detection of individual spikes and an average sensitivity of 88.6% with a false detection rate of 1.4% for the detection of intracranial EEG contacts containing the most prominent spikes. Prominent spikes occurred closer to the seizure onset area than less prominent spikes but they overlapped with it only in a minority of cases (3/18).

CONCLUSIONS

Automatic detection and quantification of the morphology of spikes increases their utility to localize the seizure onset area. Prominent spikes tend to originate mostly from contacts located in the close vicinity of the seizure onset area rather than from within it.

SIGNIFICANCE

Quantitative analysis of time-frequency characteristics and spatial distribution of intracranial spikes provides complementary information that may be useful for the localization of the seizure-onset zone.

Interictal networks in magnetoencephalography

Epileptic networks involve complex relationships across several brain areas. Such networks have been shown on intracerebral EEG (stereotaxic EEG, SEEG), an invasive technique. Magnetoencephalography (MEG) is a noninvasive tool, which was recently proven to be efficient for localizing the generators of epileptiform discharges. However, despite the importance of characterizing non-invasively network aspects in partial epilepsies, only few studies have attempted to retrieve fine spatiotemporal dynamics of interictal discharges with MEG. Our goal was to assess the relevance of magnetoencephalography for detecting and characterizing the brain networks involved in interictal epileptic discharges. We propose here a semi-automatic method based on independent component analysis (ICA) and on co-occurrence of events across components. The method was evaluated in a series of seven patients by comparing its results with networks identified in SEEG. On both MEG and SEEG, we found that interictal discharges can involve remote regions which are acting in synchrony. More regions were identified in SEEG (38 in total) than in MEG (20). All MEG regions were confirmed by SEEG when an electrode was present in the vicinity. In all patients, at least one region could be identified as leading according to our criteria. A majority (71%) of MEG leaders were confirmed by SEEG. We have therefore shown that MEG measurements can extract a significant proportion of the networks visible in SEEG. This suggests that MEG can be a useful tool for defining noninvasively interictal epileptic networks, in terms of regions and patterns of connectivity, in search for a "primary irritative zone".

Seizure outcomes of lesionectomy in pediatric lesional epilepsy with brain tumor -- single institute experience

PURPOSE

To determine the clinical characteristics, surgical strategy, and outcome in pediatric lesional epilepsy patients younger than 5years of age undergoing surgery in a single institute.

METHOD

Retrospective data were collected and analyzed on patients younger than 5years of age who underwent lesionectomy for lesional epilepsy at single institute from January 2001 to August 2010. Fourteen pediatric lesional epilepsy patients were enrolled in this study. Engel classification was used to classify seizure outcome.

RESULTS

Median preoperative seizure period was 1month (range, 1-21). Median post-operative follow up period was 35months (range 13-84). Ten patients who underwent gross total resection of tumor showed Engel class Ia seizure outcome without any antiepileptic drug (AED). Subtotal resection was performed in four patients to avoid eloquent area injury. Two of these four patients with subtotal removal became seizure-free (Engel class Ia) without AED, while two were in Engel class Ib with AED medication. There was no significant surgical morbidity or mortality.

CONCLUSION

Lesionectomy in children younger than 5years of age is relatively safe and effective in controlling seizures. Short preoperative seizure periods and total removal of tumor might be associated with good outcome. Therefore, early and complete lesionectomy alone may help allow for seizure freedom and optimal brain development in pediatric patients.

How to establish causality in epilepsy surgery

Focality in electro-clinical or neuroimaging data often motivates epileptologists to consider epilepsy surgery in patients with medically-uncontrolled seizures, while not all focal findings are causally associated with the generation of epileptic seizures. With the help of Hill's criteria, we have discussed how to establish causality in the context of the presurgical evaluation of epilepsy. The strengths of EEG include the ability to determine the temporal relationship between cerebral activities and clinical events; thus, scalp video-EEG is necessary in the evaluation of the majority of surgical candidates. The presence of associated ictal discharges can confirm the epileptic nature of a particular spell and whether an observed neuroimaging abnormality is causally associated with the epileptic seizure. Conversely, one should be aware that scalp EEG has a limited spatial resolution and sometimes exhibits propagated epileptiform discharges more predominantly than in situ discharges generated at the seizure-onset zone. Intraoperative or extraoperative electrocorticography (ECoG) is utilized when noninvasive presurgical evaluation, including anatomical and functional neuroimaging, fails to determine the margin between the presumed epileptogenic zone and eloquent cortex. Retrospective as well as prospective studies have reported that complete resection of the seizure-onset zone on ECoG was associated with a better seizure outcome, but not all patients became seizure-free following such resective surgery. Some retrospective studies suggested that resection of sites showing high-frequency oscillations (HFOs) at >80Hz on interictal or ictal ECoG was associated with a better seizure outcome. Others reported that functionally-important areas may generate HFOs of a physiological nature during rest as well as sensorimotor and cognitive tasks. Resection of sites showing task-related augmentation of HFOs has been reported to indeed result in functional loss following surgery. Thus, some but not all sites showing interictal HFOs are causally associated with seizure generation. Furthermore, evidence suggests that some task-related HFOs can be transiently suppressed by the prior occurrence of interictal spikes. The significance of interictal HFOs should be assessed by taking into account the eloquent cortex, seizure-onset zone, and cortical lesions. Video-EEG and ECoG generally provide useful but still limited information to establish causality in presurgical evaluation. A comprehensive assessment of data derived from multiple modalities is ultimately required for successful management.

Intracranially recorded interictal spikes: relation to seizure onset area and effect of medication and time of day

OBJECTIVE

The relationship between seizures and interictal spikes remains undetermined. We analyzed intracranial EEG (icEEG) recordings to examine the relationship between the seizure onset area and interictal spikes.

METHODS

80 unselected patients were placed into 5 temporal, 4 extratemporal, and one unlocalized groups based on the location of the seizure onset area. We studied 4-h icEEG epochs, removed from seizures, from day-time and night-time during both on- and off-medication periods. Spikes were detected automatically from electrode contacts sampling the hemisphere ipsilateral to the seizure onset area.

RESULTS

There was a widespread occurrence of spikes over the hemisphere ipsilateral to the seizure onset area. The spatial distributions of spike rates for the different patient groups were different (p<0.0001, chi-square test). The area with the highest spike rate coincided with the seizure onset area only in half of the patients.

CONCLUSION

The spatial distribution of spike rates is strongly associated with the location of the seizure onset area, suggesting the presence of a distributed spike generation network, which is related to the seizure onset area.

SIGNIFICANCE

The spatial distribution of spike rates, but not the area with the highest spike rate, may hold value for the localization of the seizure onset area.

Network oscillations modulate interictal epileptiform spike rate during human memory

Eleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in interictal epileptiform spike rate in the amygdala, hippocampus, and temporal cortex. During the earliest encoding period (0-2000 ms after image presentation) in these trials there was a widespread decrease in the power of theta, alpha and beta band local field potential oscillations that coincided with emergent focal gamma frequency activity. Interictal epileptiform spike rate correlated with spectral band power changes and broadband (4-150 Hz) desynchronization, which predicted significant reduction in interictal epileptiform spike rate. Spike-triggered averaging of the field potential power spectrum detected a burst of low frequency synchronization 200 ms before the interictal epileptiform spikes that arose during this period of encoding. We conclude that interictal epileptiform spikes are modulated by the patterns of network oscillatory activity that accompany human memory offering a new mechanistic insight into the interplay of cognitive processing, local field potential dynamics and interictal epileptiform spike generation.

Identifying the cortical substrates of interictal epileptiform activity in patients with extratemporal epilepsy: An EEG-fMRI sequential analysis and FDG-PET study

PURPOSE

The aim of this study was to apply sequential analysis of electroencephalography-functional magnetic resonance imaging (EEG-fMRI) data to study the cortical substrates related to the generation of the interictal epileptiform activity (IEA) in patients with pharmacoresistant extratemporal epilepsy.

METHODS

We analyzed fMRI data from 21 children, adolescents, and young adults patients who showed frequent bursts or runs of spikes on EEG, by using the sequential analysis method. We contrasted consecutive fixed-width blocks of 10 s to obtain the relative variations in cerebral activity along the entire fMRI runs. Significant responses (p < 0.05, family-wise error (FWE) corrected), time-related to the IEA recorded on scalp EEG, were considered potential IEA cortical sources. These results were compared with those from the fluorodeoxyglucose-positron emission tomography (FDG-PET), intracranial EEG (two patients), and surgery outcome (eight patients).

KEY FINDINGS

The typical IEA was recorded in all patients. After the sequential analysis, at least one significant blood oxygen level-dependent (BOLD) response spatially consistent with the presumed epileptogenic zone was found. These IEA-related activation areas coincided when superimposed with the hypometabolism depicted by the FDG-PET. These data were also consistent with the invasive EEG findings. Epileptic seizures were recorded in eight patients. A subset of IEA-associated fMRI activations was consistent the activations at seizure-onset determined by sequential analysis. The inclusion of the IEA-related areas in the resection rendered the patients seizure-free (five of eight operated patients).

SIGNIFICANCE

The EEG-fMRI data sequential analysis could noninvasively identify cortical areas involved in the IEA generation. The spatial relationship of these areas with the cortical metabolic abnormalities depicted by the FDG-PET and their intrinsic relationship regarding the ictal-onset zone could be useful in epilepsy surgery planning.

Interictal spikes, fast ripples and seizures in partial epilepsies--combining multi-level computational models with experimental data

Epileptic seizures, epileptic spikes and high-frequency oscillations (HFOs) are recognized as three electrophysiological markers of epileptogenic neuronal systems. It can be reasonably hypothesized that distinct (hyper)excitability mechanisms underlie these electrophysiological signatures. The question is 'What are these mechanisms?'. Solving this difficult question would considerably help our understanding of epileptogenic processes and would also advance our interpretation of electrophysiological signals. In this paper, we show how computational models of brain epileptic activity can be used to address this issue. With a special emphasis on the hippocampal activity recorded in various experimental models (in vivo and in vitro) as well as in epileptic patients, we confront results and insights we can get from computational models lying at two different levels of description, namely macroscopic (neural mass) and microscopic (detailed network of neurons). At each level, we show how spikes, seizures and HFOs can (or cannot) be generated depending on the model features. The replication of observed signals, the prediction of possible mechanisms as well as their experimental validation are described and discussed; as are the advantages and limitations of the two modelling approaches.