Seizure Onset Patterns Research Articles

Progressive alterations in electrophysiological and epileptic network properties during the development of temporal lobe epilepsy in rats

ObjectiveRefractory temporal lobe epilepsy (TLE) with recurring seizures causing continuing pathological changes in neural reorganization. There is an incomplete understanding of how spatiotemporal electrophysiological characteristics changes during the development of TLE. Long-term multi-site epilepsy patients’ data is hard to obtain. Thus, our study relied on animal models to reveal the changes in electrophysiological and epileptic network characteristics systematically. MethodsLong-term local field potentials (LFPs) were recorded over a period of 1 to 4 months from 6 pilocarpine-treated TLE rats. We compared variations of seizure onset zone (SOZ), seizure onset pattern (SOP), the latency of seizure onsets, and functional connectivity network from 10-channel LFPs between the early and late stages. Moreover, three machine learning classifiers trained by early-stage data were used to test seizure detection performance in the late stage. ResultsCompared to the early stage, the earliest seizure onset was more frequently detected in hippocampus areas in the late stage. The latency of seizure onsets between electrodes became shorter. Low-voltage fast activity (LVFA) was the most common SOP and the proportion of it increased in the late stage. Different brain states were observed during seizures using Granger causality (GC). Moreover, seizure detection classifiers trained by early-stage data were less accurate when tested in late-stage data. SignificanceNeuromodulation especially closed-loop deep brain stimulation (DBS) is effective in the treatment of refractory TLE. Although the frequency or amplitude of the stimulation is generally adjusted in existing closed-loop DBS devices in clinical usage, the adjustment rarely considers the pathological progression of chronic TLE. This suggests that an important factor affecting the therapeutic effect of neuromodulation may have been overlooked. The present study reveals time-varying electrophysiological and epileptic network properties in chronic TLE rats and indicates that classifiers of seizure detection and neuromodulation parameters might be designed to adapt to the current state dynamically with the progression of epilepsy.

Time-Series Generative Adversarial Network Approach of Deep Learning Improves Seizure Detection From the Human Thalamic SEEG.

Seizure detection algorithms are often optimized to detect seizures from the epileptogenic cortex. However, in non-localizable epilepsies, the thalamus is frequently targeted for neuromodulation. Developing a reliable seizure detection algorithm from thalamic SEEG may facilitate the translation of closed-loop neuromodulation. Deep learning algorithms promise reliable seizure detectors, but the major impediment is the lack of larger samples of curated ictal thalamic SEEG needed for training classifiers. We aimed to investigate if synthetic data generated by temporal Generative Adversarial Networks (TGAN) can inflate the sample size to improve the performance of a deep learning classifier of ictal and interictal states from limited samples of thalamic SEEG. Thalamic SEEG from 13 patients (84 seizures) was obtained during stereo EEG evaluation for epilepsy surgery. Overall, TGAN generated synthetic data augmented the performance of the bidirectional Long-Short Term Memory (BiLSTM) performance in classifying thalamic ictal and baseline states. Adding synthetic data improved the accuracy of the detection model by 18.5%. Importantly, this approach can be applied to classify electrographic seizure onset patterns or develop patient-specific seizure detectors from implanted neuromodulation devices.

Ictal high-frequency activity in limbic thalamic nuclei varies with electrographic seizure-onset patterns in temporal lobe epilepsy

ObjectiveTo characterize ictal high-frequency activity (HFA, 80–500 Hz) within the limbic thalami and correlate HFA with seizure onset patterns in patients with temporal lobe epilepsy (TLE). MethodsPatients with TLE undergoing stereoelectroencephalography (SEEG) for presurgical workup were prospectively recruited for electrode implantation in one of the anterior (AN), centromedian (CeM), or mediodorsal (MD) thalamic nuclei. HFA was computed by three complementary methods: (1.) power-spectral density (PSD), (2.) power-law based (i.e., 1/f) regression, and (3.) envelope-based (ENV) power analysis. Electrographic onset patterns in the seizure onset zone were classified in three distinct patterns, including low amplitude fast activity (LAFA). ResultsFrom 11 patients, 44 seizures were analyzed. Ictal HFA was observed in all three thalamic nuclei. HFA was greatest during ictal onset in the AN and MD and greatest during termination in the CeM (P < 0.001). LAFA-onset seizures were associated with earlier peak HFA compared to those with other onset patterns (P = 0.006). ConclusionsDynamics of ictal HFA seem to vary by thalamic subnuclei. AN and MD may facilitate seizure propagation while CeM may play a role in termination. LAFA-onset seizures rapidly propagate to the thalamus. SignificanceCharacterizing nucleus-specific ictal dynamics of neural activities facilitates precise therapy for epilepsy treatment with closed-loop deep brain stimulation.

Localizing and Lateralizing Value of Seizure Onset Pattern on Surface EEG in FCD Type II

BackgroundSurface ictal electroencephalographic (EEG) monitoring has an important role in the presurgical evaluation of patients with focal cortical dysplasia (FCD). This study aimed to examine the characteristics of seizure onset pattern (SOP) on surface ictal EEG. This information will be useful for invasive monitoring planning. MethodsWe reviewed 290 seizures from 31 patients with intractable seizures related to FCD type II (6 patients with FCD IIa and 25 patients with FCD IIb). We categorized the SOPs into five patterns and evaluated the relationships between the SOPs and the location and pathology of the FCD II subtype. ResultsThe most common SOP was no apparent change (39.0%), followed by rhythmic slow wave and repetitive spikes/sharp waves. The SOP of rhythmic slow wave was associated with FCD II in the temporal lobe (P < 0.001), and the SOP of no apparent change was associated with FCD II in the occipital lobe (P = 0.012). The SOPs of rhythmic slow waves and fast activity were most common in FCD IIa, P < 0.001 and 0.031, respectively. The repetitive spikes/sharp waves SOP was the most common pattern in FCD IIb (P < 0.001). The surface SOPs provided correct localization and lateralization of epileptic foci in FCD in 62.1% and 62.7%, respectively. In 61.3% of the patients, over 50% of the SOPs in each patient indicated accurate localization. ConclusionsSOPs in surface EEG monitoring are beneficial for presurgical evaluation and lead to localization of epileptic foci and pathologic subtypes of FCD.

Predictors of surgical outcome in focal cortical dysplasia and its subtypes.

The authors analyzed predictors of surgical outcome in patients with focal cortical dysplasia (FCD) and its ILAE (International League Against Epilepsy) subtypes after noninvasive multimodal evaluation and calculated time to first seizure. Data of 355 patients with refractory epilepsy, confirmed FCD pathology, and 2-13 years of postsurgical follow-up were analyzed to determine the predictive roles of clinical, EEG, imaging, and surgical factors that influence seizure freedom. The mean ± SD age at surgery was 20.26 ± 12.18 years. In total, 142 (40.0%) patients had daily seizures and 90 (25.3%) had multiple seizure types. MRI showed clear-cut FCD in 289 (81.4%) patients. Pathology suggested type I FCD in 27.3% of patients, type II in 28.4%, and type III in 42.8% of patients. At latest follow-up, 72.1% of patients were seizure free and 11.8% were seizure free and not receiving antiepileptic drugs. Among the subtypes, 88.8% of patients with type III, 69.3% with type II, and 50.5% with type I FCD were seizure free. Multiple seizure types, acute postoperative seizures (APOS), and type I FCD were predictors of persistent seizures, whereas type III FCD was the strongest predictor of seizure freedom. Type I FCD was associated with daily seizures, frontal and multilobar distribution, subtle findings on MRI, incomplete resection, and persistent seizures. Type II and III FCD were associated with clear-cut lesion on MRI, regional interictal and ictal EEG onset pattern, focal pattern on ictal SPECT, complete resection, and seizure freedom. Type III FCD was associated with temporal location, whereas type I and II FCD were associated with extratemporal location. Nearly 80% of patients with persistent seizures, mostly those with type I FCD, had their first seizure within 6 months postsurgery. Long-term seizure freedom after surgery can be achieved in more than two-thirds of patients with FCD after noninvasive multimodal evaluation. Multiple seizure types, type I FCD, and APOS were predictors of persistent seizures. Seizures recurred in about 80% of patients within 6 months postsurgery.

Robust chronic convulsive seizures, high frequency oscillations, and human seizure onset patterns in an intrahippocampal kainic acid model in mice

Intrahippocampal kainic acid (IHKA) has been widely implemented to simulate temporal lobe epilepsy (TLE), but evidence of robust seizures is usually limited. To resolve this problem, we slightly modified previous methods and show robust seizures are common and frequent in both male and female mice. We employed continuous wideband video-EEG monitoring from 4 recording sites to best demonstrate the seizures. We found many more convulsive seizures than most studies have reported. Mortality was low. Analysis of convulsive seizures at 2–4 and 10–12 wks post-IHKA showed a robust frequency (2–4 per day on average) and duration (typically 20–30 s) at each time. Comparison of the two timepoints showed that seizure burden became more severe in approximately 50% of the animals. We show that almost all convulsive seizures could be characterized as either low-voltage fast or hypersynchronous onset seizures, which has not been reported in a mouse model of epilepsy and is important because these seizure types are found in humans. In addition, we report that high frequency oscillations (>250 Hz) occur, resembling findings from IHKA in rats and TLE patients. Pathology in the hippocampus at the site of IHKA injection was similar to mesial temporal lobe sclerosis and reduced contralaterally. In summary, our methods produce a model of TLE in mice with robust convulsive seizures, and there is variable progression. HFOs are robust also, and seizures have onset patterns and pathology like human TLE. SignificanceAlthough the IHKA model has been widely used in mice for epilepsy research, there is variation in outcomes, with many studies showing few robust seizures long-term, especially convulsive seizures. We present an implementation of the IHKA model with frequent convulsive seizures that are robust, meaning they are >10 s and associated with complex high frequency rhythmic activity recorded from 2 hippocampal and 2 cortical sites. Seizure onset patterns usually matched the low-voltage fast and hypersynchronous seizures in TLE. Importantly, there is low mortality, and both sexes can be used. We believe our results will advance the ability to use the IHKA model of TLE in mice. The results also have important implications for our understanding of HFOs, progression, and other topics of broad interest to the epilepsy research community. Finally, the results have implications for preclinical drug screening because seizure frequency increased in approximately half of the mice after a 6 wk interval, suggesting that the typical 2 wk period for monitoring seizure frequency is insufficient.

Direct Cortical Stimulation to Probe the Ictogenicity of the Epileptogenic Nodes in Temporal Lobe Epilepsy.

Accurate mapping of the seizure onset zone (SOZ) is critical to the success of epilepsy surgery outcomes. Epileptogenicity index (EI) is a statistical method that delineates hyperexcitable brain regions involved in the generation and early propagation of seizures. However, EI can overestimate the SOZ for particular electrographic seizure onset patterns. Therefore, using direct cortical stimulation (DCS) as a probing tool to identify seizure generators, we systematically evaluated the causality of the high EI nodes (>0.3) in replicating the patient's habitual seizures. Specifically, we assessed the diagnostic yield of high EI nodes, i.e., the proportion of high EI nodes that evoked habitual seizures. A retrospective single-center study that included post-stereo encephalography (SEEG) confirmed TLE patients (n = 37) that had all high EI nodes stimulated, intending to induce a seizure. We evaluated the nodal responses (true and false responder rate) to stimulation and correlated with electrographic seizure onset patterns (hypersynchronous-HYP and low amplitude fast activity patterns-LAFA) and clinically defined SOZ. The ictogenicity (i.e., the propensity to induce the patient's habitual seizure) of a high EI node was only 44.5%. The LAFA onset pattern had a significantly higher response rate to DCS (i.e., higher evoked seizures). The concordance of an evoked habitual seizure with a clinically defined SOZ with good outcomes was over 50% (p = 0.0025). These results support targeted mapping of SOZ in LAFA onset patterns by performing DCS in high EI nodes to distinguish seizure generators (true responders) from hyperexcitable nodes that may be involved in early propagation.

Dynamic training of a novelty classifier algorithm for real-time detection of early seizure onset

ObjectiveTo develop an adaptive framework for seizure detection in real-time that is practical to use in the Epilepsy Monitoring Unit (EMU) as a warning signal, and whose output helps characterize epileptiform activity. MethodsOur algorithm was tested on intracranial EEG from epilepsy patients admitted to the EMU for presurgical evaluation. Our framework uses a one-class Support Vector Machine (SVM) that is being trained dynamically according to past activity in all available channels to classify the novelty of the current activity.In this study we compared multiple configurations using a one-class SVM to assess if there is significance over specific neural features or electrode locations. ResultsOur results show that the algorithm reaches a sensitivity of 87% for early-onset seizure detection and of 97.7% as a generic seizure detection. ConclusionsOur algorithm is capable of running in real-time and achieving a high performance for early seizure-onset detection with a low false positive rate and robustness in detection of different type of seizure-onset patterns. SignificanceThis algorithm offers a solution to warning systems in the EMU as well as a tool for seizure characterization during post-hoc analysis of intracranial EEG data for surgical resection of the epileptogenic network.

EEG seizure onset patterns in status epilepticus

Introduction: The seizure-onset (SOn) patterns have been studied especially with intracranial electrodes to improve the determination of the epileptogenic zone. Qualitative and quantitative EEG studies characterizing the onset pattern in status epilepticus (SE) are lacking. We aimed to classify the different SOn patterns and to compare them in order to determine any possible differences in terms of mortality, morbidity and treatment response.

Multiple ictal onset patterns underlie seizure generation in seizure-free patients with temporal lobe epilepsy surgery: an SEEG study

PurposeSeizure originates from different pathological substrate; however, the same pathologies may have distinct mechanisms underlying seizure generation. We aimed to improve the understanding of such mechanisms in patients with temporal lobe epilepsy (TLE) by investigating the stereoelectroencephalography (SEEG) ictal onset patterns (IOPs).MethodsWe analyzed data from a cohort of 19 consecutive patients explored by SEEG and had 1–3-year seizure-freedom following temporal lobe resection.ResultsSix IOPs were identified. They were low voltage fast activity (LVFA) (36.5%), rhythmic spikes or spike-waves at low frequency and with high amplitude (34.1%), runs of spikes (10.6%), rhythmic sharp waves (8.2%), low frequency high amplitude repetitive spiking (LFRS) (7.1%), and delta activity (3.5%). All six patterns were found in patients with mesial temporal onset and only two patterns were found in patients with temporal neocortical onset. The most prevalent patterns for patients with mesial temporal onset were rhythmic spikes or spike-waves, followed by LVFA with a mean discharge rate 74 Hz. For patients with temporal neocortical onset, the most prevalent IOP pattern was LVFA with a mean discharge rate 35 Hz, followed by runs of spikes. Compared with Lateral TLE (LTLE), the duration between the onset of the IOPs to the onset of the symptom was longer for patients with MTLE (Mesial TLE) (MTLE:55.7 ± 50.6 s vs LTLE:19.5 ± 16.4 s).ConclusionMultiple IOPs underlie seizure generation in patients with TLE. However, the mesial and lateral temporal lobes share distinct IOPs.

In vitro ictogenesis is stochastic at the single neuron level.

Seizure initiation is the least understood and most disabling element of epilepsy. Studies of ictogenesis require high speed recordings at cellular resolution in the area of seizure onset. However, in vivo seizure onset areas cannot be determined at the level of resolution necessary to enable such studies. To circumvent these challenges, we used novel GCaMP7-based calcium imaging in the organotypic hippocampal slice culture model of post-traumatic epilepsy in mice. Organotypic hippocampal slice cultures generate spontaneous, recurrent seizures in a preparation in which it is feasible to image the activity of the entire network (with no unseen inputs existing). Chronic calcium imaging of the entire hippocampal network, with paired electrophysiology, revealed three patterns of seizure onset: (i) low amplitude fast activity; (ii) sentinel spike; and (iii) spike burst and low amplitude fast activity onset. These patterns recapitulate common features of human seizure onset, including low voltage fast activity and spike discharges. Weeks-long imaging of seizure activity showed a characteristic evolution in onset type and a refinement of the seizure onset zone. Longitudinal tracking of individual neurons revealed that seizure onset is stochastic at the single neuron level, suggesting that seizure initiation activates neurons in non-stereotyped sequences seizure to seizure. This study demonstrates for the first time that transitions to seizure are not initiated by a small number of neuronal 'bad actors' (such as overly connected hub cells), but rather by network changes which enable the onset of pathology among large populations of neurons.

Intracranial EEG seizure onset and termination patterns and their association

ObjectiveThe study of seizure onset and termination patterns has the potential to enhance our understanding of the underlying mechanisms of seizure generation and cessation. It is largely unclear whether seizures with distinct onset patterns originate from varying network interactions and terminate through different termination pathways. MethodsWe investigated the morphology and location of 103 intracranial EEG seizure onset and termination patterns from 20 patients with drug-resistant focal epilepsy. We determined if seizure onset patterns were associated with specific termination patterns. Finally, we looked at network interactions prior to the generation of distinct seizure onset patterns by calculating directed functional connectivity matrices. ResultsWe identified nine seizure onset and six seizure termination patterns. The most common onset pattern was Low-Voltage Fast Activity (36 %), and the most frequent termination pattern was Burst Suppression (44 %). All seizures with fast (>13 Hz) termination patterns had a fast (>13 Hz) onset pattern type. Almost any onset pattern could terminate with the Burst Suppression and rhythmic Spike/PolySpike and Wave (rSW/rPSW) termination patterns. Seizures with a fast activity onset had higher inflow to the seizure onset zone from other regions in the gamma and high gamma frequency ranges prior to their generation compared to seizures with a slow onset. SignificanceOur observations suggest that different mechanisms underlie the generation of different seizure onset patterns although seizure onset patterns can share a common termination pattern. Possible mechanisms underlying these patterns are discussed.

Brain-responsive corticothalamic stimulation in the pulvinar nucleus for the treatment of regional neocortical epilepsy: A case series.

Drug‐resistant focal epilepsy with regional neocortical seizure onsets originating from the posterior quadrant can be particularly difficult to treat with resective surgery due to the overlap with eloquent cortex. Published reports indicate that corticothalamic treatment targeting the anterior or centromedian nucleus of the thalamus with direct brain‐responsive stimulation may be an effective approach to treat regional neocortical epilepsy. The pulvinar has remained largely unstudied as a neurostimulation target to treat refractory epilepsy. Because the pulvinar has connections with the posterior quadrant, neurostimulation may be effective if applied to seizures originating in this area. We performed a retrospective chart review of patients with regional neocortical seizure onsets in the posterior quadrant treated with the RNS System. Demographics, epilepsy history, clinical seizure frequencies, and neuropsychological testing results were obtained from the chart. Electrocorticogram (ECoG) records stored by the RNS System were reviewed to evaluate electrographic seizure onset patterns. Our patients were followed for 10, 12.5, and 15 months. All patients were responders (≥50% seizure reduction), and two of the three patients experienced a ≥90% reduction in seizures at the last follow‐up. Pre‐ and postsurgical neuropsychological evaluations were compared for two of the patients, and there was no evidence of cognitive decline found in either patient. Interestingly, mild cognitive improvements were reported. The third patient had only postimplant neuropsychological testing data available. Findings for this patient suggested executive dysfunction that was present prior to the RNS System which did not worsen with surgery. A visual inspection of ECoGs revealed near‐simultaneous seizure onsets in neocortical and pulvinar leads in two patients. Seizure onsets in the third patient were more variable. This is the first published report of brain‐responsive neurostimulation targeting the pulvinar to treat refractory regional onset epilepsy of posterior quadrant origin.

Defining Dravet syndrome: An essential pre-requisite for precision medicine trials.

ObjectiveThe classical description of Dravet syndrome, the prototypic developmental and epileptic encephalopathy, is of a normal 6‐month‐old infant presenting with a prolonged, febrile, hemiclonic seizure and showing developmental slowing after age 1 year. SCN1A pathogenic variants are found in >80% of patients. Many patients have atypical features resulting in diagnostic delay and inappropriate therapy. We aimed to provide an evidence‐based definition of SCN1A‐Dravet syndrome in readiness for precision medicine trials.MethodsEpilepsy patients were recruited to the University of Melbourne Epilepsy Genetics Research Program between 1995 and 2020 by neurologists from around the world. Patients with SCN1A pathogenic variants were reviewed and only those with Dravet syndrome were included. Clinical data, including seizure and developmental course, were analyzed in all patients with SCN1A‐Dravet syndrome.ResultsTwo hundred and five patients were studied at a median age of 8.5 years (range 10 months to 60 years); 25 were deceased. The median seizure‐onset age was 5.7 months (range 1.5–20.6 months). Initial seizures were tonic‐clonic (52%) and hemiclonic (35%), with only 55% being associated with fever. Only 34% of patients presented with status epilepticus (seizure lasting ≥30 minutes). Median time between first and second seizure was 30 days (range 4 hours to 8 months), and seven patients (5%) had at least 6 months between initial seizures. Median ages at onset of second and third seizure types were 9.1 months (range 3 months–25.4 years) and 15.5 months (range 4 months–8.2 years), respectively. Developmental slowing occurred prior to 12 months in 27%.SignificanceAn evidence‐based definition of SCN1A‐Dravet syndrome is essential for early diagnosis. We refine the spectrum of Dravet syndrome, based on patterns of seizure onset, type, and progression. Understanding of the full spectrum of SCN1A‐Dravet syndrome presentation is essential for early diagnosis and optimization of treatment, especially as precision medicine trials become available.

P3. Significance of intracranial EEG parameters in prediction of seizure freedom

Introduction. In patients with focal drug-resistant epilepsy (DRE), intracranial electroencephalography (iEEG) with subdural electrodes (SDE) is used to delineate the seizure onset zone (SOZ) and to distinguish eloquent cortex areals, if non-invasive diagnostics did not yield conclusive results. Previous studies have shown ambiguous findings on the significance of iEEG parameters with respect to prediction of seizure freedom after resective epilepsy surgery. Most studies focused on subgroups of patients, such as those with frontal or temporal lobe epilepsy, or on some iEEG parameters, only. To that end, we comprehensively analyzed the significance of several iEEG parameters in one set of consecutive patients with DRE. Methods. All patients who had undergone invasive monitoring with SDE between 2005 and 2015 at our tertiary epilepsy center were included in this study 1 . We retrospectively analyzed iEEG parameters including seizure onset pattern (SOP), size of SOZ, latency to EEG seizure propagation and latency from clinical to EEG seizure onset. Furthermore, we assessed associations with post-operative seizure freedom, histopathology und brain region of SOZ. Results. Eighty-one patients (34 female) with 324 seizures were assessed. Low-voltage fast activity (LVFA, 37%) and sharp activity < 13 Hz (30%) were the most frequent SOPs. Focal SOZ (≤2 cm) was the only iEEG parameter independently associated with 1-year post-operative seizure freedom (OR 4.1, 95% CI 1.433–11.679). While no SOP was linked to specific histopathologies, LVFA was associated with temporal neocortical SOZ ( p < 0.01). Median latencies to EEG seizure propagation were significantly longer ( p < 0.001) in seizures originating from temporo-mesial SOZ (median 16.0 s) compared with temporo-neocortical (median 8.0 s) and frontal seizure onset (median 5.5 s). Also, latencies from clinical to EEG seizure onset were significantly longer ( p < 0.001) in seizures from temporo-mesial SOZ (median −20.0 s) compared with temporo-neocortical (median −12.0 s) and frontal seizure onset (median −6.0 s). Discussion. A focal EEG seizure onset but no specific SOP predicted seizure freedom after surgery. Also, different SOPs could be generated by the same histopathology and vice versa, putting clinical significance of SOPs into question. LVFA was associated with temporal neocortical seizure onset, possibly indicating a close-by seizure generator. Longer latencies until seizure spread and clinical signs or symptoms in seizures originating from temporo-mesial SOZ may be explained by inhibitory circuits in the hippocampus. Reference 1. Steinbart D, Steinbrenner M, Oltmanns F, Holtkamp M. Prediction of seizure freedom after epilepsy surgery – critical reappraisal of significance of intracranial EEG parameters. Clin Neurophysiol. 2020;131(11):2682-2690. doi:https://doi.org/10.1016/j.clinph.2020.08.018

WS1.6. Focal-Onset Seizures: Surface Ictal EEG Recordings and Localization

Ictal EEG can be identified by sustained electrographic discharges showing onsets and offsets being clearly distinguished from background rhythm, consisting of rhythmic discharges of variable frequencies and morphology showing gradual variations in frequency and amplitude. Morphology of ictal onset patterns in focal epilepsies are quite diverse and varies even in a same patient. For localizing purposes, onset patterns of ictal EEG are most important than following ictal discharges and they are topographically divided into focal, regional, lateralized, and diffuse. From the electrophysiological point of view, scalp ictal EEG in focal epilepsy requires a source area of synchronized EEG activities spreading over at least 10 cm2, indicating that an ictal onset usually reflects already spreaded activities from the EZ, thus the localization of EZ should not be based upon ictal EEG onset alone but should require its correlation with other investigations. Considering that scalp EEG reflects electrical activities from the cortical surface, ictal discharges arising from the EZ locating in deep sulci or deep cortical structures are not readily picked up by scalp EEG until they spread a significant distance to the cortical surface under the recording electrodes. Another caveat of ictal EEG is that the degree of synchronization is difficult to recognize from the surface EEG. In cases of poor synchrony, scalp EEG may not detect any clear focal or regional discharges but showing widely spread arrhythmic activities, thus fail to carry any localizing information. The lateralizing value of ictal scalp EEG seem to be higher in temporal lobe epilepsy than extratemporal lobe epilepsy, which were reported 76% to 83% and 47% to 65%, respectively. The probability of false lateralization was around 1% to 7% with remaining proportion of ictal EEG being unhelpful due to contamination by severe artifacts or diffuse discharges without focal features. The source localization of ictal onset rhythm by high-density EEG is an emerging technique that seems to perform similarly well to the source localization of interictal spike, which has been proved in large patient cohorts to be accurate and clinically relevant, with positive and negative predictive values rivaling those of structural MRI, although there remain questions regarding the processing of signals for reliable results. A further promising development in seizure onset localization is the inclusion of directed connectivity analysis: thus, not only the most active source is taken into consideration when localizing the onset of a seizure, but also how strongly each source broadcasts its activity to other brain regions (the so-called outgoing connections). Such an approach was shown to be more accurate than merely considering the most active source.

O-EG003. Can spike voltage topography predict the ictal patterns in temporal lobe epilepsy?

Introduction . To study whether voltage topographic analysis of interictal epileptiform discharges (IEDs) in temporal lobe epilepsy (TLE) help to predict the type of scalp ictal onset pattern. Methods . IEDs from 74 patients with drug resistant TLE and unilateral mesial temporal sclerosis (MTS) who underwent presurgical evaluation were categorized according to dipolar fields into Types A and B temporal IEDs. Type A IEDs were defined as those with dipolar fields (tangential/ vertical) with sharply defined negativity over the infero-lateral temporal scalp and positivity over contra lateral centro-parietal scalp. Type B IEDs included all other IEDs other than Type A. Scalp ictal electrographic patterns were classified into rhythms confined to temporal lobe ipsilateral to MTS (“focal”), lateralized to the hemisphere (“regional”), and diffuse, nonlateralized and non-localized rhythms (“diffuse”) and ictal onset to the contra lateral side of MTS (“discordant”). Results . A total of 5476 IEDs and 377 seizures were analyzed. They were divided into four categories based on the side of MTS: 1) Type A IEDs ipsilateral to MTS (44 patients); 2) bilateral Type A IEDs (16 patients); 3) Type B IEDs ipsilateral and Type A IEDs contra laterally (7 patients); 4) Bilateral type B IEDs (7 patients). In 51 of 60 (85%) patients with Type A IEDs (either ipsilateral and/or bilateral to MTS), the ictal pattern was either focal or regional and only in 9 patients (15%) it was “diffuse”.12 of 14 (86%) patients with either ipsilateral or bilateral Type B IEDs showed a diffuse ictal onset, whereas 2 (14%) showed a contralateral ictal onset. Conclusion . In MTS, Type A IEDs are associated with clearly localized ictal onset and Type B IEDs with diffuse ictal onset. A spikevoltage topographic analysis is sufficient for selection of cases for antero-medial temporal lobe resection. Additional home-video recordings of seizures can rule out psychogenic non-epileptiform events.

The accuracy of quantitative EEG biomarker algorithms depends upon seizure onset dynamics

ObjectiveTo compare the performance of different ictal quantitative biomarkers of the seizure onset zone (SOZ) across many seizures in a cohort of consecutive patients with a variety of seizure onset patterns. MethodsThe Epileptogenicity Index (EI, a measure of fast activity) and Slow Polarizing Shift index (SPS, a measure of infraslow activity) were calculated for 212 seizures (22 patients). After stratification by onset pattern, median index values inside and outside the SOZ were compared in aggregate and for each of the onset patterns. Receiver Operating Characteristic (ROC) curves were constructed to compare the performance of each index. ResultsMedian values of EI (0.056 vs 0.0087), SPS (0.27 vs 0.19), and CI (0.21 vs 0.12) were significantly higher for contacts inside the SOZ, all p < 0.0001. Analysis of AUC showed variable performance of these indices across seizure types, although AUC for EI and SPS was generally greatest for seizures with fast activity at onset. ConclusionsAll indices were significantly higher for contacts inside the SOZ; however, the performance of these indices varied depending on the pattern of seizure onset. SignificanceThese findings suggest that future studies of quantitative biomarkers of the SOZ should account for seizure onset pattern.

Altered ripple density inside seizure onset zone in patients with focal cortical dysplasia-associated epilepsy.

PurposeTo evaluate the clinical and stereoelectroencephalography (SEEG) features and postsurgical outcome in a uniform series of patients who underwent epilepsy surgery and had pathologically confirmation of focal cortical dysplasia (FCD).MethodsWe studied consecutive patients with drug‐refractory epilepsy who underwent SEEG recording. The high‐frequency oscillations (HFOs) features of SEEG, clinical characteristics, and surgical outcome were evaluated.ResultsSixty patients (31 FCD type I, 13 II, and 16 III) were analyzed retrospectively. Patients with type II tended to have their seizures at an earlier age than those with I and III (p < .01). Six different ictal onset patterns (IOPs) were identified. In patients with temporal lobe epilepsy (TLE), the most common patterns were rhythmic spikes or spike waves and LFRS, and in patients with extratemporal epilepsy, the most common patterns were low‐voltage fast activity (LVFA) and rhythmic spikes or spike waves. In addition, ripple density was found to increase significantly from the interictal to ictal onset sections and from the ictal onset to ictal evolution sections in patients with FCD I (p < .001). Regarding the distinct IOPs, ripple density continued to increase significantly between the interictal and ictal onset sections in LVFA, rhythmic spikes or spike waves, and burst of high‐amplitude polyspikes (p < .05). Ripple density decreased between ictal onset and ictal evolution sections in patterns of LVFA and rhythmic spikes or spike waves (p < .05). The mean follow‐up duration was 2.7 years (range 1–4.2), and 66.7% (n = 40) were class I. Patients with subtypes III and II had favorable surgical outcome than those with I.ConclusionThe clinical expression of seizure may depend on the pathological types with FCD II patients exhibiting their seizures at an earlier age. Distinct IOPs may demonstrate different ripple features and distinguishing the IOPs is very necessary to have an insight into the electrophysiological characteristics.

Deciphering the Great Mimicker.

Mapping the Insula With Stereo-Electroencephalography: The Emergence of Semiology in Insula Lobe Seizures Singh R, Principe A, Tadel F, et al. Ann Neurol. 2020;88(3):477-488. PMID: 32542728. doi:10.1002/ana.25817Objective:Insula epilepsy is rare and can be evaluated effectively by stereotactic intracerebral electroencephalography. Many previous studies of insulo-opercular seizures have been unable to separate insular and opercular onset. With adequate sampling of the insula, this study shows this is possible.Methods:We analyzed intrainsular dynamics and extrainsular propagation in 12 patients with “pure” insula epilepsy (n = 9) or insular and only deepest opercular involvement (n = 3) at seizure onset. Review of semiology defined clinical groups, agglomerative cluster, and principal component analysis of semiological features were performed. Quantitative epileptogenicity and intrainsular and extrainsular propagation were computed via time frequency analysis and epileptogenicity mapping.Results:Seizure-onset patterns were heterogeneous; the seizure-onset zone was focal. Seizure-onset and first ictal change within insula functional subdivision correlated with aura and reflex component. No paninsular spread occurred; contralateral insular spread was very early. While the discharge was intrainsular, clinical signs were related to aura or vegetative signs. Extrainsular propagation was early and related to the emergence of the majority of clinical signs. Cluster analysis found an anterior, intermediate, and posterior insula seizure-onset group. The largest principal component separated anterior insula manifestations, including early hypermotor signs, early recovery, and no aura from posterior insula features of early dystonia, early tonic motor features, and sensorimotor aura.Interpretation:Aura is vital to identifying seizure onset and relates to insula functional subdivision. Seizures are heterogenous; extrainsular propagation occurs early, accounting for most of the semiology. With adequate sampling, “pure” insula epilepsy can be identified and focal curative resection is possible.