Interictal Epileptiform Discharges Research Articles

Dynamics of Electrical Activity in Epileptic Brain and Induced Changes Due to Interictal Epileptiform Discharges

Dynamics of Electrical Activity in Epileptic Brain and Induced Changes Due to Interictal Epileptiform Discharges

Automated spike detection: Which software package?

PurposeWe assessed three commercial automated spike detection software packages (Persyst, Encevis and BESA) to see which had the best performance. MethodsThirty prolonged EEG records from people aged at least 16 years were collected and 30-minute representative epochs were selected. Interictal epileptiform discharges (IEDs) were marked by three human experts and by all three software packages. For each 30-minutes selection and for each 10-second epoch we measured whether or not IEDs had occurred. We defined the gold standard as the combined detections of the experts. Kappa scores, sensitivity and specificity were estimated for each software package. ResultsSensitivity for Persyst in the default setting was 95% for 30-minute selections and 82% for 10-second epochs. Sensitivity for Encevis was 86% (30-minute selections) and 61% (10-second epochs). The specificity for both packages was 88% for 30-minute selections and 96%-99% for the 10-second epochs. Interrater agreement between Persyst and Encevis and the experts was similar than between experts (0.67–0.83 versus 0.63–0.67). Sensitivity for BESA was 40% and specificity 100%. Interrater agreement (0.25) was low. ConclusionsIED detection by the Persyst automated software is better than the Encevis and BESA packages, and similar to human review, when reviewing 30-minute selections and 10-second epochs. This findings may help prospective users choose a software package.

Temporal Lobe Spikes Affect Distant Intrinsic Connectivity Networks.

Objective: To evaluate local and distant blood oxygen level dependent (BOLD) signal changes related to interictal epileptiform discharges (IED) in drug-resistant temporal lobe epilepsy (TLE).Methods: Thirty-three TLE patients undergoing EEG–functional Magnetic Resonance Imaging (fMRI) as part of the presurgical workup were consecutively enrolled. First, a single-subject spike-related analysis was performed: (a) to verify the BOLD concordance with the presumed Epileptogenic Zone (EZ); and (b) to investigate the Intrinsic Connectivity Networks (ICN) involvement. Then, a group analysis was performed to search for common BOLD changes in TLE.Results: Interictal epileptiform discharges were recorded in 25 patients and in 19 (58%), a BOLD response was obtained at the single-subject level. In 42% of the cases, BOLD changes were observed in the temporal lobe, although only one patient had a pure concordant finding, with a single fMRI cluster overlapping (and limited to) the EZ identified by anatomo-electro-clinical correlations. In the remaining 58% of the cases, BOLD responses were localized outside the temporal lobe and the presumed EZ. In every patient, with a spike-related fMRI map, at least one ICN appeared to be involved. Four main ICNs were preferentially involved, namely, motor, visual, auditory/motor speech, and the default mode network. At the single-subject level, EEG–fMRI proved to have high specificity (above 65%) in detecting engagement of an ICN and the corresponding ictal/postictal symptom, and good positive predictive value (above 67%) in all networks except the visual one. Finally, in the group analysis of BOLD changes related to IED revealed common activations at the right precentral gyrus, supplementary motor area, and middle cingulate gyrus.Significance: Interictal temporal spikes affect several distant extra-temporal areas, and specifically the motor/premotor cortex. EEG–fMRI in patients with TLE eligible for surgery is recommended not for strictly localizing purposes rather it might be useful to investigate ICNs alterations at the single-subject level.

Epilepsy Centers in the United States

The modern era of epilepsy surgery began at Queen's Square in the 1880s. Resections were directed by semiology alone and outcomes were improved through a meticulous surgical approach. The first EEG recordings of interictal epileptiform discharges were recorded in the 1930s. During the 1940s and 1950s, interictal EEG findings were used to plan temporal lobectomies. In the 1970s, the advent of CT imaging and routine preoperative video EEG monitoring revolutionized the approach to the evaluation for epilepsy surgery. Subsequent developments of MRI, PET, laser resections, stimulation therapies, and other advances have continued to optimize preoperative and surgical approaches in the management of drug-resistant epilepsy (DRE).

Higher-order tensor decomposition based scalp-to-intracranial EEG projection for detection of interictal epileptiform discharges

Objective. Interictal epileptiform discharges (IEDs) occur between two seizures onsets. IEDs are mainly captured by intracranial recordings and are often invisible over the scalp. This study proposes a model based on tensor factorization to map the time-frequency (TF) features of scalp EEG (sEEG) to the TF features of intracranial EEG (iEEG) in order to detect IEDs from over the scalp with high sensitivity. Approach. Continuous wavelet transform is employed to extract the TF features. Time, frequency, and channel modes of IED segments from iEEG recordings are concatenated into a four-way tensor. Tucker and CANDECOMP/PARAFAC decomposition techniques are employed to decompose the tensor into temporal, spectral, spatial, and segmental factors. Finally, TF features of both IED and non-IED segments from scalp recordings are projected onto the temporal components for classification. Main results. The model performance is obtained in two different approaches: within- and between-subject classification approaches. Our proposed method is compared with four other methods, namely a tensor-based spatial component analysis method, TF-based method, linear regression mapping model, and asymmetric–symmetric autoencoder mapping model followed by convolutional neural networks. Our proposed method outperforms all these methods in both within- and between-subject classification approaches by respectively achieving 84.2% and 72.6% accuracy values. Significance. The findings show that mapping sEEG to iEEG improves the performance of the scalp-based IED detection model. Furthermore, the tensor-based mapping model outperforms the autoencoder- and regression-based mapping models.

Prognostic implications of persistent interictal epileptiform discharges on antiseizure medication withdrawal in patients with epilepsy in five-year remission

PurposeWhether patients with epilepsy in long-term remission and interictal epileptiform discharges (IEDs) can stop antiseizure medication (ASM) remains a challenging topic even though multiple studies have investigated ASM withdrawal. This study aimed to estimate seizure relapse and its risk factors in patients with epilepsy in five-year remission and persistent IEDs. MethodsPatients with epilepsy and persistent IEDs were prospectively recruited from the Affiliated Nanjing Brain Hospital of Nanjing Medical University from Dec.1, 2010 to Dec.30, 2019. All enrolled patients achieved seizure remission for over five years and were divided into the ASM withdrawal and continuous treatment groups according to their personal preference. Seizure outcomes and 24 h video electroencephalogram findings were obtained through clinical visits or telephone interviews every three months until March 31, 2021. The cumulative recurrence rate and its diversity between the ASM withdrawal and continuous treatment groups were tested using Kaplan–Meier analysis. Multivariate Cox regression analysis was performed to explore the independent predictors for seizure recurrence. Relapsed patients were further monitored for their seizure control and prognosis. ResultsA total of 83 patients with epilepsy in five-year remission and persistent IEDs were enrolled in this study, including 41 (49.4%) in the ASM withdrawal group and 42 (50.6%) in the continuous ASM treatment group. During the follow-up with a median time of 36.8 months (range from 18.7 to 104.6 months), the seizure relapse in off-medication patients (43.9%, 18/41) was higher than that in on-medication patients (21.4%, 9/42; P = 0.031). In the multivariate analysis model, independent predictors for seizure recurrence were structural-metabolic epilepsy or unknown cause (HR = 6.185, 95% CI 1.166–32.805) and multiple seizure types (HR = 2.807, 95% CI 1.051–7.502). ASM withdrawal was not found to be an independent risk factor for seizure recurrence. Of 27 patients with seizure recurrence, 25 were given reinstitution or continuous ASM therapy, whereas two chose sustained observation without medication. At the end of the follow-up, 70.4% (19/27) of recurrence patients were completely free from seizures for at least one year again, and only one patient developed refractory epilepsy. ConclusionFor patients with epilepsy in five-year remission and persistent IEDs, drug withdrawal may be a rational choice after the individualized assessment of benefits and risks. Furthermore, the independent risk factors for the seizure relapse were structural-metabolic epilepsy or an unknown cause, and multiple seizure types. Finally, patients with epilepsy relapsing after ASM withdrawal could achieve seizure remission again after ASM retreatment.

Spike-Associated Networks Predict Postsurgical Outcomes in Children With Refractory Epilepsy.

Up to half of the children undergoing epilepsy surgery will continue to have seizures (szs) despite a cortical resection or ablation. Functional connectivity has shown promise in better identifying the epileptogenic zone. We hypothesized that cortical areas showing high information outflow during interictal epileptiform discharges are part of the epileptogenic zone. We identified 22 children with focal epilepsy who had undergone stereo electroencephalography, surgical resection or ablation, and had ≥1 year of postsurgical follow-up. The mean phase slope index, a directed measure of functional connectivity, was calculated for each electrode contact during interictal epileptiform discharges. The positive predictive value and negative predictive value for a sz-free outcome were calculated based on whether high information outflow brain regions were resected. Resection of high outflow (z-score ≥ 1) and very high outflow (z-score ≥ 2) electrode contacts was associated with higher sz freedom (high outflow: χ 2 statistic = 59.1; P < 0.001; very high outflow: χ 2 statistic = 31.3; P < 0.001). The positive predictive value and negative predictive value for sz freedom based on resection at the electrode level increased at higher z-score thresholds with a peak positive predictive value of 0.86 and a peak negative predictive value of 0.9. Better identification of the epileptogenic zone has the potential to improve epilepsy surgery outcomes. If the surgical plan can be modified to include these very high outflow areas, more children might achieve sz freedom. Conversely, if deficits from resecting these areas are unacceptable, ineffective surgeries could be avoided and alternative therapies offered.

Early and Bi-hemispheric seizure onset in a rat glioblastoma Multiforme model

GBM is the most life-threatening neurological disease with annual incidence of ∼ 5 cases per 100,000 people and a median survival of less than 15 months. Seizures are the first clinical symptoms in 40%-45% of patients with GBM and its epileptogenic mechanisms are poorly understood, largely due to the challenge to develop a clinically-relevant animal model and the unknown latent period. In this study, we used continuous video-EEG monitoring to detect the earliest interictal and ictal events in a CRISPR- IUE GBM rat model that shares pathological and clinical features with those observed in human patients. To our best knowledge, we showed for the first time that interictal epileptiform discharges emerged during early postnatal weeks and the first ictal event occurred during the fourth postnatal week. We also showed GBM animals showed independent bi-hemispheric epileptogenic events, suggesting a widespread circuitry dysregulation. Together, our work identified the temporal- and spatial frame of epileptogenic network in a highly clinically-relevant GBM animal model, paving ways for mechanistic studies at molecular, cellular and circuitry levels.

Diagnostic Yield of Five Minutes Compared to Three Minutes Hyperventilation During Electroencephalography in Children.

Purpose: To investigate whether hyperventilation (HV) for 5 minutes increases the diagnostic yield of electroencephalography (EEG) compared to 3 minutes HV and to determine whether performing HV for 5 minutes is feasible and safe in children. Methods: Data were evaluated from 579 children aged less than 18 years, referred to EEG for epilepsy evaluation. Occurrence of seizures, HV induced interictal epileptiform discharges precipitation and potentiation and adverse events if any were noted during the first 3 minutes and last 2 minutes of HV separately. Results: 398 children (68.7%) completed 5 minutes HV. Seizures were precipitated during the first 3 minutes of HV in 2 children, and during the last 2 minutes in one more child. Inter-ictal EEG abnormalities were precipitated in the first 3 minutes of HV in 31 children, and during the last 2 min in 4 more children. All 398 children completed HV during the last 2 minutes successfully and no adverse events occurred during the last 2 minutes of HV. Conclusion: 33.33% of seizures and 11.5% of inter-ictal EEG abnormalities triggered by HV occurred during the last 2 min of HV. This finding supports the utility of prolonged hyperventilation for 5 minutes. Prolonged HV for 5 minutes increases the diagnostic yield of EEG in paediatric population and it is safe and feasible.

Interictal Activity Is Associated With Slower Binocular Rivalry in Idiopathic Generalized Epilepsy.

Objective: Perceptual alternations evoked by binocular rivalry (BR) reflect cortical dynamics strongly dependent on the excitatory–inhibitory balance, suggesting potential utility as a biomarker for epileptogenesis. Therefore, we investigated the characteristics of BR in patients with idiopathic generalized epilepsy (IGE) and potential associations with clinical variables.Methods: Sixty-two healthy controls (HCs) and 94 IGE patients completed BR task. Perceptual alternation rates were compared between HC and IGE groups as well as among the HC group and IGE patients stratified according to the presence or absence of interictal activity on the ambulatory electroencephalogram (EEG), termed the abnormal ambulatory EEG group (AB-AEEG, n = 64) and normal ambulatory EEG group (N-AEEG, n = 30), respectively.Results: The IGE patients demonstrated a slower rate of BR perceptual alternation than HC subjects (t = −4.364, p < 0.001). The alternation rate also differed among the HC, AB-AEEG, and N-AEEG groups (F = 44.962, df = 2, p < 0.001), and post hoc comparisons indicated a significantly slower alternation rate in the AB-AEEG group compared with the N-AEEG and HC groups (0.28 vs. 0.46, and 0.43 Hz). Stepwise linear regression revealed positive correlations between the BR alternation rate and both the ambulatory EEG status (β, 0.173; standard error, 0.022 p < 0.001) and Montreal Cognitive Assessment score (β, 0.013; standard error, 0.004; p = 0.003). Receiver operating characteristic curve analysis of the BR alternation rate distinguished AB-AEEG from N-AEEG subjects with 90.00% sensitivity and 76.90% specificity (area under the curve = 0.881; 95% confidence interval = 0.801– 0.961, cut-off = 0.319). Alternatively, Montreal Cognitive Assessment score did not accurately distinguish AB-AEEG from N-AEEG subjects and the area under the receiver operating characteristic curve combining the BR alternation rate and Montreal Cognitive Assessment score was not markedly larger than that of the BR alternation rate alone (0.894, 95% confidence interval = 0.822–0.966, p < 0.001). K-fold cross-validation was used to evaluate the predictive performance of BR alternation rate, MoCA score, and the combination of both, which yielded average AUC values of 0.870, 0.584 and 0.847, average sensitivity values of 89.36, 92.73, and 91.28%, and average specificity values of 62.25, 13.42, and 61.78%, respectively. The number of interictal epileptiform discharges was significantly correlated with the alternation rate in IGE patients (r = 0.296, p = 0.018). A forward stepwise linear regression model identified the number of interictal epileptiform discharges (β, 0.001; standard error, 0.001; p = 0.025) as an independent factor associated with BR alternation rate in these patients.Conclusion: These results suggest that interictal epileptiform discharges are associated with disruptions in perceptual awareness, and that the BR may be a useful auxiliary behavioral task to diagnosis and dynamically monitor IGE patients with interictal discharge.

Pilot study of focused ultrasound for drug-resistant epilepsy.

ObjectiveThe neuromodulatory effects of focused ultrasound (FUS) have been demonstrated in animal epilepsy models; however, the safety and efficacy of FUS in humans with epilepsy have not been well established. Patients with drug‐resistant epilepsy (DRE) undergoing stereo‐electroencephalography (SEEG) provide an opportunity to investigate the neuromodulatory effects of FUS in humans.MethodsPatients with DRE undergoing SEEG for localization of the seizure onset zone (SOZ) were prospectively enrolled. FUS was delivered to the SOZ using a neuronavigation‐guided FUS system (ceiling spatial‐peak temporal‐average intensity level = 2.8 W/cm2, duty cycle = 30%, modulating duration = 10 min). Simultaneous SEEG recordings were obtained during sonication and for 3 days after treatment. Seizures, interictal epileptiform discharges, and adverse events after FUS were monitored.ResultsSix patients met the eligibility criteria and completed FUS treatment. A decrease in seizure frequency was observed in two patients within the 3‐day follow‐up; however, one patient presented an increase in the frequency of subclinical seizures. Posttreatment magnetic resonance imaging revealed neither lesion nor brain edema. Significant changes in spectral power of SEEG were noted at the targeted electrodes during FUS treatment. One patient reported subjective scalp heating during FUS, and one patient developed transient naming and memory impairment that resolved within 3 weeks after FUS.SignificanceFUS can be safely delivered to the SOZ of patients with DRE, resulting in significant changes in spectral power of SEEG. A larger sample cohort and pursuing optimal sonication parameters will be required to elucidate the neuromodulatory effects of FUS when used for seizure control.

Clinical spectrum of pediatric drug refractory epilepsy secondary to parieto-occipital gliosis

BackgroundParieto-occipital (PO) gliosis secondary to perinatal insult, is often associated with neurologic sequelae such as epilepsy, which can be drug resistant. ObjectiveTo evaluate the spectrum of epilepsy among patients presenting with seizures in association with PO gliosis and to determine factors that influence the development of epileptic encephalopathy (EE) in these patients. MethodsWe retrospectively evaluated patients aged < 16 years with drug refractory epilepsy and PO gliosis who underwent video electroencephalography (Video EEG). We evaluated the clinical, electrophysiological and radiological profile including treatment responsiveness of subjects with EE. ResultsOne hundred one patients (M: F=3:1) with mean age of onset of epilepsy at 28.9 ± 33.1 months were recruited into the study. Based on video EEG findings, Based on video EEG findings, the commonest type of focal onset ictus was tonic seizures with impaired awareness (n = 26, 29.9%). Myoclonic jerks (n = 20, 23%) were the commonest type of generalised onset seizures. Ictal onset from parieto occipital region were observed in 28 patients. Ictal onset from frontal, temporal and fronto temporal region were observed in 6 (6.8%), 7(7.9%) and 9 (8.9%) patients, respectively. Comparison of the seizure types and ictal onset among subgroups of patients with occipital gliosis, parieto-occipital gliosis and parieto-occipital with frontal gliosis revealed that the extent of gliosis did not significantly affect seizure semiology or ictal onset. EE was significantly associated with presence of neonatal seizures (p = 0.04), hypoglycaemia (p = 0.005), longer duration of ICU stay (Z score = −3.55, p < 0.001) and younger age of onset of seizures (Z score = - 2.97, p = 0.03). Eleven out of eighteen (64.7%) subjects with EE showed greater than 50% improvement in seizure frequency following three months of pulse intravenous methylprednisolone therapy. ConclusionsAmong subjects with PO gliosis on MRI, the seizure semiology is unaffected by laterality, radiologic extension beyond the occipital cortex or presence of ulegyria. Patients with PO gliosis can have florid interictal epileptiform discharges anteriorly and can have seizures with ictal onset from frontal and temporal region. Development of EE is strongly related to the age of onset of seizures, neonatal seizures, prolonged NICU admission, rather than the radiological findings. Subjects with EE and PO gliosis show good response to intravenous pulse methylprednisolone.

Electric Source Imaging on Intracranial EEG Localizes Spatiotemporal Propagation of Interictal Spikes in Children with Epilepsy.

Interictal epileptiform discharges (IEDs) serve as sensitive but not specific biomarkers of epilepsy that can delineate the epileptogenic zone (EZ) in patients with drug resistant epilepsy (DRE) undergoing surgery. Intracranial EEG (icEEG) studies have shown that IEDs propagate in time across large areas of the brain. The onset of this propagation is regarded as a more specific biomarker of epilepsy than areas of spread. Yet, the limited spatial resolution of icEEG does not allow to identify the onset of this activity with high precision. Here, we propose a new method of mapping the spatiotemporal propagation of IEDs (and identify its onset) by using Electrical Source Imaging (ESI) on icEEG bypassing the spatial limitations of icEEG. We validated our method on icEEG recordings from 8 children with DRE who underwent surgery with good outcome (Engel score =1). On each icEEG channel, we detected IEDs and identified the propagation onset using an automated algorithm. We localized the propagation of IEDs with dynamic Statistical Parametric Mapping (dSPM) using a time-sliding window approach. We defined two brain regions: the ESI-onset and ESI-spread zone. We estimated the overlap of these regions with resection volume (in percentage), which served as the gold-standard of the EZ. We also estimated the mean distance of these regions from resection and clinically defined seizure onset zone (SOZ). We observed spatio-temporal propagation of IEDs in all patients across several channels (98 [85-102]) with a mean duration of 155 ms [96-186 ms]. A higher overlap with resection was seen for the ESI-onset zone compared to spread (73.3 % [ 47.4-100 %], 36.5 % [20.3-59.9 %], p = 0.008). The distance of the ESI-onset from resection was shorter compared to the ESI-spread zone (4.3 mm [3.4-5.5 mm], 7.4 mm [6.0-20.6 mm], p = 0.008) and the same trend was observed for the distance from the SOZ (11.9 mm [7.2-15.1 mm], 20.6 mm [15.4-27.2 mm], p = 0.02). These findings show that our method can map the spatiotemporal propagation of IEDs and de-lineate its onset, which is a reliable and focal biomarker of the EZ in children with DRE.Clinical Relevance - ESI on icEEG recordings of children with DRE can localize the spikes propagation phenomenon and help in the delineation of the EZ.

Mapping Functional Connectivity of Epileptogenic Networks through Virtual Implantation.

Children with medically refractory epilepsy (MRE) require resective neurosurgery to achieve seizure freedom, whose success depends on accurate delineation of the epileptogenic zone (EZ). Functional connectivity (FC) can assess the extent of epileptic brain networks since intracranial EEG (icEEG) studies have shown its link to the EZ and predictive value for surgical outcome in these patients. Here, we propose a new noninvasive method based on magnetoencephalography (MEG) and high-density (HD-EEG) data that estimates FC metrics at the source level through an "implantation" of virtual sensors (VSs). We analyzed MEG, HD-EEG, and icEEG data from eight children with MRE who underwent surgery having good outcome and performed source localization (beamformer) on noninvasive data to build VSs at the icEEG electrode locations. We analyzed data with and without Interictal Epileptiform Discharges (IEDs) in different frequency bands, and computed the following FC matrices: Amplitude Envelope Correlation (AEC), Correlation (CORR), and Phase Locking Value (PLV). Each matrix was used to generate a graph using Minimum Spanning Tree (MST), and for each node (i.e., each sensor) we computed four centrality measures: betweenness, closeness, degree, and eigenvector. We tested the reliability of VSs measures with respect to icEEG (regarded as benchmark) via linear correlation, and compared FC values inside vs. outside resection. We observed higher FC inside than outside resection (p<0.05) for AEC [alpha (8-12 Hz), beta (12-30 Hz), and broadband (1-50 Hz)] on data with IEDs and AEC theta (4-8 Hz) on data without IEDs for icEEG, AEC broadband (1-50 Hz) on data without IEDs for MEG-VSs, as well as for all centrality measures of icEEG and MEG/HD-EEG-VSs. Additionally, icEEG and VSs metrics presented high correlation (0.6-0.9, p<0.05). Our data support the notion that the proposed method can potentially replicate the icEEG ability to map the epileptogenic network in children with MRE.Clinical Relevance - The estimation of FC with noninvasive techniques, such as MEG and HD-EEG, via VSs is a promising tool that would help the presurgical evaluation by delineating the EZ without waiting for a seizure to occur, and potentially improve the surgical outcome of patients with MRE undergoing surgery.

P.125 Discriminating sharp-wave ripples and interictal epileptiform discharges in patients with mesial temporal epilepsy using intracranial EEG recordings

Background: Interictal epileptiform discharges (IEDs) are known as epilepsy biomarkers for seizure detection, and It is essential for clinicians to detect them from from physiological events with similar temporal frequency characteristics. Methods: We analyzed the SEEG recordings obtained from patients with medically-resistant epilepsy (MRE) implanted with DE at the Western University Hospital Epilepsy Unit. The data were cleaned, denoised, montaged and segmented based on the clinical annotations, such as sleep intervals and observed Ictals. For event detection, the signal waveform and its power were extracted symmetrically in non-overlapping intervals of 500 ms. Each waveform’s power across all detected spikes was computed and clustered based on their energy distributions. Results: The recordings included thirteen sessions of 24 hours of extracellular recordings from two patients, with 312 hours extracted from four hippocampus electrodes anterior and posterior hippocampus. Our results indicate IEDs carrying the most different characteristics in the bands [25-75] Hz; SWR, on the other hand, are distributed between [80-170] Hz. Conclusions: Our algorithm detected and successfully distinguished IED from SWRs based on their carrying energy during non-sleep periods. Also, the most powerful spectral features that they were distinguished from occur in [15-30] Hz and [75-90] Hz.

A STUDY ON COMPARATIVE YIELDS OF STANDARD SHORT TERM ELECTROENCEPHALOGRAM AND LONG TERM ELECTROENCEPHALOGRAM RECORDING IN SUSPECTED EPILEPSY PATIENTS

Objective: To compare the yield of interictal epileptiform discharges on prolonged (1-2 hours) electroencephalogram (EEG) as compared to standard routine (30 minutes) electroencephalogram (EEG).&#x0D; Study Design: Comparative observational study.&#x0D; Place and Duration of Study: Pak Emirates Military Hospital, Rawalpindi from Oct 2019 to Sep 2020.&#x0D; Methodology: A total of 364 outdoor patients with suspected epilepsy were recruited for the study. Out of these 55 electroencephalograms were excluded after applying exclusion criteria and 309 were included for final analysis. Electro-encephalograms were recorded using a 10-20 international system of electrode placement. The duration of each standard electroencephalogram was 30 minutes. It was followed by recording for an extended period of 60 minutes at least. The time to the appearance of the first abnormal interictal epileptiform discharge was noted. For analytical purposes, epileptiform discharges were classified as “early” if they appeared within the first 30 minutes and as “late” if appeared afterward. All electro-encephalograms were evaluated independently by two neurologists.&#x0D; Results: A total of 309 electroencephalograms were included for final analysis. Interictal epileptiform discharges were seen in 48 (15.6%) recordings. The mean time to appearance of first interictal epileptiform discharge was 14.6 ± 19.09 minutes. In 36 (11.7%) cases, discharges appeared early (within the first 30 minutes) whereas in the remaining 12 (3.9%) cases, discharges appeared late. This translates into a 33% increase in the diagnostic yield of electroencephalogram with an extended period of recording.&#x0D; Conclusion: Extending the electroencephalogram recording time results in a significantly better diagnostic yield of outdoor electroencephalogram.

Relative Source Power: A novel method for localizing epileptiform EEG discharges

ObjectiveTo validate relative source power (RSP) imaging of extratemporal interictal epileptiform discharges (IEDs). MethodsThe accuracy of RSP was validated in a cohort of patients with extratemporal focal epilepsy and a confined epileptogenic lesion (<19 cm3) using distance to the lesion, concordance with resected area and postoperative outcome. Performance was compared with three conventional methods: voltage maps, equivalent current dipole and a distributed source model. ResultsThirty-three of 41 consecutive patients (80%) had IED averages suitable for analysis. While the peak negativity in voltage maps localized above the epileptogenic lesion only in 18 cases, RSP-maps matched in 29 cases (88%, p < 0.0026). Source localization showed a median distance of 9.8 mm from the lesion. Source-regions with 20 mm radius included 98% of all source-to-lesion distances. In the 21 surgical cases, outcome showed a sensitivity of 82.35% and specificity of 50% without significant differences between the three source imaging methods. ConclusionsRSP-maps provide a rapid, intuitive and more accurate source estimation than voltage maps. At sublobar level, RSP localizes with an accuracy similar to conventional methods and results of previous studies. SignificanceThe definition of a source region with 20 mm radius helps in guiding further exploration in extratemporal focal epilepsy.

Reiterating the role of corpus callosum in generalization of interictal and ictal epileptiform discharges: a case report with post-callosotomy intracranial electroencephalography in Lennox–Gastaut syndrome

Lennox–Gastaut syndrome (LGS) is an epileptic encephalopathy characterized by delayed mental development and intractable multiple seizure types, predominantly tonic. Drop attacks are the commonest and the most disabling type of seizures. Resective surgery is often not possible in LGS as the electroencephalogram (EEG) abnormalities are usually multifocal and generalized, and magnetic resonance image is often either normal or multilesional. We report a case of LGS with bilateral parieto-occipital gliosis where EEG before and after callosotomy demonstrated synchronized bilateral interictal epileptiform discharges and ictal discharges becoming desynchronized and running down. This phenomenon emphasizes the role of the corpus callosum in secondary bilateral synchrony.

AiED: Artificial intelligence for the detection of intracranial interictal epileptiform discharges

ObjectiveDeep learning provides an appealing solution for the ongoing challenge of automatically classifying intracranial interictal epileptiform discharges (IEDs). We report results from an automated method consisting of a template-matching algorithm and convolutional neural network (CNN) for the detection of intracranial IEDs (“AiED”). Methods1000 intracranial electroencephalogram (EEG) epochs extracted randomly from 307 subjects with refractory epilepsy were annotated independently by two expert neurophysiologists. These annotated epochs were divided into 1062 two-second epochs with IEDs and 1428 two-second epochs without IEDs, which were transformed into spectrograms prior to training the neural network. The highest performing network was validated on an annotated external test set. ResultsThe final network had an F1-score of 0.95 (95% CI: 0.91–0.98) and an average Area Under the Receiver Operating Characteristic of 0.98 (95% CI: 0.96–1.00). For the external test set, it showed an overall F1-score of 0.71, correctly identifying 100% of all high-amplitude IED complexes, 96.23% of all high-amplitude isolated IEDs, and 66.15% of all IEDs of atypical morphology. ConclusionsTemplate-matching combined with a CNN offers a fast, robust method for detecting intracranial IEDs. Significance“AiED” is generalizable and achieves comparable performance to human reviewers; it may support clinical and research EEG analyses.

Efficacy of cathodal transcranial direct current stimulation on electroencephalographic functional networks in patients with focal epilepsy: Preliminary findings

BackgroundNeuromodulation is a promising therapeutic alternative for epilepsy. We aimed to explore the efficacy and safety of cathodal transcranial current direct stimulation (ctDCS) on electroencephalographic functional networks in focal epilepsy. MethodsA sham-controlled, double-blinded, randomized study was conducted on 25 participants with focal epilepsy who underwent a 5-day, −1.0 mA, 20 min ctDCS, which targeted at the most active interictal epileptiform discharge (IED) region. We examined the electroencephalograms (EEGs) at baseline, immediately and at 4 weeks following ctDCS. The graph theory-based brain networks were established through time-variant partial directed coherence (TVPDC), and were calculated between each pair of EEG signals. The functional networks were characterized using average clustering coefficient, characteristic path length, and small-worldness index. The seizure frequencies, IEDs, graph-theory metrics and cognitive tests were compared. ResultsPreliminary findings indicated an IED reduction of 30.2% at the end of 5-day active ctDCS compared to baseline (p < 0.10) and a significant IED reduction of 33.4% 4 weeks later (p < 0.05). In terms of the EEG functional network, the small-worldness index significantly reduced by 3.5% (p < 0.05) and the characteristic path length increased by 1.8% (p < 0.10) at the end of the session compared to the baseline. No obvious change was found in the seizure frequency during follow-up (p > 0.05). The Mini-Mental State Examination (MMSE) showed no difference between the active and sham groups (p > 0.05). No severe adverse reactions were observed. ConclusionsIn focal epilepsy, the 5-day consecutive ctDCS may potentially decrease the IEDs and ameliorate the EEG functional network, proposing a novel personalized therapeutic scenario for epilepsy.