Epileptogenic Area Research Articles

Awake surgery with mapping-based resection to treat focal epilepsy in eloquent brain areas.

Resective surgery is a potential therapeutic option for select patients with intractable focal epilepsy. However, the presence of ictal onset zones within or surrounding highly functional brain areas presents a surgical challenge, leading to poor seizure and functional outcomes. This report describes our experiences with awake mapping-tailored resection of epileptogenic areas involving eloquent cortices and evaluates their feasibility, tolerance, limitations, and significance. The study included patients who underwent surgery for drug-resistant focal epilepsy at our center under awake conditions. The surgical approach aimed to achieve maximum resection of preoperatively defined epileptogenic zones, considering the boundaries defined by surrounding functional areas. We collected data on preoperative evaluations, intraoperative tests and seizures, postoperative status epilepticus, and neurological functional outcomes. We included 22 patients, 10 of whom had non-lesional epilepsy. Language, motor function, and sensory function were at risk in 19, 9, and 4 patients, respectively. Resection was performed as planned in 14 (63.6%) patients, while modifications were necessary in 8 (36.4%) patients due to functional constraints. The mean follow-up duration was 29.8months. Sixteen (72.7%) patients achieved Engel class Ia outcomes, indicating seizure freedom, while none of the patients experienced clinically significant permanent postoperative neurological deficits. Resective surgery with intraoperative brain mapping under awake conditions was a valid treatment option for achieving a cure in cases of drug-resistant focal epilepsy, even in situations in which the condition is considered inoperable due to the risk of significant postoperative neurological deficits.

1135 Classification of Temporal Lobe Epilepsy Anatomo-clinico-electrical Hypotheses: A Stereo EEG Study

INTRODUCTION: Temporal lobe epilepsy (TLE) has historically been divided into mesial and lateral (neocortical) TLE, but electrophysiological, semiological, and anatomical evidence indicate that the epileptogenic zone (EZ) and areas of propagation involve both temporal and extratemporal structures. Hypothesis-driven, structured interrogation is crucial for a successful stereo EEG (SEEG) exploration and subsequent successful surgical intervention. METHODS: 59 patients (ages 19-77) with drug-resistant TLE underwent SEEG at our institution from 2020-2022. We retrospectively reviewed each patient’s multidisciplinary discussions, history, imaging, and outcomes. We proposed four types of implantation hypotheses: temporal, temporal/basal/occipital, anterior perisylvian, and perisylvian. We quantitatively validated these types against anatomic coverage and semiology using unsupervised clustering and clinically by comparing classification to rates of successful localization of the epileptogenic zone (EZ) and seizure outcomes. RESULTS: Temporal (only) hypotheses were the least frequent (13.6%), followed by temporal/basal/occipital (25.4%), anterior perisylvian (30.5%), and perisylvian (30.5%). The hypotheses were not different in age at SEEG (p = 0.32), sex (p = 0.67), and handedness (p = 0.33). Frequent semiological features by type were: temporal – autonomic features, dÉjÀ vu; temporal/basal/occipital – visual and language disturbance; anterior perisylvian – oromotor; perisylvian – sensory manifestation. Clustering was validated against semiology (RI = 0.63) and lobar coverage (RI = 0.73). Successful localization of the EZ occurred in 79.7% and did not associate with hypothesis type (p = 0.22). Hypothesis type (p = 0.30) or EZ localization (p = 1.00) did not associate with the presence of an MRI lesion. 6-month Engel 1a rate was 71% and did not vary by hypothesis type (p = 0.29). CONCLUSIONS: The anatomo-clinico-electrical hypotheses in TLE must consider both temporal and extratemporal structures and not be limited by a medial vs. lateral TLE mindset. This proposed classification of TLE hypotheses can serve as starting point for multidisciplinary patient discussion as well as a tool to compare SEEG exploration and outcomes across centers.

DCT based multi-head attention-BiGRU model for EEG source location

Electroencephalogram source imaging (ESI) pertains to localize brain sources. Due to the one-to-many relationship between electroencephalogram (EEG) signals and brain sources, ESI becomes a complex inverse problem with poor conditioning, leaving a lot of research space. This article proposes an enhanced multi-head attention (MA) and discrete cosine transform (DCT) based Bidirectional Gated Recurrent Unit (BiGRU) (MA-DCT-BiGRU for short) for addressing the EEG inverse problem. Initially, EEG signal characteristics are captured employing multi-head attention with the inclusion of average hidden states. Then, the DCT is used to project brain source signals into the low, medium, and high frequency subspaces composed of spatial frequency basis vectors. The spatial low-frequency component serves as a filter for extended source reconstruction. Subsequently, BiGRU is employed to learn the mapping from the output of the attention layer to the low frequency DCT coefficients of the brain-derived signals. The simulation results undeniably establish the superiority of the MA-DCT-BiGRU configuration in comparison to other state-of-the-art (SOA) methods for source recovery, irrespective of the source modes and signal-to-noise ratio conditions. Experimental results, utilizing both synthetic and actual epilepsy data, clearly demonstrate the effectiveness of the framework presented in this article for epileptogenic area localization.

Thermosensitive/thermochromic silicone and infrared thermography mapping in 60 consecutive cases of epilepsy surgery.

Epilepsy surgery represents a therapeutic opportunity for those patients who do not respond to drug therapy. However, an important challenge is the precise identification of the epileptogenic area during surgery. Since it can be hard to delineate, it makes it necessary to use auxiliary tools as a guide during the surgical procedure. Electrocorticography (ECoG), despite having shown favorable results in terms of reducing post-surgical seizures, have certain limitations. Brain mapping using infrared thermography mapping and a new thermosensitive/thermochromic silicone (TTS) in epilepsy surgery has introduced a new resource of noninvasive and real-time devices that allow the localization of irritative zones. Sixty consecutive patients with drug-resistant epilepsy with surgical indications who decided to participate voluntarily in the study were included in the study. We measured brain temperature using two quantitative methods and a qualitative method: the TTS sheet. In all cases, we used ECoG as the gold standard to identify irritative areas, and all brain tissue samples obtained were sent to pathology for diagnosis. In the subgroup in which the ECoG detected irritative areas (n = 51), adding the results in which there was a correlation with the different methods, the efficiency obtained to detect irritative areas is 94.11% (n = 48/51, P ≤ 0.0001) while the infrared thermography mapping method independently has an efficiency of 91.66% (P ≤ 0.0001). The TTS has a sensitivity of 95.71% and a specificity of 97.9% (P ≤ 0.0001) to detect hypothermic areas that correlate with the irritative zones detected by ECoG. No postoperative infections or wound dehiscence were documented, so the different methodologies used do not represent an additional risk for the surgical proceedings. We consider that the infrared thermography mapping using high-resolution infrared thermography cameras and the TTS are both accurate and safe methods to identify irritative areas in epilepsy surgeries.

Effects of midazolam on high-frequency oscillations in amygdala and hippocampus of epilepsy patients.

High-frequency oscillations (HFOs) are associated with normal brain function, but are also increasingly recognized as potential biomarkers of epileptogenic tissue. Considering the important role of interneuron activity in physiological HFO generation, we studied their modulation by midazolam (MDZ), an agonist of γ-aminobutyric acid type A (GABAA)-benzodiazepine receptors. Here, we analyzed 80 intracranial electrode contacts in amygdala and hippocampus of 13 patients with drug-refractory focal epilepsy who had received MDZ for seizure termination during presurgical monitoring. Ripples (80-250 Hz) and fast ripples (FRs; 250-400 Hz) were compared before and after seizures with MDZ application, and according to their origin either within or outside the individual seizure onset zone (SOZ). We found that MDZ distinctly suppressed all HFOs (ripples and FRs), whereas the reduction of ripples was significantly less pronounced inside the SOZ compared to non-SOZ contacts. The rate of FRs inside the SOZ was less affected, especially in hippocampal contacts. In a few cases, even a marked increase of FRs following MDZ administration was seen. Our results demonstrate, for the first time, a significant HFO modulation in amygdala and hippocampus by MDZ, thus giving insights into the malfunction of GABA-mediated inhibition within epileptogenic areas and its role in HFO generation.

Clinical and anatomical analysis of the epileptogenic spread patterns in focal cortical dysplasia patients.

Focal cortical dysplasia (FCD) is one of the main causes of intractable epilepsy, which is amendable by surgery. During the surgical management of FCD, the understanding of its epileptogenic foci, interconnections, and spreading pathways is crucial for attaining a good postoperative seizure free outcome. We retrospectively evaluated 54 FCD patients operated in Federal Center of Neurosurgery, Tyumen, Russia. The electroencephalogram findings were correlated to the involved brain anatomical areas. Subsequently, we analyzed the main white matter tracts implicated during the epileptogenic spreading in some representative cases. We prepared 10 human hemispheres using Klinger's method and dissected them through the fiber dissection technique. The clinical results were displayed and the main white matter tracts implicated in the seizure spread were described in 10 patients. Respective FCD foci, interconnections, and ectopic epileptogenic areas in each patient were discussed. A strong understanding of the main implicated tracts in epileptogenic spread in FCD patient remains cardinal for neurosurgeons dealing with epilepsy. To achieve meaningful seizure freedom, despite the focal lesion resection, the interconnections and tracts should be understood and somehow disconnected to stop the spreading.

Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data

Neuronal oscillations and their synchronization between brain areas are fundamental for healthy brain function. Yet, synchronization levels exhibit large inter-individual variability that is associated with behavioral variability. We test whether individual synchronization levels are predicted by individual brain states along an extended regime of critical-like dynamics – the Griffiths phase (GP). We use computational modelling to assess how synchronization is dependent on brain criticality indexed by long-range temporal correlations (LRTCs). We analyze LRTCs and synchronization of oscillations from resting-state magnetoencephalography and stereo-electroencephalography data. Synchronization and LRTCs are both positively linearly and quadratically correlated among healthy subjects, while in epileptogenic areas they are negatively linearly correlated. These results show that variability in synchronization levels is explained by the individual position along the GP with healthy brain areas operating in its subcritical and epileptogenic areas in its supercritical side. We suggest that the GP is fundamental for brain function allowing individual variability while retaining functional advantages of criticality.

Cell-type specific and multiscale dynamics of human focal seizures in limbic structures.

The relationship between clinically accessible epileptic biomarkers and neuronal activity underlying the transition to seizure is complex, potentially leading to imprecise delineation of epileptogenic brain areas. In particular, the pattern of interneuronal firing at seizure onset remains under debate, with some studies demonstrating increased firing and others suggesting reductions. Previous study of neocortical sites suggests that seizure recruitment occurs upon failure of inhibition, with intact feedforward inhibition in non-recruited territories. We investigated whether the same principle applies in limbic structures. We analysed simultaneous electrocorticography (ECoG) and neuronal recordings of 34 seizures in a cohort of 19 patients (10 male, 9 female) undergoing surgical evaluation for pharmacoresistant focal epilepsy. A clustering approach with five quantitative metrics computed from ECoG and multiunit data was used to distinguish three types of site-specific activity patterns during seizures, which at times co-existed within seizures. Overall, 156 single units were isolated, subclassified by cell-type and tracked through the seizure using our previously published methods to account for impacts of increased noise and single-unit waveshape changes caused by seizures. One cluster was closely associated with clinically defined seizure onset or spread. Entrainment of high-gamma activity to low-frequency ictal rhythms was the only metric that reliably identified this cluster at the level of individual seizures (P < 0.001). A second cluster demonstrated multi-unit characteristics resembling those in the first cluster, without concomitant high-gamma entrainment, suggesting feedforward effects from the seizure. The last cluster captured regions apparently unaffected by the ongoing seizure. Across all territories, the majority of both excitatory and inhibitory neurons reduced (69.2%) or ceased firing (21.8%). Transient increases in interneuronal firing rates were rare (13.5%) but showed evidence of intact feedforward inhibition, with maximal firing rate increases and waveshape deformations in territories not fully recruited but showing feedforward activity from the seizure, and a shift to burst-firing in seizure-recruited territories (P = 0.014). This study provides evidence for entrained high-gamma activity as an accurate biomarker of ictal recruitment in limbic structures. However, reduced neuronal firing suggested preserved inhibition in mesial temporal structures despite simultaneous indicators of seizure recruitment, in contrast to the inhibitory collapse scenario documented in neocortex. Further study is needed to determine if this activity is ubiquitous to hippocampal seizures or indicates a 'seizure-responsive' state in which the hippocampus is not the primary driver. If the latter, distinguishing such cases may help to refine the surgical treatment of mesial temporal lobe epilepsy.

EPILEPTIC EEG SIGNALS RHYTHMS ANALYSIS IN THE DETECTION OF FOCAL AND NON-FOCAL SEIZURES BASED ON OPTIMISED MACHINE LEARNING AND DEEP NEURAL NETWORK ARCHITECTURE

Objective: Most studies in epileptic seizure detection and classification focused on classifying different types of epileptic seizures. However, localization of the epileptogenic zone in epilepsy patient brain’s is paramount to assist the doctor in locating a focal region in patients screened for surgery. Therefore, this paper proposed robust models for the localization of epileptogenic areas for the success of epilepsy surgery. Method: Advanced feature extraction techniques were proposed as effective feature extraction techniques based on Electroencephalogram (EEG) rhythms extracted from Fourier Basel Series Expansion Multivariate Empirical Wavelet Transform (FBSE-MEWT). The proposed extracted EEG rhythms of [Formula: see text] and [Formula: see text] features were used to obtain a joint instantaneous frequency and amplitude components using a sub-band alignment approach. The features are used in Sparse Autoencoder (SAE), Deep Belief Network (DBN), and Support Vector Machine (SVM) with the optimized capability to develop three new models: 1. FMEWT–SVM 2. FMEWT_SAE–SVM, and 3. FMEWT–DBN–SVM. The EEG signal was preprocessed using a proposed Multiscale Principal Component Analysis (mPCA) to denoise the noise embedded in the signal. Main results: The developed models show a significant performance improvement, with the SAE–SVM outperforming other proposed models and some recently reported works in literature with an accuracy of 99.7% using [Formula: see text]-rhythms in channels 1 and 2. Significance: This study validates the EEG rhythm as a means of discriminating the embedded features in epileptic EEG signals to locate the focal and non-focal regions in the epileptic patient’s brain to increase the success of the surgery and reduce computational cost.

Continuous theta-burst stimulation in patients with drug-resistant epilepsy: A single-blind placebo-controlled cross-over pilot study

ObjectivesTo evaluate the effect of continuous theta-burst stimulation (cTBS) in patients with drug-resistant epilepsy (DRE). MethodsTwelve patients with DRE (five with idiopathic generalized and seven with focal epilepsy) were included in this cross-over design study and randomized to either first sham or first active stimulation, each applied for 5 consecutive days. A round coil over the vertex was used in generalized epilepsy or a figure-of-8 coil over the “epileptogenic area” in focal epilepsy. Sham stimulation was given by placing the coil 90° perpendicular to the head. The number of seizures, electroencephalography findings, Quality of Life in Epilepsy Inventory (QOLIE-84), and Symptom Check List (SCL-90) scores evaluated during the 8–12 weeks before and after active and sham stimulations were compared statistically. ResultsEight patients could complete both active and sham stimulation periods of 5 days and two patients completed active stimulation sessions, without any significant adverse effects. The number of seizures significantly reduced after active cTBS, but not after sham stimulation, when compared with those recorded before the stimulation period. QOLIE scores were increased, but interictal epileptiform discharges and SCL-90 scores showed no difference after cTBS. Active stimulation was stopped in one patient after he experienced an aggravation of myoclonic seizures. ConclusionscTBS seemed to be relatively safe and gave promising results in reducing the frequency of seizures in patients with both generalized and focal DRE. This time-saving technique may ease the introduction of repetitive transcranial magnetic stimulation into the routine practice of busy epilepsy clinics.

Classification of focal and non-focal EEG signals using optimal geometrical features derived from a second-order difference plot of FBSE-EWT rhythms

Background/introduction:Manual detection and localization of the brain’s epileptogenic areas using electroencephalogram (EEG) signals is time-intensive and error-prone. An automated detection system is, thus, highly desirable for support in clinical diagnosis. A set of relevant and significant non-linear features plays a major role in developing a reliable, automated focal detection system. Methods:A new feature extraction method is designed to classify focal EEG signals using eleven non-linear geometrical attributes derived from the Fourier–Bessel series expansion-based empirical wavelet transform (FBSE-EWT) segmented rhythm’s second-order difference plot (SODP). A total of 132 features (2 channels × 6 rhythms × 11 geometrical attributes) were computed. However, some of the obtained features might be non-significant and redundant features. Hence, to acquire an optimal set of relevant non-linear features, a new hybridization of ‘Kruskal–Wallis statistical test (KWS)’ with ‘VlseKriterijuska Optimizacija I Komoromisno Resenje’ termed as the KWS-VIKOR approach was adopted. The KWS-VIKOR has a two-fold operational feature. First, the significant features are selected using the KWS test with a p-value lesser than 0.05. Next, the multi-attribute decision-making (MADM) based VIKOR method ranks the selected features. Several classification methods further validate the efficacy of the features of the selected top n%. Results:The proposed framework has been evaluated using the Bern-Barcelona dataset. The highest classification accuracy of 98.7% was achieved using the top 35% ranked features in classifying the focal and non-focal EEG signals with the least-squares support vector machine (LS-SVM) classifier. Conclusions:The achieved results exceeded those reported through other methods. Hence, the proposed framework will more effectively assist the clinician in localizing the epileptogenic areas.

Pathomorphological Diagnostic Criteria for Focal Cortical Dysplasias and Other Common Epileptogenic Lesions-Review of the Literature.

Focal cortical dysplasia (FCD) represents a heterogeneous group of morphological changes in the brain tissue that can predispose the development of pharmacoresistant epilepsy (recurring, unprovoked seizures which cannot be managed with medications). This group of neurological disorders affects not only the cerebral cortex but also the subjacent white matter. This work reviews the literature describing the morphological substrate of pharmacoresistant epilepsy. All illustrations presented in this study are obtained from brain biopsies from refractory epilepsy patients investigated by the authors. Regarding classification, there are three main FCD types, all of which involve cortical dyslamination. The 2022 revision of the International League Against Epilepsy (ILAE) FCD classification includes new histologically defined pathological entities: mild malformation of cortical development (mMCD), mild malformation of cortical development with oligodendroglial hyperplasia in frontal lobe epilepsy (MOGHE), and "no FCD on histopathology". Although the pathomorphological characteristics of the various forms of focal cortical dysplasias are well known, their aetiologic and pathogenetic features remain elusive. The identification of genetic variants in FCD opens an avenue for novel treatment strategies, which are of particular utility in cases where total resection of the epileptogenic area is impossible.

Applied Fence-Post Techniques Using Deep Electrodes Instead of Catheters for Resection of Glioma Complicated with Frequent Epileptic Seizures: A Case Report

Fence-post catheter techniques are used to use tumor margins when resecting gliomas. In the present study, deep electrodes instead of catheters were used as fence-posts. The case of a 25-year-old female patient whose magnetic resonance images (MRI) revealed a tumor in the left cingulate gyrus is presented in this study. She underwent daily seizures without loss of consciousness under the administration of anti-seizure medications. Despite video electroencephalography (EEG) monitoring, the scalp inter-ictal EEG did not show obvious epileptiform discharges. We were consequently uncertain whether such frequent seizures were epileptic seizures or not. As a result, deep electrodes were used as fence-posts: three deep electrodes were inserted into the tumor's anterior, lateral, and posterior margins using a navigation-guided method. The highest epileptic discharge was detected from the anterior deep electrode. As a result, ahead of the tumor was extendedly resected, and epileptic discharges were eliminated using EEG. The postoperative MRI revealed that the tumor was resected. The patient has never experienced seizures after the surgery. In conclusion, when supratentorial gliomas complicated by frequent seizures are resected, intraoperative EEG monitoring using deep electrodes as fence-posts is useful for estimating epileptogenic areas.

On a Low-Frequency and Contrast-Stabilized Full-Wave Volume Integral Equation Solver for Lossy Media

In this article, we present a new regularized electric flux volume integral equation (D-VIE) for modeling high-contrast conductive dielectric objects in a broad frequency range. This new formulation is particularly suitable for modeling biological tissues at low frequencies, as it is required by brain epileptogenic area imaging, but also at higher ones, as it is required by several applications, including, but not limited to, deep brain stimulation (DBS). When modeling inhomogeneous objects with high complex permittivities at low frequencies, the traditional D-VIE is ill-conditioned and suffers from numerical instabilities that result in slower convergence and less accurate solutions. In this work, we address these shortcomings by leveraging a new set of volume quasi-Helmholtz projectors. Their scaling by the material permittivity matrix allows for the rebalancing of the equation when applied to inhomogeneous scatterers and, thereby, makes the proposed method accurate and stable even for high complex permittivity objects until arbitrarily low frequencies. Numerical results, canonical and realistic, corroborate the theory and confirm the stability and the accuracy of this new method both in the quasi-static regime and at higher frequencies.

Deep learning for the diagnosis of mesial temporal lobe epilepsy.

This study aimed to enable the automatic detection of the hippocampus and diagnose mesial temporal lobe epilepsy (MTLE) with the hippocampus as the epileptogenic area using artificial intelligence (AI). We compared the diagnostic accuracies of AI and neurosurgical physicians for MTLE with the hippocampus as the epileptogenic area. In this study, we used an AI program to diagnose MTLE. The image sets were processed using a code written in Python 3.7.4. and analyzed using Open Computer Vision 4.5.1. The deep learning model, which was a fine-tuned VGG16 model, consisted of several layers. The diagnostic accuracies of AI and board-certified neurosurgeons were compared. AI detected the hippocampi automatically and diagnosed MTLE with the hippocampus as the epileptogenic area on both T2-weighted imaging (T2WI) and fluid-attenuated inversion recovery (FLAIR) images. The diagnostic accuracies of AI based on T2WI and FLAIR data were 99% and 89%, respectively, and those of neurosurgeons based on T2WI and FLAIR data were 94% and 95%, respectively. The diagnostic accuracy of AI was statistically higher than that of board-certified neurosurgeons based on T2WI data (p = 0.00129). The deep learning-based AI program is highly accurate and can diagnose MTLE better than some board-certified neurosurgeons. AI can maintain a certain level of output accuracy and can be a reliable assistant to doctors.

Association of ictal aphasia with hypoperfusion in language areas in temporal lobe epilepsy patients

Ictal clinical phenomenology, including aphasia, is usually associated with increased regional cerebral perfusion. We present an unusual pattern of ictal cerebral perfusion in three patients with pharmacoresistant, lesional temporal lobe epilepsy and ictal/postictal aphasia studied with prolonged video-EEG, ictal, and interictal SPECT and MRI for pre-surgical evaluation. Subtraction of ictal-interictal SPECT images co-registered with MRI (SISCOM) showed ictal hyperperfusion in the temporal epileptogenic area in all patients. In addition, hypoperfusion of Broca's area in one case, Wernicke's area in other patient, and both areas in the remaining one were observed. Ictal aphasia in these patients may be explained by functional inhibition of a primary language area, driven by the epileptogenic network. This pattern can contribute to understand the pathophysiology of some ictal signs, with an impact on the evaluation of individual surgical risks.

Relationship between visuoperceptual functions and parietal structural abnormalities in temporal lobe epilepsy.

Progressive gray matter volume reductions beyond the epileptogenic area has been described in temporal lobe epilepsy. There is less evidence regarding correlations between gray and white matter volume changepres and multi-domain cognitive performance in this setting. We aimed to investigate correlations between volume changes in parietal structures and visuospatial performance in temporal lobe epilepsy patients. we performed a cross-sectional study comparing global and regional brain volume data from 34 temporal lobe epilepsy patients and 30 healthy controls. 3D T1-weighted sequences were obtained on a 3.0 T magnet, and data were analyzed using age and sex-adjusted linear regression models. Global and regional brain volumes and cortical thickness in patients were correlated with standardized visual memory, visuoperceptual, visuospatial, and visuoconstructive parameters obtained in a per-protocol neuropsychological assessment. temporal lobe epilepsy patients had smaller volume fractions of the deep gray matter structures, putamen and nucleus accumbens, and larger cerebrospinal fluid volume fraction than controls. Correlations were found between: 1) visual memory and precuneus and inferior parietal cortical thickness; 2) visuoperceptual performance and precuneus and supramarginal white matter volumes; 3) visuospatial skills and precuneus, postcentral, and inferior and superior parietal white matter volumes; 4) visuoconstructive performance and inferior parietal white matter volume. Brain volume loss is widespread in temporal lobe epilepsy. Volumetric reductions in parietal lobe structures were associated with visuoperceptual cognitive performance.

Potential new roles for glycogen in epilepsy.

Seizures often originate in epileptogenic foci. Between seizures (interictally), these foci and some of the surrounding tissue often show low signals with 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) in many epileptic patients, even when there are no radiologically detectable structural abnormalities. Low FDG-PET signals are thought to reflect glucose hypometabolism. Here, we review knowledge about metabolism of glucose and glycogen and oxidative stress in people with epilepsy and in acute and chronic rodent seizure models. Interictal brain glucose levels are normal and do not cause apparent glucose hypometabolism, which remains unexplained. During seizures, high amounts of fuel are needed to satisfy increased energy demands. Astrocytes consume glycogen as an additional emergency fuel to supplement glucose during high metabolic demand, such as during brain stimulation, stress, and seizures. In rodents, brain glycogen levels drop during induced seizures and increase to higher levels thereafter. Interictally, in people with epilepsy and in chronic epilepsy models, normal glucose but high glycogen levels have been found in the presumed brain areas involved in seizure generation. We present our new hypothesis that as an adaptive response to repeated episodes of high metabolic demand, high interictal glycogen levels in epileptogenic brain areas are used to support energy metabolism and potentially interictal neuronal activity. Glycogenolysis, which can be triggered by stress or oxidative stress, leads to decreased utilization of plasma glucose in epileptogenic brain areas, resulting in low FDG signals that are related to functional changes underlying seizure onset and propagation. This is (partially) reversible after successful surgery. Last, we propose that potential interictal glycogen depletion in epileptogenic and surrounding areas may cause energy shortages in astrocytes, which may impair potassium buffering and contribute to seizure generation. Based on these hypotheses, auxiliary fuels or treatments that support glycogen metabolism may be useful to treat epilepsy.

Mapping Interictal activity in epilepsy using a hidden Markov model: A magnetoencephalography study.

Epilepsy is a highly heterogeneous neurological disorder with variable etiology, manifestation, and response to treatment. It is imperative that new models of epileptiform brain activity account for this variability, to identify individual needs and allow clinicians to curate personalized care. Here, we use a hidden Markov model (HMM) to create a unique statistical model of interictal brain activity for 10 pediatric patients. We use magnetoencephalography (MEG) data acquired as part of standard clinical care for patients at the Children's Hospital of Philadelphia. These data are routinely analyzed using excess kurtosis mapping (EKM); however, as cases become more complex (extreme multifocal and/or polymorphic activity), they become harder to interpret with EKM. We assessed the performance of the HMM against EKM for three patient groups, with increasingly complicated presentation. The difference in localization of epileptogenic foci for the two methods was 7± 2 mm (mean ±SD over all 10 patients); and 94% ± 13% of EKM temporal markers were matched by an HMM state visit. The HMM localizes epileptogenic areas (in agreement with EKM) and provides additional information about the relationship between those areas. A key advantage over current methods is that the HMM is a data-driven model, so the output is tuned to each individual. Finally, the model output is intuitive, allowing a user (clinician) to review the result and manually select the HMM epileptiform state, offering multiple advantages over previous methods and allowing for broader implementation of MEG epileptiform analysis in surgical decision-making for patients with intractable epilepsy.

Ictal direct current shifts contribute to defining the core ictal focus in epilepsy surgery.

Identifying the minimal and optimal epileptogenic area to resect and cure is the goal of epilepsy surgery. To achieve this, EEG analysis is recognized as the most direct way to detect epileptogenic lesions from spatiotemporal perspectives. Although ictal direct-current shifts (below 1 Hz) and ictal high-frequency oscillations (above 80 Hz) have received increasing attention as good indicators that can add more specific information to the conventionally defined seizure-onset zone, large cohort studies on postoperative outcomes are still lacking. This work aimed to clarify whether this additional information, particularly ictal direct-current shifts which is assumed to reflect extracellular potassium concentration, really improve postoperative outcomes. To assess the usefulness in epilepsy surgery, we collected unique EEG data sets recorded with a longer time constant of 10 s using an alternate current amplifier. Sixty-one patients (15 with mesial temporal lobe epilepsy and 46 with neocortical epilepsy) who had undergone invasive presurgical evaluation for medically refractory seizures at five institutes in Japan were retrospectively enrolled in this study. Among intracranially implanted electrodes, the two core electrodes of both ictal direct-current shifts and ictal high-frequency oscillations were independently identified by board-certified clinicians based on unified methods. The occurrence patterns, such as their onset time, duration, and amplitude (power) were evaluated to extract the features of both ictal direct-current shifts and ictal high-frequency oscillations. Additionally, we examined whether the resection ratio of the core electrodes of ictal direct-current shifts and ictal high-frequency oscillations independently correlated with favourable outcomes. A total of 53 patients with 327 seizures were analyzed for wide-band EEG analysis, and 49 patients were analyzed for outcome analysis. Ictal direct-current shifts were detected in the seizure-onset zone more frequently than ictal high-frequency oscillations among both patients (92% versus 71%) and seizures (86% versus 62%). Additionally, ictal direct-current shifts significantly preceded ictal high-frequency oscillations in patients exhibiting both biomarkers, and ictal direct-current shifts occurred more frequently in neocortical epilepsy patients than in mesial temporal lobe epilepsy patients. Finally, although a low corresponding rate was observed for ictal direct-current shifts and ictal high-frequency oscillations (39%) at the electrode level, complete resection of the core area of ictal direct-current shifts significantly correlated with favourable outcomes, similar to ictal high-frequency oscillation outcomes. Our results provide a proof of concept that the independent significance of ictal direct-current shifts from ictal high-frequency oscillations should be considered as reliable biomarkers to achieve favourable outcomes in epilepsy surgery. Moreover, the different distribution of the core areas of ictal direct-current shifts and ictal high-frequency oscillations may provide new insights into the underlying mechanisms of epilepsy, in which not only neurons but also glial cells may be actively involved via extracellular potassium levels.