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This case report shows the importance of multimodal evaluation to formulate a proper diagnosis of negative motor seizures (NMSs). Only few reports in literature document NMSs with video-electroencephalographic (EEG) and electromyographic coregistration. A multimodal evaluation is crucial to exclude common mimics and propose correct therapy. We describe a case of a 62-year-old man with drug-resistant focal epilepsy and NMSs, evaluated with video-EEG recording with polygraphy, magnetoencephalography (MEG), and brain magnetic resonance imaging (MRI). Video-EEG monitoring showed 182 focal NMSs, with preserved awareness and comprehension. The patient reported complex paresthesia of the left hand followed by left facial grimace, left arm flaccid paralysis, and bradycardia. EEG showed ictal discharges in the right frontocentral region associated with sudden electromyographical silence in left limb muscles consistent with loss of tonic contraction from distal to proximal muscles of the arm. MEG localized the epileptic zone in the right opercular region, consistent with MRI evidence of type II cortical dysplasia in the right inferior frontal gyrus. Multimodal evaluation is essential to document the temporal relationship between ictal discharges, clinical onset of limb paresis, and electrophysiologic evidence of loss of tonic muscular contraction. It allows definition of the specific cortical area involved in NMSs, offering new insight into physiological brain functioning., (© 2024 The Author(s). Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

The identification of the epileptogenic zone (EZ) boundaries is crucial for effective focal epilepsy surgery. We verify the value of a neurophysiological biomarker of focal ictogenesis, characterized by a low-voltage fast-activity ictal pattern (chirp) recorded with intracerebral electrodes during invasive presurgical monitoring (stereoelectroencephalography [SEEG]). The frequency content of SEEG signals was retrospectively analyzed with semiautomatic software in 176 consecutive patients with focal epilepsies that either were cryptogenic or presented with discordant anatomoelectroclinical findings. Fast activity seizure patterns with the spectrographic features of chirps were confirmed by computer-assisted analysis in 95.4% of patients who presented with heterogeneous etiologies and diverse lobar location of the EZ. Statistical analysis demonstrated (1) correlation between seizure outcome and concordance of sublobar regions included in the EZ defined by visual analysis and chirp-generating regions, (2) high concordance in contact-by contact analysis of 68 patients with Engel class Ia outcome, and (3) that discordance between chirp location and the visually outlined EZ correlated with worse seizure outcome. Seizure outcome analysis confirms the fast activity chirp pattern is a reproducible biomarker of the EZ in a heterogeneous group of patients undergoing SEEG., (© 2024 International League Against Epilepsy.)

Objective: Postsurgical seizure freedom in drug-resistant epilepsy (DRE) patients varies from 30% to 80%, implying that in many cases the current approaches fail to fully map the epileptogenic zone (EZ). We aimed to advance a novel approach to better characterize epileptogenicity and investigate whether the EZ encompasses a broader epileptogenic network (EpiNet) beyond the seizure zone (SZ) that exhibits seizure activity., Methods: We first used computational modeling to test putative complex systems-driven and systems neuroscience-driven mechanistic biomarkers for epileptogenicity. We then used these biomarkers to extract features from resting-state stereoelectroencephalograms recorded from DRE patients and trained supervised classifiers to localize the SZ against gold standard clinical localization. To further explore the prevalence of pathological features in an extended brain network outside of the clinically identified SZ, we also used unsupervised classification., Results: Supervised SZ classification trained on individual features achieved accuracies of .6-.7 area under the receiver operating characteristic curve (AUC). Combining all criticality and synchrony features further improved the AUC to .85. Unsupervised classification discovered an EpiNet-like cluster of brain regions, in which 51% of brain regions were outside of the SZ. Brain regions in the EpiNet-like cluster engaged in interareal hypersynchrony and locally exhibited high-amplitude bistability and excessive inhibition, which was strikingly similar to the high seizure risk regime revealed by our computational modeling., Significance: The finding that combining biomarkers improves SZ localization accuracy indicates that the novel mechanistic biomarkers for epileptogenicity employed here yield synergistic information. On the other hand, the discovery of SZ-like brain dynamics outside of the clinically defined SZ provides empirical evidence of an extended pathophysiological EpiNet., (© 2024 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Human and animal EEG data demonstrate that focal seizures start with low-voltage fast activity, evolve into rhythmic burst discharges and are followed by a period of suppressed background activity. This suggests that processes with dynamics in the range of tens of seconds govern focal seizure evolution. We investigate the processes associated with seizure dynamics by complementing the Hodgkin-Huxley mathematical model with the physical laws that dictate ion movement and maintain ionic gradients. Our biophysically realistic computational model closely replicates the electrographic pattern of a typical human focal seizure characterized by low voltage fast activity onset, tonic phase, clonic phase and postictal suppression. Our study demonstrates, for the first time in silico, the potential mechanism of seizure initiation by inhibitory interneurons via the initial build-up of extracellular K + due to intense interneuronal spiking. The model also identifies ionic mechanisms that may underlie a key feature in seizure dynamics, that is, progressive slowing down of ictal discharges towards the end of seizure. Our model prediction of specific scaling of inter-burst intervals is confirmed by seizure data recorded in the whole guinea pig brain in vitro and in humans, suggesting that the observed termination pattern may hold across different species. Our results emphasize ionic dynamics as elementary processes behind seizure generation and indicate targets for new therapeutic strategies., Competing Interests: DG, Md, VG, PS No competing interests declared, (© 2022, Gentiletti et al.)

Purpose: To define Stereo-EEG (SEEG) ictal and interictal patterns associated with different pathologies in a cohort of patients with drug-resistant focal epilepsy., Methods: We retrospectively analyzed findings from 102 patient with epilepsy due to Polymicrogyria (PMG), Periventricular Nodular Heterotopia (PNH), Focal Cortical Dysplasia (FCD) type I, IIa, IIb and Hippocampal Sclerosis (HS). Ictal and interictal SEEG recordings were reviewed to describe Seizure Onset Zone (SEEG-SOZ) patterns and to define the Lesional and Irritative Zones., Results: Five SEEG-SOZ patterns were identified: significant associations were found between low-voltage fast activity and PMG and between repetitive fast spikes bursts and FCD type IIa. A trend was found between fast activity and PNH, rhythmic sharp activity and FCD type I, repetitive fast spikes bursts and FCD type IIb, slow burst and HS. In 62 of the 102 patients, a complete surgical resection of the SEEG-SOZ was performed, and in 12 patients a partial resection was carried out to preserve eloquent areas. In 18 patients (15 with PNH) the SEEG-SOZ was thermo-coagulated. Seizure freedom was achieved in 58% of surgically treated patients and in 72% of those treated with thermocoagulation (mean ± SD follow-up 5.9 ± 2.3 years). Seizure freedom after surgery was achieved in 84% of the patients with PMG, FCD I, IIa and IIb presenting with characteristic SEEG-SOZ patterns. With the exception of FCD type II, interictal activity was not sufficient to identify SEEG-SOZ boundaries., Conclusion: The study demonstrates that specific histopathologies correlate with particular neurophysiological patterns, reflecting lesion-specific seizure patterns in focal epilepsies., (Copyright © 2019 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)

Objective: Animal and human studies have shown that the seizure-generating region is vastly dependent on distant neuronal hubs that can decrease duration and propagation of ongoing seizures. However, we still lack a comprehensive understanding of the impact of distant brain areas on specific interictal and ictal epileptic activities (e.g., isolated spikes, spike trains, seizures). Such knowledge is critically needed, because all kinds of epileptic activities are not equivalent in terms of clinical expression and impact on the progression of the disease., Methods: We used surface high-density electroencephalography and multisite intracortical recordings, combined with pharmacological silencing of specific brain regions in the well-known kainate mouse model of temporal lobe epilepsy. We tested the impact of selective regional silencing on the generation of epileptic activities within a continuum ranging from very transient to more sustained and long-lasting discharges reminiscent of seizures., Results: Silencing the contralateral hippocampus completely suppresses sustained ictal activities in the focus, as efficiently as silencing the focus itself, but whereas focus silencing abolishes all focus activities, contralateral silencing fails to control transient spikes. In parallel, we observed that sustained focus epileptiform discharges in the focus are preceded by contralateral firing and more strongly phase-locked to bihippocampal delta/theta oscillations than transient spiking activities, reinforcing the presumed dominant role of the contralateral hippocampus in promoting long-lasting, but not transient, epileptic activities., Significance: Altogether, our work provides suggestive evidence that the contralateral hippocampus is necessary for the interictal to ictal state transition and proposes that crosstalk between contralateral neuronal activity and ipsilateral delta/theta oscillation could be a candidate mechanism underlying the progression from short- to long-lasting epileptic activities., (© 2024 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Objective: Long-term recording with intracerebral electrodes is commonly utilized to identify brain areas responsible for seizure generation (epileptogenic zone) and to tailor therapeutic surgical resections in patients with focal drug-resistant epilepsy. This invasive diagnostic procedure generates a wealth of data that contribute to understanding human epilepsy. We analyze intracerebral signals to identify and classify focal ictal patterns., Methods: We retrospectively analyzed stereo-electroencephalographic (EEG) data in a cohort of patients either cryptogenic (magnetic resonance imaging negative) or presenting with noncongruent anatomoelectroclinical data. A computer-assisted method based on EEG signal analysis in frequency and space domains was applied to 467 seizures recorded in 105 patients submitted to stereo-EEG presurgical monitoring., Results: Two main focal seizure patterns were identified. P-type seizures, typical of neocortex, were observed in 73 patients (69.5%), lasted 22 ± 13 seconds (mean +SD), and were characterized by a sharp-onset/sharp-offset transient superimposed on low-voltage fast activity (126 ± 19 Hz). L-type seizures were observed in 43 patients (40.9%) and consistently involved mesial temporal structures; they lasted longer (93 ± 48 second), started with 116 ± 21 Hz low-voltage fast activity superimposed on a slow potential shift, and terminated with large-amplitude, periodic bursting activity. In 23 patients (21.9%), the L-type seizure was preceded by a P seizure. Spasmlike and unclassifiable EEG seizures were observed in 11.4% of cases., Significance: The proposed computer-assisted approach revealed signal information concealed to visual inspection that contributes to identifying two principal seizure patterns typical of the neocortex and of mesial temporal networks., (Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.)

Electroencephalography (EEG)-the direct recording of the electrical activity of populations of neurons-is a tremendously important tool for diagnosing, treating, and researching epilepsy. Although standard procedures for recording and analyzing human EEG exist and are broadly accepted, there are no such standards for research in animal models of seizures and epilepsy-recording montages, acquisition systems, and processing algorithms may differ substantially among investigators and laboratories. The lack of standard procedures for acquiring and analyzing EEG from animal models of epilepsy hinders the interpretation of experimental results and reduces the ability of the scientific community to efficiently translate new experimental findings into clinical practice. Accordingly, the intention of this report is twofold: (1) to review current techniques for the collection and software-based analysis of neural field recordings in animal models of epilepsy, and (2) to offer pertinent standards and reporting guidelines for this research. Specifically, we review current techniques for signal acquisition, signal conditioning, signal processing, data storage, and data sharing, and include applicable recommendations to standardize collection and reporting. We close with a discussion of challenges and future opportunities, and include a supplemental report of currently available acquisition systems and analysis tools. This work represents a collaboration on behalf of the American Epilepsy Society/International League Against Epilepsy (AES/ILAE) Translational Task Force (TASK1-Workgroup 5), and is part of a larger effort to harmonize video-EEG interpretation and analysis methods across studies using in vivo and in vitro seizure and epilepsy models., (Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.)

In vivo electrophysiological recordings are widely used in neuroscience research, and video-electroencephalography (vEEG) has become a mainstay of preclinical neuroscience research, including studies of epilepsy and cognition. Studies utilizing vEEG typically involve comparison of measurements obtained from different experimental groups, or from the same experimental group at different times, in which one set of measurements serves as "control" and the others as "test" of the variables of interest. Thus, controls provide mainly a reference measurement for the experimental test. Control rodents represent an undiagnosed population, and cannot be assumed to be "normal" in the sense of being "healthy." Certain physiological EEG patterns seen in humans are also seen in control rodents. However, interpretation of rodent vEEG studies relies on documented differences in frequency, morphology, type, location, behavioral state dependence, reactivity, and functional or structural correlates of specific EEG patterns and features between control and test groups. This paper will focus on the vEEG of standard laboratory rodent strains with the aim of developing a small set of practical guidelines that can assist researchers in the design, reporting, and interpretation of future vEEG studies. To this end, we will: (1) discuss advantages and pitfalls of common vEEG techniques in rodents and propose a set of recommended practices and (2) present EEG patterns and associated behaviors recorded from adult rats of a variety of strains. We will describe the defining features of selected vEEG patterns (brain-generated or artifactual) and note similarities to vEEG patterns seen in adult humans. We will note similarities to normal variants or pathological human EEG patterns and defer their interpretation to a future report focusing on rodent seizure patterns., (Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.)

Objective: Seizures in mesial temporal lobe epilepsy (MTLE) associated with hippocampal sclerosis are thought to develop with various latency intervals after an initial transient brain insult. To study seizure dynamics after an initial transient precipitating insult in a systematic fashion, we utilized continuous video-electroencephalography (EEG) monitoring after the induction of status epilepticus (SE) in a mouse MTLE model., Methods: Continuous 24/7 video/telemetric hippocampal EEG recordings in the systemic pilocarpine MTLE mouse model., Results: After SE, we observed emerging seizures interfering with the circadian EEG rhythms. The physiologic circadian EEG pattern of mice was transiently suppressed for 2.9 (mean) ± (SEM) 0.5 days after SE. This period was accompanied predominately by nonconvulsive seizure activity, followed by convulsive seizures at later stages. After the circadian rhythm was restored, spontaneous generalized seizures occurred mainly in a clustered manner in a narrow time window between 4 and 7 p.m. (light cycle 7 a.m./7 p.m.). Moreover, we demonstrate that depth-electrode implantation surgery transiently disturbs the physiologic EEG circadian cycle; variation of the time point of SE induction after electrode insertion surgery revealed a substantial impact on the epilepsy phenotype, which was more severe when SE occurred after postsurgical reappearance of EEG circadian cycling., Significance: These data have several experimental and pathophysiologic implications. The impact of depth-electrode surgery on the phenotype has to be tightly controlled. In mice monitored after pilocarpine-induced SE, the "epileptogenesis" period is characterized by the dynamics of epileptiform activity toward behavioral recurrent seizure patterns. The striking clustering of spontaneous seizures at the transition from sleep to activity stages of mice has to be taken into account for future studies on the model. Improving our understanding of the molecular mechanisms that determine the circadian dynamics of seizure threshold remains an intriguing task for the future., (Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.)

Objective: Quantification of the epileptogenic zone network (EZN) most frequently implies analysis of seizure onset. However, important information can also be obtained from the postictal period, characterized by prominent changes in the EZN. We used permutation entropy (PE), a measure of signal complexity, to analyze the peri-ictal stereoelectroencephalography (SEEG) signal changes with emphasis on the postictal state. We sought to determine the best PE-derived parameter (PEDP) for identifying the EZN., Methods: Several PEDPs were computed retrospectively on SEEG-recorded seizures of 86 patients operated on for drug-resistant epilepsy: mean baseline preictal entropy, minimum ictal entropy, maximum postictal entropy, the ratio between the maximum postictal and the minimum ictal entropy, and the ratio between the maximum postictal and the baseline preictal entropy. The performance of each biomarker was assessed by comparing the identified epileptogenic contacts or brain regions against the EZN defined by clinical analysis incorporating the Epileptogenicity Index and the connectivity epileptogenicity index methods (EZNc), using the receiver-operating characteristic and precision-recall., Results: The ratio between the maximum postictal and the minimum ictal entropy (defined as the Permutation Entropy Index [PEI]) proved to be the best-performing PEDP to identify the EZN C . It demonstrated the highest area under the curve (AUC) and F1 score at the contact level (AUC 0.72; F1 0.39) and at the region level (AUC 0.78; F1 0.47). PEI values gradually decreased between the EZN, the propagation network, and the non-involved regions. PEI showed higher performance in patients with slow seizure-onset patterns than in those with fast seizure-onset patterns. The percentage of resected epileptogenic regions defined by PEI was significantly correlated with surgical outcome., Significance: PEI is a promising tool to improve the delineation of the EZN. PEI combines ease and robustness in a routine clinical setting with high sensitivity for seizures without fast activity at seizure onset., (© 2023 International League Against Epilepsy.)

The neurophysiological patterns that correlate with partial (focal) seizures are well defined in humans by standard electroencephalogram (EEG) and presurgical depth electrode recordings. Seizure patterns with similar features are reproduced in animal models of partial seizures and epilepsy. However, the network determinants that support interictal spikes, as well as the initiation, progression, and termination of seizures, are still elusive. Recent findings show that inhibitory networks are prominently involved at the onset of these seizures, and that extracellular changes in potassium contribute to initiate and sustain seizure progression. The end of a partial seizure correlates with an increase in network synchronization, which possibly involves both excitatory and inhibitory mechanisms., (Copyright © 2015 Cold Spring Harbor Laboratory Press; all rights reserved.)

Presurgical monitoring with intracerebral electrodes in patients with drug-resistant focal epilepsy represents a standard invasive procedure to localize the sites of seizures origin, defined as the epileptogenic zone (EZ). During presurgical evaluation, intracerebral single-pulse electrical stimulation (SPES) is performed to define the boundaries of eloquent areas and to evoke seizure-associated symptoms. Extensive intracranial exploration and stimulation generate a large dataset on brain connectivity that can be used to improve EZ detection and to understand the organization of the human epileptic brain. We developed a protocol to analyse field responses evoked by intracranial stimulation. Intracerebral recordings were performed with 105-162 recording sites positioned in fronto-temporal regions in 12 patients with pharmacoresistant focal epilepsy. Recording sites were used for bipolar SPES at 1 Hz. Reproducible early and late phases (<60 ms and 60-500 ms from stimulus artefact, respectively) were identified on averaged evoked responses. Phase 1 and 2 responses recorded at all and each recording sites were plotted on a 3D brain reconstructions. Based on connectivity properties, electrode contacts were primarily identified as receivers, mainly activators or bidirectional. We used connectivity patterns to construct networks and applied cluster partitioning to study the proprieties between potentials evoked/stimulated in different regions. We demonstrate that bidirectional connectivity during phase 1 is a prevalent feature that characterize contacts included in the EZ. This study shows that the application of an analytical protocol on intracerebral stimulus-evoked recordings provides useful information that may contribute to EZ detection and to the management of surgical-remediable epilepsies., (Copyright © 2014 Wiley Periodicals, Inc.)

Objective: In one third of patients with a diagnosis of pharmacoresistant focal epilepsy who are candidates for therapeutic surgery, cerebral areas responsible for seizure generation can be defined exclusively with invasive intracranial recordings. A correct presurgical identification of the epileptogenic zone (EZ) with intracranial electrodes has a direct impact on postsurgical outcome. We aimed at identifying biomarkers of the EZ based on computer-assisted inspection of intracranial electroencephalography (EEG)., Methods: Computer-driven intracranial EEG analysis in the domains of time, frequency, and space was retrospectively applied to a population of 10 patients with focal epilepsy to detect EZ electrophysiologic markers. Next, a prospective study was performed on 14 surgery candidate patients. The stereo-EEG computer-assisted analysis of EZ boundaries performed blind from patients data was compared to that defined with the traditional visual inspection completed by neurophysiologists., Results: In the retrospective study, the EZ was characterized by the combined detection of three biomarkers observed at seizure onset: (1) fast activity at 80-120 Hz associated with (2) very slow transient polarizing shift and (3) voltage depression (flattening). Correlations between these indexes were calculated for each seizure. In the prospective study, the quantified analysis based on the three biomarkers confirmed a complete overlap between leads within the EZ identified by expert clinicians. In 2 of 14 patients the proposed biomarkers partially identified the EZ., Significance: Our findings demonstrate and validate with a prospective unbiased study the use of three neurophysiologic intracranial EEG parameters as excellent biomarkers of ictogenesis and as reliable indicators of EZ boundaries., (Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.)

Purpose: The identification of the epileptogenic zone (EZ) is crucial for planning epilepsy surgery in patients with drug-resistant partial epilepsy. This task may require intracerebral encephalography (EEG) monitoring, the results of which are usually interpreted by visual presurgical inspection. A computer-assisted method for rapidly identifying reproducible ictal patterns based on the analysis of time, frequency, and spatial domains of stereo-EEG (SEEG) signals is described here., Methods: A new method for EZ detection was tested on SEEG recordings performed by intracerebral electrodes in eight patients with pharmacoresistant partial epilepsy. SEEG data were exported to a program developed in LabView., Key Findings: Prevalent frequencies during seizure events were evaluated by Fourier transform and further integral algorithms. Different frequencies and the relative powers were simultaneously evaluated in all recording leads. Patterns characterized by specific and prevalent frequencies were identified in a subset of recording sites during both seizure onset and seizure development. Three-dimensional (3D) maps of the measurements obtained from each recording channel were reconstructed on magnetic resonance coordinates to visualize the spatial distribution of the EZ. With this method, the reproducibility of ictal patterns in the same patient was characterized. The boundaries of the EZ identified with this algorithm correlated well with the EZ recognized with the traditional approach (n = 8). The spatial distribution of specific SEEG signals associated with different types of seizures was also analyzed in two patients., Significance: We describe a computer-assisted method to acquire information on EZ boundaries and to verify reproducibility of seizure patterns from intracerebral recordings performed in patients with pharmacoresistant partial epilepsies., (Wiley Periodicals, Inc. © 2011 International League Against Epilepsy.)

Objective: High-frequency oscillations are considered among the most promising interictal biomarkers of the epileptogenic zone in patients suffering from pharmacoresistant focal epilepsy. However, there is no clear definition of pathological high-frequency oscillations, and the existing detectors vary in methodology, performance, and computational costs. This study proposes relative entropy as an easy-to-use novel interictal biomarker of the epileptic tissue., Methods: We evaluated relative entropy and high-frequency oscillation biomarkers on intracranial electroencephalographic data from 39 patients with seizure-free postoperative outcome (Engel Ia) from three institutions. We tested their capability to localize the epileptogenic zone, defined as resected contacts located in the seizure onset zone. The performance was compared using areas under the receiver operating curves (AUROCs) and precision-recall curves. Then we tested whether a universal threshold can be used to delineate the epileptogenic zone across patients from different institutions., Results: Relative entropy in the ripple band (80-250 Hz) achieved an average AUROC of .85. The normalized high-frequency oscillation rate in the ripple band showed an identical AUROC of .85. In contrast to high-frequency oscillations, relative entropy did not require any patient-level normalization and was easy and fast to calculate due to its clear and straightforward definition. One threshold could be set across different patients and institutions, because relative entropy is independent of signal amplitude and sampling frequency., Significance: Although both relative entropy and high-frequency oscillations have a similar performance, relative entropy has significant advantages such as straightforward definition, computational speed, and universal interpatient threshold, making it an easy-to-use promising biomarker of the epileptogenic zone., (© 2023 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

The mechanisms that control the transition into a focal seizure are still uncertain. The introduction of presurgical intracranial recordings to localize the epileptogenic zone in patients with drug-resistant focal epilepsies opened a new window to the interpretation of seizure generation (ictogenesis). One of the most frequent focal patterns observed with intracranial electrodes at seizure onset is characterized by low-voltage fast activity in the beta-gamma range that may or may not be preceded by changes of ongoing interictal activities. In the present commentary, the mechanisms of generation of focal seizures are reconsidered, focusing on low-voltage fast activity patterns. Experimental findings on models of temporal lobe seizures support the view that the low-voltage fast activity observed at seizure onset is associated with reinforcement and synchronization of inhibitory networks. A minor role for the initiation of the ictal pattern is played by principal neurons that are progressively recruited with a delay, when inhibition declines and synchronous high-voltage discharges ensue. The transition from inhibition into excitatory recruitment is probably mediated by local increase in potassium concentration associated with synchronized interneuronal firing. These findings challenge the classical theory that proposes an increment of excitation and/or a reduction of inhibition as a cause for the transition to seizure in focal epilepsies. A new definition of ictogenesis mechanisms, as herewith hypothesized, might possibly help to develop new therapeutic strategies for focal epilepsies.

Fast (gamma) oscillations in the cortex underlie the rapid temporal coordination of large-scale neuronal assemblies in the processing of sensory stimuli. Cortical gamma rhythm is modulated in vivo by cholinergic innervation from the basal forebrain and can be generated in vitro after exogenous cholinergic stimulation. Using the isolated guinea pig brain, an in vitro preparation that allows for the study of an intact cerebrum, we studied the spatial features of gamma activity evoked by the cholinomimetic carbachol (CCh) in the medial entorhinal cortex (mEC). gamma activity induced by either arterial perfusion or intraparenchymal application of CCh showed a phase reversal across mEC layer II and was reduced or abolished in a spatially localized region by focal infusions of atropine, bicuculline, and CNQX. In addition, a spatially restricted zone of gamma activity could be induced by passive diffusion of CCh from a recording pipette. Finally, gamma oscillations recorded at multiple sites across the surface of the mEC using array electrodes during arterial perfusion of CCh demonstrated a decline in synchronization (coherence) as the interelectrode distance increased. This effect was independent of the signal amplitude and was specific for gamma as opposed to theta-like activity induced by CCh in the same experiments. These results suggest that CCh-induced gamma oscillations in the mEC are mediated through direct muscarinic excitation of a highly localized reciprocal inhibitory-excitatory network located in superficial layers. We propose that functional cortical modules of highly synchronous gamma oscillations may organize incoming (cortical) and outgoing (hippocampal) information in the mEC.

Objective: The aim of this study was to investigate the different ictal onset stereoelectroencephalography patterns (IOPs) in patients with drug-resistant temporal lobe epilepsy (TLE). We examined whether the IOPs relate to different TLE subtypes, MRI findings, and underlying pathologies, and we evaluated their prognostic value for predicting the surgical outcome., Methods: We retrospectively analyzed data from patients with TLE who underwent stereoelectroencephalography (SEEG) monitoring followed by surgical resection between January 2018 and January 2020. The SEEG recordings were independently analyzed by two epileptologists., Results: Forty-five patients were included in the study, and 61seizures were analyzed. Five IOPs were identified: low voltage fast activity (LVFA; 44.3%), spike-and-wave activity (16.4%), low frequency high-amplitude periodic spikes (LFPS; 18%), a burst of high-amplitude polyspikes (8.2%), and rhythmic sharp activity at ≤ 13 Hz (13.1%). Thirty-two patients were found to have a single IOP, while the other 13 patients had two or more IOPs. All five IOPs were found to occur in the medial temporal lobe epilepsy (MTLE), while four IOPs occurred in the lateral temporal lobe epilepsy (LTLE). The LFPS was a common IOP that could distinguish MTLE from LTLE (x 2  = 7.046, p = 0.011). Among the MTLE patients, the LFPS was exclusively seen in cases of hippocampal sclerosis (x 2  = 5.058, p = 0.038), while the LVFA was associated with nonspecific histology (x 2  = 6.077, p = 0.023). The IOPs were not found to differ according to whether the MRI scans were positive or negative. After surgery, patients achieved the higher seizure-free rate at 81.8% and 77.8%, respectively, if the LFPS and LVFA were the predominant patterns. Multiple IOPs or a negative MRI did not indicate a poor prognosis., Conclusions: Five distinct IOPs were identified in the patients with TLE. The differences found have important clinical implications and could provide complementary information for surgical decision-making, especially in MRI-negative patients., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

The cyclical organization of seizures in epilepsy has been described since antiquity. However, historical explanations for seizure cycles-based on celestial, hormonal, and environmental factors-have only recently become testable with the advent of chronic electroencephalography (cEEG) and modern statistical techniques. Here, factors purported over millennia to influence seizure timing are viewed through a contemporary lens. We discuss the emerging concept that seizures are organized over multiple timescales, each involving differential influences of external and endogenous rhythm generators. Leveraging large cEEG datasets and circular statistics appropriate for cyclical phenomena, we present new evidence for circadian (day-night), multidien (multi-day), and circannual (about-yearly) variation in seizure activity. Modulation of seizure timing by multiscale temporal variables has implications for diagnosis and therapy in clinical epilepsy. Uncovering the mechanistic basis for seizure cycles, particularly the factors that govern multidien periodicity, will be a major focus of future work., (© 2020 International League Against Epilepsy.)

Objective: We use the dynamic electroencephalography-functional magnetic resonance imaging (EEG-fMRI) method to incorporate variability in the amplitude and field of the interictal epileptic discharges (IEDs) into the fMRI analysis. We ask whether IED variability analysis can (a) identify additional activated brain regions during the course of IEDs, not seen in standard analysis; and (b) demonstrate the origin and spread of epileptic activity. We explore whether these functional changes recapitulate the structural connections and propagation of epileptic activity during seizures., Methods: Seventeen patients with focal epilepsy and at least 30 IEDs of a single type during simultaneous EEG-fMRI were studied. IED variability and EEG source imaging (ESI) analysis extracted time-varying dynamic changes. General linear modeling (GLM) generated static functional maps. Dynamic maps were compared to static functional maps. The dynamic sequence from IED variability was compared to the ESI results. In a subset of patients, we investigated structural connections between active brain regions using diffusion-based fiber tractography., Results: IED variability distinguished the origin of epileptic activity from its propagation in 15 of 17 (88%) patients. This included two cases where no result was obtained from the standard GLM analysis. In both of these cases, IED variability revealed activation in line with the presumed epileptic focus. Two cases showed no result from either method. Both had very high spike rates associated with dysplasia in the postcentral gyrus. In all 15 cases with dynamic activation, the observed dynamics were concordant with ESI. Fiber tractography identified specific white matter pathways between brain regions that were active at IED onset and propagation., Significance: Dynamic techniques involving IED variability can provide additional power for EEG-fMRI analysis, compared to standard analysis, revealing additional biologically plausible information in cases with no result from the standard analysis and gives insight into the origin and spread of IEDs., (© 2020 International League Against Epilepsy.)

Interictal spiking is seen in the EEG of epileptic patients between seizures. To date, the roles played by interictal events in seizure occurrence and in epileptogenesis remain elusive. While interictal spikes may herald the onset of electrographic seizures, experimental data indicate that hippocampus-driven interictal events prevent seizure precipitation. Even less clear than the role of interictal events in seizure occurrence is whether and how interictal spikes contribute to epileptogenesis. Thus, while plastic changes within limbic neuronal networks may result from ongoing interictal activity, experimental evidence supports the view that epileptogenesis is accompanied by a decrease in hippocampus-driven interictal activity. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG), which can intuitively monitor and record the discharge activities of neuronal groups in the brain, is a crucial scientific and clinical diagnostic technique in the field of neuroscience. EEG has been developed and innovated for nearly a century, and it offers advantages of non-invasiveness, convenience, real-time, and continuity. The rapid advancement and multidisciplinary integration of computer technology and other imaging techniques has led to the application of EEG technology in a wide range of areas, including epilepsy, sleep disorders, and critical care. The purpose of this article is to enhance clinical comprehension and implementation of EEG technology by reviewing its development history, clinical applications, and future prospects. [ABSTRACT FROM AUTHOR]

Objective: Perampanel (PER), a noncompetitive a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor antagonist, has been approved as adjunctive therapy for focal and generalized epilepsy. Limited information is available regarding the measurable impact of anti-seizure medications (ASM). In this study, we aimed to investigate the effects of PER on electroencephalography (EEG) background activity and interictal epileptic discharge. Methods: This study included all patients with a clinical diagnosis of epilepsy who underwent routine EEG before and after PER treatment between 2018 and 2023. EEG findings were examined according to their background activity and clinical features such as risk factors of epilepsy, the occurrence of sleep-related seizures, sleep disorders, intellectual disability, abnormality of magnetic resonance imaging and EEG, multifocal features on EEG, the duration between EEG and initiation of PER treatment, frequency of seizures before and after PER treatment (seizure freedom or >50% reduction in seizures), previous epilepsy surgery, the number of current and previous ASM, and dosage of PER. Results: In a total of 11 patients, epilepsy type was focal in 8 (73%), all of the patients were on polytherapy, and 4 of them had undergone epilepsy surgery. PER treatment resulted in seizure freedom in 36% of patients and a >50% decrease in seizures in 55% of patients. There was no statistically significant relationship between background activity, phase reversal, and equipotential in EEG before and after PER treatment. In addition, pre- and posttreatment responses to activation procedures and disruption in sleep structure did not differ significantly. The relationship between seizure freedom and phase reversal decrease after PER treatment was statistically significant. The relationship between a >50% decrease in the frequency of seizures and epileptic discharges also reached statistical significance. Conclusion: To summarize, seizure freedom following PER treatment appears to be associated with reduced epileptic discharge, and EEG monitoring might help determine prognosis. [ABSTRACT FROM AUTHOR]

The European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing, as well as draw conclusions on the predictability of preclinical models. To address this, a consortium including multiple research laboratories from academia and industry participated in a series of electroencephalography (EEG) experiments in mice aimed to detect sources of variance and to gauge how protocol harmonisation and data analytics impact such variance. Ultimately, the goal of this first ever between-laboratory comparison of EEG recordings and analyses was to validate the principles that supposedly increase data quality, robustness, and comparability. Experiments consisted of a Localisation phase, which aimed to identify the factors that influence between-laboratory variability, a Harmonisation phase to evaluate whether harmonisation of standardized protocols and centralised processing and data analysis reduced variance, and a Ring-Testing phase to verify the ability of the harmonised protocol to generate consistent findings. Indeed, between-laboratory variability reduced from Localisation to Harmonisation and this reduction remained during the Ring-Testing phase. Results obtained in this multicentre preclinical qEEG study also confirmed the complex nature of EEG experiments starting from the surgery and data collection through data pre-processing to data analysis that ultimately influenced the results and contributed to variance in findings across laboratories. Overall, harmonisation of protocols and centralized data analysis were crucial in reducing laboratory-to-laboratory variability. To this end, it is recommended that standardized guidelines be updated and followed for collection and analysis of preclinical EEG data. [ABSTRACT FROM AUTHOR]

Objective: Interictal biomarkers are critical for identifying the epileptogenic focus. However, spikes and ripples lack specificity while fast ripples lack sensitivity. These biomarkers propagate from more epileptogenic onset to areas of spread. The pathophysiological mechanism of these propagations is elusive. Here, we examine zones where spikes and high frequency oscillations co‐occur (SHFO), the spatiotemporal propagations of spikes, ripples, and fast ripples, and evaluate the spike–ripple onset overlap (SRO) as an epilepsy biomarker. Methods: We retrospectively analyzed intracranial EEG data from 41 patients with drug‐resistant epilepsy. We mapped propagations of spikes, ripples, and fast ripples, and identified their onset and spread zones, as well as SHFO and SRO. We then estimated the SRO prognostic value in predicting surgical outcome and compared it to onset and spread zones of spike, ripple, and fast ripple propagations, and SHFO. Results: We detected spikes and ripples in all patients and fast ripples in 12 patients (29%). We observed spike and ripple propagations in 40 (98%) patients. Spike and ripple onsets overlapped in 35 (85%) patients. In good outcome patients, SRO showed higher specificity and precision (p < 0.05) in predicting resection compared to onset and zones of spikes, ripples, and SHFO. Only SRO resection predicted outcome (p = 0.01) with positive and negative predictive values of 82% and 57%, respectively. Interpretation: SRO is a specific and precise biomarker of the epileptogenic zone whose removal predicts outcome. SRO is present in most patients with drug‐resistant epilepsy. Such a biomarker may reduce prolonged intracranial monitoring and improve outcome. [ABSTRACT FROM AUTHOR]

Epilepsy is a common neurological disorder, affecting over 65 million people worldwide. Unfortunately, despite resective surgery, over 30% of patients with drug-resistant epilepsy continue to experience seizures. Retrospective studies considering connectivity using intracranial electrocorticography (ECoG) obtained during neuromonitoring have shown that treatment failure is likely driven by failure to consider critical components of the seizure network, an idea first formally introduced in 2002. However, current studies only capture snapshots in time, precluding the ability to consider seizure network development. Over the past few years, multiwell microelectrode arrays have been increasingly used to study neuronal networks in vitro. As such, we sought to develop a novel in vitro MEA seizure model to allow for study of seizure networks. Specifically, we used 4-aminopyridine (4-AP) to capture hyperexcitable activity, and then show increased network changes after 2 days of chronic treatment. We characterize network changes using functional connectivity measures and a novel technique using dimensionality reduction. We find that 4-AP successfully captures persistently elevated mean firing rate and significant changes in underlying connectivity patterns. We believe this affords a robust in vitro seizure model from which longitudinal network changes can be studied, laying groundwork for future studies exploring seizure network development. [ABSTRACT FROM AUTHOR]

One aspect of reproducibility in preclinical research that is frequently overlooked is the physical condition in which physiological, pharmacological, or behavioural recordings are conducted. In this study, the physical conditions of mice were altered through the attachments of wireless electrophysiological recording devices (Neural Activity Tracker-1, NAT-1). NAT-1 devices are miniaturised multichannel devices with onboard memory for direct high-resolution recording of brain activity for >48 h. Such devices may limit the mobility of animals and affect their behavioural performance due to the added weight (total weight of approximately 3.4 g). The mice were additionally treated with saline (control), N-methyl-D-aspartate (NMDA) receptor antagonist MK801 (0.85 mg/kg), or the muscarinic acetylcholine receptor blocker scopolamine (0.65 mg/kg) to allow exploration of the effect of NAT-1 attachments in pharmacologically treated mice. We found only minimal differences in behavioural outcomes with NAT-1 attachments in standard parameters of locomotor activity widely reported for the open field test between the drug treatments. Hypoactivity was globally observed as a consistent outcome in the MK801-treated mice and hyperactivity in scopolamine groups regardless of NAT-1 attachments. These data collectively confirm the reproducibility for combined behavioural, pharmacological, and physiological endpoints even in the presence of lightweight wireless data loggers. The NAT-1 therefore constitutes a pertinent tool for investigating brain activity in, e.g., drug discovery and models of neuropsychiatric and/or neurodegenerative diseases with minimal effects on pharmacological and behavioural outcomes. [ABSTRACT FROM AUTHOR]

Electrophysiological methods of research are widely used in neurobiology. To assess the bioelectrical activity of the brain in small laboratory animals, electrocorticography (ECoG) is most often used, which allows the recording of signals directly from the cerebral cortex. To date, a number of methodological approaches to the manufacture and implantation of ECoG electrodes have been proposed, the complexity of which is determined by experimental tasks and logistical capabilities. Existing methods for analyzing bioelectrical signals are used to assess the functional state of the nervous system in test animals, as well as to identify correlates of pathological changes or pharmacological effects. The review presents current areas of applications of ECoG in neuropharmacological studies in small laboratory animals. Traditionally, this method is actively used to study the antiepileptic activity of new molecules. However, the possibility of using ECoG to assess the neuroprotective activity of drugs in models of traumatic, vascular, metabolic, or neurodegenerative CNS damage remains clearly underestimated. Despite the fact that ECoG has a number of disadvantages and methodological difficulties, the recorded data can be a useful addition to traditional molecular and behavioral research methods. An analysis of the works in recent years indicates a growing interest in the method as a tool for assessing the pharmacological activity of psychoactive drugs, especially in combination with classification and prediction algorithms. [ABSTRACT FROM AUTHOR]

Electroencephalogram (EEG) plays a pivotal role in the detection and analysis of epileptic seizures, which affects over 70 million people in the world. Nonetheless, the visual interpretation of EEG signals for epilepsy detection is laborious and time-consuming. To tackle this open challenge, we introduce a straightforward yet efficient hybrid deep learning approach, named ResBiLSTM, for detecting epileptic seizures using EEG signals. Firstly, a one-dimensional residual neural network (ResNet) is tailored to adeptly extract the local spatial features of EEG signals. Subsequently, the acquired features are input into a bidirectional long short-term memory (BiLSTM) layer to model temporal dependencies. These output features are further processed through two fully connected layers to achieve the final epileptic seizure detection. The performance of ResBiLSTM is assessed on the epileptic seizure datasets provided by the University of Bonn and Temple University Hospital (TUH). The ResBiLSTM model achieves epileptic seizure detection accuracy rates of 98.88–100% in binary and ternary classifications on the Bonn dataset. Experimental outcomes for seizure recognition across seven epilepsy seizure types on the TUH seizure corpus (TUSZ) dataset indicate that the ResBiLSTM model attains a classification accuracy of 95.03% and a weighted F1 score of 95.03% with 10-fold crossvalidation. These findings illustrate that ResBiLSTM outperforms several recent deep learning state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) has been the primary diagnostic tool in clinical epilepsy for nearly a century. Its review is performed using qualitative clinical methods that have changed little over time. However, the intersection of higher resolution digital EEG and analytical tools developed in the past decade invites a re‐exploration of relevant methodology. In addition to the established spatial and temporal markers of spikes and high‐frequency oscillations, novel markers involving advanced postprocessing and active probing of the interictal EEG are gaining ground. This review provides an overview of the EEG‐based passive and active markers of cortical excitability in epilepsy and of the techniques developed to facilitate their identification. Several different emerging tools are discussed in the context of specific EEG applications and the barriers we must overcome to translate these tools into clinical practice. [ABSTRACT FROM AUTHOR]

Absence seizures--generalized rhythmic spike-and-wave discharges (SWDs) are the defining property of childhood (CAE) and juvenile (JAE) absence epilepsies. Such seizures are the most compelling examples of pathological neuronal hypersynchrony. All the absence detection algorithms proposed so far have been derived from the properties of individual SWDs. In this work, we investigate EEG phase synchronization in patients with CAE/JAE and healthy subjects to explore the possibility of using the wavelet phase synchronization index to detect seizures and quantify their disorganization (fragmentation). The overlap of the ictal and interictal probability density functions was high enough to preclude effective seizure detection based solely on changes in EEG synchronization. We used a machine learning classifier with the phase synchronization index (calculated for 1 s data segments with 0.5 s overlap) and the normalized amplitude as features to detect generalized SWDs. Using 19 channels (10-20 setup), we identified 99.2% of absences. However, the overlap of the segments classified as ictal with seizures was only 83%. The analysis showed that seizures were disorganized in approximately half of the 65 subjects. On average, generalized SWDs lasted about 80% of the duration of abnormal EEG activity. The disruption of the ictal rhythm can manifest itself as the disappearance of epileptic spikes (with high-amplitude delta waves persisting), transient cessation of epileptic discharges, or loss of global synchronization. The detector can analyze a real-time data stream. Its performance is good for a six-channel setup (Fp1, Fp2, F7, F8, O1, O2), which can be implemented as an unobtrusive EEG headband. False detections are rare for controls and young adults (0.03% and 0.02%, respectively). In patients, they are more frequent (0.5%), but in approximately 82% cases, classification errors are caused by short epileptiform discharges. Most importantly, the proposed detector can be applied to parts of EEGwith abnormal EEGactivity to quantitatively determine seizure fragmentation. This property is important because a previous study reported that the probability of disorganized discharges is eight times higher in JAE than in CAE. Future research must establish whether seizure properties (frequency, length, fragmentation, etc.) and clinical characteristics can help distinguish CAE and JAE. [ABSTRACT FROM AUTHOR]

Background: Riluzole (RLZ) has demonstrated neuroprotective effects in several neurological disorders. These neuroprotective effects seem to be mainly due to its ability to inhibit the excitatory glutamatergic neurotransmission, acting on different targets located both at the presynaptic and postsynaptic levels. Methods: In the present study, we evaluated the effects of Riluzole (RLZ) against limbic seizures, induced by AMPA, kainate, and NMDA receptor agonists in Sprague–Dawley rats, and in a well-validated genetic model of absence epilepsy, the WAG/Rij rat. Furthermore, in this latter model, we also studied the effect of RLZ in co-administration with the competitive NMDA receptor antagonist, CPP, or the non-competitive AMPA receptor antagonist, THIQ-10c, on spike-wave discharges (SWDs) in WAG/Rij rats, to understand the potential involvement of AMPA and NMDA receptors in the anti-absence effect of RLZ. Results: In Sprague–Dawley rats, RLZ pretreatment significantly reduced the limbic seizure severity induced by glutamatergic agonists, suggesting an antagonism of RLZ mainly on NMDA rather than non-NMDA receptors. RLZ also reduced SWD parameters in WAG/Rij rats. Interestingly, the co-administration of RLZ with CPP did not increase the anti-absence activity of RLZ in this model, advocating a competitive effect on the NMDA receptor. In contrast, the co-administration of RLZ with THIQ-10c induced an additive effect against absence seizure in WAG/Rij rats. Conclusions: these results suggest that the antiepileptic effects of RLZ, in both seizure models, can be mainly due to the antagonism of the NMDA glutamatergic receptors. [ABSTRACT FROM AUTHOR]

Despite recent advances in neuroimaging and genetics, electroencephalography (EEG) continues to play a central role in the diagnosis and management of epilepsy. One application of EEG is called pharmaco-EEG. This technique is highly sensitive in detecting the effects of drugs on brain functioning and shows potential in predicting the efficacy and tolerability of anti-seizure medications (ASMs). In this narrative review, the authors discuss the most salient data concerning the effects of different ASMs on EEG. The authors aim to provide a clear and concise overview of the current state of research in this area, while also identifying opportunities for future investigation. To date, pharmaco-EEG does not appear to be clinically reliable for predicting treatment response in epilepsy, as the literature is limited by underreporting of negative results, a lack of controls in many studies and insufficient direct replication of previous findings. Future research should focus on controlled interventional studies, which are currently lacking. [ABSTRACT FROM AUTHOR]

Long-term home monitoring of people living with epilepsy cannot be achieved using the standard full-scalp electroencephalography (EEG) coupled with video. Wearable seizure detection devices, such as behind-the-ear EEG (bte-EEG), offer an unobtrusive method for ambulatory follow-up of this population. Combining bte-EEG with electrocardiography (ECG) can enhance automated seizure detection performance. However, such frameworks produce high false alarm rates, making visual review necessary. This study aimed to evaluate a semi-automated multimodal wearable seizure detection framework using bte-EEG and ECG. Using the SeizeIT1 dataset of 42 patients with focal epilepsy, an automated multimodal seizure detection algorithm was used to produce seizure alarms. Two reviewers evaluated the algorithm's detections twice: (1) using only bte-EEG data and (2) using bte-EEG, ECG, and heart rate signals. The readers achieved a mean sensitivity of 59.1% in the bte-EEG visual experiment, with a false detection rate of 6.5 false detections per day. Adding ECG resulted in a higher mean sensitivity (62.2%) and a largely reduced false detection rate (mean of 2.4 false detections per day), as well as an increased inter-rater agreement. The multimodal framework allows for efficient review time, making it beneficial for both clinicians and patients. [ABSTRACT FROM AUTHOR]

Lowvoltage fast (LVF) and hypersynchronous (HYP) patterns are the seizure-onset patterns most frequently observed in intracranial EEG recordings from mesial temporal lobe epilepsy (MTLE) patients. Both patterns also occur in models of MTLE in vivo and in vitro, and these studies have highlighted the predominant involvement of distinct neuronal network/neurotransmitter receptor signaling in each of them. First, LVF-onset seizures in epileptic rodents can originate from several limbic structures, frequently spread, and are associated with high-frequency oscillations in the ripple band (80-200 Hz), whereas HYP onset seizures initiate in the hippocampus and tend to remain focal with predominant fast ripples (250-500 Hz). Second, in vitro intracellular recordings from principal cells in limbic areas indicate that pharmacologically induced seizure-like discharges with LVF onset are initiated by a synchronous inhibitory event or by a hyperpolarizing inhibitory postsynaptic potential barrage; in contrast, HYP onset is associated with a progressive impairment of inhibition and concomitant unrestrained enhancement of excitation. Finally, in vitro optogenetic experiments show that, under comparable experimental conditions (i.e., 4-aminopyridine application), the initiation of LVFor HYP-onset seizures depends on the preponderant involvement of interneuronal or principal cell networks, respectively. Overall, these data may provide insight to delineate better therapeutic targets in the treatment of patients presenting with MTLE and, perhaps, with other epileptic disorders as well. [ABSTRACT FROM AUTHOR]

Objectives: Hemispherotomy (HT) is a surgical option for treatment of drug-resistant seizures due to hemispheric structural lesions. Factors affecting seizure outcome have not been fully clarified. In our study, we used a brain Machine Learning (ML) approach to evaluate the possible role of Inter-hemispheric EEG Connectivity (IC) in predicting post-surgical seizure outcome. Methods: We collected 21 pediatric patients with drug-resistant epilepsy; who underwent HT in our center from 2009 to 2020; with a follow-up of at least two years. We selected 5-s windows of wakefulness and sleep pre-surgical EEG and we trained Artificial Neuronal Network (ANN) to estimate epilepsy outcome. We extracted EEG features as input data and selected the ANN with best accuracy. Results: Among 21 patients, 15 (71%) were seizure and drug-free at last follow-up. ANN showed 73.3% of accuracy, with 85% of seizure free and 40% of non-seizure free patients appropriately classified. Conclusions: The accuracy level that we reached supports the hypothesis that pre-surgical EEG features may have the potential to predict epilepsy outcome after HT. Significance: The role of pre-surgical EEG data in influencing seizure outcome after HT is still debated. We proposed a computational predictive model, with an ML approach, with a high accuracy level. [ABSTRACT FROM AUTHOR]

Background: Brain function is thought to rely on complex interactions of dynamic neural systems, which depend on the integrity of structural and functional networks. Focal epilepsy is considered to result from excessive focal synchronization in the network. Synchronization analysis of multichannel electrocorticography (ECoG) contributes to the understanding of and orientation of epilepsy. The aim of this study was to explore the synchronization in multichannel ECoG recordings from patients with neocortical epilepsy and characterize neural activity inside and outside the onset zone. Methods: Four patients with neocortical epilepsy, who became seizure-free for more than 1 year after surgery guided by ECoG monitoring, were included in this study. ECoG data recorded during pre-surgical evaluation were analyzed. Synchronizations in phase and amplitude of different frequency bands between ECoG channels was analyzed using MATLAB. We generated 100 surrogate data from the original ECoG data using Amplitude Adjusted Fourier Transform to calculate the enhanced synchronization. The relationship between synchronization characteristics and seizure onset zone was analyzed. Results: We found synchronization clusters in the 14–30 Hz and 30–80 Hz bands around the onset areas during both interictal and the beginning of ictal periods in all four patients. Conclusions: The enhanced-synchronization clusters play a central role in epilepsy, and may activate the onset areas and contribute to the spreading of epileptiform activity. [ABSTRACT FROM AUTHOR]

Under physiological conditions, neuronal network synchronization leads to different oscillatory EEG patterns that are associated with specific behavioral and cognitive functions. Excessive synchronization can, however, lead to focal or generalized epileptiform activities. It is indeed well established that in both epileptic patients and animal models, focal epileptiform EEG patterns are characterized by interictal and ictal (seizure) discharges. Over the last three decades, employing in vitro and in vivo recording techniques, several experimental studies have firmly identified a paradoxical role of GABAA signaling in generating interictal discharges, and in initiating—and perhaps sustaining—focal seizures. Here, we will review these experiments and we will extend our appraisal to evidence suggesting that GABAA signaling may also contribute to epileptogenesis, i.e., the development of plastic changes in brain excitability that leads to the chronic epileptic condition. Overall, we anticipate that this information should provide the rationale for developing new specific pharmacological treatments for patients presenting with focal epileptic disorders such as mesial temporal lobe epilepsy (MTLE). [ABSTRACT FROM AUTHOR]

There is an urgent need for more informative quantitative techniques that non-invasively and objectively assess strategies for epilepsy surgery. Invasive intracranial electroencephalography (iEEG) remains the clinical gold standard to investigate the nature of the epileptogenic zone (EZ) before surgical resection. However, there are major limitations of iEEG, such as the limited spatial sampling and the degree of subjectivity inherent in the analysis and clinical interpretation of iEEG data. Recent advances in network analysis and dynamical network modeling provide a novel aspect toward a more objective assessment of the EZ. The advantage of such approaches is that they are data-driven and require less or no human input. Multiple studies have demonstrated success using these approaches when applied to iEEG data in characterizing the EZ and predicting surgical outcomes. However, the limitations of iEEG recordings equally apply to these studies—limited spatial sampling and the implicit assumption that iEEG electrodes, whether strip, grid, depth or stereo EEG (sEEG) arrays, are placed in the correct location. Therefore, it is of interest to clinicians and scientists to see whether the same analysis and modeling techniques can be applied to whole-brain, non-invasive neuroimaging data (from MRI-based techniques) and neurophysiological data (from MEG and scalp EEG recordings), thus removing the limitation of spatial sampling, while safely and objectively characterizing the EZ. This review aims to summarize current state of the art non-invasive methods that inform epilepsy surgery using network analysis and dynamical network models. We also present perspectives on future directions and clinical applications of these promising approaches. [ABSTRACT FROM AUTHOR]

Background: Patients with generalized epilepsy who had lateralized EEG abnormalities after corpus callosotomy (CC) occasionally undergo subsequent surgeries to control intractable epilepsy. Objectives: This study evaluated retrospectively the combination of EEG multiscale entropy (MSE) and FDG-PET for identifying lateralization of the epileptogenic zone after CC. Methods: This study included 14 patients with pharmacoresistant epilepsy who underwent curative epilepsy surgery after CC. Interictal scalp EEG and FDG-PET obtained after CC were investigated to determine (1) whether the MSE calculated from the EEG and FDG-PET findings was lateralized to the surgical side, and (2) whether the lateralization was associated with seizure outcomes. Results: Seizure reduction rate was higher in patients with lateralized findings to the surgical side than those without (MSE: p < 0.05, FDG-PET: p < 0.05, both: p < 0.01). Seizure free rate was higher in patients with lateralized findings in both MSE and FDG-PET than in those without (p < 0.05). Conclusions: This study demonstrated that patients with lateralization of MSE and FDG-PET to the surgical side had better seizure outcomes. The combination of MSE and conventional FDG-PET may help to select surgical candidates for additional surgery after CC with good postoperative seizure outcomes. [ABSTRACT FROM AUTHOR]

Objective: The features of cerebral metabolism associated with loss of consciousness in patients with temporal lobe epilepsy (TLE) have not been fully elucidated. We aim to investigate the alterations in cortical-subcortical metabolism in temporal lobe epilepsy with impaired awareness seizures (IAS). Methods: Regional cerebral metabolism was measured using fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET) in patients with TLE-IAS and healthy controls. All patients had a comprehensive evaluation to confirm their seizure origin and lateralization. Videos of all seizures were viewed and rated by at least two epileptologists to identify the state of consciousness when a seizure occurred. By synthesizing the seizure history, semeiology, and video EEG of all patients, as long as the patients had one seizure with impaired awareness, she/he will be included. 76 patients with TLE-IAS and 60 age-matched healthy controls were enrolled in this study. Regional cerebral metabolic patterns were analyzed for TLE-IAS and healthy control groups using statistical parametric mapping. Besides, we compared the MRI-negative patients and MRI-positive patients with healthy controls, respectively. Results: There were no significant differences in the age and sex of TLE-IAS patients and healthy control. TLE-IAS patients showed extensive bilateral hypermetabolism in the frontoparietal regions, cingulate gyrus, corpus callosum, occipital lobes, basal ganglia, thalamus, brainstem, and cerebellum. The region of metabolic change was more extensive in right TLE-IAS than that of the left, including extensive hypometabolism in the ipsilateral temporal, frontal, parietal, and insular lobes. And contralateral temporal lobe, bilateral frontoparietal regions, occipital lobes, the anterior and posterior regions of the cingulate gyrus, bilateral thalamus, bilateral basal ganglia, brainstem, and bilateral cerebellum showed hypermetabolism. The TLE patients with impaired awareness seizure showed hypermetabolism in the cortical-subcortical network including the arousal system. Additionally, 48 MRI-positive and 28 MRI-negative TLE-IAS patients were included in our study. TLE-IAS patients with MRI-negative and MRI-positive were both showed hypermetabolism in the cingulate gyrus. Hypometabolism in the bilateral temporal lobe was showed in the TLE-IAS with MRI-positive. Conclusion: These findings suggested that the repetitive consciousness impairing ictal events may have an accumulative effect on brain metabolism, resulting in abnormal interictal cortical-subcortical metabolic disturbance in TLE patients with impaired awareness seizure. Understanding these metabolic mechanisms may guide future clinical treatments to prevent seizure-related awareness deficits and improve quality of life in people with TLE. [ABSTRACT FROM AUTHOR]

Epilepsy surgery can be a very effective therapy in medication refractory patients. During patient evaluation intracranial EEG is analyzed by clinical experts to identify the brain tissue generating epileptiform events. Quantitative EEG analysis increasingly complements this approach in research settings, but not yet in clinical routine. We investigate the correspondence between epileptiform events and a specific quantitative EEG marker. We analyzed 99 preictal epochs of multichannel intracranial EEG of 40 patients with mixed etiologies. Time and channel of occurrence of epileptiform events (spikes, slow waves, sharp waves, fast oscillations) were annotated by a human expert and non-linear excess interrelations were calculated as a quantitative EEG marker. We assessed whether the visually identified preictal events predicted channels that belonged to the seizure onset zone, that were later resected or that showed strong non-linear interrelations. We also investigated whether the seizure onset zone or the resection were predicted by channels with strong non-linear interrelations. In patients with temporal lobe epilepsy (32 of 40), epileptic spikes and the seizure onset zone predicted the resected brain tissue much better in patients with favorable seizure control after surgery than in unfavorable outcomes. Beyond that, our analysis did not reveal any significant associations with epileptiform EEG events. Specifically, none of the epileptiform event types did predict non-linear interrelations. In contrast, channels with strong non-linear excess EEG interrelations predicted the resected channels better in patients with temporal lobe epilepsy and favorable outcome. Also in the small number of patients with seizure onset in the frontal and parietal lobes, no association between epileptiform events and channels with strong non-linear excess EEG interrelations was detectable. In contrast to patients with temporal seizure onset, EEG channels with strong non-linear excess interrelations did neither predict the seizure onset zone nor the resection of these patients or allow separation between patients with favorable and unfavorable seizure control. Our study indicates that non-linear excess EEG interrelations are not strictly associated with epileptiform events, which are one key concept of current clinical EEG assessment. Rather, they may provide information relevant for surgery planning in temporal lobe epilepsy. Our study suggests to incorporate quantitative EEG analysis in the workup of clinical cases. We make the EEG epochs and expert annotations publicly available in anonymized form to foster similar analyses for other quantitative EEG methods. [ABSTRACT FROM AUTHOR]

Background: Epileptic seizures are caused by abnormal brain wave hypersynchronization leading to a range of signs and symptoms. Tools for detecting seizures in everyday life typically focus on cardiac rhythm, electrodermal activity, or movement (EMG, accelerometry); however, these modalities are not very effective for non-motor seizures. Ultra long-term subcutaneous EEG-devices can detect the electrographic changes that do not depend on clinical changes. Nonetheless, this also means that it is not possible to assess whether a seizure is clinical or subclinical based on an EEG signal alone. Therefore, we combine EEG and movement-related modalities in this work. We focus on whether it is possible to define an individual "multimodal ictal fingerprint" which can be exploited in different epilepsy management purposes. Methods: This study used ultra long-term data from an outpatient monitoring trial of persons with temporal lobe epilepsy obtained with a subcutaneous EEG recording system. Subcutaneous EEG, an EMG estimate and chest-mounted accelerometry were extracted from four persons showing more than 10 well-defined electrographic seizures each. Numerous features were computed from all three modalities. Based on these, the Gini impurity measure of a Random Forest classifier was used to select the most discriminative features for the ictal fingerprint. A total of 74 electrographic seizures were analyzed. Results: The optimal individual ictal fingerprints included features extracted from all three tested modalities: an acceleration component; the power of the estimated EMG activity; and the relative power in the delta (0.5–4 Hz), low theta (4–6 Hz), and high theta (6–8 Hz) bands of the subcutaneous EEG. Multimodal ictal fingerprints were established for all persons, clustering seizures within persons, while separating seizures across persons. Conclusion: The existence of multimodal ictal fingerprints illustrates the benefits of combining multiple modalities such as EEG, EMG, and accelerometry in future epilepsy management. Multimodal ictal fingerprints could be used by doctors to get a better understanding of the individual seizure semiology of people with epilepsy. Furthermore, the multimodal ictal fingerprint gives a better understanding of how seizures manifest simultaneously in different modalities. A knowledge that could be used to improve seizure acknowledgment when reviewing EEG without video. [ABSTRACT FROM AUTHOR]

Objective: Accurate estimation of the epileptogenic zone (EZ) is essential for favorable outcomes in epilepsy surgery. Conventional ictal electrocorticography (ECoG) onset is generally used to detect the EZ but is insufficient in achieving seizure-free outcomes. By contrast, high-frequency oscillations (HFOs) could be useful markers of the EZ. Hence, we aimed to detect the EZ using interictal spikes and investigated whether the onset area of interictal spike-related HFOs was within the EZ. Methods: The EZ is considered to be included in the resection area among patients with seizure-free outcomes after surgery. Using a complex demodulation technique, we developed a method to determine the onset channels of interictal spike-related ripples (HFOs of 80–200 Hz) and investigated whether they are within the resection area. Results: We retrospectively examined 12 serial patients who achieved seizure-free status after focal resection surgery. Using the method that we developed, we determined the onset channels of interictal spike-related ripples and found that for all 12 patients, they were among the resection channels. The onset frequencies of ripples were in the range of 80–150 Hz. However, the ictal onset channels (evaluated based on ictal ECoG patterns) and ripple onset channels coincided in only 3 of 12 patients. Conclusions: Determining the onset area of interictal spike-related ripples could facilitate EZ estimation. This simple method that utilizes interictal ECoG may aid in preoperative evaluation and improve epilepsy surgery outcomes. [ABSTRACT FROM AUTHOR]

It is now widely accepted that seizures arise from the coordinated activity of epileptic networks, and as a result, traditional methods of analyzing seizures have been augmented by techniques like single‐pulse electrical stimulation (SPES) that estimate effective connectivity in brain networks. We used SPES and graph analytics in 18 patients undergoing intracranial EEG monitoring to investigate effective connectivity between recording sites within and outside mesial temporal structures. We compared evoked potential amplitude, network density, and centrality measures inside and outside the mesial temporal region (MTR) across three patient groups: focal epileptogenic MTR, multifocal epileptogenic MTR, and non‐epileptogenic MTR. Effective connectivity within the MTR had significantly greater magnitude (evoked potential amplitude) and network density, regardless of epileptogenicity. However, effective connectivity between MTR and surrounding non‐epileptogenic regions was of greater magnitude and density in patients with focal epileptogenic MTR compared to patients with multifocal epileptogenic MTR and those with non‐epileptogenic MTR. Moreover, electrodes within focal epileptogenic MTR had significantly greater outward network centrality compared to electrodes outside non‐epileptogenic regions and to multifocal and non‐epileptogenic MTR. Our results indicate that the MTR is a robustly connected subnetwork that can exert an overall elevated propagative influence over other brain regions when it is epileptogenic. Understanding the underlying effective connectivity and roles of epileptogenic regions within the larger network may provide insights that eventually lead to improved surgical outcomes. [ABSTRACT FROM AUTHOR]

Introduction: Despite all the efforts for optimizing epilepsy management in children over the past decades, there is no clear consensus regarding whether to treat or not to treat epileptiform discharges (EDs) after a first unprovoked seizure or the optimal duration of therapy with anti-seizure medication (ASM). It is therefore highly needed to find markers on scalp electroencephalogram (EEG) that can help identify pathological EEG discharges that require treatment. Aim of the study: This retrospective study aimed to identify whether the coexistence of ripples/high-frequency oscillations (HFOs) with interictal EDs (IEDs) in routinely acquired scalp EEG is associated with a higher risk of seizure recurrence and could be used as a prognostic marker. Methods: 100 children presenting with new onset seizure to Children's Medical Center- Dallas during 2015–2016, who were not on ASM and had focal EDs on an awake and sleep EEG recorded with sample frequency of 500 HZ, were randomly identified by database review. EEGs were analyzed blinded to the data of the patients. HFOs were visually identified using review parameters including expanded time base and adjusted filter settings. Results: The average age of patients was 6.3 years (±4.35 SD). HFOs were visually identified in 19% of the studied patients with an inter-rater reliability of 99% for HFO negative discharges and 78% agreement for identification of HFOs. HFOs were identified more often in the younger age group; however, they were identified in 11% of patients >5 years old. They were more frequently associated with spikes than with sharp waves and more often with higher amplitude EDs. Patients with HFOs were more likely to have a recurrence of seizures in the year after the first seizure (P < 0.05) and to continue to have seizures after 2 years (P < 0.0001). There was no statistically significant difference between the two groups with regards to continuing ASM after 2 years. Conclusion: Including analysis for HFOs in routine EEG interpretation may increase the yield of the study and help guide the decision to either start or discontinue ASM. In the future, this may also help to identify pathological discharges with deleterious effects on the growing brain and set a new target for the management of epilepsy. [ABSTRACT FROM AUTHOR]

Objective: Paroxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations. Methods: Confounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome‐wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses. Results: Our analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations. Significance: Our results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy. [ABSTRACT FROM AUTHOR]

Polymicrogyria (PMG) is a common malformation of cortical development associated with a higher susceptibility to epileptic seizures. Seizures secondary to PMG are characterized by difficult-to-localize cerebral sources due to the complex and widespread lesion structure. Tracing the dynamics of interictal epileptiform discharges (IEDs) in patients with epilepsy has been shown to reveal the location of epileptic activity sources, crucial for successful treatment in cases of focal drug-resistant epilepsy. In this case series IED dynamics were evaluated with simultaneous EEG-fMRI recordings in four patients with unilateral peri-sylvian polymicrogyria (PSPMG) by tracking BOLD activations over time: before, during and following IED appearance on scalp EEG. In all cases, focal BOLD activations within the lesion itself preceded the activity associated with the time of IED appearance on EEG, which showed stronger and more widespread activations. We therefore propose that early hemodynamic activity corresponding to IEDs may hold important localizing information potentially leading to the cerebral sources of epileptic activity. IEDs are suggested to develop within a small area in the PSPMG lesion with structural properties obscuring the appearance of their electric field on the scalp and only later engage widespread structures which allow the production of large currents which are recognized as IEDs on EEG. [ABSTRACT FROM AUTHOR]