Epileptogenicity of brain structures in human temporal lobe epilepsy: a quantified study from intracerebral EEG

A comparative study between a power and a connectivity sEEG biomarker for seizure-onset zone identification in temporal lobe epilepsy

BACKGROUND

Ictal stereo-encephalography (sEEG) biomarkers for seizure onset zone (SOZ) localization can be classified depending on whether they target abnormalities in signal power or functional connectivity between signals, and they may depend on the frequency band and time window at which they are estimated.

NEW METHOD

This work aimed to compare and optimize the performance of a power and a connectivity-based biomarker to identify SOZ contacts from ictal sEEG recordings. To do so, we used a previously introduced power-based measure, the normalized mean activation (nMA), which quantifies the ictal average power activation. Similarly, we defined the normalized mean strength (nMS), to quantify the ictal mean functional connectivity of every contact with the rest. The optimal frequency bands and time windows were selected based on optimizing AUC and F2-score.

RESULTS

The analysis was performed on a dataset of 67 seizures from 10 patients with pharmacoresistant temporal lobe epilepsy. Our results suggest that the power-based biomarker generally performs better for the detection of SOZ than the connectivity-based one. However, an equivalent performance level can be achieved when both biomarkers are independently optimized. Optimal performance was achieved in the beta and lower-gamma range for the power biomarker and in the lower- and higher-gamma range for connectivity, both using a 20 or 30 s period after seizure onset.

CONCLUSIONS

The results of this study highlight the importance of this optimization step over frequency and time windows when comparing different SOZ discrimination biomarkers. This information should be considered when training SOZ classifiers on retrospective patients' data for clinical applications.

The epileptogenic network concept: Applications in the SEEG exploration of lesional focal epilepsies

The advent of advanced brain imaging techniques has significantly enhanced the understanding and treatment of focal epilepsies, with identifiable brain lesions present in 80 % of cases. Despite this, surgical outcomes remain varied, often influenced by lesion type and location. Traditional lesion-centric approaches may overlook the complex organization of the epileptogenic zone (EZ), which often extends beyond the visible lesion, emphasizing the need for comprehensive presurgical evaluations like stereo-electroencephalography (SEEG) in some cases. This article delves into the concept of epileptogenic networks, moving beyond the notion of a lesional epileptic focus. Through SEEG, three primary network types have been identified: the Epileptogenic Zone Network (EZN), characterized by regions with heightened epileptogenicity and seizure initiation; the Propagation Zone Network (PZN), involving regions with delayed and less intense epileptic activity; and Non-Involved networks (NI). Quantitative measures, such as the epileptogenicity index (EI), aid in delineating these networks, revealing that EZN can be focal or networked, with the latter being more prevalent. The relationship between epilepsy-associated lesions and network organization is complex. Intrinsically epileptogenic lesions, like focal cortical dysplasia and periventricular nodular heterotopias, often generate epileptiform activities but may still involve broader epileptogenic networks. Non-intrinsically epileptogenic lesions, such as cavernomas and post-stroke lesions, typically lack inherent neuronal activity but can facilitate the development of extensive epileptogenic networks. Understanding the intricacies of these networks is crucial for optimizing surgical interventions. Recognizing that lesions may represent just one node within a broader epileptogenic network underscores the importance of comprehensive SEEG evaluations to achieve better surgical outcomes.

Interictal stereo-electroencephalography features below 45 Hz are sufficient for correct localization of the epileptogenic zone and postsurgical outcome prediction

OBJECTIVE

Evidence suggests that the most promising results in interictal localization of the epileptogenic zone (EZ) are achieved by a combination of multiple stereo-electroencephalography (SEEG) biomarkers in machine learning models. These biomarkers usually include SEEG features calculated in standard frequency bands, but also high-frequency (HF) bands. Unfortunately, HF features require extra effort to record, store, and process. Here we investigate the added value of these HF features for EZ localization and postsurgical outcome prediction.

METHODS

In 50 patients we analyzed 30 min of SEEG recorded during non-rapid eye movement sleep and tested a logistic regression model with three different sets of features. The first model used broadband features (1-500 Hz); the second model used low-frequency features up to 45 Hz; and the third model used HF features above 65 Hz. The EZ localization by each model was evaluated by various metrics including the area under the precision-recall curve (AUPRC) and the positive predictive value (PPV). The differences between the models were tested by the Wilcoxon signed-rank tests and Cliff's Delta effect size. The differences in outcome predictions based on PPV values were further tested by the McNemar test.

RESULTS

The AUPRC score of the random chance classifier was .098. The models (broad-band, low-frequency, high-frequency) achieved median AUPRCs of .608, .582, and .522, respectively, and correctly predicted outcomes in 38, 38, and 33 patients. There were no statistically significant differences in AUPRC or any other metric between the three models. Adding HF features to the model did not have any additional contribution.

SIGNIFICANCE

Low-frequency features are sufficient for correct localization of the EZ and outcome prediction with no additional value when considering HF features. This finding allows significant simplification of the feature calculation process and opens the possibility of using these models in SEEG recordings with lower sampling rates, as commonly performed in clinical routines.

Prognostic value of scalp EEG ictal patterns in epilepsy surgery of hippocampal sclerosis

BACKGROUND

Temporal lobe epilepsy associated with hippocampal sclerosis (TLE-HS) is a surgically treatable epileptic syndrome. While the core of pre-surgical evaluations rely on video-EEG, recent studies question the necessity of recorded seizures denying a possible role of ictal EEG in surgical decision. This study aims to retrospectively assess the prognostic value of EEG ictal patterns in TLE-HS, in order to identify which patients need further investigations before offering surgery.

METHODS

We included TLE-HS patients who underwent surgery with at least one captured seizure during non-invasive pre-surgical video-EEG recordings. They were classified in "mesial" and "lateral/mixed", according to the ictal EEG patterns, defined by the frequency of the discharge (mesial ≥ 5 Hz, lateral < 5 Hz). Seizure outcome was assessed by Engel's Class. Statistical analyses were performed to evaluate associations between EEG patterns and post-surgical outcomes.

RESULTS

Sixty-nine exhibited a mesial pattern, forty- two displayed lateral/mixed patterns. Mesial pattern group had a significantly higher rate of postsurgical seizure freedom (82.7% vs. 28.6%). Gender, age of onset, age at surgery, duration of epilepsy, seizure frequency, and lateralization did not influence the outcome. Mesial pattern significantly correlated with favorable outcomes (p < 0.001), suggesting its potential predictive value.

CONCLUSION

This retrospective study proposes ictal EEG patterns as possible predictors of postoperative prognosis in TLE-HS. A mesial pattern correlates with better outcomes, indicating a potentially more circumscribed epileptogenic zone. Patients with lateral/mixed patterns may benefit from additional investigations to delineate the epileptogenic zone. Further studies are warranted to validate and extend these findings.

Brain sodium MRI-derived priors support the estimation of epileptogenic zones using personalized model-based methods in epilepsy

Patients presenting with drug-resistant epilepsy are eligible for surgery aiming to remove the regions involved in the production of seizure activities, the so-called epileptogenic zone network (EZN). Thus the accurate estimation of the EZN is crucial. Data-driven, personalized virtual brain models derived from patient-specific anatomical and functional data are used in Virtual Epileptic Patient (VEP) to estimate the EZN via optimization methods from Bayesian inference. The Bayesian inference approach used in previous VEP integrates priors, based on the features of stereotactic-electroencephalography (SEEG) seizures' recordings. Here, we propose new priors, based on quantitative 23Na-MRI. The 23Na-MRI data were acquired at 7T and provided several features characterizing the sodium signal decay. The hypothesis is that the sodium features are biomarkers of neuronal excitability related to the EZN and will add additional information to VEP estimation. In this paper, we first proposed the mapping from 23Na-MRI features to predict the EZN via a machine learning approach. Then, we exploited these predictions as priors in the VEP pipeline. The statistical results demonstrated that compared with the results from current VEP, the result from VEP based on 23Na-MRI prior has better balanced accuracy, and the similar weighted harmonic mean of the precision and recall.

Transient alteration of Awareness triggered by direct electrical stimulation of the brain

BACKGROUND

Awareness is a state of consciousness that enables a subject to interact with the environment. Transient alteration of awareness (AA) is a disabling sign of many types of epileptic seizures. The brain mechanisms of awareness and its alteration are not well known.

OBJECTIVE/HYPOTHESIS

Transient and isolated AA induced by electrical brain stimulation during a stereoelectroencephalography (SEEG) recording represents an ideal model for studying the associated modifications of functional connectivity and locating the hubs of awareness networks.

METHODS

We investigated the SEEG signals-based brain functional connectivity (FC) changes vs background occurring during AA triggered by three thalamic and two insular stimulations in three patients explored by SEEG in the frame of presurgical evaluation for focal drug-resistant epilepsy. The results were compared to the stimulations of the same sites that did not induce clinical changes (negative stimulations).

RESULTS

We observed decreased node strength in the pulvinar, insula, and parietal associative cortices during the thalamic and insular stimulations that induced AA. The link strengths characterizing functional coupling between the thalamus and the insular, prefrontal, temporal, or parietal associative cortices were also decreased. In contrast, there was an increased synchronization between the precuneus and the temporal lateral cortex. These FC changes were absent during the negative stimulations.

CONCLUSION

Our study highlights the role of the pulvinar, insular, and parietal hubs in maintaining the awareness networks and paves the way for invasive or non-invasive neuromodulation protocols to reduce AA manifestations during epileptic seizures.

Investigating current clinical opinions in stereoelectroencephalography-informed epilepsy surgery

OBJECTIVE

Stereoelectroencephalography (SEEG) is increasingly utilized worldwide in epilepsy surgery planning. International guidelines for SEEG terminology and interpretation are yet to be proposed. There are worldwide differences in SEEG definitions, application of features in epilepsy surgery planning, and interpretation of surgical outcomes. This hinders the clinical interpretation of SEEG findings and collaborative research. We aimed to assess the global perspectives on SEEG terminology, differences in the application of presurgical features, and variability in the interpretation of surgery outcome scores, and analyze how clinical expert demographics influenced these opinions.

METHODS

We assessed the practices and opinions of epileptologists with specialized training in SEEG using a survey. Data were qualitatively analyzed, and subgroups were examined based on geographical regions and years of experience. Primary outcomes included opinions on SEEG terminology, features used for epilepsy surgery, and interpretation of outcome scores. Additionally, we conducted a multilevel regression and poststratification analysis to characterize the nonresponders.

RESULTS

A total of 321 expert responses from 39 countries were analyzed. We observed substantial differences in terminology, practices, and use of presurgical features across geographical regions and SEEG expertise levels. The majority of experts (220, 68.5%) favored the Lüders epileptogenic zone definition. Experts were divided regarding the seizure onset zone definition, with 179 (55.8%) favoring onset alone and 135 (42.1%) supporting onset and early propagation. In terms of presurgical SEEG features, a clear preference was found for ictal features over interictal features. Seizure onset patterns were identified as the most important features by 265 experts (82.5%). We found similar trends after correcting for nonresponders using regression analysis.

SIGNIFICANCE

This study underscores the need for standardized terminology, interpretation, and outcome assessment in SEEG-informed epilepsy surgery. By highlighting the diverse perspectives and practices in SEEG, this research lays a solid foundation for developing globally accepted terminology and guidelines, advancing the field toward improved communication and standardization in epilepsy surgery.

Innovative minimally invasive options to treat drug-resistant epilepsies

Despite the regular discovery of new molecules, one-third of epileptic patients are resistant to antiepileptic drugs. Only a few can benefit from resective surgery, the current gold standard. Although effective in 50-70% of cases, this therapy remains risky, costly, and can be associated with long-term cognitive or neurological side effects. In addition, patients are increasingly reluctant to have a craniotomy, emphasizing the need for new less invasive therapies for focal drug-resistant epilepsies. Here, we review different minimally invasive approaches already in use in the clinic or under preclinical development to treat drug-resistant epilepsies. Localized thermolesion of the epileptogenic zone has been developed in the clinic using high-frequency thermo-coagulations or magnetic resonance imaging-guided laser or ultrasounds. Although less invasive, they have not yet significantly improved the outcomes when compared with resective surgery. Radiosurgery techniques have been used in the clinic for the last 20years and have proven efficiency. However, their efficacy is not better than resective surgery, and various side effects have been reported as well as the potential risk of sudden unexpected death associated with epilepsy. Recently, a new strategy of radiosurgery has emerged using synchrotron-generated X-ray microbeams: microbeam radiation therapy (MRT). The low divergence and high-flux of the synchrotron beams and the unique tolerance to MRT by healthy brain tissues, allows a precise targeting of specific brain regions with minimal invasiveness and limited behavioral or functional consequences in animals. Antiepileptic effects over several months have been recorded in animal models, and histological and synaptic tracing analysis suggest a reduction of neuronal connectivity as a mechanism of action. The possibility of transferring this approach to epileptic patients is discussed in this review.

Localization of epileptogenic zone based on time-varying effective networks

Surgical resection of the epileptogenic zone (EZ) is an effective method for treating drug-resistant epilepsy. At present, the accuracy of EZ localization needs to be further improved. The characteristics of graph theory based on partial directed coherence networks have been applied to the localization of EZ, but the application of network control theory to effective networks to locate EZ is rarely reported. In this study, the method of partial directed coherence analysis was utilized to construct the time-varying effective brain networks of stereo-electroencephalography (SEEG) signals from 20 seizures in 12 patients. Combined with graph theory and network control theory, the differences in network characteristics between epileptogenic and non-epileptogenic zones during seizures were analyzed. We also used dung beetle optimized support vector machine classification model to evaluate the localization effect of EZ based on brain network characteristics of graph theory and controllability. The results showed that the classification of the average controllability feature was the best, and the area under the receiver operating characteristic (ROC) curve (AUC) was 0.9505, which is 1.32 % and 1.97 % higher than the traditional methods. The AUC value increased to 0.9607 after integrating the average controllability with other features. This study proved the effectiveness of controllability characteristic in identifying the EZ and provided a theoretical basis for the clinical application of network controllability in the EZ.

Ictal Asystole During Focal Seizures Due to Left Occipital Glioneuronal Tumor: A Report of Case Treated With Cardiac Neuromodulation

Ictal asystole (IA) is a rare but potentially life-threatening complication of focal epilepsy. The sudden onset of loss of consciousness and drop attacks in a patient with chronic epilepsy should suggest the possibility of this complication. Once the diagnosis is established, rapid management should be considered, especially in high-risk cases. The approach does not differ between temporal and extratemporal lobe epilepsies. Strategies can be aimed at preventing the emergence of cortical epileptic activity from the beginning (surgery, antiseizure therapy), neutralizing negative chronotropic effects on the heart (cardiac neuromodulation), or restarting the heart rhythm with a pacemaker. Pacemaker implantation is not a completely complication-free treatment, and living with a device that requires care and follow-up throughout life makes alternative treatment methods more valid for young patients with many years to live or cases that could benefit from surgery. In this article, we present a patient with a left occipital glioneuronal tumor and drug-resistant occipital lobe epilepsy. IA was documented by long-term video EEG monitoring (VEM). During about 2 years of follow-up after a cardiac neuromodulation procedure, there were no drop attacks or asystole with seizures, confirmed by long-term VEM.

Whole-brain simulation of interictal epileptic discharges for patient-specific interpretation of interictal SEEG data

In patients with refractory epilepsy, the clinical interpretation of stereoelectroencephalographic (SEEG) signals is crucial to delineate the epileptogenic network that should be targeted by surgery. We propose a pipeline of patient-specific computational modeling of interictal epileptic activity to improve the definition of regions of interest. Comparison between the computationally defined regions of interest and the resected region confirmed the efficiency of the pipeline. This result suggests that computational modeling can be used to reconstruct signals and aid clinical interpretation.

The role of SEEG in the presurgical decision-making process in MRI-normal mesial temporal lobe epilepsy

OBJECTIVES

In patients with mesial temporal lobe epilepsy (mTLE) and normal MRI, anterior temporal lobectomy sparing the hippocampus might be considered because of the risk of post-operative memory deficit. However, it is unclear whether some patients with normal MRI and non-invasive EEG and semiological pattern highly suggestive of mesial temporal seizures demonstrate a seizure onset network sparing the hippocampus, potentially warranting surgery.

METHODS

A retrospective study of 17 patients with mTLE epilepsy and normal MRI who underwent SEEG. Only patients whose non-invasive presurgical data suggested an unilateral mesial temporal epileptogenic zone (EZ), as defined by combination of ictal semiology and ictal EEG during scalp video-EEG, were included. SEEG data were analyzed using both visual and quantitative approaches. Two EZ organization were defined: (i) EZ involved the hippocampus at the onset of the ictal discharge (HIP group): (ii) patients in whom a delay>1sec was observed between the seizure onset and the involvement of the hippocampus (nHIP group). Non-invasive clinical and functional imaging data, as well as post-operative outcomes, were compared across groups.

RESULTS

Eleven patients were included in HIP group and 6 in the nHIP group. In the nHIP group, the maximal epileptogenicity was in the amygdala in five patients and in the entorhinal cortex in one. The hippocampus normalized interictal spiking activity was not different between groups. None of the patients characteristics collected during the non-invasive presurgical workup was associated with the SEEG-based organization of the EZ. Twelve patients underwent a surgical resection, including temporal cortectomy sparing hippocampus in six. Seizure and neuropsychological post-operative outcomes were similar.

CONCLUSION

In patients with MRI-normal mTLE, SEEG should be included in the surgical decision-making process because seizure organization cannot be predicted from non-invasive investigations. When hippocampus is not included in the EZ, temporal resection sparing the hippocampus can be considered.

Epileptic network identification: insights from dynamic mode decomposition of sEEG data

Objective.For medically-refractory epilepsy patients, stereoelectroencephalography (sEEG) is a surgical method using intracranial electrode recordings to identify brain networks participating in early seizure organization and propagation (i.e. the epileptogenic zone, EZ). If identified, surgical EZ treatment via resection, ablation or neuromodulation can lead to seizure-freedom. To date, quantification of sEEG data, including its visualization and interpretation, remains a clinical and computational challenge. Given elusiveness of physical laws or governing equations modelling complex brain dynamics, data science offers unique insight into identifying unknown patterns within high-dimensional sEEG data. We apply here an unsupervised data-driven algorithm, dynamic mode decomposition (DMD), to sEEG recordings from five focal epilepsy patients (three with temporal lobe, and two with cingulate epilepsy), who underwent subsequent resective or ablative surgery and became seizure free.Approach.DMD obtains a linear approximation of nonlinear data dynamics, generating coherent structures ('modes') defining important signal features, used to extract frequencies, growth rates and spatial structures. DMD was adapted to produce dynamic modal maps (DMMs) across frequency sub-bands, capturing onset and evolution of epileptiform dynamics in sEEG data. Additionally, we developed a static estimate of EZ-localized electrode contacts, termed the higher-frequency mode-based norm index (MNI). DMM and MNI maps for representative patient seizures were validated against clinical sEEG results and seizure-free outcomes following surgery.Main results.DMD was most informative at higher frequencies, i.e. gamma (including high-gamma) and beta range, successfully identifying EZ contacts. Combined interpretation of DMM/MNI plots best identified spatiotemporal evolution of mode-specific network changes, with strong concordance to sEEG results and outcomes across all five patients. The method identified network attenuation in other contacts not implicated in the EZ.Significance.This is the first application of DMD to sEEG data analysis, supporting integration of neuroengineering, mathematical and machine learning methods into traditional workflows for sEEG review and epilepsy surgical decision-making.

LncRNA ILF3-AS1 mediates oxidative stress and inflammation through miR-504-3p/HMGB1 axis in a cellular model of temporal lobe epilepsy

BACKGROUND

Temporal lobe epilepsy (TLE), a prevalent neurological disorder, is associated with hippocampal oxidative stress and inflammation. A recent study reveals that the long noncoding RNA ILF3 divergent transcript (ILF3-AS1) level is elevated in the hippocampus of TLE patients; however, the functional roles of ILF3-AS1 in TLE and underlying mechanisms deserve further investigation. Hence, this study aimed to elucidate whether ILF3-AS1 is involved in the pathogenesis of TLE by regulating oxidative stress and inflammation and to explore its underlying mechanism in vitro.

METHODS

Human hippocampal neurons were subjected to a magnesium-free (Mg2+-free) solution to establish an in vitro model of TLE. The potential binding sites between ILF3-AS1 and miRNA were predicted by TargetScan/Starbase and confirmed by dual luciferase reporter assay. Cell viability and damage were assessed by cell counting kit-8 and lactate dehydrogenase assay kits, respectively. Levels of reactive oxygen species, malondialdehyde, and superoxide dismutase were determined by commercial kits. Levels of Interleukin-6 (IL-6), IL-1β, and tumor necrosis factor-alpha were quantified by enzyme-linked immunosorbent assay. The expressions of gene and protein were determined by quantitative real-time polymerase chain reaction and Western blot analysis.

RESULTS

In Mg2+-free-treated hippocampal neurons, both ILF3-AS1 and HMGB1 were highly up-regulated, whereas miR-504-3p was down-regulated. ILF3-AS1 knockdown ameliorated Mg2+-free-induced cellular damage, oxidative stress, and inflammatory response. Bioinformatics analysis revealed that miR-504-3p was a target of ILF3-AS1 and was negatively regulated by ILF3-AS1. MiR-504-3p inhibitor blocked the protection of ILF3-AS1 knockdown against Mg2+-free-induced neuronal injury. Further analysis presented that ILF3-AS1 regulated HMGB1 expression by sponging miR-504-3p. Moreover, HMGB1 overexpression reversed the protective functions of ILF3-AS1 knockdown.

CONCLUSION

Our findings indicate that ILF3-AS1 contributes to Mg2+-free-induced hippocampal neuron injuries, oxidative stress, and inflammation by targeting the miR-504-3p/HMGB1 axis. These results provide a novel mechanistic understanding of ILF3-AS1 in TLE and suggest potential therapeutic targets for the treatment of epilepsy.

Identifying epileptogenic abnormality by decomposing intracranial EEG and MEG power spectra

BACKGROUND

Accurate identification of abnormal electroencephalographic (EEG) activity is pivotal for diagnosing and treating epilepsy. Recent studies indicate that decomposing brain activity into periodic (oscillatory) and aperiodic (trend across all frequencies) components can illuminate the drivers of spectral activity changes.

NEW METHODS

We analysed intracranial EEG (iEEG) data from 234 subjects, creating a normative map. This map was compared to a cohort of 63 patients with refractory focal epilepsy under consideration for neurosurgery. The normative map was computed using three approaches: (i) relative complete band power, (ii) relative band power with the aperiodic component removed, and (iii) the aperiodic exponent. Abnormalities were calculated for each approach in the patient cohort. We evaluated the spatial profiles, assessed their ability to localize abnormalities, and replicated the findings using magnetoencephalography (MEG).

RESULTS

Normative maps of relative complete band power and relative periodic band power exhibited similar spatial profiles, while the aperiodic normative map revealed higher exponent values in the temporal lobe. Abnormalities estimated through complete band power effectively distinguished between good and bad outcome patients. Combining periodic and aperiodic abnormalities enhanced performance, like the complete band power approach.

COMPARISON WITH EXISTING METHODS AND CONCLUSIONS

Sparing cerebral tissue with abnormalities in both periodic and aperiodic activity may result in poor surgical outcomes. Both periodic and aperiodic components do not carry sufficient information in isolation. The relative complete band power solution proved to be the most reliable method for this purpose. Future studies could investigate how cerebral location or pathology influences periodic or aperiodic abnormalities.

Involvement of the contralateral hippocampus in ictal-like but not interictal epileptic activities in the kainate mouse model of temporal lobe epilepsy

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.

Systematic review of seizure-onset patterns in stereo-electroencephalography: Current state and future directions

OBJECTIVE

Increasing evidence suggests that the seizure-onset pattern (SOP) in stereo-electroencephalography (SEEG) is important for localizing the "true" seizure onset. Specifically, SOPs with low-voltage fast activity (LVFA) are associated with seizure-free outcome (Engel I). However, several classifications and various terms corresponding to the same pattern have been reported, challenging its use in clinical practice.

METHOD

Following the Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA) guideline, we performed a systematic review of studies describing SOPs along with accompanying figures depicting the reported SOP in SEEG.

RESULTS

Of 1799 studies, 22 met the selection criteria. Among the various SOPs, we observed that the terminology for low frequency periodic spikes exhibited the most variability, whereas LVFA is the most frequently used term of this pattern. Some SOP terms were inconsistent with standard EEG terminology. Finally, there was a significant but weak association between presence of LVFA and seizure-free outcome.

CONCLUSION

Divergent terms were used to describe the same SOPs and some of these terms showed inconsistencies with the standard EEG terminology. Additionally, our results confirmed the link between patterns with LVFA and seizure-free outcomes. However, this association was not strong.

SIGNIFICANCE

These results underline the need for standardization of SEEG terminology.

The Voyage of SEEG

SUMMARY

It took 50 years for stereoelectroencephalography (SEEG) to cross the Atlantic. Conceived and designed before the advent of computers and modern technology, this method turned out to be perfectly suited to brain imaging and modern video and electrophysiological tools. It eventually benefited from robotics and signal processing. However, a critical step remains accurate electrode implantation, which is based on individual patients' noninvasive phase I data. A limiting factor, especially in MRI-negative cases, is a thorough perictal and postictal clinical testing for ensuring meaningful electroclinical correlations. Adapted epilepsy monitoring units' architecture and specific technicians and nurses training are required to improve the granularity of information needed to generate valid hypotheses on localization. SEEG interpretation is based on a knowledge base in neural networks, cognitive/behavioral neuroscience, and electrophysiology quite distinct from electroencephalography. Tailored to the needs of focal epilepsy complexity exploration, SEEG does not fit well with simplification. Specific teaching and development of clinical research inside the epilepsy monitoring units will help to flatten the team learning curve and to build knowledge base from shared clinical experience.

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes

BACKGROUND AND OBJECTIVES

Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties.

METHODS

We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time.

RESULTS

Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes.

DISCUSSION

Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

A spatial perturbation framework to validate implantation of the epileptogenic zone

Stereo-electroencephalography (SEEG) is the gold standard to delineate surgical targets in focal drug-resistant epilepsy. SEEG uses electrodes placed directly into the brain to identify the seizure-onset zone (SOZ). However, its major constraint is limited brain coverage, potentially leading to misidentification of the 'true' SOZ. Here, we propose a framework to assess adequate SEEG sampling by coupling epileptic biomarkers with their spatial distribution and measuring the system's response to a perturbation of this coupling. We demonstrate that the system's response is strongest in well-sampled patients when virtually removing the measured SOZ. We then introduce the spatial perturbation map, a tool that enables qualitative assessment of the implantation coverage. Probability modelling reveals a higher likelihood of well-implanted SOZs in seizure-free patients or non-seizure free patients with incomplete SOZ resections, compared to non-seizure-free patients with complete resections. This highlights the framework's value in sparing patients from unsuccessful surgeries resulting from poor SEEG coverage.

Differential cortical layer engagement during seizure initiation and spread in humans

Despite decades of research, we still do not understand how spontaneous human seizures start and spread - especially at the level of neuronal microcircuits. In this study, we used laminar arrays of micro-electrodes to simultaneously record the local field potentials and multi-unit neural activities across the six layers of the neocortex during focal seizures in humans. We found that, within the ictal onset zone, the discharges generated during a seizure consisted of current sinks and sources only within the infra-granular and granular layers. Outside of the seizure onset zone, ictal discharges reflected current flow in the supra-granular layers. Interestingly, these patterns of current flow evolved during the course of the seizure - especially outside the seizure onset zone where superficial sinks and sources extended into the deeper layers. Based on these observations, a framework describing cortical-cortical dynamics of seizures is proposed with implications for seizure localization, surgical targeting, and neuromodulation techniques to block the generation and propagation of seizures.

Artificial intelligence in epilepsy - applications and pathways to the clinic

Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy have increased exponentially over the past decade. Integration of AI into epilepsy management promises to revolutionize the diagnosis and treatment of this complex disorder. However, translation of AI into neurology clinical practice has not yet been successful, emphasizing the need to consider progress to date and assess challenges and limitations of AI. In this Review, we provide an overview of AI applications that have been developed in epilepsy using a variety of data modalities: neuroimaging, electroencephalography, electronic health records, medical devices and multimodal data integration. For each, we consider potential applications, including seizure detection and prediction, seizure lateralization, localization of the seizure-onset zone and assessment for surgical or neurostimulation interventions, and review the performance of AI tools developed to date. We also discuss methodological considerations and challenges that must be addressed to successfully integrate AI into clinical practice. Our goal is to provide an overview of the current state of the field and provide guidance for leveraging AI in future to improve management of epilepsy.

Modification of brain conductivity in human focal epilepsy: A model-based estimation from stereoelectroencephalography

OBJECTIVE

We have developed a novel method for estimating brain tissue electrical conductivity using low-intensity pulse stereoelectroencephalography (SEEG) stimulation coupled with biophysical modeling. We evaluated the hypothesis that brain conductivity is correlated with the degree of epileptogenicity in patients with drug-resistant focal epilepsy.

METHODS

We used bipolar low-intensity biphasic pulse stimulation (.2 mA) followed by a postprocessing pipeline for estimating brain conductivity. This processing is based on biophysical modeling of the electrical potential induced in brain tissue between the stimulated contacts in response to pulse stimulation. We estimated the degree of epileptogenicity using a semi-automatic method quantifying the dynamic of fast discharge at seizure onset: the epileptogenicity index (EI). We also investigated how the location of stimulation within specific anatomical brain regions or within lesional tissue impacts brain conductivity.

RESULTS

We performed 1034 stimulations of 511 bipolar channels in 16 patients. We found that brain conductivity was lower in the epileptogenic zone (EZ; unpaired median difference = .064, p < .001) and inversely correlated with the epileptogenic index value (p < .001, Spearman rho = -.32). Conductivity values were also influenced by anatomical site, location within lesion, and delay between SEEG electrode implantation and stimulation, and had significant interpatient variability. Mixed model multivariate analysis showed that conductivity is significantly associated with EI (F = 13.45, p < .001), anatomical regions (F = 5.586, p < .001), delay since implantation (F = 14.71, p = .003), and age at SEEG (F = 6.591, p = .027), but not with the type of lesion (F = .372, p = .773) or the delay since last seizure (F = 1.592, p = .235).

SIGNIFICANCE

We provide a novel model-based method for estimating brain conductivity from SEEG low-intensity pulse stimulations. The brain tissue conductivity is lower in EZ as compared to non-EZ. Conductivity also varies significantly across anatomical brain regions. Involved pathophysiological processes may include changes in the extracellular space (especially volume or tortuosity) in epileptic tissue.

Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy

OBJECTIVE

The aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy.

METHODS

We developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome.

RESULTS

For these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves.

CONCLUSIONS

The proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy.

SIGNIFICANCE

These models are likely to play a key role in the mechanistic interpretation of epileptiform activity.

Correspondence between scalp-EEG and stereoelectroencephalography seizure-onset patterns in patients with MRI-negative drug-resistant focal epilepsy

OBJECTIVE

Our objective was to evaluate the relationship between scalp-EEG and stereoelectroencephalography (SEEG) seizure-onset patterns (SOP) in patients with MRI-negative drug-resistant focal epilepsy.

METHODS

We analyzed retrospectively 41 patients without visible lesion on brain MRI who underwent video-EEG followed by SEEG. We defined five types of SOPs on scalp-EEG and eight types on SEEG. We examined how various clinical variables affected scalp-EEG SOPs.

RESULTS

The most prevalent scalp SOPs were rhythmic sinusoidal activity (56.8%), repetitive epileptiform discharges (22.7%), and paroxysmal fast activity (15.9%). The presence of paroxysmal fast activity on scalp-EEG was always seen without delay from clinical onset and correlated with the presence of low-voltage fast activity in SEEG (sensitivity = 22.6%, specificity = 100%). The main factor explaining the discrepancy between the scalp and SEEG SOPs was the delay between clinical and scalp-EEG onset. There was a correlation between the scalp and SEEG SOPs when the scalp onset was simultaneous with the clinical onset (p = 0.026). A significant delay between clinical and scalp discharge onset was observed in 25% of patients and featured always with a rhythmic sinusoidal activity on scalp, corresponding to similar morphology of the discharge on SEEG. The presence of repetitive epileptiform discharges on scalp was associated with an underlying focal cortical dysplasia (sensitivity = 30%, specificity = 90%). There was no significant association between the scalp SOP and the epileptogenic zone location (deep or superficial), or surgical outcome.

SIGNIFICANCE

In patients with MRI-negative focal epilepsy, scalp SOP could suggest the SEEG SOP and some etiology (focal cortical dysplasia) but has no correlation with surgical prognosis. Scalp SOP correlates with the SEEG SOP in cases of simultaneous EEG and clinical onset; otherwise, scalp SOP reflects the propagation of the SEEG discharge.

PLAIN LANGUAGE SUMMARY

We looked at the correspondence between the electrical activity recorded during the start of focal seizure using scalp and intracerebral electrodes in patients with no visible lesion on MRI. If there is a fast activity on scalp, it reflects similar activity inside the brain. We found a good correspondence between scalp and intracerebral electrical activity for cases without significant delay between clinical and scalp electrical onset (seen in 75% of the cases we studied). Visualizing repetitive epileptic activity on scalp could suggest a particular cause of the epilepsy: a subtype of brain malformation called focal cortical dysplasia.

Generalisability of epileptiform patterns across time and patients

The complexity of localising the epileptogenic zone (EZ) contributes to surgical resection failures in achieving seizure freedom. The distinct patterns of epileptiform activity during interictal and ictal phases, varying across patients, often lead to suboptimal localisation using electroencephalography (EEG) features. We posed two key questions: whether neural signals reflecting epileptogenicity generalise from interictal to ictal time windows within each patient, and whether epileptiform patterns generalise across patients. Utilising an intracranial EEG dataset from 55 patients, we extracted a large battery of simple to complex features from stereo-EEG (SEEG) and electrocorticographic (ECoG) neural signals during interictal and ictal windows. Our features (n = 34) quantified many aspects of the signals including statistical moments, complexities, frequency-domain and cross-channel network attributes. Decision tree classifiers were then trained and tested on distinct time windows and patients to evaluate the generalisability of epileptogenic patterns across time and patients, respectively. Evidence strongly supported generalisability from interictal to ictal time windows across patients, particularly in signal power and high-frequency network-based features. Consistent patterns of epileptogenicity were observed across time windows within most patients, and signal features of epileptogenic regions generalised across patients, with higher generalisability in the ictal window. Signal complexity features were particularly contributory in cross-patient generalisation across patients. These findings offer insights into generalisable features of epileptic neural activity across time and patients, with implications for future automated approaches to supplement other EZ localisation methods.

How Can a Focal Seizure Lead to a Dacrystic Behavior? A Case Analyzed with Functional Connectivity in Stereoelectroencephalography

We present a case of a patient with focal non-motor emotional seizures with dacrystic expression in the context of drug-resistant magnetic resonance imaging negative epilepsy. The pre-surgical evaluation suggested a hypothesis of a right fronto-temporal epileptogenic zone. Stereoelectroencephalography recorded dacrystic seizures arising from the right anterior operculo-insular (pars orbitalis) area with secondary propagation to temporal and parietal cortices during the dacrystic behavior. We analyzed functional connectivity during the ictal dacrystic behavior and found an increase of the functional connectivity within a large right fronto-temporo-insular network, broadly similar to the "emotional excitatory" network. It suggests that focal seizure, potentially, from various origins but leading to disorganization of these physiological networks may generate dacrystic behavior.

Combining independent component analysis and source localization for improving spatial sampling of stereoelectroencephalography in epilepsy

Stereoelectroencephalography is a powerful intracerebral EEG recording method for the presurgical evaluation of epilepsy. It consists in implanting depth electrodes in the patient's brain to record electrical activity and map the epileptogenic zone, which should be resected to render the patient seizure-free. Stereoelectroencephalography has high spatial accuracy and signal-to-noise ratio but remains limited in the coverage of the explored brain regions. Thus, the implantation might provide a suboptimal sampling of epileptogenic regions. We investigate the potential of improving a suboptimal stereoelectroencephalography recording by performing source localization on stereoelectroencephalography signals. We propose combining independent component analysis, connectivity measures to identify components of interest, and distributed source modelling. This approach was tested on two patients with two implantations each, the first failing to characterize the epileptogenic zone and the second giving a better diagnosis. We demonstrate that ictal and interictal source localization performed on the first stereoelectroencephalography recordings matches the findings of the second stereo-EEG exploration. Our findings suggest that independent component analysis followed by source localization on the topographies of interest is a promising method for retrieving the epileptogenic zone in case of suboptimal implantation.

Simultaneous high-resolution whole-brain MR spectroscopy and [18F]FDG PET for temporal lobe epilepsy

PURPOSE

Precise lateralizing the epileptogenic zone in patients with drug-resistant mesial temporal lobe epilepsy (mTLE) remains challenging, particularly when routine MRI scans are inconclusive (MRI-negative). This study aimed to investigate the synergy of fast, high-resolution, whole-brain MRSI in conjunction with simultaneous [18F]FDG PET for the lateralization of mTLE.

METHODS

Forty-eight drug-resistant mTLE patients (M/F 31/17, age 12-58) underwent MRSI and [18F]FDG PET on a hybrid PET/MR scanner. Lateralization of mTLE was evaluated by visual inspection and statistical classifiers of metabolic mappings against routine MRI. Additionally, this study explored how disease status influences the associations between altered N-acetyl aspartate (NAA) and FDG uptake using hierarchical moderated multiple regression.

RESULTS

The high-resolution whole-brain MRSI data offers metabolite maps at comparable resolution to [18F]FDG PET. Visual examinations of combined MRSI and [18F]FDG PET showed an mTLE lateralization accuracy rate of 91.7% in a 48-patient cohort, surpassing routine MRI (52.1%). Notably, out of 23 MRI-negative mTLE, combined MRSI and [18F]FDG PET helped detect 19 cases. Logistical regression models combining hippocampal NAA level and FDG uptake improved lateralization performance (AUC=0.856), while further incorporating extrahippocampal regions such as amygdala, thalamus, and superior temporal gyrus increased the AUC to 0.939. Concurrent MRSI/PET revealed a moderating influence of disease duration and hippocampal atrophy on the association between hippocampal NAA and glucose uptake, providing significant new insights into the disease's trajectory.

CONCLUSION

This paper reports the first metabolic imaging study using simultaneous high-resolution MRSI and [18F]FDG PET, which help visualize MRI-unidentifiable lesions and may thus advance diagnostic tools and management strategies for drug-resistant mTLE.

Permutation entropy-derived parameters to estimate the epileptogenic zone network

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 EZNC . 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.

Learn how to interpret and use intracranial EEG findings

Epilepsy surgery is the therapy of choice for many patients with drug-resistant focal epilepsy. Recognizing and describing ictal and interictal patterns with intracranial electroencephalography (EEG) recordings is important in order to most efficiently leverage advantages of this technique to accurately delineate the seizure-onset zone before undergoing surgery. In this seminar in epileptology, we address learning objective "1.4.11 Recognize and describe ictal and interictal patterns with intracranial recordings" of the International League against Epilepsy curriculum for epileptologists. We will review principal considerations of the implantation planning, summarize the literature for the most relevant ictal and interictal EEG patterns within and beyond the Berger frequency spectrum, review invasive stimulation for seizure and functional mapping, discuss caveats in the interpretation of intracranial EEG findings, provide an overview on special considerations in children and in subdural grids/strips, and review available quantitative/signal analysis approaches. To be as practically oriented as possible, we will provide a mini atlas of the most frequent EEG patterns, highlight pearls for its not infrequently challenging interpretation, and conclude with two illustrative case examples. This article shall serve as a useful learning resource for trainees in clinical neurophysiology/epileptology by providing a basic understanding on the concepts of invasive intracranial EEG.

Metabolic connectivity as a predictor of surgical outcome in mesial temporal lobe epilepsy

OBJECTIVE

The study investigated metabolic connectivity (MC) differences between patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) with hippocampal sclerosis (HS) and healthy controls (HCs), based on [18 F]-fluorodeoxyglucose (FDG)-PET data. We focused on the MC changes dependent on the lateralization of the epileptogenic lobe and on correlations with postoperative outcomes.

METHODS

FDG-PET scans of 47 patients with unilateral MTLE with histopathologically proven HS and 25 HC were included in the study. All the patients underwent a standard anterior temporal lobectomy and were more than 2 years after the surgery. MC changes were compared between the two HS groups (left HS, right HS) and HC. Differences between the metabolic network of seizure-free and non-seizure-free patients after surgery were depicted afterward. Network changes were correlated with clinical characteristics.

RESULTS

The study showed widespread metabolic network changes in the HS patients as compared to HC. The changes were more extensive in the right HS than in the left HS. Unfavorable surgical outcomes were found in patients with decreased MC within the network including both the lesional and contralesional hippocampus, ipsilesional frontal operculum, and contralesional insula. Favorable outcomes correlated with decreased MC within the network involving both orbitofrontal cortices and the ipsilesional temporal lobe.

SIGNIFICANCE

There are major differences in the metabolic networks of left and right HS, with more extensive changes in right HS. The changes within the metabolic network could help predict surgical outcomes in patients with HS. MC may identify patients with potentially unfavorable outcomes and direct them to a more detailed presurgical evaluation.

PLAIN LANGUAGE SUMMARY

Metabolic connectivity is a promising method for metabolic network mapping. Metabolic networks in mesial temporal lobe epilepsy are dependent on lateralization of the epileptogenic lobe and could predict surgical outcomes.

Magnetoencephalography for Epilepsy Presurgical Evaluation

PURPOSE OF THE REVIEW

Magnetoencephalography (MEG) is a functional neuroimaging technique that records neurophysiology data with millisecond temporal resolution and localizes it with subcentimeter accuracy. Its capability to provide high resolution in both of these domains makes it a powerful tool both in basic neuroscience as well as clinical applications. In neurology, it has proven useful in its ability to record and localize epileptiform activity. Epilepsy workup typically begins with scalp electroencephalography (EEG), but in many situations, EEG-based localization of the epileptogenic zone is inadequate. The complementary sensitivity of MEG can be crucial in such cases, and MEG has been adopted at many centers as an important resource in building a surgical hypothesis. In this paper, we review recent work evaluating the extent of MEG influence of presurgical evaluations, novel analyses of MEG data employed in surgical workup, and new MEG instrumentation that will likely affect the field of clinical MEG.

RECENT FINDINGS

MEG consistently contributes to presurgical evaluation and these contributions often change the plan for epilepsy surgery. Extensive work has been done to develop new analytic methods for localizing the source of epileptiform activity with MEG. Systems using optically pumped magnetometry (OPM) have been successfully deployed to record and localize epileptiform activity. MEG remains an important noninvasive tool for epilepsy presurgical evaluation. Continued improvements in analytic methodology will likely increase the diagnostic yield of the test. Novel instrumentation with OPM may contribute to this as well, and may increase accessibility of MEG by decreasing cost.

Acute Effect of Vagus Nerve Stimulation in Patients with Drug-Resistant Epilepsy: A Preliminary Exploration via Stereoelectroencephalogram

As the pathophysiological mechanisms of vagus nerve stimulation (VNS) causing individual differences in the vagal ascending network remains unclear, stereoelectroencephalography (SEEG) provides a unique platform to explore the brain networks affected by VNS and helps to understand the anti-seizure mechanism of VNS more comprehensively. This study presents a preliminary exploration of the acute effect of VNS. SEEG signals were collected to assess the acute effect of VNS on neural synchronization in patients with drug-resistant epilepsy, especially in epileptogenic networks. The results show that the better the efficacy of VNS, the wider the spread of desynchronization assessed by weighted phase lag index at a high frequency band caused by VNS. Future studies should focus on the association between the change in synchronization and the efficacy of VNS, exploring the possibility of synchronization as a biomarker for patient screening and parameter programming.

Hippocampal barques and their manifestation as 14&6 Hz positive spikes during sleep

OBJECTIVE

This study investigates variations in hippocampal barque occurrence during sleep and compares findings to respective variations of their scalp manifestation as 14&6/sec positive spikes.

METHODS

From 11 epilepsy patients, 12 non-epileptogenic hippocampi with barques were identified for this study. Using the first seizure-free whole-night sleep stereo-encephalography (sEEG) recording, we performed sleep staging and measured the occurrence of barques and 14&6/sec positive spikes variants.

RESULTS

Hippocampal barques (total count: 9,183; mean count per record: 765.2 ± 251.2) occurred predominantly during non-rapid eye movement (NREM) II sleep (total: 5,744; mean: 478.6 ± 176.1; 62.2 ± 6.0%) and slow-wave sleep (SWS) (total: 2,950; mean: 245.83 ± 92.9; 32.0 ± 6.2%), with rare to occasional occurrence in NREM I (total: 85; mean: 7.0 ± 2.8; 0.9 ± 0.4%), rapid eye movement (REM) (total: 153; mean: 12.75 ± 4.0; 1.7 ± 0.6) and wakefulness (total: 251; mean: 20.9 ± 6.3; 2.9 ± 0.9%). Barque rate increased during SWS (mean: 2.7 ± 1.0 per min) compared to NREM II (2.2 ± 1.0 per min) and other states (wakefulness: 0.1 ± 0.0 per min; NREM I: 0.3 ± 0.1 per min; REM: 0.1 ± 0.0 per min). The 14&6/sec positive spikes variant (total count: 2,406; mean: 343.7 ± 106.7) was present in NREM II (total: 2,059; mean: 249.1 ± 100.2, 84.9 ± 3.6%) and SWS (total: 347; mean: 49.5 ± 12.8, 15.0 ± 3.6%) stages, and absent from the rest of sleep and wakefulness. While all 14&6/sec positive spikes correlated with barques, only 44.7 ± 6.1% of barques manifested as 14&6/sec positive spikes.

CONCLUSIONS

Hippocampal barques are predominant in NREM II and SWS, and tend to increase their presence during SWS. Their scalp manifestation as 14&6/sec positive spikes is confounded by wakefulness, REM and NREM I stages, and "masked" by the co-occurrence of NREM II and SWS slow waves, and overlapping reactive micro-arousal elements.

SIGNIFICANCE

Our study highlighted the overnight profile of hippocampal barques, in relation to the respective profile of their scalp manifestation, the 14&6/sec positive spikes variant.

Epilepsy Networks and Their Surgical Relevance

Surgical epilepsy is a rapidly evolved field. As the understanding and concepts of epilepsy shift towards a network disorder, surgical outcomes may shed light on numerous components of these systems. This review documents the evolution of the understanding of epilepsy networks and examines the data generated by resective, ablative, neuromodulation, and invasive monitoring surgeries in epilepsy patients. As these network tools are better integrated into epilepsy practice, they may eventually inform surgical decisions and improve clinical outcomes.

Differential Regulation of Wnt/β-catenin Signaling in Acute and Chronic Epilepsy in Repeated Low Dose Lithium-Pilocarpine Rat Model of Status Epilepticus

Epilepsy is a chronic neurological complication characterized by unprovoked seizure episodes due to the imbalance between excitatory and inhibitory neurons. The epileptogenesis process has been reported to be involved in chronic epilepsy however, the mechanism underlying epileptogenesis remains unclear. Recent studies have shown the possible involvement of Wnt/β-catenin signaling in the neurogenesis and neuronal reorganization in epileptogenesis. In this study, we used repeated low dose lithium-pilocarpine model of status epilepsy (SE) to study the involvement of Wnt/β-catenin signaling at acute and chronic stages post SE induction. The acute study ranged from day 0 to day 28 post SE induction and the chronic study ranged from day 0 to day 56 post SE induction. Several neurobehavioral parameters and seizure score and seizure frequency was analysed until the end of the study. The proteins involved in the regulation of Wnt/β-catenin signaling and downstream cascading were analysed using western blot and quantitative real-time PCR analysis. The Wnt/β-catenin pathway was found inactive in acute SE, while the same was found activated at the chronic stage. Our findings suggest that the activated Wnt/β-catenin signaling in chronic epilepsy might be the possible mechanism underlying epileptogenesis as indicated by increased neuronal count, increased synaptic density, astrogliosis and apoptosis in chronic epilepsy. These findings can help target the Wnt/β-catenin pathway differentially depending upon the type of epilepsy. The acute stage characterized by SE can be improved by targeting GSK-3β levels and the chronic stage characterized by temporal lobe epilepsy can be improved by targeting β-catenin and disheveled proteins.

Identification of epileptic networks with graph convolutional network incorporating oscillatory activities and evoked synaptic responses

Stereoelectroencephalography (SEEG) offers unique neural data from in-depth brain structures with fine temporal resolutions to better investigate the origin of epileptic brain activities. Although oscillatory patterns from different frequency bands and functional connectivity computed from the SEEG datasets are employed to study the epileptic zones, direct electrical stimulation-evoked electrophysiological recordings of synaptic responses, namely cortical-cortical evoked potentials (CCEPs), from the same SEEG electrodes are not explored for the localization of epileptic zones. Here we proposed a two-stream model with unsupervised learning and graph convolutional network tailored to the SEEG and CCEP datasets in individual patients to perform localization of epileptic zones. We compared our localization results with the clinically marked electrode sites determined for surgical resections. Our model had good classification capability when compared to other state-of-the-art methods. Furthermore, based on our prediction results we performed group-level brain-area mapping analysis for temporal, frontal and parietal epilepsy patients and found that epileptic and non-epileptic brain networks were distinct in patients with different types of focal epilepsy. Our unsupervised data-driven model provides personalized localization analysis for the epileptic zones. The epileptic and non-epileptic brain areas disclosed by the prediction model provide novel insights into the network-level pathological characteristics of epilepsy.

Kindling in humans: Does secondary epileptogenesis occur?

The relevance of secondary epileptogenesis for human epilepsy remains a controversial subject decades after it was first described in animal models. Whether or not a previously normal brain region can become independently epileptogenic through a kindling-like process has not, and cannot, be definitely proven in humans. Rather than reliance on direct experimental evidence, attempts to answering this question must depend on observational data. In this review, observations based largely upon contemporary surgical series will advance the case for secondary epileptogenesis in humans. As will be argued, hypothalamic hamartoma-related epilepsy provides the strongest case for this process; all the stages of secondary epileptogenesis can be observed. Hippocampal sclerosis (HS) is another pathology where the question of secondary epileptogenesis frequently arises, and observations from bitemporal and dual pathology series are explored. The verdict here is far more difficult to reach, in large part because of the scarcity of longitudinal cohorts; moreover, recent experimental data have challenged the claim that HS is acquired consequent to recurrent seizures. Synaptic plasticity more than seizure-induced neuronal injury is the likely mechanism of secondary epileptogenesis. Postoperative running-down phenomenon provides the best evidence that a kindling-like process occurs in some patients, evidenced by its reversal. Finally, a network perspective of secondary epileptogenesis is considered, as well as the possible role for subcortical surgical interventions.

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.

Organization of the epileptogenic zone and signal analysis at seizure onset in patients with drug-resistant epilepsy due to focal cortical dysplasia with mTOR pathway gene mutations-An SEEG study

Epilepsy surgery in genetic drug-resistant epilepsy is a debated subject as more histological and molecular data are available. We retrospectively collected data from focal drug-resistant epilepsy patients that underwent stereoelectroencephalography (SEEG) invasive recordings. Patients with nonlesional brain imaging or in whom a first epilepsy surgery failed to control seizures were selected. We computed and displayed the intracranial ictal onset activity pattern on structural imaging. Patients underwent epilepsy gene panel testing, next generation sequencing-NGS. Of 113 patients, 13 underwent genetic testing, and in 6 patients, a mechanistic target of rapamycin pathway gene germline mutation (mTOR) was identified. Brain imaging was nonlesional except for one patient in whom two abnormalities suggestive of focal cortical dysplasia (FCD) were found. Patients underwent tailored brain surgery based on SEEG data, tissue analysis revealed FCD and postsurgical outcome was favorable. Our findings are similar to previous case series suggesting that epilepsy surgery can be a treatment option in patients with mTOR pathway mutation. In patients with mTOR pathway mutation, the postsurgical outcome is favorable if complete resection of the epileptogenic zone is performed. Electrophysiological seizure onset patterns in FCDs associated with mTOR pathway mutations display low-voltage fast activity as previously described.

Involvement of the posterior cingulate gyrus in temporal lobe epilepsy: A study using stereo-EEG

OBJECTIVE

To analyze the involvement of the posterior cingulate gyrus (PCG) during mesial temporal lobe seizures (MTLS).

METHODS

We retrospectively reviewed the stereo-EEG (SEEG) recordings of patients with MTLS performed in our institution from February 2013 to December 2020. Only patients who had electrode implantation in the PCG were included. Patients with lesions that could potentially alter the seizure spread pathways were excluded. We assessed the propagation patterns of MTLS with respect to the different structures sampled.

RESULTS

Nine of 97 patients who had at least one seizure originating in the mesial temporal region met the inclusion criteria. A total of 174 seizures were analyzed. The PCG was the first site of propagation in most of the cases (8/9 patients and 77.5% of seizures, and 7/8 patients and 65.6% of seizures after excluding an outlier patient). The fastest propagation times were towards the contralateral mesial temporal region and ipsilateral PCG. Seven patients underwent standard anterior temporal lobectomy and, of these, all but one were Engel 1 at last follow up.

CONCLUSION

We found the PCG to be the first propagation site of MTLS in this group of patients. These results outline the relevance of the PCG in SEEG planning strategies. Further investigations are needed to corroborate whether fast propagation to the PCG predicts a good surgical outcome.

Physiological and pathological neuronal connectivity in the living human brain based on intracranial EEG signals: the current state of research

Over the past decades, studies of human brain networks have received growing attention as the assessment and modelling of connectivity in the brain is a topic of high impact with potential application in the understanding of human brain organization under both physiological as well as various pathological conditions. Under specific diagnostic settings, human neuronal signal can be obtained from intracranial EEG (iEEG) recording in epilepsy patients that allows gaining insight into the functional organisation of living human brain. There are two approaches to assess brain connectivity in the iEEG-based signal: evaluation of spontaneous neuronal oscillations during ongoing physiological and pathological brain activity, and analysis of the electrophysiological cortico-cortical neuronal responses, evoked by single pulse electrical stimulation (SPES). Both methods have their own advantages and limitations. The paper outlines available methodological approaches and provides an overview of current findings in studies of physiological and pathological human brain networks, based on intracranial EEG recordings.

The role of quantitative markers in surgical prognostication after stereoelectroencephalography

OBJECTIVE

Stereoelectroencephalography (SEEG) is the reference method in the presurgical exploration of drug-resistant focal epilepsy. However, prognosticating surgery on an individual level is difficult. A quantified estimation of the most epileptogenic regions by searching for relevant biomarkers can be proposed for this purpose. We investigated the performances of ictal (Epileptogenicity Index, EI; Connectivity EI, cEI), interictal (spikes, high-frequency oscillations, HFO [80-300 Hz]; Spikes × HFO), and combined (Spikes × EI; Spikes × cEI) biomarkers in predicting surgical outcome and searched for prognostic factors based on SEEG-signal quantification.

METHODS

Fifty-three patients operated on following SEEG were included. We compared, using precision-recall, the epileptogenic zone quantified using different biomarkers (EZq ) against the visual analysis (EZC ). Correlations between the EZ resection rates or the EZ extent and surgical prognosis were analyzed.

RESULTS

EI and Spikes × EI showed the best precision against EZc (0.74; 0.70), followed by Spikes × cEI and cEI, whereas interictal markers showed lower precision. The EZ resection rates were greater in seizure-free than in non-seizure-free patients for the EZ defined by ictal biomarkers and were correlated with the outcome for EI and Spikes × EI. No such correlation was found for interictal markers. The extent of the quantified EZ did not correlate with the prognosis.

INTERPRETATION

Ictal or combined ictal-interictal markers overperformed the interictal markers both for detecting the EZ and predicting seizure freedom. Combining ictal and interictal epileptogenicity markers improves detection accuracy. Resection rates of the quantified EZ using ictal markers were the only statistically significant determinants for surgical prognosis.

Localizing epileptogenic zones with high-frequency oscillations and directed connectivity

PURPOSE

Precise localization of the epileptogenic zone (EZ) is essential for epilepsy surgery. Existing methods often fail to detect slow onset patterns or similar neural activities presented in the recorded signals. To address this issue, we propose a new measure to quantify epileptogenicity, i.e., the connectivity high-frequency epileptogenicity index (cHFEI).

METHODS

The cHFEI method combines directed connectivity and high-frequency oscillations (HFOs) to measure the epileptogenicity of regions involved in a brain network. By applying this method to stereoelectroencephalography (SEEG) recordings of 49 seizures in 20 patients, we calculated the accuracy, sensitivity, and precision with a visually identified epileptogenic zone as a reference. The performance was evaluated by the confusion matrix and the area under the receiver operating characteristic (ROC) curve.

RESULTS

Epileptic network estimation based on cHFEI successfully distinguished brain regions involved in seizure onset from the propagation network. Moreover, cHFEI outperformed other existing detection methods in the estimation of EZs in all patients, with an average area under the ROC curve of 0.88 and an accuracy of 0.85.

CONCLUSIONS

cHFEI can characterize EZ in a robust manner despite various seizure onset patterns and has potential application in epilepsy therapy.

Ictogenesis proceeds through discrete phases in hippocampal CA1 seizures in mice

Epilepsy is characterized by spontaneous non-provoked seizures, yet the mechanisms that trigger a seizure and allow its evolution remain underexplored. To dissect out phases of ictogenesis, we evoked hypersynchronous activity with optogenetic stimulation. Focal optogenetic activation of putative excitatory neurons in the mouse hippocampal CA1 reliably evoked convulsive seizures in awake mice. A time-vs-time pulsogram plot characterized the evolution of the EEG pulse response from a light evoked response to induced seizure activity. Our results depict ictogenesis as a stepwise process comprised of three distinctive phases demarcated by two transition points. The induction phase undergoes the first transition to reverberant phase activity, followed by the second transition into the paroxysmal phase or a seizure. Non-seizure responses are confined to either induction or reverberant phases. The pulsogram was then constructed in seizures recorded from a murine model of temporal lobe epilepsy and it depicted a similar reverberance preceding spontaneous seizures. The discovery of these distinct phases of ictogenesis may offer means to abort a seizure before it develops.

Perturbed Information Processing Complexity in Experimental Epilepsy

Comorbidities, such as cognitive deficits, which often accompany epilepsies, constitute a basal state, while seizures are rare and transient events. This suggests that neural dynamics, in particular those supporting cognitive function, are altered in a permanent manner in epilepsy. Here, we test the hypothesis that primitive processes of information processing at the core of cognitive function (i.e., storage and sharing of information) are altered in the hippocampus and the entorhinal cortex in experimental epilepsy in adult, male Wistar rats. We find that information storage and sharing are organized into substates across the stereotypic states of slow and theta oscillations in both epilepsy and control conditions. However, their internal composition and organization through time are disrupted in epilepsy, partially losing brain state selectivity compared with controls, and shifting toward a regimen of disorder. We propose that the alteration of information processing at this algorithmic level of computation, the theoretical intermediate level between structure and function, may be a mechanism behind the emergent and widespread comorbidities associated with epilepsy, and perhaps other disorders.SIGNIFICANCE STATEMENT Comorbidities, such as cognitive deficits, which often accompany epilepsies, constitute a basal state, while seizures are rare and transient events. This suggests that neural dynamics, in particular those supporting cognitive function, are altered in a permanent manner in epilepsy. Here, we show that basic processes of information processing at the core of cognitive function (i.e., storage and sharing of information) are altered in the hippocampus and the entorhinal cortex (two regions involved in memory processes) in experimental epilepsy. Such disruption of information processing at the algorithmic level itself could underlie the general performance impairments in epilepsy.