Search

Stereo-electroencephalography (SEEG)-derived epilepsy networks are used to better understand a patient's epilepsy; however, a unimodal approach provides an incomplete picture. We combine tractography and SEEG to determine the relationship between spike propagation and the white matter architecture and to improve our understanding of spike propagation mechanisms.Probablistic tractography from diffusion imaging (dMRI) of matched subjects from the Human Connectome Project (HCP) was combined with patient-specific SEEG-derived spike propagation networks. Two regions-of-interest (ROIs) with a significant spike propagation relationship constituted a Propagation Pair.In 56 of 59 patients, Propagation Pairs were more often tract-connected as compared to all ROI pairs (p 0.01; d = -1.91). The degree of spike propagation between tract-connected ROIs was greater (39 ± 21%) compared to tract-unconnected ROIs (31 ± 18%; p 0.0001). Within the same network, ROIs receiving propagation earlier were more often tract-connected to the source (59.7%) as compared to late receivers (25.4%; p 0.0001).Brain regions involved in spike propagation are more likely to be connected by white matter tracts. Between nodes, presence of tracts suggests a direct course of propagation, whereas the absence of tracts suggests an indirect course of propagation.We demonstrate a logical and consistent relationship between spike propagation and the white matter architecture.

Pathological high-frequency oscillations (HFOs) in intracranial EEG are promising biomarkers of epileptogenic tissue, and their physiological counterparts play a role in sensorimotor and cognitive function. HFOs have also been found in scalp EEG, but an overview of all studies is lacking. In this systematic review, we assessed the methodology to detect scalp HFOs and their clinical potential.We searched PubMed, Embase and the Cochrane Library for studies on HFOs in scalp EEG, and extracted methodological and clinical data.We included 60 studies with data from 1149 unique individuals. Two-thirds of studies analyzed HFOs visually in the time or time-frequency domain, and one-third automatically with visual validation. Most studies evaluated interictal ripples during sleep in children. Pathological HFOs were overall better than spikes in localizing the epileptogenic zone and predicting outcome, correlated negatively with cognition and positively with disease activity and severity, and decreased after medical and surgical treatment.The methodologies of the 60 studies were heterogeneous, but pathological scalp HFOs were clinically valuable as biomarkers in various situations, particularly in children with epilepsy.This systematic review gives an extensive overview of methodological and clinical data on scalp HFOs, establishing their clinical potential and discussing their limitations.

Introduction Whereas sawtooth waves have been described as phasic bursts of slow oscillations in the scalp EEG during rapid-eye-movement (REM) sleep sixty years ago, little is known about their generators and functional role. Stereo-electroencephalography recordings (SEEG) performed for presurgical evaluation in drug-resistant focal epilepsy have allowed to demonstrate a peculiar slow activity in the thalamic medial pulvinar nucleus during REM sleep, contrasting with the fast desynchronized cortical activity. However, the link between this slow thalamic activity and sawtooth waves remains unexplored. Here, we used combined polysomnography and SEEG to investigate the dynamics of thalamic activity and thalamocortical functional connectivity at the time of scalp EEG sawtooth waves. Methods Night sleep recordings from six patients investigated with SEEG including thalamic recording in the Epilepsy Department of Lyon University Hospital were analyzed. Sawtooth waves were visually detected in the scalp EEG and compared with control segments selected in REM sleep. Thalamic SEEG and cortical EEG spectral power as well as thalamo-cortical functional connectivity assessed by the phase locking value were compared between sawtooth waves and control segments using paired t-tests. The effect size was assessed with Cohen’s d. Results A significant increase in the delta-theta (2-5 Hz, p< 0.003, d=0.31) and gamma (30-100 Hz, p< 0.003, d=0.31) power bands was found in posterior nuclei of the thalamus at the time of scalp-detected sawtooth waves. Functional thalamocortical connectivity in the 2-5 Hz band was enhanced during sawtooth waves as compared to control segments, with the thalamus driving the cortex (p< 0.001; d=0.84, average +/- SD time lag: 23 +/- 22 ms). Conclusion Our results provide evidence that sawtooth waves involve not only cortical areas but also the thalamus, suggesting a relation with ponto-geniculo-occipital waves. They may hence represent phasic brainstem-triggered short windows of an increased thalamocortical dialogue during REM sleep. Support (if any) B.F was supported by the Natural Sciences and Engineering Research Council of Canada RGPIN2020-04127 and RGPAS-2020-00021, and by the Fonds de Recherche du Québec–Santé 2021-2025 Salary Award “Chercheur-boursier clinicien Senior”. T.A. was supported by the “Healthy Brains, Healthy Lives initiative at McGill University” from the Canada First Research Excellence Fund and Fonds de recherche du Québec 2021-2022.

Epileptic spikes are the traditional interictal electroencephalographic (EEG) biomarker for epilepsy. Given their low specificity for identifying the epileptogenic zone (EZ), they are given only moderate attention in presurgical evaluation. This study aims to demonstrate that it is possible to identify specific spike features in intracranial EEG that optimally define the EZ and predict surgical outcome.We analyzed spike features on stereo-EEG segments from 83 operated patients from 2 epilepsy centers (37 Engel IA) in wakefulness, non-rapid eye movement sleep, and rapid eye movement sleep. After automated spike detection, we investigated 135 spike features based on rate, morphology, propagation, and energy to determine the best feature or feature combination to discriminate the EZ in seizure-free and non-seizure-free patients by applying 4-fold cross-validation.The rate of spikes with preceding gamma activity in wakefulness performed better for surgical outcome classification (4-fold area under receiver operating characteristics curve [AUC] = 0.755 ± 0.07) than the seizure onset zone, the current gold standard (AUC = 0.563 ± 0.05, p = 0.015) and the ripple rate, an emerging seizure-independent biomarker (AUC = 0.537 ± 0.07, p = 0.006). Channels with a spike-gamma rate exceeding 1.9/min had an 80% probability of being in the EZ. Combining features did not improve the results.Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom. This rate could be applied to determine the minimal number of spiking channels requiring resection. In addition to quantitative analysis, this feature is easily accessible to visual analysis, which could aid clinicians during presurgical evaluation. ANN NEUROL 2022.

Study Objectives Whereas there is plenty of evidence on the influence of epileptic activity on non-rapid eye movement (NREM) sleep macro- and micro-structure, data on the impact of epilepsy on rapid eye movement (REM) sleep remains sparse. Using high-density electroencephalography (HD-EEG), we assessed global and focal disturbances of sawtooth waves (STW) as cortically generated sleep oscillations of REM sleep in patients with focal epilepsy. Methods Twenty-two patients with drug-resistant focal epilepsy (13 females; mean age, 32.6 ± 10.7 years; 12 temporal lobe epilepsy) and 12 healthy controls (3 females; 24.0 ± 3.2 years) underwent combined overnight HD-EEG and polysomnography. STW rate, duration, frequency, power, spatial extent, IED rates and sleep homeostatic properties were analyzed. Results STW rate and duration were reduced in patients with focal epilepsy compared to healthy controls (rate: 0.64/min ± 0.46 vs. 1.12/min ± 0.41, p = .005, d = −0.98; duration: 3.60 s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = −1.01). Not surprisingly given the fronto-central maximum of STW, the reductions were driven by extratemporal lobe epilepsy patients (rate: 0.45/min ± 0.31 vs. 1.12/min ± 0.41, p = .0004, d = −1.35; duration: 3.49 s ± 0.92 vs. 4.57 ± 1.00, p = .017, d = −0.99) and were more pronounced in the first vs. the last sleep cycle (rate first cycle patients vs. controls: 0.60/min ± 0.49 vs. 1.10/min ± 0.55, p = .016, d = −0.90, rate last cycle patients vs. controls: 0.67/min ± 0.51 vs. 0.99/min ± 0.49, p = .11, d = −0.62; duration first cycle patients vs. controls: 3.60s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = −1.01, duration last cycle patients vs. controls: 3.66s ± 0.84 vs. 4.51 ± 1.26, p = .039, d = −0.80). There was no regional decrease of STWs in the region with the epileptic focus vs. the contralateral side (all p > .05). Conclusion Patients with focal epilepsy and in particular extratemporal lobe epilepsy show a global reduction of STW activity in REM sleep. This may suggest that epilepsy impacts cortically generated sleep oscillations even in REM sleep when epileptic activity is low.

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery., This work was funded by K23NS104252 (A.A.L.) R01 MH117777 (E.B., J.W.R.) Whitehall Foundation (KH) 5F31NS120783-02 (Z.L.) 1U19NS104590 (A.L.) R01NS106611-02 (J.S., M.K.) MTEC-20-06-MOM013 (J.S., M.K.) 1U19NS107609-01 (I.S., J.L.) 1U19NS104590 (A.L., J.S.F., I.S.) 1U19NS107609 (E.A.B., J.W.R., J.J.L., I.S.) La Caixa LCF/PR/HR21/52410030 (A.N.O., L.dl.P) European Research Council Consolidator Grant 101001121 (B.P.S.) U.S.-Israel BSF grant 2017015 (RM)U01-NS113198 (J.J.) NSF CAREER IOS-1844935 (M.vdM.) 1R01NS121764-01 (B.L.M.) R01 MH122391 (G.B.) 30MH126483 (J.A.G.) Fondation pour la Recherche Médicale EQU202103012768 (M.Z.) 1R16-NS131108-01 (L.L.).

BackgroundMagnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation.MethodWe validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (IEEG) atlas (https://mni-open-ieegatlas.research.mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space, by applying a forward model to the MEG reconstructed source maps and estimated virtual IEEG (VIEEG) potentials on each IEEG channel location and quantitatively compared those with actual IEEG signals from the atlas for 38 regions of interest in the canonical frequency bands.ResultsThe MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the VIEEG than in the IEEG were more accurately recovered. In the deep regions, MEG estimated amplitudes were largely underestimated and the spectra were poorly recovered. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of IEEG but detected by MEG. Importantly, we found that MEG estimated spectra were more comparable to spectra from the IEEG atlas after the aperiodic components were removed.ConclusionThis study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies.HighlightsValidation of MEG source imaging with intracranial EEE atlasAssessment of resting state human brain oscillations from healthy brainAdapted source imaging method, wMEM, to localize resting state oscillationsIdentified brain regions with oscillations accurately estimated by MEGMEG estimated spectra dominated by oscillations in the alpha band

We aimed to clarify the pathophysiology of epilepsy involving seizures with apparently generalized onset, progressing to focal ictal rhythm through stereotactic EEG (SEEG) implantation, recording, stimulation and high-frequency oscillation (HFO) analysis.We identified two patients with seizures with bilateral electrographic onset evolving to focal ictal rhythm, who underwent SEEG implantation. Patients had pre-surgical epilepsy work-up, including prolonged video scalp EEG, brain MRI, PET, ictal/interictal SPECT, MEG, and EEG-fMRI prior to SEEG implantation.Both patients had childhood-onset seizures involving behavioural arrest and left versive head and eye deviation, evolving to bilateral tonic-clonic convulsions. Seizures were electrographically preceded by diffuse, bilateral 3-Hz activity resembling absence seizures. Both had suspected focal lesions based on neuroimaging, including 3T MRI and voxel-based post-processing in one patient. Electrode stimulation did not elicit any habitual electroclinical seizures. HFO analysis showed bilateral focal regions with high fast-ripple rates.“Generalized-to-focal” seizures may occur due to a diffuse, bilateral epileptic network, however, both patients showed ictal evolution from a generalized pattern to a single dominant focus which may explain why the focal aspect of their seizures had a consistent clinical semiology. Patients such as these may have a unique form of generalized epilepsy, but focal/multifocal cerebral abnormalities are also a possibility.

Simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) is a unique and noninvasive method for investigating epileptic activity. Interictal epileptiform discharge-related EEG-fMRI provides cortical and subcortical blood oxygen level-dependent (BOLD) signal changes specific to epileptic discharges. As a result, EEG-fMRI has revealed insights into generators and networks involved in epileptic activity in different types of epilepsy, demonstrating-for instance-the implication of the thalamus in human generalized spike and wave discharges and the role of the default mode network in absences and focal epilepsy, and has suggested a mechanism for the cortico-subcortical interactions in Lennox-Gastaut syndrome discharges. EEG-fMRI can find deep sources of epileptic activity not available to scalp EEG or magnetoencephalography, and provides critical new information to delineate the epileptic focus when considering surgical treatment or electrode implantation. In recent years, methodological advances, such as artifact removal and automatic detection of events, have rendered this method easier to implement, and its clinical potential has since been established by evidence of the impact of BOLD response on clinical decision-making and of the relationship between concordance of BOLD responses with extent of resection and surgical outcome. This review presents the recent developments in EEG-fMRI methodology and EEG-fMRI studies in different types of epileptic disorders as follows: EEG-fMRI acquisition, gradient and pulse artifact removal, statistical analysis, clinical applications, presurgical evaluation, altered physiological state in generalized genetic epilepsy, and pediatric EEG-fMRI studies.

Objective To determine if properties of epileptic networks could be delineated using interictal spike propagation seen on stereo‐electroencephalography (SEEG) and if these properties could predict surgical outcome in patients with drug‐resistant epilepsy. Methods We studied the SEEG of 45 consecutive drug‐resistant epilepsy patients who underwent subsequent epilepsy surgery: 18 patients with good post‐surgical outcome (Engel I) and 27 with poor outcome (Engel II–IV). Epileptic networks were derived from interictal spike propagation; these networks described the generation and propagation of interictal epileptic activity. We compared the regions in which spikes were frequent and the regions responsible for generating spikes to the area of resection and post‐surgical outcome. We developed a measure termed source spike concordance, which integrates information about both spike rate and region of spike generation. Results Inclusion in the resection of regions with high spike rate is associated with good post‐surgical outcome (sensitivity = 0.82, specificity = 0.73). Inclusion in the resection of the regions responsible for generating interictal epileptic activity independently of rate is also associated with good post‐surgical outcome (sensitivity = 0.88, specificity = 0.82). Finally, when integrating the spike rate and the generators, we find that the source spike concordance measure has strong predictability (sensitivity = 0.91, specificity = 0.94). Interpretations Epileptic networks derived from interictal spikes can determine the generators of epileptic activity. Inclusion of the most active generators in the resection is strongly associated with good post‐surgical outcome. These epileptic networks may aid clinicians in determining the area of resection during pre‐surgical evaluation.

Objective Gain insight and improve our interpretation of measurements from intracerebral electrodes. Determine if interpretation of intracerebral EEG is dependent on electrode characteristics. Methods We use intracerebral EEG measurements differing only in the recording electrodes (Dixi or homemade electrodes), and numerical simulations to determine the spatial sensitivity of intracerebral electrodes and its dependence on several parameters. Results There is a difference in the high frequency (>20 Hz) power depending on the electrode type, which cannot be explained by the different contact sizes or distance between contacts. Simulations show that the width of the gap between electrode and brain and the extent of the generators have an effect on sensitivity, while other parameters are less important. Conclusions The sensitivity of intracerebral electrodes is not affected in an important way by the dimensions of the contacts, but depends on the extent of generators. The unusual insertion technique of homemade electrodes resulting in a large gap between functional brain and electrodes, explains the observed signal difference. Significance Numerical simulation is a useful tool in the choice or design of intracerebral electrodes, and increases our understanding of their measurements. The interpretation of intracerebral EEG is not affected by differences between typical commercially available electrodes.

We present a rare patient clinically suspected to have mixed idiopathic generalized and focal epilepsy, which was supported by BOLD pattern based on EEG-fMRI. A 37-year-old female with three types of refractory seizures starting at age six - tonic with breathing difficulties and confusion, generalized tonic-clonic, and focal with brief impairment of awareness and versive head movement, initially thought to represent atypical absences - was evaluated by EEG-fMRI. She was also shown to have three types of interictal epileptic discharges: generalized spike or polyspikes and slow waves, and left fronto-temporal and right fronto-temporal discharges. We assessed BOLD activation and deactivation for each type. For generalized patterns, the BOLD activation and deactivation were typical of that seen in primary generalized epilepsy. Whereas maximum activation for left fronto-temporal EEG patterns was observed in the left superior frontal gyrus and posterior superior temporal gyrus, maximum activation for right fronto-temporal patterns was bilateral in the right posterior middle temporal gyrus and left posterior middle temporal gyrus. The EEG-fMRI results suggested that the patient had both refractory idiopathic generalized and focal epilepsy, and not a generalized epilepsy originating from a focus.

Sawtooth waves (STW) are bursts of frontocentral slow oscillations recorded in the scalp electroencephalogram (EEG) during rapid eye movement (REM) sleep. Little is known about their cortical generators and functional significance. Stereo-EEG performed for presurgical epilepsy evaluation offers the unique possibility to study neurophysiologyin situin the human brain. We investigated intracranial correlates of scalp-detected STW in 26 patients (14 women) undergoing combined stereo-EEG/polysomnography. We visually marked STW segments in scalp EEG and selected stereo-EEG channels exhibiting normal activity for intracranial analyses. Channels were grouped in 30 brain regions. The spectral power in each channel and frequency band was computed during STW and non-STW control segments. Ripples (80-250 Hz) were automatically detected during STW and control segments. The spectral power in the different frequency bands and the ripple rates were then compared between STW and control segments in each brain region. An increase in 2-4 Hz power during STW segments was found in all brain regions, except the occipital lobe, with large effect sizes in the parietotemporal junction, the lateral and orbital frontal cortex, the anterior insula, and mesiotemporal structures. A widespread increase in high-frequency activity, including ripples, was observed concomitantly, involving the sensorimotor cortex, associative areas, and limbic structures. This distribution showed a high spatiotemporal heterogeneity. Our results suggest that STW are associated with widely distributed, but locally regulated REM sleep slow oscillations. By driving fast activities, STW may orchestrate synchronized reactivations of multifocal activities, allowing tagging of complex representations necessary for REM sleep-dependent memory consolidation.SIGNIFICANCE STATEMENTSawtooth waves (STW) present as scalp electroencephalographic (EEG) bursts of slow waves contrasting with the low-voltage fast desynchronized activity of REM sleep. Little is known about their cortical origin and function. Using combined stereo-EEG/polysomnography possible only in the human brain during presurgical epilepsy evaluation, we explored the intracranial correlates of STW. We found that a large set of regions in the parietal, frontal, and insular cortices shows increases in 2-4 Hz power during scalp EEG STW, that STW are associated with a strong and widespread increase in high frequencies, and that these slow and fast activities exhibit a high spatiotemporal heterogeneity. These electrophysiological properties suggest that STW may be involved in cognitive processes during REM sleep.

ObjectiveTo examine whether fast ripples (FRs) are an accurate marker of the epileptogenic zone, we analyzed overnight stereo-EEG recordings from 43 patients and hypothesized that FR resection ratio, maximal FR rate, and FR distribution predict postsurgical seizure outcome.MethodsWe detected FRs automatically from an overnight recording edited for artifacts and visually from a 5-minute period of slow-wave sleep. We examined primarily the accuracy of removing ≥50% of total FR events or of channels with FRs to predict postsurgical seizure outcome (Engel class I = good, classes II–IV = poor) according to the whole-night and 5-minute analysis approaches. Secondarily, we examined the association of low overall FR rates or absence or incomplete resection of 1 dominant FR area with poor outcome.ResultsThe accuracy of outcome prediction was highest (81%, 95% confidence interval [CI] 67%–92%) with the use of the FR event resection ratio and whole-night recording (vs 72%, 95% CI 56%–85%, for the visual 5-minute approach). Absence of channels with FR rates >6/min (p = 0.001) and absence or incomplete resection of 1 dominant FR area (p < 0.001) were associated with poor outcome.ConclusionsFRs are accurate in predicting epilepsy surgery outcome at the individual level when overnight recordings are used. Absence of channels with high FR rates or absence of 1 dominant FR area is a poor prognostic factor that may reflect suboptimal spatial sampling of the epileptogenic zone or multifocality, rather than an inherently low sensitivity of FRs.Classification of evidenceThis study provides Class II evidence that FRs are accurate in predicting epilepsy surgery outcome.

As the brain is a complex system with occurrence of self-similarity at different levels, a dedicated analysis of the complexity of brain signals is of interest to elucidate the functional role of various brain regions across the various stages of vigilance. We exploited intracranial electroencephalogram data from 38 cortical regions using the Higuchi fractal dimension (HFD) as measure to assess brain complexity, on a dataset of 1772 electrode locations. HFD values depended on sleep stage and topography. HFD increased with higher levels of vigilance, being highest during wakefulness in the frontal lobe. HFD did not change from wake to stage N2 in temporo-occipital regions. The transverse temporal gyrus was the only area in which the HFD did not differ between any two vigilance stages. Interestingly, HFD of wakefulness and stage R were different mainly in the precentral gyrus, possibly reflecting motor inhibition in stage R. The fusiform and parahippocampal gyri were the only areas showing no difference between wakefulness and N2. Stages R and N2 were similar only for the postcentral gyrus. Topographical analysis of brain complexity revealed that sleep stages are clearly differentiated in fronto-central brain regions, but that temporo-occipital regions sleep differently.

Objective. To perform automatic sleep scoring based only on intracranial electroencephalography (iEEG), without the need for scalp EEG), electrooculography (EOG) and electromyography (EMG), in order to study sleep, epilepsy, and their interaction. Approach. Data from 33 adult patients was used for development and training of the automatic scoring algorithm using both oscillatory and non-oscillatory spectral features. The first step consisted in unsupervised clustering of channels based on feature variability. For each cluster the classification was done in two steps, a multiclass tree followed by binary classification trees to distinguish the more challenging stage N1. The test data consisted in 11 patients, in whom the classification was done independently for each channel and then combined to get a single stage per epoch. Main results. An overall agreement of 78% was observed in the test set between the sleep scoring of the algorithm using iEEG alone and two human experts scoring based on scalp EEG, EOG and EMG. Balanced sensitivity and specificity were obtained for the different sleep stages. The performance was excellent for stages W, N2, and N3, and good for stage R, but with high variability across patients. The performance for the challenging stage N1 was poor, but at a similar level as for published algorithms based on scalp EEG. High confidence epochs in different stages (other than N1) can be identified with median per patient specificity >80%. Significance. The automatic algorithm can perform sleep scoring of long-term recordings of patients with intracranial electrodes undergoing presurgical evaluation in the absence of scalp EEG, EOG and EMG, which are normally required to define sleep stages but are difficult to use in the context of intracerebral studies. It also constitutes a valuable tool to generate hypotheses regarding local aspects of sleep, and will be significant for sleep evaluation in clinical epileptology and neuroscience research.

Commentary on Scalp Ripples Can Predict Development of Epilepsy After First Unprovoked Seizure in Childhood Klotz, Sag Y, Schonberger J, Jacobs J. Ann Neurol. 2021;89(1):134-142. doi:10.1002/ana.25...

The integration of high-frequency oscillations (HFOs; ripples [80-250 Hz], fast ripples [250-500 Hz]) in epilepsy evaluation is hampered by physiological HFOs, which cannot be reliably differentiated from pathological HFOs. We evaluated whether defining abnormal HFO rates by statistical comparison to region-specific physiological HFO rates observed in the healthy brain improves identification of the epileptic focus and surgical outcome prediction.We detected HFOs in 151 consecutive patients who underwent stereo-electroencephalography and subsequent resective epilepsy surgery at two tertiary epilepsy centers. We compared how HFOs identified the resection cavity and predicted seizure-free outcome using two thresholds from the literature (HFO rate1/min; 50% of the total number of a patient's HFOs) and three thresholds based on normative rates from the Montreal Neurological Institute Open iEEG Atlas (https://mni-open-ieegatlas.mcgill.ca/): global Atlas threshold, regional Atlas threshold, and regional + 10% threshold after regional Atlas correction.Using ripples, the regional + 10% threshold performed best for focus identification (77.3% accuracy, 27% sensitivity, 97.1% specificity, 80.6% positive predictive value [PPV], 78.2% negative predictive value [NPV]) and outcome prediction (69.5% accuracy, 58.6% sensitivity, 76.3% specificity, 60.7% PPV, 74.7% NPV). This was an improvement for focus identification (+1.1% accuracy, +17.0% PPV; p .001) and outcome prediction (+12.0% sensitivity, +1.0% PPV; p = .05) compared to the 50% threshold. The improvement was particularly marked for foci in cortex, where physiological ripples are frequent (outcome: +35.3% sensitivity, +5.3% PPV; p = .014). In these cases, the regional + 10% threshold outperformed fast ripple rate1/min (+3.6% accuracy, +26.5% sensitivity, +21.6% PPV; p .001) and seizure onset zone (+13.5% accuracy, +29.4% sensitivity, +17.0% PPV; p .05-.01) for outcome prediction. Normalization did not improve the performance of fast ripples.Defining abnormal HFO rates by statistical comparison to rates in healthy tissue overcomes an important weakness in the clinical use of ripples. It improves focus identification and outcome prediction compared to standard HFO measures, increasing their clinical applicability.

In drug-resistant focal epilepsy, interictal high-frequency oscillations (HFOs) recorded from intracranial EEG (iEEG) may provide clinical information for delineating epileptogenic brain tissue. The iEEG electrode contacts that contain HFO are hypothesized to delineate the epileptogenic zone; their resection should then lead to postsurgical seizure freedom. We test whether our prospective definition of clinically relevant HFO is in agreement with postsurgical seizure outcome. The algorithm is fully automated and is equally applied to all data sets. The aim is to assess the reliability of the proposed detector and analysis approach. We use an automated data-independent prospective definition of clinically relevant HFO that has been validated in data from two independent epilepsy centres. In this study, we combine retrospectively collected data sets from nine independent epilepsy centres. The analysis is blinded to clinical outcome. We use iEEG recordings during NREM sleep with a minimum of 12 epochs of 5 min of NREM sleep. We automatically detect HFO in the ripple (80-250 Hz) and in the fast ripple (250-500 Hz) band. There is no manual rejection of events in this fully automated algorithm. The type of HFO that we consider clinically relevant is defined as the simultaneous occurrence of a fast ripple and a ripple. We calculate the temporal consistency of each patient's HFO rates over several data epochs within and between nights. Patients with temporal consistency50% are excluded from further analysis. We determine whether all electrode contacts with high HFO rate are included in the resection volume and whether seizure freedom (ILAE 1) was achieved at ≥2 years follow-up. Applying a previously validated algorithm to a large cohort from several independent epilepsy centres may advance the clinical relevance and the generalizability of HFO analysis as essential next step for use of HFO in clinical practice.

Virtual Resection Predicts Surgical Outcome for Drug-Resistant EpilepsyKini LG, Bernabei JM, Mikhail F, et al. Brain. 2019;142(12):3892-3905. doi:10.1093/brain/awz303.Patients with drug-resistant e...

Objective A vast network involving the nodules and overlying cortices is believed to be responsible for the epileptogenicity in gray matter heterotopia with multiple nodules, which often associated with difficult‐to‐treat epilepsy. We sought to determine if functional magnetic resonance imaging (fMRI) could detect internodular functional connectivity (FC), and if this connectivity reflects an actual synchronized neuronal activity and partakes in epileptogenicity. Methods We studied 16 epilepsy patients with multiple heterotopic nodules; eight underwent subsequent intracerebral EEG. We examined the internodular FC using fMRI and its correspondence with internodular synchrony of intracerebral interictal activity. We then compared the spreading speed of ictal activity between connected and unconnected nodules; and the FC among possible combinations of nodule pairs in terms of their involvement at seizure onset. Results Seventy nodules were studied: 83% have significant connection to at least one other nodule. Among the 49 pairs studied with intracerebral EEG, (1) synchronized interictal activity is more prevalent in fMRI‐connected pairs (P

Resting state functional magnetic resonance imaging is used to study how brain regions are functionally connected by measuring temporal correlation of the fMRI signals, when a subject is at rest. Sparse dictionary learning is used to estimate a dictionary of resting state networks by decomposing the whole brain signals into several temporal features (atoms), each being shared by a set of voxels associated to a network. Recently, we proposed and validated a new method entitled Sparsity-based Analysis of Reliable K-hubness (SPARK), suggesting that connector hubs of brain networks participating in inter-network communication can be identified by counting the number of atoms involved in each voxel (sparse number k). However, such hub analysis can be corrupted by the presence of noise-related atoms, where physiological fluctuations in cardiorespiratory processes may remain even after band-pass filtering and regression of confound signals from the white matter and cerebrospinal fluid. Handling this issue might require manual classification of noisy atoms, which is a time-consuming and subjective task. Motivated by the fact that the physiological fluctuations are often localized in tissues close to large vasculatures, i.e. sagittal sinus, we propose an automatic classification of physiological noise-related atoms for SPARK using spatial priors and a stepwise regression procedure. We measured the degree to which the noise-characteristic time-courses within the mask are explained by each atom, and classified noise-related atoms using a subject-specific threshold estimated using a bootstrap resampling based strategy. Using real data from healthy subjects (N = 25), manual classification of the atoms by two independent reviewers showed the presence of sagittal sinus related noise in 65% of the runs. Applying the same manual classification after the proposed automatic removal method reduced this rate to 19%. A 10-fold cross-validation on real data showed good specificity and accuracy of the proposed automated method in classifying the target noise (area under the ROC curve= 0.89), when compared to the manual classification considered as the reference. We demonstrated decrease in k-hubness values in the voxels involved in the sagittal sinus at both individual and group levels, suggesting a significant improvement of SPARK, which is particularly important when considering clinical applications.

Objective We hypothesized that the number of interictal epileptic discharges (IEDs) during scan and their spatial extent are contributing factors in obtaining appropriate activations that reveal the seizure onset zone (SOZ) in EEG-fMRI. Methods 157 IED types, each corresponding to one EEG scalp distribution, in 64 consecutive EEG-fMRI studies from 64 patients with refractory localization-related epilepsy were reviewed. To determine reliable activation, we used the threshold corresponding to corrected whole-brain topological false discovery rate (FDR). The location with maximum activation was compared to the presumed SOZ as defined by a comprehensive evaluation for each patient. Results The number of IEDs was significantly higher in the types with t-value above FDR than with t-value below FDR. The presumed SOZ could be delineated in 30 of the 64 patients. Among these patients, the types of IED concordant with the SOZ had significantly larger extent on scalp EEG than the IED types discordant with the SOZ. Conclusions The number of IEDs is important factor in obtaining reliable activations in EEG-fMRI. IEDs with larger spatial extent are more likely to reveal, on maximum BOLD, accurate location of the SOZ. Significance Widespread discharges are more likely to yield a reliable activation for SOZ in EEG-fMRI.

OBJECTIVE To investigate whether high-frequency oscillations (HFOs) show spatiotemporal propagation and assess the relevance of the earliest oscillations in relation to the seizure onset zone (SOZ) and postsurgical outcome. METHODS We retrospectively investigated the intracerebral electroencephalography (EEG) of patients who became seizure free after subsequent surgery. We marked HFOs during 1 hour of recordings. We calculated the time delay between pairs of channels as the median delay between their HFOs and constructed a time line of the delay of each channel with respect to the earliest channel (first source channel). A network was defined when a temporal order could be established among the channels based on the existence of statistically significant delays. RESULTS Fifteen patients with good surgical outcome were included. We found ripple networks in all patients, and fast ripple networks in 9. For ripples, first source channels were found in a higher proportion in the SOZ than the rest of the network channels (15 of 27 [56%] versus 93 of 262 [35%]; p = 0.04). For both ripples and fast ripples, first source channels were resected more often that the rest of the network channels (ripples: 13 of 27 [48%] versus 65 of 262 [25%]; p = 0.01; fast ripples: 8 of 9 [89%] versus 17 of 40 [43%]; p = 0.002); channels with the highest rates of ripples and fast ripples were resected in a similar proportion. INTERPRETATION These results demonstrate that interictal HFOs are organized in networks and indicate a possible need for the resection of first source channels. However, resecting them is not superior to resecting channels with highest rates of HFOs. Ann Neurol 2019;85:485-494.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG (good temporal resolution) and fMRI (good spatial resolution) to measure neuronal activity during an electrographic event, through hemodynamic responses known as blood-oxygen-level-dependent (BOLD) changes. It is a non-invasive research tool that is utilized in neuroscience research and is highly beneficial to the clinical community, especially for the management of neurological diseases, provided that proper equipment and protocols are administered during data acquisition. Although recording EEG-fMRI is apparently straightforward, the correct preparation, especially in placing and securing the electrodes, is not only important for safety but is also critical in ensuring the reliability and analyzability of the EEG data obtained. This is also the most experience-demanding part of the preparation. To address these issues, a straightforward protocol that ensures data quality was developed. This article provides a step-by-step guide for acquiring reliable EEG data during EEG-fMRI using this protocol that utilizes readily available medical products. The presented protocol can be adapted to different applications of EEG-fMRI in research and clinical settings, and may be beneficial to both inexperienced and expert operators.

OBJECTIVE In an attempt to improve postsurgical seizure outcomes for poorly defined cases (PDCs) of pediatric focal epilepsy (i.e., those that are not visible or well defined on 3T MRI), the authors modified their presurgical evaluation strategy. Instead of relying on concordance between video-electroencephalography and 3T MRI and using functional imaging and intracranial recording in select cases, the authors systematically used a multimodal, 3-tiered investigation protocol that also involved new collaborations between their hospital, the Montreal Children’s Hospital, and the Montreal Neurological Institute. In this study, the authors examined how their new strategy has impacted postsurgical outcomes. They hypothesized that it would improve postsurgical seizure outcomes, with the added benefit of identifying a subset of tests contributing the most. METHODS Chart review was performed for children with PDCs who underwent resection following the new strategy (i.e., new protocol [NP]), and for the same number who underwent treatment previously (i.e., preprotocol [PP]); ≥ 1-year follow-up was required for inclusion. Well-defined, multifocal, and diffuse hemispheric cases were excluded. Preoperative demographics and clinical characteristics, resection volumes, and pathology, as well as seizure outcomes (Engel class Ia vs > Ia) at 1 year postsurgery and last follow-up were reviewed. RESULTS Twenty-two consecutive NP patients were compared with 22 PP patients. There was no difference between the two groups for resection volumes, pathology, or preoperative characteristics, except that the NP group underwent more presurgical evaluation tests (p < 0.001). At 1 year postsurgery, 20 of 22 NP patients and 10 of 22 PP patients were seizure free (OR 11.81, 95% CI 2.00–69.68; p = 0.006). Magnetoencephalography and PET/MRI were associated with improved postsurgical seizure outcomes, but both were highly correlated with the protocol group (i.e., independent test effects could not be demonstrated). CONCLUSIONS A new presurgical evaluation strategy for children with PDCs of focal epilepsy led to improved postsurgical seizure freedom. No individual presurgical evaluation test was independently associated with improved outcome, suggesting that it may be the combined systematic protocol and new interinstitutional collaborations that makes the difference rather than any individual test.

Background and ObjectivesTo assess the utility of EEG-fMRI for epilepsy surgery, we evaluated surgical outcome in relation to the resection of the most significant EEG-fMRI response.MethodsPatients with postoperative neuroimaging and follow-up of at least 1 year were included. In EEG-fMRI responses, we defined as primary the cluster with the highest absolute t value located in the cortex and evaluated 3 levels of confidence for the results. The threshold for low confidence was t ≥ 3.1 (p < 0.005); the one for medium confidence corresponded to correction for multiple comparisons with a false discovery rate of 0.05; and a result reached high confidence when the primary cluster was much more significant than the next highest cluster. Concordance with the resection was determined by comparison to postoperative neuroimaging.ResultsWe evaluated 106 epilepsy surgeries in 84 patients. An increasing association between concordance and surgical outcome with higher levels of confidence was demonstrated. If the peak response was not resected, the surgical outcome was likely to be poor: for the high confidence level, no patient had a good outcome; for the medium and low levels, only 18% and 28% had a good outcome. The positive predictive value remained low for all confidence levels, indicating that removing the maximum cluster did not ensure seizure freedom.DiscussionResection of the primary EEG-fMRI cluster, especially in high confidence cases, is necessary to obtain a good outcome but not sufficient.Classification of EvidenceThis study provides Class II evidence that failure to resect the primary EEG-fMRI cluster is associated with poorer epilepsy surgery outcomes.

Epilepsy associated with periventricular nodular heterotopia (PNH), a developmental malformation, is frequently drug-resistant and requires focal therapeutic intervention. Invasive EEG study is usually necessary to delineate the epileptogenic zone, but constructing an accurate hypothesis to define an appropriate electrode implantation scheme and the treatment is challenging. This article reviews recent studies that help understanding the epileptogenicity and potential therapeutic options in PNH. New noninvasive diagnostic and intracerebral EEG analytic tools demonstrated that cortical hyperexcitability and aberrant connectivity (between nodules and cortices and among nodules) are likely mechanisms causing epilepsy in most patients. The deeply seated PNH, if epileptogenic, are ideal target for stereotactic ablative techniques, which offer concomitant ablation of multiple regions with relatively satisfactory seizure outcome. Advance in diagnostic and analytic tools have enhanced our understanding of the complex epileptogenicity in PNH. Development in stereotactic ablative techniques now offers promising therapeutic options for these patients.

This project aims to explore if stronger functional connectivity (FC) exists in the maximal BOLD response of EEG/fMRI analysis when it is concordant with seizure-onset-zone (SOZ). Twenty-six patients with drug-resistant focal epilepsy who had an EEG/fMRI and later underwent stereo-EEG implantation were included. Different types of IEDs were labeled in scalp EEG and IED-related maximal BOLD responses were evaluated separately, each constituting one study. After evaluating concordance between maximal BOLD and SOZ, twenty-seven studies were placed in the concordant group and eight in the discordant group. We evaluated the local connectivity and ipsilaterally distant connectivity difference between the maximal BOLD and the contralateral homotopic region. Significantly stronger local FC was found for the maximal BOLD in the concordant group (p

Recent technological advances in signal acquisition and analysis have led to the discovery of high-frequency oscillatory events in animal models of mesial temporal lobe epilepsy (MTLE) and in the EEG of epileptic patients. These high-frequency oscillations (HFOs) in the 80–500 Hz frequency range are thought to reflect the activity of dysfunctional neuronal networks that may sustain epileptogenesis and ictogenesis. In this chapter, we review recent findings on HFOs in MTLE and their contribution to the identification of the pathophysiological mechanisms underlying the development of this epileptic condition. We describe the presumptive cellular and network mechanisms underlying ripples (80–200 Hz) and fast ripples (250–500 Hz) as well as their relation with interictal spikes and seizures. In addition, we discuss their contribution to epileptogenesis and ictogenesis in epileptic patients and animal models of MTLE.

IMPORTANCE: Stereoelectroencephalography (SEEG) has become the criterion standard in case of inconclusive noninvasive presurgical epilepsy workup. However, up to 40% of patients are subsequently not offered surgery because the seizure-onset zone is less focal than expected or cannot be identified. OBJECTIVE: To predict focality of the seizure-onset zone in SEEG, the 5-point 5-SENSE score was developed and validated. DESIGN, SETTING, AND PARTICIPANTS: This was a monocentric cohort study for score development followed by multicenter validation with patient selection intervals between February 2002 to October 2018 and May 2002 to December 2019. The minimum follow-up period was 1 year. Patients with drug-resistant epilepsy undergoing SEEG at the Montreal Neurological Institute were analyzed to identify a focal seizure-onset zone. Selection criteria were 2 or more seizures in electroencephalography and availability of complete neuropsychological and neuroimaging data sets. For validation, patients from 9 epilepsy centers meeting these criteria were included. Analysis took place between May and July 2021. MAIN OUTCOMES AND MEASURES: Based on SEEG, patients were grouped as focal and nonfocal seizure-onset zone. Demographic, clinical, electroencephalography, neuroimaging, and neuropsychology data were analyzed, and a multiple logistic regression model for developing a score to predict SEEG focality was created and validated in an independent sample. RESULTS: A total of 128 patients (57 women [44.5%]; median [range] age, 31 [13-58] years) were analyzed for score development and 207 patients (97 women [46.9%]; median [range] age, 32 [16-70] years) were analyzed for validation. The score comprised the following 5 predictive variables: focal lesion on structural magnetic resonance imaging, absence of bilateral independent spikes in scalp electroencephalography, localizing neuropsychological deficit, strongly localizing semiology, and regional ictal scalp electroencephalography onset. The 5-SENSE score had an optimal mean (SD) probability cutoff for identifying a focal seizure-onset zone of 37.6 (3.5). Area under the curve, specificity, and sensitivity were 0.83, 76.3% (95% CI, 66.7-85.8), and 83.3% (95% CI, 72.30-94.1), respectively. Validation showed 76.0% (95% CI, 67.5-84.0) specificity and 52.3% (95% CI, 43.0-61.5) sensitivity. CONCLUSIONS AND RELEVANCE: High specificity in score development and validation confirms that the 5-SENSE score predicts patients where SEEG is unlikely to identify a focal seizure-onset zone. It is a simple and useful tool for assisting clinicians to reduce unnecessary invasive diagnostic burden on patients and overutilization of limited health care resources.

Objective High-frequency oscillations (HFOs) are a promising biomarker for the epileptogenic zone. It has not been possible, however, to differentiate physiological from pathological HFOs, and baseline rates of HFO occurrence vary substantially across brain regions. This project establishes region-specific normative values for physiological HFOs and high-frequency activity (HFA). Methods Intracerebral stereo-encephalographic recordings with channels displaying normal physiological activity from nonlesional tissue were selected from 2 tertiary epilepsy centers. Twenty-minute sections from N2/N3 sleep were selected for automatic detection of ripples (80-250Hz), fast ripples (>250Hz), and HFA defined as long-lasting activity > 80Hz. Normative values are provided for 17 brain regions. Results A total of 1,171 bipolar channels with normal physiological activity from 71 patients were analyzed. The highest rates of ripples were recorded in the occipital cortex, medial and basal temporal region, transverse temporal gyrus and planum temporale, pre- and postcentral gyri, and medial parietal lobe. The mean rate of fast ripples was very low (0.038/min). Only 5% of channels had a rate > 0.2/min HFA was observed in the medial occipital lobe, pre- and postcentral gyri, transverse temporal gyri and planum temporale, and lateral occipital lobe. Interpretation This multicenter atlas is the first to provide region-specific normative values for physiological HFO rates and HFA in common stereotactic space; rates above these can now be considered pathological. Physiological ripples are frequent in eloquent cortex. In contrast, physiological fast ripples are very rare, making fast ripples a good candidate for defining the epileptogenic zone. Ann Neurol 2018;84:374-385.

ObjectiveTo evaluate the use of interictal high-frequency oscillations (HFOs) in epilepsy surgery for prediction of postsurgical seizure outcome in a prospective multicenter trial.MethodsWe hypothesized that a seizure-free outcome could be expected in patients in whom the surgical planning included the majority of HFO-generating brain tissue while a poor seizure outcome could be expected in patients in whom only a few such areas were planned to be resected. Fifty-two patients were included from 3 tertiary epilepsy centers during a 1-year period. Ripples (80–250 Hz) and fast ripples (250–500 Hz) were automatically detected during slow-wave sleep with chronic intracranial EEG in 2 centers and acute intraoperative electrocorticography in 1 patient.ResultsThere was a correlation between the removal of HFO-generating regions and seizure-free outcome at the group level for all patients. No correlation was found, however, for the center-specific analysis, and an individual prognostication of seizure outcome was true in only 36 patients (67%). Moreover, some patients became seizure-free without removal of the majority of HFO-generating tissue. The investigation of influencing factors, including comparisons of visual and automatic analysis, using a threshold analysis for areas with high HFO activity, and excluding contacts bordering the resection, did not result in improved prognostication.ConclusionsOn an individual patient level, a prediction of outcome was not possible in all patients. This may be due to the analysis techniques used. Alternatively, HFOs may be less specific for epileptic tissue than earlier studies have indicated.

Objectives There are different neurophysiological markers of the Epileptogenic Zone (EZ), but their sensitivity and specificity for the EZ is not known in Focal Cortical Dysplasia (FCD) patients. Methods We studied patients with FCD who underwent stereoelectroencephalography (SEEG) and surgery. We marked in the SEEG: (a) typical and atypical interictal epileptiform patterns, (b) ictal onset patterns, and (c) rates of ripples (80–250 Hz) and fast ripples (FRs) (>250 Hz). High frequency oscillations were marked automatically during one hour of deep sleep. Surgical outcome was defined as good (Engel I) or poor (Engel II–IV). We computed the sensitivity and, as a measure of specificity, the false positive rate to identify the EZ, and compared them across the different neurophysiological markers. Results We studied 21 patients, 19 with FCD II. Ictal and typical interictal pattern were the markers with highest sensitivity, while the atypical interictal pattern had the lowest. We found no significant difference in specificity among markers. However, there is a tendency that FRs had the lowest false positive rate. Conclusion The typical interictal pattern has the highest sensitivity. The clinical use of FRs is limited by their low sensitivity. Significance We suggest to analyze the typical interictal pattern first. FRs should be analyzed in a second step. If, for instance, a focus with FRs and no typical interictal pattern is found, this area could be considered for resection.

BACKGROUND The detection of high-frequency oscillations (HFOs, ripples: 80-200 Hz, fast ripples: 250-500 Hz) is often based on considering ripples or fast ripples in isolation; overlapping ripples and fast ripples are excluded from further analysis. Here, we studied overlapping HFOs during spontaneous seizures in pilocarpine-treated animals. NEW METHOD Spontaneous seizures (n = 6 animals) presented with either hypersynchronous- (HYP, n = 18) or low-voltage fast-onset (LVF, n = 21) pattern. Ripples and fast ripples overlapping by more than 30% were analysed. RESULTS Overlapping HFOs could show a unimodal power spectrum between 80-500 Hz (n = 188, 58.9%) or a bimodal power spectrum, with peaks in power between 80 and 200 Hz and between 250 and 500 Hz (n = 131, 41.1%,). Overlapping HFOs occurred at higher rates during HYP seizures compared to the pre-ictal period in seizure onset zones (p

In contrast to scalp EEG, our knowledge of the normal physiological intracranial EEG activity is scarce. This multicentre study provides an atlas of normal intracranial EEG of the human brain during wakefulness. Here we present the results of power spectra analysis during wakefulness. Intracranial electrodes are placed in or on the brain of epilepsy patients when candidates for surgical treatment and non-invasive approaches failed to sufficiently localize the epileptic focus. Electrode contacts are usually in cortical regions showing epileptic activity, but some are placed in normal regions, at distance from the epileptogenic zone or lesion. Intracranial EEG channels defined using strict criteria as very likely to be in healthy brain regions were selected from three tertiary epilepsy centres. All contacts were localized in a common stereotactic space allowing the accumulation and superposition of results from many subjects. Sixty-second artefact-free sections during wakefulness were selected. Power spectra were calculated for 38 brain regions, and compared to a set of channels with no spectral peaks in order to identify significant peaks in the different regions. A total of 1785 channels with normal brain activity from 106 patients were identified. There were on average 2.7 channels per cm 3 of cortical grey matter. The number of contacts per brain region averaged 47 (range 6-178). We found significant differences in the spectral density distributions across the different brain lobes, with beta activity in the frontal lobe (20-24 Hz), a clear alpha peak in the occipital lobe (9.25-10.25 Hz), intermediate alpha (8.25-9.25 Hz) and beta (17-20 Hz) frequencies in the parietal lobe, and lower alpha (7.75-8.25 Hz) and delta (0.75-2.25 Hz) peaks in the temporal lobe. Some cortical regions showed a specific electrophysiological signature: peaks present in > 60% of channels were found in the precentral gyrus (lateral: peak frequency range, 20-24 Hz; mesial: 24-30 Hz), opercular part of the inferior frontal gyrus (20-24 Hz), cuneus (7.75-8.75 Hz), and hippocampus (0.75-1.25 Hz). Eight per cent of all analysed channels had more than one spectral peak; these channels were mostly recording from sensory and motor regions. Alpha activity was not present throughout the occipital lobe, and some cortical regions showed peaks in delta activity during wakefulness. This is the first atlas of normal intracranial EEG activity; it includes dense coverage of all cortical regions in a common stereotactic space, enabling direct comparisons of EEG across subjects. This atlas provides a normative baseline against which clinical EEGs and experimental results can be compared. It is provided as an open web resource (https://mni-open-ieegatlas.research.mcgill.ca).

Simultaneous scalp EEG/functional MRI measures non-invasively haemodynamic responses to interictal epileptic discharges, which are related to the epileptogenic zone. High frequency oscillations are also an excellent indicator of this zone, but are primarily recorded from intracerebral EEG. We studied the spatial overlap of these two important markers in patients with drug-resistant epilepsy to assess if their combination could help better define the extent of the epileptogenic zone. We included patients who underwent EEG-functional MRI and later intracerebral EEG. Based on intracerebral EEG findings, we separated patients with unifocal seizures from patients with multifocal or unknown onset seizures. Haemodynamic t-maps were coregistered with the intracerebral electrode positions. Each EEG channel was classified as pertaining to one of the following categories: primary haemodynamic cluster (maximum t-value), secondary cluster (t-value > 90% of the primary cluster) or outside the primary and secondary clusters. We marked high frequency oscillations (ripples: 80–250 Hz; fast ripples: 250–500 Hz) during 1 h of slow wave sleep, and compared their rates in each haemodynamic category. After classifying channels as high- or low-rate, the proportion of high-rate channels within the primary or primary plus secondary clusters was compared to the proportion expected by chance. Twenty-five patients, 11 with unifocal and 14 with multifocal/unknown seizure onsets, were studied. We found a significantly higher median high frequency oscillation rate in the primary cluster compared to secondary cluster and outside these two clusters for the unifocal group (P < 0.0001), but not for the multifocal/unknown group. For the unifocal group, the number of high-rate channels within the primary or primary plus secondary clusters was significantly higher than expected by chance. This held only for the high-ripple-rate channels in the multifocal/unknown group. At the patient level, most patients (18/25, or 72%) had at least one high-rate channel within a primary cluster. In patients with unifocal epilepsy, the maximum haemodynamic response (primary cluster) related to scalp interictal discharges overlaps with the tissue generating high frequency oscillations at high rates. If intracranial EEG is warranted, this response should be explored. As a tentative clinical use of the combination of these techniques we propose that higher high frequency oscillation rates inside than outside the maximum response indicates that the patient has indeed a focal epileptogenic zone demarcated by this response, whereas similar rates inside and outside may indicate a widespread epileptogenic zone or an epileptogenic zone not covered by the implantation.

Objectives Electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) allows imaging of brain-wide epileptic networks, and demonstrates that focal interictal epileptic activity is sometimes accompanied by bilateral functional activations. The corpus callosum (CC) facilitates bilateral spread of epileptic activity and at times targeted surgically for drug-resistant epilepsy (DRE). We hypothesized that focal epileptic networks are more unilateral in patients lacking intact CC. Methods We included focal DRE patients who underwent pre-surgical EEG-fMRI and had CC agenesis (group A, n = 5), patients who previously underwent anterior callosotomy as treatment for drop attacks and continued having seizures (group B, n = 6), and control group of patients with focal epilepsy and intact CC (group C, n = 9). Blood-oxygenation-level-dependent (BOLD) signal maps were generated for interictal epileptic discharges. To quantify bi-hemispheric distribution of epileptic networks, laterality indices were compared between groups. Anatomical and diffusion-weighted imaging demonstrated white matter pathways. Results 96% of studies demonstrated bilateral activations. Laterality indices were similar in groups A and C, whereas group B demonstrated a more bilateral network than group C (p = 0.028). Diffusion-weighted and anatomical imaging showed aberrant white matter pathways and larger anterior commissure in groups A and B. 68% of studies showed maximal activation cluster concordant with the presumed epileptic focus, 28% showed non-maximal activation at presumed focus. Significance Focal epileptic activity is associated with bilateral functional activations despite lack of intact CC, and is associated with stronger contralateral activation in patients after anterior callosotomy compared to controls. These findings disprove our initial hypothesis, and combined with white matter structural imaging, may indicate that the CC is not a sole route of propagation of epileptic activity, which might spread via anterior commissure. Our study demonstrates the utility of EEG-fMRI in assessing epileptic networks and potentially aiding in tailoring surgical treatments in DRE patients with callosal anomalies, and in callosal surgeries.

SummaryObjective To increase the diagnostic power of scalp electroencephalography (EEG) by investigating whether lesion type and location influence the morphology of interictal epileptic discharges (IEDs) and the likelihood that IEDs and high-frequency oscillations (HFOs) are present. Methods We studied EEG activity in epilepsy patients with lesional epilepsy. Lesions were classified by type and by location (region and depth). We marked a maximum of 50 IEDs during deep non–rapid eye movement sleep. IEDs were identified as spikes or sharp waves with or without slow waves, or bursts of spikes or sharp waves with or without slow waves. We analyzed HFOs in the studies showing at least 50 IEDs. Results In 192 scalp EEG studies, the differences in the percentage of studies showing IEDs in each depth-related group were not statistically significant, whereas HFOs (55 studies) predominated in patients exhibiting superficial lesions (p

Objective: Structural and functional imaging studies in focal epilepsy often reveal distributed regions of abnormality. These are interpreted as representing the existence of epileptic networks but the presence of actual neuronal interactions between these regions has not been demonstrated. We sought to determine if the distributed hemodynamic responses often seen in fMRI studies of scalp interictal epileptic discharges (IEDs) actually correspond to synchronized neuronal activities when examining the intracerebral EEG (iEEG) at distant nodes of the network. Methods: We studied 28 patients who underwent first EEG-fMRI and then iEEG, and had significant hemodynamic responses in the gray matter. We co-registered the hemodynamic responses to the iEEG electrode contacts positions and analyzed synchrony, measured by correlation, between IEDs recorded by iEEG in regions with and without hemodynamic responses. Results: The synchrony of intracerebral IED activity between pairs of regions showing a hemodynamic response was higher compared to that between pairs of regions without (p

SummaryObjective Intracranial electroencephalography (EEG), performed presurgically in patients with drug-resistant and difficult-to-localize focal epilepsy, samples only a small fraction of brain tissue and thus requires strong hypotheses regarding the possible localization of the epileptogenic zone. EEG/fMRI (functional magnetic resonance imaging), a noninvasive tool resulting in hemodynamic responses, could contribute to the generation of these hypotheses. This study assessed how these responses, despite their interictal origin, predict the seizure-onset zone (SOZ). Methods We retrospectively studied 37 consecutive patients who underwent stereo-EEG (SEEG) and EEG/fMRI that resulted in significant hemodynamic responses. Hemodynamic response maps were co-registered to postimplantation anatomic imaging, allowing inspection of these responses in relation to SEEG electrode's location. The area containing the most significant t-value (primary cluster) explored with an electrode was assessed for concordance with SEEG-defined SOZ. Discriminant analysis was performed to distinguish the primary clusters having a high probability of localizing the SOZ. Results Thirty-one patients had at least one study with primary cluster explored with an electrode, and 24 (77%) had at least one study with primary cluster concordant with the SOZ. Each patient could have multiple types of interictal discharge and therefore multiple studies. Among 59 studies from the 37 patients, 44 had a primary cluster explored with an electrode and 30 (68%) were concordant with the SOZ. Discriminant analysis showed that the SOZ is predictable with high confidence (>90%) if the primary cluster is highly significant and if the next significant cluster is much less significant or absent. Significance The most significant hemodynamic response to interictal discharges delineates the subset of the irritative zone that generates seizures in a high proportion of patients with difficult-to-localize focal epilepsy. EEG/fMRI generates responses that are valuable targets for electrode implantation and may reduce the need for implantation in patients in whom the most significant response satisfies the condition of our discriminant analysis.

Sleep spindles and K-complexes (KCs) are a hallmark of N2 sleep. While the functional significance of spindles is comparatively well investigated, there is still ongoing debate about the role of the KC: it is unclear whether it is a cortical response to an arousing stimulus (either external or internal) or whether it has sleep-promoting properties. Invasive intracranial EEG recordings from individuals with drug-resistant epilepsy offer a unique opportunity to study in-situ human brain physiology. To better understand the function of the KC, we aimed to (i) investigate the intracranial correlates of spontaneous scalp KCs, and (ii) compare the intracranial activity of scalp KCs associated or not with arousals. Whole-night recordings from adults with drug-resistant focal epilepsy who underwent combined intracranial-scalp EEG for pre-surgical evaluation at the Montreal Neurological Institute between 2010 and 2018 were selected. KCs were visually marked in the scalp and categorized according to the presence of microarousals: (i) Pre-microarousal KCs; (ii) KCs during an ongoing microarousal; and (iii) KCs without microarousal. Power in different spectral bands was computed to compare physiological intracranial EEG activity at the time of scalp KCs relative to the background, as well as to compare microarousal subcategories. A total of 1198 scalp KCs selected from 40 subjects were analyzed, resulting in 32,504 intracranial KC segments across 992 channels. Forty-seven percent of KCs were without microarousal, 30% were pre-microarousal, and 23% occurred during microarousals. All scalp KCs were accompanied by widespread cortical increases in delta band power (0.3–4 ​Hz) relative to the background: the highest percentages were observed in the parietal (60–65%) and frontal cortices (52–58%). Compared to KCs without microarousal, pre-microarousal KCs were accompanied by increases (66%) in beta band power (16–30 ​Hz) in the motor cortex, which was present before the peak of the KC. In addition, spatial distribution of spectral power changes following each KC without microarousal revealed that certain brain regions were associated with increases in delta power (25–62%) or decreases in alpha/beta power (11–24%), suggesting a sleep-promoting pattern, whereas others were accompanied by increases of higher frequencies (12–27%), suggesting an arousal-related pattern. This study shows that KCs can be generated across widespread cortical areas. Interestingly, the motor cortex shows awake-like EEG activity before the onset of KCs followed by microarousals. Our findings also highlight region-specific sleep- or arousal-promoting responses following KCs, suggesting a dual role for the human KC.

PURPOSE In comatose patients, distinguishing between nonconvulsive status epilepticus and diffuse structural or metabolic encephalopathies is often challenging. Both conditions can generate periodic discharges on EEG with similar morphology and periodicity. We investigated the occurrence of high-frequency oscillations-potential biomarkers of epileptogenesis-on scalp EEG of comatose patients with periodic discharges in the EEG. METHODS Fifteen patients were included. Patients were divided into three groups, according to underlying etiology: Group 1, seizure related; group 2, structural; group 3, nonstructural. EEG recordings were compared with respect to the presence and rates of gamma (30-80 Hz) and ripples (80-250 Hz). RESULTS Patients were 23 to 106 years old (median, 68 years); 60% were female. 206 channels were eligible for analysis (median, 15 channels/patient). Overall, 43% of channels showed gamma, and 24% had ripples. Group 2 showed the highest proportion of channels with gamma (47%), followed by group 1 (38%) and group 3 (36%). Mean gamma rates were higher in group 2 (4.65 gamma/min/channel) than in group 1 (1.52) and group 3 (1.44) (P < 0.001). Group 2 showed the highest proportion of channels with ripples (29.2%), followed by group 1 (15%) and group 3 (24.2%). Mean ripple rates were higher in group 2 (5.09 ripple/min/channel) than in group 1 (0.96) and group 3 (0.83) (P < 0.001). CONCLUSIONS Fast oscillations, including high-frequency oscillations, can be detected in scalp EEG of patients with altered consciousness. High rates of fast activity may suggest an underlying structural brain lesion. Future studies are needed to determine whether fast oscillations in the setting of acute/subacute brain lesions are a biomarker of subsequent development of human epilepsy.

Objective Regional variations in oscillatory activity during human sleep remain unknown. Using the unique ability of intracranial electroencephalography to study in situ brain physiology, this study assesses regional variations of electroencephalographic sleep activity and creates the first atlas of human sleep using recordings from the first sleep cycle. Methods Intracerebral electroencephalographic recordings with channels displaying physiological activity from nonlesional tissue were selected from 91 patients of 3 tertiary epilepsy centers. Sections during non-rapid eye movement sleep (stages N2 and N3) and rapid eye movement sleep (stage R) were selected from the first sleep cycle for oscillatory and nonoscillatory signal analysis. Results of 1,468 channels were grouped into 38 regions covering all cortical areas. Results We found regional differences in the distribution of sleep transients and spectral content during all sleep stages. There was a caudorostral gradient, with more slow frequencies and fewer spindles in temporoparieto-occipital than in frontal cortex. Moreover, deep-seated structures showed spectral peaks differing from the baseline electroencephalogram. The regions with >60% of channels presenting significant rhythmic activity were either mesial or temporal basal structures that contribute minimally to the scalp electroencephalogram. Finally, during deeper sleep stages, electroencephalographic analysis revealed a more homogeneous spatial distribution, with increased coupling between high and low frequencies. Interpretation This study provides a better understanding of the regional variability of sleep, and establishes a baseline for human sleep in all cortical regions during the first sleep cycle. Furthermore, the open-access atlas will be a unique resource for research (https://mni-open-ieegatlas. Research mcgill.ca). ANN NEUROL 2020;87:289-301.