Brain regions and epileptogenicity influence epileptic interictal spike production and propagation during NREM sleep in comparison with wakefulness

Mechanistic insights into the interaction between epilepsy and sleep

Epidemiological evidence has demonstrated associations between sleep and epilepsy, but we lack a mechanistic understanding of these associations. If sleep affects the pathophysiology of epilepsy and the risk of seizures, as suggested by correlative evidence, then understanding these effects could provide crucial insight into the basic mechanisms that underlie the development of epilepsy and the generation of seizures. In this Review, we provide in-depth discussion of the associations between epilepsy and sleep at the cellular, network and system levels and consider the mechanistic underpinnings of these associations. We also discuss the clinical relevance of these associations, highlighting how they could contribute to improvements in the management of epilepsy. A better understanding of the mechanisms that govern the interactions between epilepsy and sleep could guide further research and the development of novel approaches to the management of epilepsy.

Combined value of interictal markers and stimulated seizures to estimate the seizure onset zone in stereoelectroencephalography

OBJECTIVE

This study was undertaken to investigate the potential of interictal electroencephalographic (EEG) findings and electrically stimulated seizures during stereo-EEG (SEEG) as surrogate markers for the spontaneous seizure onset zone (spSOZ). We hypothesized that combining the localizing information of these markers would allow clinically meaningful estimation of the spSOZ.

METHODS

We included all patients (n = 63) who underwent SEEG between January 2013 and March 2020 at Helsinki University Hospital and had spontaneous seizures during the recording. We scored spikes, gamma activity, and background abnormality on each channel visually during a 12-h epoch containing waking state and sleep. Based on semiology, we classified stimulated seizures as typical or atypical/unclassifiable and estimated the stimulated SOZ (stimSOZ) for typical seizures. To assess which markers increased the odds of channel inclusion in the spSOZ, we fitted mixed effects logistic regression models.

RESULTS

A combined regression model including the stimSOZ and interictal markers scored during sleep performed better in estimating which channels were part of the spSOZ than models based on stimSOZ (p < .001) or interictal markers (p < .001) alone. Of the individual markers, the effect sizes were greatest for inclusion of a channel in the stimSOZ (odds ratio [OR] = 60, 95% confidence interval [CI] = 37-97, p < .001) and for continuous (OR = 25, 95% CI = 12-55, p < .001) and subcontinuous (OR = 36, 95% CI = 21-64, p < .001) interictal spiking. At the individual level, the model's accuracy to predict spSOZ inclusion varied markedly (median accuracy = 85.7, range = 54.4-100), which was not explained by etiology (p > .05).

SIGNIFICANCE

Compared to either marker alone, combining visually rated interictal SEEG markers and stimulated seizures improved prediction of which SEEG channels belonged to the spSOZ. Inclusion in the stimSOZ and continuous or subcontinuous spikes increased the odds of spSOZ inclusion the most. Future studies should investigate whether suboptimal sampling of the true epileptogenic zone can explain the model's poor performance in certain patients.

Utility of Various Activation Procedures in Provoking Ictal and Interictal Patterns, during Routine Electroencephalogram (rEEG) Recording

BACKGROUND

Activation procedures (APs) are adopted during routine electroencephalography (rEEG) to provoke interictal epileptiform abnormalities (EAs). This study aimed to observe interictal and ictal (EAs) of different EEG patterns, provoked by various APs.

METHODOLOGY

This cross-sectional study was performed in the neurology department of King Fahd hospital of university, Saudi Arabia. The EEGs and medical records of patients who presented for EEG recordings were screened initially, then 146 EEGs provoked EAs due to utilization of APs, were included for analysis.

RESULTS

Among all EEGs with provoked EAs, Non-rapid eye movement sleep (NREM) provoked EAs in 93 (63.7%) patients with following patterns, focal spike wave discharges (FSWDs) 45 (P= 0.01), focal spike wave discharges with bilateral synchrony (FSWDBS) 27 (P=0.03) and generalized spike wave discharges (GSWDs) 46 (P=0.01). Intermittent photic stimulation (IPS) most significantly provoked FSWDs in 07 patient (P =0.01) and GSWDs in 30 patients (P=<0.001) 7 patients (P = 0.01) and GSWDs in 30 patients (P < 0.001). Hyperventilation (HV) was associated with a higher occurrence of GSWDs in 37 patients (P =0.01). Female sex 7 (P = 0.02), provoked GSWDs 3 (P = 0.03), NREM sleep 8 (P = 0.04), prolonged EEG record 3 (P = 0.02), clinical events during recording 5 (P ≤ 0.01), diagnosis of genetic 05 (P = 0.03), and immune-mediated epilepsies 2 (P = 0.001) were associated with the provocation of ictal EAs; however, in multiple logistic regression analysis, no statistically significant association of these variables (P ≥ 0.05 each) was noted.

CONCLUSION

The provocation of EAs in rEEG with different APs varies according to circumstances, including seizure types, epilepsy etiology, and the type of AP applied. These clinical and procedural parameters affect the diagnostic yield of rEEG and need careful consideration during rEEG recordings. APs adopted during rEEG recording can induce FSWDs, FSWDBS, and GSWDs in the form of either interictal or ictal EAs in various etiologies of epilepsy. Ictal EAs may appear in the form of GSWDs, during NREM sleep, in prolonged EEG records; however, their independent association needs to be evaluated in larger sample studies. Further, prospective cohort studies with adequate sample sizes are warranted.

Clinical Utility of Sleep Recordings During Presurgical Epilepsy Evaluation With Stereo-Electroencephalography: A Systematic Review

SUMMARY

Although the role of sleep in modulating epileptic activity is well established, many epileptologists overlook the significance of considering sleep during presurgical epilepsy evaluations in cases of drug-resistant epilepsy. Here, we conducted a comprehensive literature review from January 2000 to May 2023 using the PubMed electronic database and compiled evidence to highlight the need to revise the current clinical approach. All articles were assessed for eligibility by two independent reviewers. Our aim was to shed light on the clinical value of incorporating sleep monitoring into presurgical evaluations with stereo-electroencephalography. We present the latest developments on the important bidirectional interactions between sleep and various forms of epileptic activity observed in stereo-electroencephalography recordings. Specifically, epileptic activity is modulated by different sleep stages, peaking in non-rapid eye movement sleep, while being suppressed in rapid eye movement sleep. However, this modulation can vary across different brain regions, underlining the need to account for sleep to accurately pinpoint the epileptogenic zone during presurgical assessments. Finally, we offer practical solutions, such as automated sleep scoring algorithms using stereo-electroencephalography data alone, to seamlessly integrate sleep monitoring into routine clinical practice. It is hoped that this review will provide clinicians with a readily accessible roadmap to the latest evidence concerning the clinical utility of sleep monitoring in the context of stereo-electroencephalography and aid the development of therapeutic and diagnostic strategies to improve patient surgical outcomes.

Network alterations in temporal lobe epilepsy during non-rapid eye movement sleep and wakefulness

OBJECTIVE

Investigate sleep and temporal lobe epilepsy (TLE) effects on brain networks derived from electroencephalography (EEG).

METHODS

High-density EEG was recorded during non-rapid eye movement (NREM) sleep stage 2 (N2) and wakefulness in 23 patients and healthy controls (HC). Epochs without epileptic discharges were source-reconstructed in 72 brain regions and connectivity was estimated. We calculated network integration and segregation at global (global efficiency, GE; average clustering coefficient, avgCC) and hemispheric level. These were compared between groups across frequency bands and correlated with the individual proportion of wakefulness- or sleep-related seizures.

RESULTS

At the global level, patients had higher delta GE, delta avgCC and theta avgCC than controls, irrespective of the vigilance state. During wakefulness, theta GE of patients was higher than controls and, for patients, theta GE during wakefulness was higher than during N2. Wake-to-sleep differences in TLE were notable only in the ipsilateral hemisphere. Only measures from wakefulness recordings correlated with the proportion of wakefulness- or sleep-related seizures.

CONCLUSIONS

TLE network alterations are more prominent during wakefulness and at lower frequencies. Increased integration and segregation suggest a pathological 'small world' configuration with a possible inhibitory role.

SIGNIFICANCE

Network alterations in TLE occur and are easier to detect during wakefulness.

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.

Widespread slow oscillations support interictal epileptiform discharge networks in focal epilepsy

Interictal epileptiform discharges (IEDs) often co-occur across spatially-separated cortical regions, forming IED networks. However, the factors prompting IED propagation remain unelucidated. We hypothesized that slow oscillations (SOs) might facilitate IED propagation. Here, the amplitude and phase synchronization of SOs preceding propagating and non-propagating IEDs were compared in 22 patients with focal epilepsy undergoing intracranial electroencephalography (EEG) evaluation. Intracranial channels were categorized into the irritative zone (IZ) and normal zone (NOZ) regarding the presence of IEDs. During wakefulness, we found that pre-IED SOs within the IZ exhibited higher amplitudes for propagating IEDs than non-propagating IEDs (delta band: p = 0.001, theta band: p < 0.001). This increase in SOs was also concurrently observed in the NOZ (delta band: p = 0.04). Similarly, the inter-channel phase synchronization of SOs prior to propagating IEDs was higher than those preceding non-propagating IEDs in the IZ (delta band: p = 0.04). Through sliding window analysis, we observed that SOs preceding propagating IEDs progressively increased in amplitude and phase synchronization, while those preceding non-propagating IEDs remained relatively stable. Significant differences in amplitude occurred approximately 1150 ms before IEDs. During non-rapid eye movement (NREM) sleep, SOs on scalp recordings also showed higher amplitudes before intracranial propagating IEDs than before non-propagating IEDs (delta band: p = 0.006). Furthermore, the analysis of IED density around sleep SOs revealed that only high-amplitude sleep SOs demonstrated correlation with IED propagation. Overall, our study highlights that transient but widely distributed SOs are associated with IED propagation as well as generation in focal epilepsy during sleep and wakefulness, providing new insight into the EEG substrate supporting IED networks.

Visualization of the Spatiotemporal Propagation of Interictal Spikes in Temporal Lobe Epilepsy: A MEG Pilot Study

Magnetoencephalography (MEG) is clinically used to localize interictal spikes in discrete brain areas of epilepsy patients through the equivalent current dipole (ECD) method, but does not account for the temporal dynamics of spike activity. Recent studies found that interictal spike propagation beyond the temporal lobe may be associated with worse postsurgical outcomes, but studies using whole-brain data such as in MEG remain limited. In this pilot study, we developed a tool that visualizes the spatiotemporal dynamics of interictal MEG spikes normalized to spike-free sleep activity to assess their onset and propagation patterns in patients with temporal lobe epilepsy (TLE). We extracted interictal source data containing focal epileptiform activity in awake and asleep states from seven patients whose MEG ECD clusters localized to the temporal lobe and normalized the data against spike-free sleep recordings. We calculated the normalized activity over time per cortical label, confirmed maximal activity at onset, and mapped the activity over a 10 ms interval onto each patient's brain using a custom-built Multi-Modal Visualization Tool. The onset of activity in all patients appeared near the clinically determined epileptogenic zone. By 10 ms, four of the patients had propagated source activity restricted to within the temporal lobe, and three had propagated source activity spread to extratemporal regions. Using this tool, we show that noninvasively identifying the onset and propagation of interictal spike activity in MEG can be achieved, which may help provide further insight into epileptic networks and guide surgical planning and interventions in patients with TLE.

Rapid eye movement sleep affects interictal epileptic activity differently in mesiotemporal and neocortical areas

OBJECTIVE

Rapid eye movement (REM) sleep reduces the rate and extent of interictal epileptiform discharges (IEDs). Breakthrough epileptic activity during REM sleep is therefore thought to best localize the seizure onset zone (SOZ). We utilized polysomnography combined with direct cortical recordings to investigate the influences of anatomical locations and the time of night on the suppressive effect of REM sleep on IEDs.

METHODS

Forty consecutive patients with drug-resistant focal epilepsy underwent combined polysomnography and stereo-electroencephalography during presurgical evaluation. Ten-minute interictal epochs were selected 2 h prior to sleep onset (wakefulness), and from the first and second half of the night during non-REM (NREM) sleep and REM sleep. IEDs were detected automatically across all channels. Anatomic localization, time of night, and channel type (within or outside the SOZ) were tested as modulating factors.

RESULTS

Relative to wakefulness, there was a suppression of IEDs by REM sleep in neocortical regions (median = -27.6%), whereas mesiotemporal regions showed an increase in IEDs (19.1%, p = .01, d = .39). This effect was reversed when comparing the regional suppression of IEDs by REM sleep relative to NREM sleep (-35.1% in neocortical, -58.7% in mesiotemporal, p < .001, d = .39). Across all patients, no clinically relevant novel IED regions were observed in REM sleep versus NREM or wakefulness based on our predetermined thresholds (4 IEDs/min in REM, 0 IEDs/min in NREM and wakefulness). Finally, there was a reduction in IEDs in late (NREM: 1.08/min, REM: .61/min) compared to early sleep (NREM: 1.22/min, REM: .69/min) for both NREM (p < .001, d = .21) and REM (p = .04, d = .14).

SIGNIFICANCE

Our results demonstrate a spatiotemporal effect of IED suppression by REM sleep relative to wakefulness in neocortical but not mesiotemporal regions, and in late versus early sleep. This suggests the importance of considering sleep stage interactions and the potential influences of anatomical locations when using IEDs to define the epileptic focus.

Sleep and epilepsy: A clinical and pathophysiological overview

The interaction between sleep and epilepsy is complex. A better understanding of the mechanisms linking sleep and epilepsy appears increasingly important as it may improve diagnosis and therapeutic strategies in patients with epilepsy. In this narrative review, we aim to (i) provide an overview of the physiological and pathophysiological processes linking sleep and epilepsy; (ii) present common sleep disorders in patients with epilepsy; (iii) discuss how sleep and sleep disorders should be considered in new therapeutic approaches to epilepsy such as neurostimulation; and (iv) present the overall nocturnal manifestations and differential diagnosis between epileptic seizures and parasomnia.

The Differing Effects of Sleep on Ictal and Interictal Network Dynamics in Drug-Resistant Epilepsy

OBJECTIVE

Sleep has important influences on focal interictal epileptiform discharges (IEDs), and the rates and spatial extent of IEDs are increased in non-rapid eye movement (NREM) sleep. In contrast, the influence of sleep on seizures is less clear, and its effects on seizure topography are poorly documented. We evaluated the influences of NREM sleep on ictal spatiotemporal dynamics and contrasted these with interictal network dynamics.

METHODS

We included patients with drug-resistant focal epilepsy who underwent continuous intracranial electroencephalography (iEEG) with depth electrodes. Patients were selected if they had 1 to 3 seizures from each vigilance state, wakefulness and NREM sleep, within a 48-hour window, and under the same antiseizure medication. A 10-minute epoch of the interictal iEEG was selected per state, and IEDs were detected automatically. A total of 25 patients (13 women; aged 32.5 ± 7.1 years) were included.

RESULTS

The seizure onset pattern, duration, spatiotemporal propagation, and latency of ictal high-frequency activity did not differ significantly between wakefulness and NREM sleep (all p > 0.05). In contrast, IED rates and spatial distribution were increased in NREM compared with wakefulness (p < 0.001, Cliff's d = 0.48 and 0.49). The spatial overlap between vigilance states was higher for seizures (57.1 ± 40.1%) than IEDs (41.7 ± 46.2%; p = 0.001, Cliff's d = 0.51).

INTERPRETATION

In contrast to its effects on IEDs, NREM sleep does not affect ictal spatiotemporal dynamics. This suggests that once the brain surpasses the seizure threshold, it will follow the underlying epileptic network irrespective of the vigilance state. These findings offer valuable insights into neural network dynamics in epilepsy and have important clinical implications for localizing seizure foci. ANN NEUROL 2023.

Progressive sleep disturbance in various transgenic mouse models of Alzheimer's disease

Alzheimer's disease (AD) is the leading cause of dementia. The relationship between AD and sleep dysfunction has received increased attention over the past decade. The use of genetically engineered mouse models with enhanced production of amyloid beta (Aβ) or hyperphosphorylated tau has played a critical role in the understanding of the pathophysiology of AD. However, their revelations regarding the progression of sleep impairment in AD have been highly dependent on the mouse model used and the specific techniques employed to examine sleep. Here, we discuss the sleep disturbances and general pathology of 15 mouse models of AD. Sleep disturbances covered in this review include changes to NREM and REM sleep duration, bout lengths, bout counts and power spectra. Our aim is to describe in detail the severity and chronology of sleep disturbances within individual mouse models of AD, as well as reveal broader trends of sleep deterioration that are shared among most models. This review also explores a variety of potential mechanisms relating Aβ accumulation and tau neurofibrillary tangles to the progressive deterioration of sleep observed in AD. Lastly, this review offers perspective on how study design might impact our current understanding of sleep disturbances in AD and provides strategies for future research.

Interictal epileptiform discharges affect memory in an Alzheimer's Disease mouse model

Interictal epileptiform discharges (IEDs) are transient abnormal electrophysiological events commonly observed in epilepsy patients but are also present in other neurological disease, such as Alzheimer's Disease (AD). Understanding the role IEDs have on the hippocampal circuit is important for our understanding of the cognitive deficits seen in epilepsy and AD. We characterize and compare the IEDs of human epilepsy patients from microwire hippocampal recording with those of AD transgenic mice with implanted multi-layer hippocampal silicon probes. Both the local field potential features and firing patterns of pyramidal cells and interneurons were similar in mouse and human. We found that as IEDs emerged from the CA3-1 circuits, they recruited pyramidal cells and silenced interneurons, followed by post-IED suppression. IEDs suppressed the incidence and altered the properties of physiological sharp-wave ripples (SPW-Rs), altered their physiological properties, and interfered with the replay of place field sequences in a maze. In addition, IEDs in AD mice inversely correlated with daily memory performance. Together, our work implicates that IEDs may present a common and epilepsy-independent phenomenon in neurodegenerative diseases that perturbs hippocampal-cortical communication and interferes with memory.

Significant Statement

Prevalence of neurodegenerative diseases and the number of people with dementia is increasing steadily. Therefore, novel treatment strategies for learning and memory disorders are urgently necessary. IEDs, apart from being a surrogate for epileptic brain regions, have also been linked to cognitive decline. Here we report that IEDs in human epilepsy patients and AD mouse models have similar local field potential characteristics and associated firing patterns of pyramidal cells and interneurons. Mice with more IEDs displayed fewer hippocampal SPW-Rs, poorer replay of spatial trajectories, and decreased memory performance. IED suppression is an unexplored target to treat cognitive dysfunction in neurodegenerative diseases.

Interictal Functional Connectivity in Focal Refractory Epilepsies Investigated by Intracranial EEG

Introduction: Focal epilepsies are diseases of neuronal excitability affecting macroscopic networks of cortical and subcortical neural structures. These networks ("epileptogenic networks") can generate pathological electrophysiological activities during seizures, and also between seizures (interictal period). Many works attempt to describe these networks by using quantification methods, particularly based on the estimation of statistical relationships between signals produced by brain regions, namely functional connectivity (FC). Results: FC has been shown to be greatly altered during seizures and in the immediate peri-ictal period. An increasing number of studies have shown that FC is also altered during the interictal period depending on the degree of epileptogenicity of the structures. Furthermore, connectivity values could be correlated with other clinical variables including surgical outcome. Significance: This leads to a conceptual change and to consider epileptic areas as both hyperexcitable and abnormally connected. These data open the door to the use of interictal FC as a marker of epileptogenicity and as a complementary tool for predicting the effect of surgery. Aim: In this article, we review the available data concerning interictal FC estimated from intracranial electroencephalograhy (EEG) in focal epilepsies and discuss it in the light of data obtained from other modalities (EEG imaging) and modeling studies.

Thalamic stereoelectroencephalography in epilepsy surgery: a scoping literature review

OBJECTIVE

Stereoelectroencephalography (sEEG) is a well-established surgical method for defining the epileptogenic network. Traditionally reserved for identifying discrete cortical regions for resection or ablation, sEEG in current practice is also used for identifying more broadly involved subcortical epileptic network components, driven by the availability of brain-based neuromodulation strategies. In particular, sEEG investigations including thalamic nuclei are becoming more frequent in parallel with the increase in therapeutic strategies involving thalamic targets such as deep brain stimulation (DBS) and responsive neurostimulation (RNS). The objective to this study was to evaluate existing evidence and trends regarding the purpose, techniques, and relevant electrographic findings of thalamic sEEG.

METHODS

MEDLINE and Embase databases were systematically queried for eligible peer-reviewed studies involving sEEG electrode implantation into thalamic nuclei of patients with epilepsy. Available data were abstracted concerning preoperative workup and purpose for implanting the thalamus, thalamic targets and trajectories, and electrophysiological methodology and findings.

RESULTS

sEEG investigations have included thalamic targets for both basic and clinical research purposes. Medial pulvinar, dorsomedial, anterior, and centromedian nuclei have been the most frequently studied. Few studies have reported any complications with thalamic sEEG implantation, and no studies have reported long-term complications. Various methods have been utilized to characterize thalamic activity in epileptic disorders including evoked potentials, power spectrograms, synchronization indices, and the epileptogenicity index. Thalamic intracranial recordings are beginning to be used to guide neuromodulation strategies including RNS and DBS, as well as to understand complex, network-dependent seizure disorders.

CONCLUSIONS

Inclusion of thalamic coverage during sEEG evaluation in drug-resistant epilepsy is a growing practice and is amenable to various methods of electrographic data analysis. Further study is required to establish well-defined criteria for thalamic implantation during invasive investigations as well as safety and ethical considerations.

Late-onset seizures and epilepsy: Electroclinical features suggestive of autoimmune etiology

Introduction

Late-onset epilepsy (LOE) has recently become a topic of intense research. Besides stroke, tumors, and dementia, autoimmune encephalitis (AE) has emerged as another possible cause of recurrent seizures in the elderly, and may account for a proportion of cases of LOE of unknown origin (LOEUO). This 24-h ambulatory electroencephalography (AEEG)-based study compared patients with LOEUO and AE to identify features suggestive of immune-mediated seizures in the elderly.

Materials and methods

We retrospectively reviewed 232 AEEG examinations performed in patients over 55 years with ≥6-month follow-up, and selected 21 subjects with AE and 25 subjects with LOEUO. Clinical charts and AEEG recordings were carefully analyzed.

Results

Twenty-five patients with LOEUO (12 women, mean age at onset 67.9 years) and 21 AE subjects (8 women, mean age at onset 65.7 years) were enrolled. High-frequency seizures were reported in 20/21 AE and 7/25 LOEUO cases (p < 0.00001). Focal aware seizures were more common in AE (14/21 vs. 6/25, p = 0.00058), whereas “isolated” focal-to-bilateral tonic-clonic seizures occurred in 5/25 patients with LOEUO only (p = 0.053). AE subjects reported ictal autonomic manifestations more frequently (p = 0.0033). Three-hundred-seventy and 24 seizures were recorded in 13/21 patients with AE and 3/25 patients with LOEUO, respectively (p = 0.0006). Interictal epileptiform discharges were observed in 70% of both groups, but their sleep activation was more common in AE (p = 0.06).

Conclusion

Our study shows that high-frequency focal seizures with autonomic manifestations should raise the suspicion of AE in the elderly with new-onset seizures. It also highlights the relevant contribution of AEEG, which might reduce the diagnostic delay and provide useful clues to recognize AE.

Interictal epileptiform discharges show distinct spatiotemporal and morphological patterns across wake and sleep

Presurgical evaluation of mesial temporal and neocortical focal pharmacoresistant epilepsy patients using intracranial EEG recordings has led to the generation of extensive data on interictal epileptiform discharges, located within or remotely from seizure onset zones. In this study, we used this data to investigate how interictal epileptiform discharges are modulated and how their spatial distribution changes during wake and sleep and analysed the relationship between these discharge events and seizure onset zones. Preoperative evaluation data from 11 adult patients with focal pharmacoresistant epilepsy were extracted from the Epilepsiae database. Interictal epileptiform discharges were automatically detected during wakefulness and over several hours of continuous seizure-free sleep (total duration of EEG recordings:106.7 h; mean per patient: 9.7 h), and analysed across four brain areas (mesial temporal, lateral neocortical, basal cortical and the temporal pole). Sleep stages were classified manually from scalp EEG. Discharge events were characterized according to their rate and morphology (amplitude, sharpness and duration). Eight patients had a seizure onset zone over mesial areas and three patients over lateral neocortical areas. Overall, discharge rates varied across brain areas during wakefulness and sleep [wake/sleep stages × brain areas interaction; Wald χ 2(df = 6) = 31.1, P < 0.0001]. N2-N3 non-rapid eye movement sleep increased interictal epileptiform discharges in mesial areas compared with wakefulness and rapid eye movement sleep (P < 0.0001), and to other areas (P < 0.0001 for all comparisons). This mesial pattern was observed both within and outside of seizure onset zones. During wakefulness, the rate of interictal epileptiform discharges was significantly higher than during N2-N3 non-rapid eye movement sleep (P = 0.04), and rapid eye movement sleep (P = 0.01) in lateral neocortical areas (referred to as lateral neocortical pattern), a finding that was more pronounced in seizures onset zones (P = 0.004). The morphological characteristics of the discharge events were modulated during wakefulness and sleep stages across brain areas. The effect of seizure onset zones on discharge morphology was conditioned by brain area and was particularly marked in temporal pole areas. Our analysis of discharge patterns in relation to cerebral localization, vigilance state and the anatomical affiliation of seizure onset zones revealed the global and local aspects of the complex relationship between interictal discharges, sleep and seizure onset zones. This novel approach may lead to a better understanding of cognitive decline and responses to therapy, as well as to adaptation of surgical interventions for epileptic patients.

Sleep and epilepsy: A snapshot of knowledge and future research lines

Sleep and epilepsy have a reciprocal relationship, and have been recognized as bedfellows since antiquity. However, research on this topic has made a big step forward only in recent years. In this narrative review we summarize the most stimulating discoveries and insights reached by the "European school." In particular, different aspects concerning the sleep-epilepsy interactions are analysed: (a) the effects of sleep on epilepsy; (b) the effects of epilepsy on sleep structure; (c) the relationship between epilepsy, sleep and epileptogenesis; (d) the impact of epileptic activity during sleep on cognition; (e) the relationship between epilepsy and the circadian rhythm; (f) the history and features of sleep hypermotor epilepsy and its differential diagnosis; (g) the relationship between epilepsy and sleep disorders.

Epileptic seizures and link to memory processes

Epileptogenesis is a complex and not well understood phenomenon. Here, we explore the hypothesis that epileptogenesis could be "hijacking" normal memory processes, and how this hypothesis may provide new directions for epilepsy treatment. First, we review similarities between the hypersynchronous circuits observed in epilepsy and memory consolidation processes involved in strengthening neuronal connections. Next, we describe the kindling model of seizures and its relation to long-term potentiation model of synaptic plasticity. We also examine how the strengthening of epileptic circuits is facilitated during the physiological slow wave sleep, similarly as episodic memories. Furthermore, we present studies showing that specific memories can directly trigger reflex seizures. The neuronal hypersynchrony in early stages of Alzheimer's disease, and the use of anti-epileptic drugs to improve the cognitive symptoms in this disease also suggests a connection between memory systems and epilepsy. Given the commonalities between memory processes and epilepsy, we propose that therapies for memory disorders might provide new avenues for treatment of epileptic patients.

Interictal Spike and Loss of Hippocampal Theta Rhythm Recorded by Deep Brain Electrodes during Epileptogenesis

Epileptogenesis is the gradual dynamic process that progressively led to epilepsy, going through the latent stage to the chronic stage. During epileptogenesis, how the abnormal discharges make theta rhythm loss in the deep brain remains not clear. In this paper, a loss of theta rhythm was estimated based on time–frequency power using the longitudinal electroencephalography (EEG), recorded by deep brain electrodes (e.g., the intracortical microelectrodes such as stereo-EEG electrodes) with monitored epileptic spikes in a rat from the first region in the hippocampal circuit. Deep-brain EEG was collected from the period between adjacent sporadic interictal spikes (lasting 3.56 s—35.38 s) to the recovery period without spikes by videos while the rats were performing exploration. We found that loss of theta rhythm became more serious during the period between adjacent interictal spikes than during the recovery period without spike, and during epileptogenesis, more loss was observed at the acute stage than the chronic stage. We concluded that the emergence of the interictal spike was the direct cause of loss of theta rhythm, and the inhibitory effect of the interictal spike on ongoing theta rhythm was persistent as well as time dependent during epileptogenesis. With the help of the intracortical microelectrodes, this study provides a temporary proof of interictal spikes to produce ongoing theta rhythm loss, suggesting that the interictal spikes could correlate with the epileptogenesis process, display a time-dependent feature, and might be a potential biomarker to evaluate the deficits in theta-related memory in the brain.

Global and intertuberal epileptic networks in tuberous sclerosis based on stereoelectroencephalographic (sEEG) findings: a quantitative EEG analysis in pediatric subjects and surgical implications

OBJECTIVE

Recent evidence favors a network concept in tuberous sclerosis (TSC) with seizure generation and propagation related to changes in global and regional connectivity between multiple, anatomically distant tubers. Direct exploration of network dynamics in TSC has been made possible through intracranial sampling with stereoelectroencephalography (sEEG). The objective of this study is to define epileptic networks in TSC using quantitative analysis of sEEG recordings. We also discuss the impact of the definition of these epileptic networks on surgical decision-making.

METHODS

Intracranial sEEG recordings were obtained from four pediatric patients who presented with medically refractory epilepsy secondary to TSC and subjected to quantitative signal analysis methods. Cortical connectivity was quantified by calculating pairwise coherence between all contacts and constructing an association matrix. The global coherence, defined as the ratio of the largest eigenvalue to the sum of all the eigenvalues, was calculated for each frequency band (delta, theta, alpha, beta, gamma). Spatial distribution of the connectivity was identified by plotting the leading principal component (product of the largest eigenvalue and its corresponding eigenvector).

RESULTS

Four pediatric subjects with TSC underwent invasive intracranial monitoring with sEEG, comprising 31 depth electrodes and 250 contacts, for localization of the epileptogenic focus and guidance of subsequent surgical intervention. Quantitative connectivity analysis revealed a change in global coherence during the ictal period in the beta/low gamma (14-30 Hz) and high gamma (31-80 Hz) bands. Our results corroborate findings from existing literature, which implicate higher frequencies as a driver of synchrony and desynchrony.

CONCLUSIONS

Coordinated high-frequency activity in the beta/low gamma and high gamma bands among spatially distant sEEG define the ictal period in TSC. This time-dependent change in global coherence demonstrates evidence for intra-tuberal and inter-tuberal connectivity in TSC. This observation has surgical implications. It suggests that targeting multiple tubers has a higher chance of seizure control as there is a higher chance of disrupting the epileptic network. The use of laser interstitial thermal therapy (LITT) allowed us to target multiple disparately located tubers in a minimally invasive manner with good seizure control outcomes.

Dynamics of hippocampus and orbitofrontal cortex activity during arousing reactions from sleep: An intracranial electroencephalographic study

Sleep is punctuated by transient elevations of vigilance level called arousals or awakenings depending on their durations. Understanding the dynamics of brain activity modifications during these transitional phases could help to better understand the changes in cognitive functions according to vigilance states. In this study, we investigated the activity of memory‐related areas (hippocampus and orbitofrontal cortex) during short (3 s to 2 min) arousing reactions detected from thalamic activity, using intracranial recordings in four drug‐resistant epilepsy patients. The average power of the signal between 0.5 and 128 Hz was compared across four time windows: 10 s of preceding sleep, the first part and the end of the arousal/awakening, and 10 s of wakefulness. We observed that (a) in most frequency bands, the spectral power during hippocampal arousal/awakenings is intermediate between wakefulness and sleep whereas frontal cortex shows an early increase in low and fast activities during non‐rapid‐eye‐movement (NREM) sleep arousals/awakenings; (b) this pattern depends on the preceding sleep stage with fewer modifications for REM than for non‐REM sleep arousal/awakenings, potentially reflecting the EEG similarities between REM sleep and wakefulness; (c) a greater activation at the arousing reaction onset in the prefrontal cortex predicts longer arousals/awakenings. Our findings suggest that hippocampus and prefrontal arousals/awakenings are progressive phenomena modulated by sleep stage, and, in the neocortex, by the intensity of the early activation. This pattern of activity could underlie the link between sleep stage, arousal/awakening duration and restoration of memory abilities including dream recall.

On the influence of prior information evaluated by fully Bayesian criteria in a personalized whole-brain model of epilepsy spread

Individualized anatomical information has been used as prior knowledge in Bayesian inference paradigms of whole-brain network models. However, the actual sensitivity to such personalized information in priors is still unknown. In this study, we introduce the use of fully Bayesian information criteria and leave-one-out cross-validation technique on the subject-specific information to assess different epileptogenicity hypotheses regarding the location of pathological brain areas based on a priori knowledge from dynamical system properties. The Bayesian Virtual Epileptic Patient (BVEP) model, which relies on the fusion of structural data of individuals, a generative model of epileptiform discharges, and a self-tuning Monte Carlo sampling algorithm, is used to infer the spatial map of epileptogenicity across different brain areas. Our results indicate that measuring the out-of-sample prediction accuracy of the BVEP model with informative priors enables reliable and efficient evaluation of potential hypotheses regarding the degree of epileptogenicity across different brain regions. In contrast, while using uninformative priors, the information criteria are unable to provide strong evidence about the epileptogenicity of brain areas. We also show that the fully Bayesian criteria correctly assess different hypotheses about both structural and functional components of whole-brain models that differ across individuals. The fully Bayesian information-theory based approach used in this study suggests a patient-specific strategy for epileptogenicity hypothesis testing in generative brain network models of epilepsy to improve surgical outcomes.

Measuring the effects of sleep on epileptogenicity with multifrequency entropy

OBJECTIVE

We demonstrate that multifrequency entropy gives insight into the relationship between epileptogenicity and sleep, and forms the basis for an improved measure of medical assessment of sleep impairment in epilepsy patients.

METHODS

Multifrequency entropy was computed from electroencephalography measurements taken from 31 children with Benign Epilepsy with Centrotemporal Spikes and 31 non-epileptic controls while awake and during sleep. Values were compared in the epileptic zone and away from the epileptic zone in various sleep stages.

RESULTS

We find that (I) in lower frequencies, multifrequency entropy decreases during non-rapid eye movement sleep stages when compared with wakefulness in a general population of pediatric patients, (II) patients with Benign Epilepsy with Centrotemporal Spikes had lower multifrequency entropy across stages of sleep and wakefulness, and (III) the epileptic regions of the brain exhibit lower multifrequency entropy patterns than the rest of the brain in epilepsy patients.

CONCLUSIONS

Our results show that multifrequency entropy decreases during sleep, particularly sleep stage 2, confirming, in a pediatric population, an association between sleep, lower multifrequency entropy, and increased likelihood of seizure.

SIGNIFICANCE

We observed a correlation between lowered multifrequency entropy and increased epileptogenicity that lays preliminary groundwork for the detection of a digital biomarker for epileptogenicity.

Localization of interictal discharge origin: A simultaneous intracranial electroencephalographic-functional magnetic resonance imaging study

OBJECTIVE

Scalp electroencephalographic (EEG)-functional magnetic resonance imaging (fMRI) studies suggest that the maximum blood oxygen level-dependent (BOLD) response to an interictal epileptiform discharge (IED) identifies the area of IED generation. However, the maximum BOLD response has also been reported in distant, seemingly irrelevant areas. Given the poor postoperative outcomes associated with extra-temporal lobe epilepsy, we hypothesized this finding is more common when analyzing extratemporal IEDs as compared to temporal IEDs. We further hypothesized that a subjective, holistic assessment of other significant BOLD clusters to identify the most clinically relevant cluster could be used to overcome this limitation and therefore better identify the likely origin of an IED. Specifically, we also considered the second maximum cluster and the cluster closest to the electrode contacts where the IED was observed.

METHODS

Maps of significant IED-related BOLD activation were generated for 48 different IEDs recorded from 33 patients who underwent intracranial EEG-fMRI. The locations of the maximum, second maximum, and closest clusters were identified for each IED. An epileptologist, blinded to these cluster assignments, selected the most clinically relevant BOLD cluster, taking into account all available clinical information. The distances between these BOLD clusters and their corresponding IEDs were then measured.

RESULTS

The most clinically relevant cluster was the maximum cluster for 56% (27/48) of IEDs, the second maximum cluster for 13% (6/48) of IEDs, and the closest cluster for 31% (15/48) of IEDs. The maximum clusters were closer to IED contacts for temporal than for extratemporal IEDs (p = .022), whereas the most clinically relevant clusters were not significantly different (p = .056).

SIGNIFICANCE

The maximum BOLD response to IEDs may not always be the most indicative of IED origin. We propose that available clinical information should be used in conjunction with EEG-fMRI data to identify a BOLD cluster representative of the IED origin.

Absolute spike frequency and different comorbidities in temporal lobe epilepsy

OBJECTIVE

The objective of this study was to examine if the absolute number of interictal epileptiform discharges (IED) is related to the presence of different comorbidities and refractivity in patients with temporal lobe epilepsy.

METHODS

Analysis with scalp EEG of the IED of 30 patients with temporal epilepsy. The analysis was performed in three selected periods of the record during N2-N3 sleep. We analyzed the number of IED and the sum of the values obtained in the three selected segments to determine the absolute interictal spike frequency.

RESULTS

The number of IED for patients varied from 11 to 450. The absolute interictal spike frequency showed a statistically significant relation with the presence of refractivity (p < 0.05), and neurological and/or psychiatric comorbidity (p < 0.05). Patients with an absolute interictal spike frequency ≤ 60 showed little refractoriness and no comorbidity. Patients with an absolute interictal spike frequency > 60 were mostly refractory and with neurological and/or psychiatric comorbidity. No significant relation was found of absolute interictal spike frequency with age at the onset of epilepsy, number of anticonvulsant drugs used, or base pathology (MRI).

CONCLUSIONS

The absolute interictal spike frequency is capable of differentiating patients with temporal lobe epilepsy, identifying those with temporal lobe epilepsy according to the severity of the condition. Only those patients with non-frequent spikes (≤60 over the affected temporal lobe) have a low percentage of refractoriness with little or no presence of comorbidity.

Chance and risk in epilepsy

PURPOSE OF REVIEW

Epilepsy is a dynamical disorder of the brain characterized by sudden, seemingly unpredictable transitions to the ictal state. When and how these transitions occur remain unresolved questions in neurology.

RECENT FINDINGS

Modelling work based on dynamical systems theory proposed that a slow control parameter is necessary to explain the transition between interictal and ictal states. Recently, converging evidence from chronic EEG datasets unravelled the existence of cycles of epileptic brain activity at multiple timescales - circadian, multidien (over multiple days) and circannual - which could reflect cyclical changes in a slow control parameter. This temporal structure of epilepsy has theoretical implications and argues against the conception of seizures as completely random events. The practical significance of cycles in epilepsy is highlighted by their predictive value in computational models for seizure forecasting.

SUMMARY

The canonical randomness of seizures is being reconsidered in light of cycles of brain activity discovered through chronic EEG. This paradigm shift motivates development of next-generation devices to track more closely fluctuations in epileptic brain activity that determine time-varying seizure risk.

Accelerated long-term forgetting in focal epilepsy: Do interictal spikes during sleep matter?

Accelerated long-term forgetting (ALF) is a particular form of amnesia mostly encountered in focal epilepsy, particularly in temporal lobe epilepsy. This type of memory loss is characterized by an impairment of long-term consolidation of declarative memory, and its mechanisms remain poorly understood. In particular, the respective contribution of lesion, seizures, interictal epileptic discharges, and sleep is still debated. Here, we provide an overview of the relationships intertwining epilepsy, sleep, and memory consolidation and, based on recent findings from intracranial electroencephalographic recordings, we propose a model of ALF pathophysiology that integrates the differential role of interictal spikes during wakefulness and sleep. This model provides a framework to account for the different timescales at which ALF may occur.

Seizures in autoimmune encephalitis: Findings from an EEG pooled analysis

PURPOSE

Seizures are common in autoimmune encephalitis (AE), and an extensive work-up is required to exclude alternative etiologies. The aim of our study was to identify possible clinical/EEG peculiarities suggesting the immune-mediated origin of late-onset seizures.

METHODS

Thirty patients diagnosed with AE (19 men, median age 68 years, 18 seronegative) were included. Overall 212 video-electroencephalographic (EEG) and 31 24-h ambulatory EEG (AEEG) recordings were retrospectively reviewed. Posterior dominant rhythm, interictal epileptiform discharges (IEDs), clinical (CSs) and subclinical seizures (SCSs) were analyzed.

RESULTS

Six-hundred-nineteen ictal events were recorded in 19/30 subjects, mostly (568/619) during AE acute stage. Among ten patients with CSs other than faciobrachial dystonic seizures, 7 showed prominent autonomic and emotional manifestations. SCSs were detected in 11 subjects, mainly via AEEG (260/287 SCSs vs 150/332 CSs, p < 0.001). Eight patients presented seizures during hyperventilation. IEDs, documented in 21 cases, were bilateral in 14 and focal temporal in 13. Multiple ictal EEG patterns were detected in 9/19 patients, 6 of whom had both CSs and SCSs, bilateral asynchronous seizures and ictal activities arising from temporal and extra-temporal regions. No correlation was found between the lateralization of MRI alterations and that of EEG findings.

CONCLUSION

Our study confirms that adult-onset, high frequency focal seizures with prominent autonomic and emotional manifestations should be investigated for AE. Multiple ictal EEG patterns could represent a 'red flag', reflecting a widespread neuronal excitability related to the underlying immune-mediated process. Finally, our work enhances the crucial role of long-lasting EEG monitoring in revealing subclinical and relapsing seizures.

Local Sleep Slow-Wave Activity Colocalizes With the Ictal Symptomatogenic Zone in a Patient With Reflex Epilepsy: A High-Density EEG Study

Background: Slow-wave activity (SWA) during non-rapid eye movement (NREM) sleep reflects synaptic potentiation during preceding wakefulness. Epileptic activity may induce increases in state-dependent SWA in human brains, therefore, localization of SWA may prove useful in the presurgical workup of epileptic patients. We analyzed high-density electroencephalography (HDEEG) data across vigilance states from a reflex epilepsy patient with a clearly localizable ictal symptomatogenic zone to provide a proof-of-concept for the testability of this hypothesis.

Methods: Overnight HDEEG recordings were obtained in the patient during REM sleep, NREM sleep, wakefulness, and during a right facial motor seizure then compared to 10 controls. After preprocessing, SWA (i.e., delta power; 1–4 Hz) was calculated at each channel. Scalp level and source reconstruction analyses were computed. We assessed for statistical differences in maximum SWA between the patient and controls within REM sleep, NREM sleep, wakefulness, and seizure. Then, we completed an identical statistical comparison after first subtracting intrasubject REM sleep SWA from that of NREM sleep, wakefulness, and seizure SWA.

Results: The topographical analysis revealed greater left hemispheric SWA in the patient vs. controls in all vigilance states except REM sleep (which showed a right hemispheric maximum). Source space analysis revealed increased SWA in the left inferior frontal cortex during NREM sleep and wakefulness. Ictal data displayed poor source-space localization. Comparing each state to REM sleep enhanced localization accuracy; the most clearly localizing results were observed when subtracting REM sleep from wakefulness.

Conclusion: State-dependent SWA during NREM sleep and wakefulness may help to identify aspects of the potential epileptogenic zone. Future work in larger cohorts may assess the clinical value of sleep SWA to help presurgical planning.

The Bayesian Virtual Epileptic Patient: A probabilistic framework designed to infer the spatial map of epileptogenicity in a personalized large-scale brain model of epilepsy spread

Despite the importance and frequent use of Bayesian frameworks in brain network modeling for parameter inference and model prediction, the advanced sampling algorithms implemented in probabilistic programming languages to overcome the inference difficulties have received relatively little attention in this context. In this technical note, we propose a probabilistic framework, namely the Bayesian Virtual Epileptic Patient (BVEP), which relies on the fusion of structural data of individuals to infer the spatial map of epileptogenicity in a personalized large-scale brain model of epilepsy spread. To invert the individualized whole-brain model employed in this study, we use the recently developed algorithms known as No-U-Turn Sampler (NUTS) as well as Automatic Differentiation Variational Inference (ADVI). Our results indicate that NUTS and ADVI accurately estimate the degree of epileptogenicity of brain regions, therefore, the hypothetical brain areas responsible for the seizure initiation and propagation, while the convergence diagnostics and posterior behavior analysis validate the reliability of the estimations. Moreover, we illustrate the efficiency of the transformed non-centered parameters in comparison to centered form of parameterization. The Bayesian framework used in this work proposes an appropriate patient-specific strategy for estimating the epileptogenicity of the brain regions to improve outcome after epilepsy surgery.

Hippocampal Interictal Spikes during Sleep Impact Long-Term Memory Consolidation

OBJECTIVE

Non-rapid eye movement (NREM) sleep is supposed to play a key role in long-term memory consolidation transferring information from hippocampus to neocortex. However, sleep also activates epileptic activities in medial temporal regions. This study investigated whether interictal hippocampal spikes during sleep would impair long-term memory consolidation.

METHOD

We prospectively measured visual and verbal memory performance in 20 patients with epilepsy investigated with stereoelectroencephalography (SEEG) at immediate, 30-minute, and 1-week delays, and studied the correlations between interictal hippocampal spike frequency during waking and the first cycle of NREM sleep and memory performance, taking into account the number of seizures occurring during the consolidation period and other possible confounding factors, such as age and epilepsy duration.

RESULTS

Retention of verbal memory over 1 week was negatively correlated with hippocampal spike frequency during sleep, whereas no significant correlation was found with hippocampal interictal spikes during waking. No significant result was found for visual memory. Regression tree analysis showed that the number of seizures was the first factor that impaired the verbal memory retention between 30 minutes and 1 week. When the number of seizures was below 5, spike frequency during sleep higher than 13 minutes was associated with impaired memory retention over 1 week.

INTERPRETATION

Our results show that activation of interictal spikes in the hippocampus during sleep and seizures specifically impair long-term memory consolidation. We hypothesize that hippocampal interictal spikes during sleep interrupt hippocampal-neocortical transfer of information. ANN NEUROL 2020;87:976-987.

Quantitative spatio-temporal characterization of epileptic spikes using high density EEG: Differences between NREM sleep and REM sleep

In this study, we applied high-density EEG recordings (HD-EEG) to quantitatively characterize the fine-grained spatiotemporal distribution of inter-ictal epileptiform discharges (IEDs) across different sleep stages. We quantified differences in spatial extent and duration of IEDs at the scalp and cortical levels using HD-EEG source-localization, during non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep, in six medication-refractory focal epilepsy patients during epilepsy monitoring unit admission. Statistical analyses were performed at single subject level and group level across different sleep stages for duration and distribution of IEDs. Tests were corrected for multiple comparisons across all channels and time points. Compared to NREM sleep, IEDs during REM sleep were of significantly shorter duration and spatially more restricted. Compared to NREM sleep, IEDs location in REM sleep also showed a higher concordance with electrographic ictal onset zone from scalp EEG recording. This study supports the localizing value of REM IEDs over NREM IEDs and suggests that HD-EEG may be of clinical utility in epilepsy surgery work-up.

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset

The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.

Are high-frequency oscillations better biomarkers of the epileptogenic zone than spikes?

PURPOSE OF REVIEW

Precise localization of the epileptogenic zone is imperative for the success of resective surgery of drug-resistant epileptic patients. To decrease the number of surgical failures, clinical research has been focusing on finding new biomarkers. For the past decades, high-frequency oscillations (HFOs, 80-500 Hz) have ousted interictal spikes - the classical interictal marker - from the research spotlight. Many studies have claimed that HFOs were more linked to epileptogenicity than spikes. This present review aims at refining this statement in light of recent studies.

RECENT FINDINGS

Analysis based on single-patient characteristics has not been able to determine which of HFOs or spikes were better marker of epileptogenic tissues. Physiological HFOs are one of the main obstacles to translate HFOs to clinical practice as separating them from pathological HFOs remains a challenge. Fast ripples (a subgroup of HFOs, 250-500 Hz) which are mostly pathological are not found in all epileptogenic tissues.

SUMMARY

Quantified measures of HFOs and spikes give complementary results, but many barriers still persist in applying them in clinical routine. The current way of testing HFO and spike detectors and their performance in delineating the epileptogenic zone is debatable and still lacks practicality. Solutions to handle physiological HFOs have been proposed but are still at a preliminary stage.

Quantitative determination of concordance in localizing epileptic focus by component-based EEG-fMRI

BACKGROUND AND OBJECTIVE

Accurate seizure onset zone (SOZ) localization is an essential step in pre-surgical assessment of patients with refractory focal epilepsy. Complex pathophysiology of epileptic cerebral structures, seizure types and frequencies have not been considered as influential features for accurate identification of SOZ using EEG-fMRI. There is a crucial need to quantitatively measure concordance between presumed SOZ and IED-related BOLD response in different brain regions to improve SOZ delineation.

METHODS

A novel component-based EEG-fMRI approach is proposed to measure physical distance between BOLD clusters and selected component dipole location using patient-specific high resolution anatomical images. The method is applied on 18 patients with refractory focal epilepsy to localize epileptic focus and determine concordance quantitatively and compare between maximum BOLD cluster with identified component dipole. To measure concordance, distance from a voxel with maximal z-score of maximum BOLD to center of extracted component dipole is measured.

RESULTS

BOLD clusters to spikes distances for concordant (<25 mm), partially concordant (25-50 mm), and discordant (>50 mm) groups were significantly different (p < 0.0001). The results showed full concordance in 17 IED types (17.85 ± 4.69 mm), partial concordance in 4 (36.47 ± 8.84 mm), and nodiscordance, which is a significant rise compared to the existing literature. The proposed method is premised on the cross-correlation between the spike template outside the scanner and the highly-ranked extracted components. It successfully surpasses the limitations of conventional EEG-fMRI studies which are largely dependent on inside-scanner spikes. More significantly, the proposed method improves localization accuracy to 97% which marks a dramatic rise compared to conventional works.

CONCLUSIONS

This study demonstrated that BOLD changes were related to epileptic spikes in different brain regions in patients with refractory focal epilepsy. In a systematic quantitative approach, concordance levels based on the distance between center of maximum BOLD cluster and dipole were determined by component-based EEG-fMRI method. Therefore, component-based EEG-fMRI can be considered as a reliable predictor of SOZ in patients with focal epilepsy and included as part of clinical evaluation for patients with medically resistant epilepsy.

The seizure onset zone drives state-dependent epileptiform activity in susceptible brain regions

OBJECTIVE

Due to variability in the patterns of propagation of interictal epileptiform discharges (IEDs), qualitative definition of the irritative zone has been challenging. Here, we introduce a quantitative approach toward exploration of the dynamics of IED propagation within the irritative zone.

METHODS

We examined intracranial EEG (iEEG) in nine participants undergoing invasive monitoring for seizure localization. We used an automated IED detector and a community detection algorithm to identify populations of electrodes exhibiting IED activity that co-occur in time, and to group these electrodes into communities.

RESULTS

Within our algorithmically-identified communities, IED activity in the seizure onset zone (SOZ) tended to lead IED activity in other functionally coupled brain regions. The tendency of pathological activity to arise in the SOZ, and to spread to non-SOZ tissues, was greater in the asleep state.

CONCLUSIONS

IED activity, and, by extension, the variability observed between the asleep and awake states, is propagated from a core seizure focus to nearby less pathological brain regions.

SIGNIFICANCE

Using an unsupervised, computational approach, we show that the spread of IED activity through the epilepsy network varies with physiologic state.

Reproducibility of interictal spike propagation in children with refractory epilepsy

OBJECTIVE

Interictal spikes are a characteristic feature of invasive electroencephalography (EEG) recordings in children with refractory epilepsy. Spikes frequently co-occur across multiple brain regions with discernable latencies, suggesting that spikes can propagate through distributed neural networks. The purpose of this study was to examine the long-term reproducibility of spike propagation patterns over hours to days of interictal recording.

METHODS

Twelve children (mean age 13.1 years) were retrospectively studied. A mean ± standard deviation (SD) of 47.2 ± 40.1 hours of interictal EEG recordings were examined per patient (range 17.5-166.5 hours). Interictal recordings were divided into 30-minute segments. Networks were extracted based on the frequency of spike coactivation between pairs of electrodes. For each 30-minute segment, electrodes were assigned a "Degree Preference (DP)" based on the tendency to appear upstream or downstream within propagation sequences. The consistency of DPs across segments ("DP-Stability") was quantified using the Spearman rank correlation.

RESULTS

Regions exhibited highly stable preferences to appear upstream, intermediate, or downstream in spike propagation sequences. Across networks, the mean ± SD DP-Stability was 0.88 ± 0.07, indicating that propagation patterns observed in 30-minute segments were representative of the patterns observed in the full interictal window. At the group level, regions involved in seizure generation appeared more upstream in spike propagation sequences.

SIGNIFICANCE

Interictal spike propagation is a highly reproducible output of epileptic networks. These findings shed new light on the spatiotemporal dynamics that may constrain the network mechanisms of refractory epilepsy.

The first-hour-of-the-day sleep EEG reliably identifies interictal epileptiform discharges during long-term video-EEG monitoring

PURPOSE

To determine the usefulness of the first-hour sleep EEG recording in identifying interictal epileptiform discharges (IEDs) during long-term video-EEG monitoring.

METHOD

We retrospectively reviewed 255 consecutive patients who underwent continuous long-term video-EEG monitoring in the adult epilepsy monitoring unit (EMU) at the University of Chicago. The complete video-EEG recording was reviewed, and the occurrence of IEDs was determined for each patient. We compared the occurrence of IEDs observed during the first-hour sleep EEG recordings with the occurrence of IEDs observed during the complete video-EEG recordings.

RESULTS

Overall, IEDs were observed in 134 (53%) of 255 patients during the full long-term video-EEG recording with a mean duration of 4 days. IEDs were identified in the first-hour sleep EEG in 125 (49%) of 225 patients. Comparing to reviewing full records, the first hour sleep EEG identified IEDs in 125 (93%) of 134 patients. Of the IED subtypes, the first-hour sleep EEG identified 92 (94%) of 98 patients with temporal lobe IEDs, 11 (92%) of 12 patients with frontal lobe IEDs, 3 (100%) of 3 patients with parietal lobe IEDs, 1(50%) of the 2 patients with occipital lobe IEDs, 16 (94%) of 17 patients with generalized IEDs, and 2 (100%) 2 patients with multi-focal IEDs.

CONCLUSIONS

The first-hour sleep EEG reliably predicts the occurrence of IEDs during the long-term video-EEG recording, and therefore can be a time-efficient tool for identifying patients with IEDs during long-term video-EEG recording in the adult epilepsy monitoring unit.

Sleep Related Epilepsy and Pharmacotherapy: An Insight

In the last several decades, sleep-related epilepsy has drawn considerable attention among epileptologists and neuroscientists in the interest of new paradigms of the disease etiology, pathogenesis and management. Sleep-related epilepsy is nocturnal seizures that manifest solely during the sleep state. Sleep comprises two distinct stages i.e., non-rapid eye movement (NREM) and rapid eye movement (REM) that alternate every 90 min with NREM preceding REM. Current findings indicate that the sleep-related epilepsy manifests predominantly during the synchronized stages of sleep; NREM over REM stage. Sleep related hypermotor epilepsy (SHE), benign partial epilepsy with centrotemporal spikes or benign rolandic epilepsy (BECTS), and Panayiotopoulos Syndrome (PS) are three of the most frequently implicated epilepsies occurring during the sleep state. Although some familial types are described, others are seemingly sporadic occurrences. In the present review, we aim to discuss the predominance of sleep-related epilepsy during NREM, established familial links to the pathogenesis of SHE, BECTS and PS, and highlight the present available pharmacotherapy options.