Focal ictal direct current shifts in human epilepsy as studied by subdural and scalp recording

Novel and reappraised wide-band EEG findings in migraineurs: Its correlation with several clinical variables

OBJECTIVE

Cortical spreading depolarization is one possible pathogenesis of migraine, of which slow neurophysiological change is barely recorded in conventional EEG settings. Using wide-band EEG conditions, we reappraised the features of EEG in migraineurs, including subdelta-band EEG changes.

METHODS

This retrospective study included 144 patients with migraine. We delineated EEG of focal delta slow (FDS) (1-4 Hz) by time constant (TC) 0.3 s and focal subdelta slow (FSDS) (< 1 Hz) by TC 2 s. Relationships between clinical variables and EEG findings were evaluated.

RESULTS

Of 144 patients, 39 had aura and 105 did not. FSDS and FDS were observed in 38 and 58 patients, respectively. No EEG was recorded during the aura. In multivariate analysis with the phase of migraine, family history, age, and percentage of sleep during EEG recording, the phase of migraine was related to the occurrence of FSDS (postdrome vs interictal, prodrome, and headache respectively (OR = 49.00 [95% CI = 3.89-616.66], 46.28 [2.99-715.78], 32.79 [2.23-481.96], p = 0.0026, 0.0061, 0.011). FDS was clinically unremarkable for differential evaluation.

CONCLUSIONS

Wide-band EEG abnormality in migraineurs, i.e., FSDS, can be affected by migraine phase.

SIGNIFICANCE

Wide-band EEG finding could be a biomarker related to clinical variables in migraines.

Uncovering spatiotemporal dynamics of the corticothalamic network at ictal onset

OBJECTIVE

Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human electroencephalographic (EEG) recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci.

METHODS

We analyzed 10 patients (aged 2.7-28.1 years) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic sampling. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM) at ictal onset.

RESULTS

In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM.

SIGNIFICANCE

It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network at ictal onset, and this knowledge could guide personalized responsive neuromodulation treatment strategies.

[Epileptic seizure and migraine attack: A revisit from the "Borderland of Epilepsy" to clinical implementation of infraslow activity/DC shifts in scalp EEG]

Migraine attacks, especially ones with aura, have symptoms similar to epileptic seizures, and the two may sometimes be difficult to differentiate clinically. However, the characteristic minute-by-minute symptom development and progress within 60 ‍min is useful for diagnosis. Although the details of its pathophysiology remain unsolved, cortical spreading depolarization (CSD) is one of the main pathogenetic factors. In epilepsy, clinical data have shown that ictal DC shifts could reflect impaired homeostasis of extracellular potassium by astrocyte dysfunction. Ictal DC shifts were found to be difficult to detect by scalp EEG, but can be clinically recorded from the seizure focus using wide-band EEG method. The similarity between DC shifts and CSD has been gaining attention from the neurophysiology point of view. The clinical implementation of infraslow activity/DC shifts analysis of scalp EEG is expected to elucidate further the pathophysiology of migraine, which may lie in the borderland of epilepsy.

Ictal Direct Current Shifts Preceded Much Earlier Than High Frequency Oscillations After Status: Is It the Effect of Status or Antiseizure Medication?

PURPOSE

While spikes and sharp waves are considered as markers of epilepsy in conventional electroencephalography, ictal direct current (DC) shifts and high-frequency oscillations (HFOs) appear to be useful biomarkers for epileptogenicity. We analyzed how ictal DC shifts and HFOs were affected by focal status epilepticus and antiseizure medications (ASMs).

METHODS

A 20-year-old female patient who underwent long-term intracranial electrode implantation for epilepsy surgery presented with 72 habitual seizures and a focal status epilepticus episode lasting for 4 h. Ten, 3, and 10 consecutive habitual seizures were analyzed before the status, after the status, and after ASM (valproate) loading, respectively.

RESULTS

Before and immediately after the status, ictal DC shifts remained the same in terms of the amplitude, duration, and slope of DC shifts. High-frequency oscillations also remained the same in terms of the duration, frequency, and power except for the power of the lower frequency band. After ASM loading, the duration, amplitude, and slope of the ictal DC shift were significantly attenuated. The duration, frequency, and power of the HFOs were significantly attenuated. Furthermore, the interval between the DC onset and HFO onset was significantly longer and the interval between the HFO onset and ictal DC shift peak was significantly shorter.

CONCLUSIONS

The attenuation of ictal DC shifts and HFOs after ASM loading implies that astrocyte and neuronal activity may be both attenuated by ASMs. This finding may help with our understanding of the pathophysiology of epilepsy and can aid with the discovery of new approaches for epilepsy management.

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.

Pitfalls in scalp EEG: Current obstacles and future directions

Although electroencephalography (EEG) serves a critical role in the evaluation and management of seizure disorders, it is commonly misinterpreted, resulting in avoidable medical, social, and financial burdens to patients and health care systems. Overinterpretation of sharply contoured transient waveforms as being representative of interictal epileptiform abnormalities lies at the core of this problem. However, the magnitude of these errors is amplified by the high prevalence of paroxysmal events exhibited in clinical practice that compel investigation with EEG. Neurology training programs, which vary considerably both in the degree of exposure to EEG and the composition of EEG didactics, have not effectively addressed this widespread issue. Implementation of competency-based curricula in lieu of traditional educational approaches may enhance proficiency in EEG interpretation amongst general neurologists in the absence of formal subspecialty training. Efforts in this regard have led to the development of a systematic, high-fidelity approach to the interpretation of epileptiform discharges that is readily employable across medical centers. Additionally, machine learning techniques hold promise for accelerating accurate and reliable EEG interpretation, particularly in settings where subspecialty interpretive EEG services are not readily available. This review highlights common diagnostic errors in EEG interpretation, limitations in current educational paradigms, and initiatives aimed at resolving these challenges.

Focal ictal direct current shifts by a time constant of 2 seconds were clinically useful for resective epilepsy surgery

OBJECTIVE

Ictal direct current shifts (icDCs) and ictal high-frequency oscillations (icHFOs) have been reported as surrogate markers for better surgical outcomes in epilepsy surgery. icDCs have been classified into two types: rapid and slow development. icDCs have been investigated with a time constant of 10 s (TC10s); however, many institutes use electroencephalography with a time constant of 2 s (TC2s). This study aimed to evaluate whether icDCs can be observed adequately with TC2s; moreover, it examined the relationship between the resected core area of icDCs or icHFOs and surgical outcomes, occurrence rate of each type of icDCs, and relationship between each type of icDCs and pathology.

METHODS

Twenty-five patients with intractable focal epilepsy were analyzed retrospectively. icDCs and icHFOs were defined according to common metrics. The amplitude of icDCs was defined at >200 μV and even <200 μV. The two electrodes producing the most prominent icDCs and icHFOs were defined as core electrodes. The correlation between the resected core electrode area and degree of seizure control after surgery was analyzed. icDCs were classified into two types based on a peak latency value cutoff of 8.9 s, and the occurrence rates of both patterns were investigated.

RESULTS

icDCs (142/147 seizures [96.6%]) and icHFOs (135/147 seizures [91.8%]) occurred in all patients (100%). Compared with the amplitude of icDCs with TC10s reported in previous studies, the amplitude of icDCs with TC2s was attenuated in the current study. A significant positive correlation was observed between the resected core electrode area and degree of seizure control in both icDCs and icHFOs. A rapid development pattern was observed in 202 of 264 electrodes (76.5%).

SIGNIFICANCE

Similar to icDCs with TC10s, those with TC2s were observed adequately. Furthermore, favorable outcomes are expected using TC2s, which is currently available worldwide.

Optimization of ictal aborting stimulation using the dynamotype taxonomy

Electrical stimulation is an increasingly popular method to terminate epileptic seizures, yet it is not always successful. A potential reason for inconsistent efficacy is that stimuli are applied empirically without considering the underlying dynamical properties of a given seizure. We use a computational model of seizure dynamics to show that different bursting classes have disparate responses to aborting stimulation. This model was previously validated in a large set of human seizures and led to a description of the Taxonomy of Seizure Dynamics and the dynamotype, which is the clinical analog of the bursting class. In the model, the stimulation is realized as an applied input, which successfully aborts the burst when it forces the system from a bursting state to a quiescent state. This transition requires bistability, which is not present in all bursters. We examine how topological and geometric differences in the bistable state affect the probability of termination as the burster progresses from onset to offset. We find that the most significant determining factors are the burster class (dynamotype) and whether the burster has a DC (baseline) shift. Bursters with a baseline shift are far more likely to be terminated due to the necessary structure of their state space. Furthermore, we observe that the probability of termination varies throughout the burster's duration, is often dependent on the phase when it was applied, and is highly correlated to dynamotype. Our model provides a method to predict the optimal method of termination for each dynamotype. These results lead to the prediction that optimization of ictal aborting stimulation should account for seizure dynamotype, the presence of a DC shift, and the timing of the stimulation.

Diverse nature of interictal oscillations: EEG-based biomarkers in epilepsy

Interictal electroencephalogram (EEG) patterns, including high-frequency oscillations (HFOs), interictal spikes (ISs), and slow wave activities (SWAs), are defined as specific oscillations between seizure events. These interictal oscillations reflect specific dynamic changes in network excitability and play various roles in epilepsy. In this review, we briefly describe the electrographic characteristics of HFOs, ISs, and SWAs in the interictal state, and discuss the underlying cellular and network mechanisms. We also summarize representative evidence from experimental and clinical epilepsy to address their critical roles in ictogenesis and epileptogenesis, indicating their potential as electrophysiological biomarkers of epilepsy. Importantly, we put forwards some perspectives for further research in the field.

Digital reconstruction of infraslow activity in human intracranial ictal recordings using a deconvolution-based inverse filter

Infraslow activity (ISA) is a biomarker that has recently become of interest in the characterization of seizure recordings. Recent data from a small number of studies have suggested that the epileptogenic zone may be identified by the presence of ISA. Investigation of low frequency activity in clinical seizure recordings, however, has been hampered by technical limitations. EEG systems necessarily include a high-pass filter early in the measurement chain to remove large artifactual drifts that can saturate recording elements such as the amplifier. This filter, unfortunately, attenuates legitimately seizure-related low frequencies, making ISA difficult to study in clinical EEG recordings. In this study, we present a deconvolution-based digital inverse filter that allows recovery of attenuated low frequency activity in intracranial recordings of temporal lobe epilepsy patients. First, we show that the unit impulse response (UIR) of an EEG system can be characterized by differentiation of the system's step response. As proof of method, we present several examples that show that the low frequency component of a high-pass filtered signal can be restored by deconvolution with the UIR. We then demonstrate that this method can be applied to biologically relevant signals including clinical EEG recordings obtained from seizure patients. Finally, we discuss how this method can be applied to study ISA to identify and assess the seizure onset zone.

Two types of clinical ictal direct current shifts in invasive EEG of intractable focal epilepsy identified by waveform cluster analysis

OBJECTIVE

To determine clinically ictal direct current (DC) shifts that can be identified by a time constant (TC) of 2 s and to delineate different types of DC shifts by different attenuation patterns between TC of 10 s and 2 s.

METHODS

Twenty-one patients who underwent subdural electrode implantation for epilepsy surgery were investigated. For habitual seizures, we compared (1) the peak amplitude and (2) peak latency of the earliest ictal DC shifts between TC of 10 s and 2 s. Cluster and logistic regression analyses were performed based on the attenuation rate of amplitude and peak latency with TC 10 s.

RESULTS

Ictal DC shifts in 120 seizures were analyzed; 89.1% of which were appropriately depicted even by a TC of 2 s. Cluster and logistic regression analyses revealed two types of ictal DC shift. Namely, a rapid development pattern was defined as the ictal DC shifts with a shorter peak latency and they also showed smaller attenuation rate of amplitude (73/120 seizures). Slow development pattern was defined as the ictal DC shifts with crosscurrent of a rapid development pattern, i.e., a longer peak latency and larger attenuation rate of amplitude (47/120 seizures). Focal cortical dysplasia (FCD) 1A tended to show a rapid development pattern (22/29 seizures) and FCD2A tended to show a slow development pattern (13 /18 seizures), indicating there might be some correlations between two types of ictal DC shift and certain pathologies.

CONCLUSIONS

Ictal DC shifts, especially rapid development pattern, can be recorded and identified by the AC amplifiers of TC of 2 s which is widely used in many institutes compared to that of TC of 10 s. Two types of ictal DC shifts were identified with possibility of corresponding pathology.

SIGNIFICANCE

Ictal DC shifts can be distinguished by their attenuation patterns.

Epileptic seizure–related changes in electrocorticogram, cortical temperature, and cerebral hemodynamics obtained via an implantable multimodal multichannel probe during preoperative monitoring: illustrative case

BACKGROUND

Electrocorticography (EcoG) plays an essential role in the preoperative evaluation of epilepsy, despite its high invasiveness. Brain temperature and cerebral hemodynamics also reflect brain activity. This study examined whether a multimodal multichannel probe that simultaneously records EcoG, cortical temperature, and cerebral hemodynamics can contribute to improving the assessment of epileptic seizures. After preoperative monitoring was performed in a patient with epilepsy, three generalized seizures and two focal seizures were observed.

OBSERVATIONS

A short-term power increase in the alternating current spectrogram, high-amplitude slow waves in direct current potential, an increase in cortical temperature, an increase in oxyhemoglobin (HbO₂) concentration and total hemoglobin (HbT) concentration, and a decrease in deoxyhemoglobin (HHb) concentration, followed by a decrease in HbO₂ and HbT concentrations and an increase in HHb concentration, were observed in generalized seizures. However, no changes in these pathophysiological signals were observed in focal seizures.

LESSONS

Seizure-related changes regarding generalized seizures were consistent with the results of previous studies. The results of generalized and focal seizures indicate that epileptic brain activity propagated from the epileptic focus in the right frontal lobe to the measurement area near the motor cortex in generalized seizures but not in focal seizures.

Full-bandwidth electrophysiology of seizures and epileptiform activity enabled by flexible graphene microtransistor depth neural probes

Mapping the entire frequency bandwidth of brain electrophysiological signals is of paramount importance for understanding physiological and pathological states. The ability to record simultaneously DC-shifts, infraslow oscillations (<0.1 Hz), typical local field potentials (0.1-80 Hz) and higher frequencies (80-600 Hz) using the same recording site would particularly benefit preclinical epilepsy research and could provide clinical biomarkers for improved seizure onset zone delineation. However, commonly used metal microelectrode technology suffers from instabilities that hamper the high fidelity of DC-coupled recordings, which are needed to access signals of very low frequency. In this study we used flexible graphene depth neural probes (gDNPs), consisting of a linear array of graphene microtransistors, to concurrently record DC-shifts and high-frequency neuronal activity in awake rodents. We show here that gDNPs can reliably record and map with high spatial resolution seizures, pre-ictal DC-shifts and seizure-associated spreading depolarizations together with higher frequencies through the cortical laminae to the hippocampus in a mouse model of chemically induced seizures. Moreover, we demonstrate the functionality of chronically implanted devices over 10 weeks by recording with high fidelity spontaneous spike-wave discharges and associated infraslow oscillations in a rat model of absence epilepsy. Altogether, our work highlights the suitability of this technology for in vivo electrophysiology research, and in particular epilepsy research, by allowing stable and chronic DC-coupled recordings.

Low frequency novel interictal EEG biomarker for localizing seizures and predicting outcomes

Localizing hyperexcitable brain tissue to treat focal seizures remains challenging. We want to identify the seizure onset zone from interictal EEG biomarkers. We hypothesize that a combination of interictal EEG biomarkers, including a novel low frequency marker, can predict mesial temporal involvement and can assist in prognosis related to surgical resections. Interictal direct current wide bandwidth invasive EEG recordings from 83 patients implanted with 5111 electrodes were retrospectively studied. Logistic regression was used to classify electrodes and patient outcomes. A feed-forward neural network was implemented to understand putative mechanisms. Interictal infraslow frequency EEG activity was decreased for seizure onset zone electrodes while faster frequencies such as delta (2-4 Hz) and beta-gamma (20-50 Hz) activity were increased. These spectral changes comprised a novel interictal EEG biomarker that was significantly increased for mesial temporal seizure onset zone electrodes compared to non-seizure onset zone electrodes. Interictal EEG biomarkers correctly classified mesial temporal seizure onset zone electrodes with a specificity of 87% and positive predictive value of 80%. These interictal EEG biomarkers also correctly classified patient outcomes after surgical resection with a specificity of 91% and positive predictive value of 87%. Interictal infraslow EEG activity is decreased near the seizure onset zone while higher frequency power is increased, which may suggest distinct underlying physiologic mechanisms. Narrowband interictal EEG power bands provide information about the seizure onset zone and can help predict mesial temporal involvement in seizure onset. Narrowband interictal EEG power bands may be less useful for predictions related to non-mesial temporal electrodes. Together with interictal epileptiform discharges and high-frequency oscillations, these interictal biomarkers may provide prognostic information prior to surgical resection. Computational modelling suggests changes in neural adaptation may be related to the observed low frequency power changes.

Phase-amplitude coupling between infraslow and high-frequency activities well discriminates between the preictal and interictal states

Infraslow activity (ISA) and high-frequency activity (HFA) are key biomarkers for studying epileptic seizures. We aimed to elucidate the relationship between ISA and HFA around seizure onset. We enrolled seven patients with drug-resistant focal epilepsy who underwent intracranial electrode placement. We comparatively analyzed the ISA, HFA, and ISA-HFA phase-amplitude coupling (PAC) in the seizure onset zone (SOZ) or non-SOZ (nSOZ) in the interictal, preictal, and ictal states. We recorded 15 seizures. HFA and ISA were larger in the ictal states than in the interictal or preictal state. During seizures, the HFA and ISA of the SOZ were larger and occurred earlier than those of nSOZ. In the preictal state, the ISA-HFA PAC of the SOZ was larger than that of the interictal state, and it began increasing at approximately 87 s before the seizure onset. The receiver-operating characteristic curve revealed that the ISA-HFA PAC of the SOZ showed the highest discrimination performance in the preictal and interictal states, with an area under the curve of 0.926. This study demonstrated the novel insight that ISA-HFA PAC increases before the onset of seizures. Our findings indicate that ISA-HFA PAC could be a useful biomarker for discriminating between the preictal and interictal states.

Epilepsy as a dynamical system, a most needed paradigm shift in epileptology

The idea of the epileptic brain being highly excitable and facilitated to synchronic activity has guided pharmacological treatment since the early twentieth century. Although tackling epilepsy's seizure-prone feature, by tonically modifying overall circuit excitability and/or connectivity, the last 50 years of drug development has not seen a substantial improvement in seizure suppression of refractory epilepsies. This review presents a new conceptual framework for epilepsy in which the temporal dynamics of the disease plays a more critical role in both its understanding and therapeutic strategies. The repetitive epileptiform pattern (characteristic during ictal activity) and other well-defined electrographic signatures (i.e., present during the interictal period) are discussed in terms of the sequential activation of the circuit motifs. Lessons learned from the physiological activation of neural circuitry are used to further corroborate the argument and explore the transition from proper function to a state of instability. Furthermore, the review explores how interfering in the temporally dependent abnormal connectivity between circuits may work as a therapeutic approach. We also review the use of probing stimulation to access network connectivity and evaluate its power to determine transitional states of the dynamical system as it moves towards regions of instability, especially when conventional electrographic monitoring is proven inefficient. Unorthodox cases, with little or no scalp electrographic correlate, in which ictogenic circuitry and/or seizure spread is temporally restricted to neurovegetative, cognitive, and motivational areas are shown as possible explanations for sudden death in epilepsy (SUDEP) and other psychiatric comorbidities. In short, this review presents a paradigm shift in the way that we address the disease and is aimed to encourage debate rather than narrow the rationale epilepsy is currently engaged in. This article is part of the Special Issue "NEWroscience 2018".

The accuracy of quantitative EEG biomarker algorithms depends upon seizure onset dynamics

OBJECTIVE

To compare the performance of different ictal quantitative biomarkers of the seizure onset zone (SOZ) across many seizures in a cohort of consecutive patients with a variety of seizure onset patterns.

METHODS

The Epileptogenicity Index (EI, a measure of fast activity) and Slow Polarizing Shift index (SPS, a measure of infraslow activity) were calculated for 212 seizures (22 patients). After stratification by onset pattern, median index values inside and outside the SOZ were compared in aggregate and for each of the onset patterns. Receiver Operating Characteristic (ROC) curves were constructed to compare the performance of each index.

RESULTS

Median values of EI (0.056 vs 0.0087), SPS (0.27 vs 0.19), and CI (0.21 vs 0.12) were significantly higher for contacts inside the SOZ, all p < 0.0001. Analysis of AUC showed variable performance of these indices across seizure types, although AUC for EI and SPS was generally greatest for seizures with fast activity at onset.

CONCLUSIONS

All indices were significantly higher for contacts inside the SOZ; however, the performance of these indices varied depending on the pattern of seizure onset.

SIGNIFICANCE

These findings suggest that future studies of quantitative biomarkers of the SOZ should account for seizure onset pattern.

Transitional pattern as a potential marker of epileptogenic zone in focal epilepsy - Clinical observations from intracerebral recordings

OBJECTIVES

To investigate the characteristics of transition from interictal to ictal phase in intracranial recordings and further to determine the potential marker of epileptogenic zone.

METHODS

Eighteen patients with drug-refractory epilepsy who underwent stereo-electroencephalography (SEEG) evaluation and subsequent resective surgery were included. All patients were seizure-free post-operatively. The recorded seizures were retrospectively reviewed and time episodes including 5 min before electrographic onset were selected for further analysis to verify the presence of a transitional pattern in the transitional phase, which was distinct from interictal background and ictal onset. Besides, the components of transitional patterns which characterized by different pathological waveforms were identified by visual analysis and time-frequency analysis. The prevalence of transitional patterns between resection and non-resection, lesion and non-lesion sites were compared. In addition, the association between transitional patterns and types of epilepsy was explored.

RESULTS

Six transitional patterns characterized by different combinations of multiple pathological waveforms by visual analysis combined with time-frequency analysis were identified: spike/spike-waves/polyspikes; spike superimposed by HFOs; spike superimposed by gamma oscillations; spike followed by suppression; spike superimposed by HFOs and followed by suppression; and spike superimposed by gamma oscillations and followed by suppression. A higher prevalence of transitional patterns in resection than non-resection (p < 0.001) and in lesion than non-lesion contacts (p < 0.001). The pattern characterized by spike superimposed by HFOs and followed by suppression was more prevalent in resection than non-resection sites (p = 0.004). Further, there was an association between the complexity of transitional patterns and the location of contacts. Patterns with higher degree of complexity were more likely to be inside the resection area (p = 0.035). Besides, we found the pattern with spike superimposed by HFOs was associated more with limbic epilepsy than neocortical epilepsy (p < 0.001), whereas another 3 patterns, spike superimposed by gamma oscillation, spike followed by suppression and spike combined with HFOs and suppression, were observed more frequently in neocortical epilepsy than limbic epilepsy (p = 0.018, 0.011 and < 0.001, respectively).

CONCLUSION

Transitional patterns from interictal to ictal state were characterized by different combinations of multiple pathological waveforms, which may be a potential marker of epileptogenic zone. Our findings support that the interaction of different neuronal oscillations or waveforms generated by different neuronal populations may be the potential mechanism of seizure generation.

Phase-amplitude coupling of ripple activities during seizure evolution with theta phase

OBJECTIVE

High-frequency activities (HFAs) and phase-amplitude coupling (PAC) are key neurophysiological biomarkers for studying human epilepsy. We aimed to clarify and visualize how HFAs are modulated by the phase of low-frequency bands during seizures.

METHODS

We used intracranial electrodes to record seizures of focal epilepsy (12 focal-to-bilateral tonic-clonic seizures and three focal-aware seizures in seven patients). The synchronization index, representing PAC, was used to analyze the coupling between the amplitude of ripples (80-250 Hz) and the phase of lower frequencies. We created a video in which the intracranial electrode contacts were scaled linearly to the power changes of ripple.

RESULTS

The main low frequency band modulating ictal-ripple activities was the θ band (4-8 Hz), and after completion of ictal-ripple burst, δ (1-4 Hz)-ripple PAC occurred. The ripple power increased simultaneously with rhythmic fluctuations from the seizure onset zone, and spread to other regions.

CONCLUSIONS

Ripple activities during seizure evolution were modulated by the θ phase. The PAC phenomenon was visualized as rhythmic fluctuations.

SIGNIFICANCE

Ripple power associated with seizure evolution increased and spread with fluctuations. The θ oscillations related to the fluctuations might represent the common neurophysiological processing involved in seizure generation.

Association of cortical spreading depression and seizures in patients with medically intractable epilepsy

OBJECTIVE

Monitoring of the ultra-low frequency potentials, particularly cortical spreading depression (CSD), is excluded in epilepsy monitoring due to technical barriers imposed by the scalp ultra-low frequency electroencephalogram (EEG). As a result, clinical studies of CSD have been limited to invasive EEG. Therefore, the occurrence of CSD and its interaction with epileptiform field potentials (EFP) require investigation in epilepsy monitoring.

METHODS

Using a novel AC/DC-EEG approach, the occurrence of DC potentials in patients with intractable epilepsy presenting different symptoms of aura was investigated during long-term video-EEG monitoring.

RESULTS

Various forms of slow potentials, including simultaneous negative direct current (DC) potentials and prolonged EFP, propagated negative DC potentials, and non-propagated single negative DC potentials were recorded from the scalp of the epileptic patients. The propagated and single negative DC potentials preceded the prolonged EFP with a time lag and seizure appeared at the final shoulder of some instances of the propagated negative DC potentials. The slow potential deflections had a high amplitude and prolonged duration and propagated slowly through the brain. The high-frequency EEG was suppressed in the vicinity of the negative DC potential propagations.

CONCLUSIONS

The study is the first to report the recording of the propagated and single negative DC potentials with EFP at the scalp of patients with intractable epilepsy. The negative DC potentials preceded the prolonged EFP and may trigger seizures. The propagated and single negative DC potentials may be considered as CSD.

SIGNIFICANCE

Recordings of CSD may serve as diagnostic and prognostic monitoring tools in epilepsy.

Coupling between infraslow activities and high-frequency oscillations precedes seizure onset

Infraslow activities and high-frequency oscillations (HFOs) are observed in seizure-onset zones. However, the relation between them remains unclear. In this study, we investigated phase-amplitude coupling between infraslow phase (0.016-1 Hz) and HFOs' amplitude of focal impaired awareness seizures followed by focal to bilateral tonic-clonic seizures, in a 28-year-old right-handed man with a dysembryoplastic neuroepithelial tumor. We recorded five habitual seizures. After the time of seizure onset, a significant increase in the power of HFOs was observed, and the power was significantly coupled with θ (4-8 Hz) phase. In contrast, coupling of infraslow activities and HFOs surged a few minutes before the seizure-onset time, and ictal HFOs discharged after that. Collectively, our results show that coupling of infraslow activities and HFOs precedes the seizure-onset time. We infer that such coupling may be a potential biomarker for seizure prediction.

[Scalp-recorded cortical spreading depolarizations (CSDs) of EEG with time constant of 2 seconds in a patient with acute traumatic brain injury]

An 82-year-old female suffered from head trauma, and developed acute consciousness disturbance 6 days after the event. Head CT showed the acute subdural hematoma in the left temporooccipital area and the patient underwent emergency hematoma evacuation and decompression. However, her consciousness disturbance became worse after surgery. Intermittent large negative infraslow shifts (lasting longer than 40 seconds) were recorded in the right posterior quadrant by scalp EEG with TC of 2 sec, that was defined as cortical spreading depolarizations (CSDs). Clinically consciousness disturbance sustained poor until 1 month after surgery in spite of treatment by anti-epileptic drugs. CSDs were observed on the right side where head injury most likely occurred. It may explain the sustained consciousness disturbance associated with significant prolonged ischemia. Once scalp EEG could record CSDs in this particular patient, the degree and its prognosis of traumatic head injury were estimated.

A taxonomy of seizure dynamotypes

Seizures are a disruption of normal brain activity present across a vast range of species and conditions. We introduce an organizing principle that leads to the first objective Taxonomy of Seizure Dynamics (TSD) based on bifurcation theory. The ‘dynamotype’ of a seizure is the dynamic composition that defines its observable characteristics, including how it starts, evolves and ends. Analyzing over 2000 focal-onset seizures from multiple centers, we find evidence of all 16 dynamotypes predicted in TSD. We demonstrate that patients’ dynamotypes evolve during their lifetime and display complex but systematic variations including hierarchy (certain types are more common), non-bijectivity (a patient may display multiple types) and pairing preference (multiple types may occur during one seizure). TSD provides a way to stratify patients in complement to present clinical classifications, a language to describe the most critical features of seizure dynamics, and a framework to guide future research focused on dynamical properties.

Epileptic seizures have been recognized for centuries. But it was only in the 1930s that it was realized that seizures are the result of out-of-control electrical activity in the brain. By placing electrodes on the scalp, doctors can identify when and where in the brain a seizure begins. But they cannot tell much about how the seizure behaves, that is, how it starts, stops or spreads to other areas. This makes it difficult to control and prevent seizures. It also helps explain why almost a third of patients with epilepsy continue to have seizures despite being on medication.

Saggio, Crisp et al. have now approached this problem from a new angle using methods adapted from physics and engineering. In these fields, “dynamics research” has been used with great success to predict and control the behavior of complex systems like electrical power grids. Saggio, Crisp et al. reasoned that applying the same approach to the brain would reveal the dynamics of seizures and that such information could then be used to categorize seizures into groups with similar properties. This would in effect create for seizures what the periodic table is for the elements.

Applying the dynamics research method to seizure data from more than a hundred patients from across the world revealed 16 types of seizure dynamics. These “dynamotypes” had distinct characteristics. Some were more common than others, and some tended to occur together. Individual patients showed different dynamotypes over time. By constructing a way to classify seizures based on the relationships between the dynamotypes, Saggio, Crisp et al. provide a new tool for clinicians and researchers studying epilepsy.

Previous clinical tools have focused on the physical symptoms of a seizure (referred to as the phenotype) or its potential genetic causes (genotype). The current approach complements these tools by adding the dynamotype: how seizures start, spread and stop in the brain. This approach has the potential to lead to new branches of research and better understanding and treatment of seizures.

Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy

Drug-resistant focal epilepsy is a large-scale brain networks disorder characterized by altered spatiotemporal patterns of functional connectivity (FC), even during interictal resting state (RS). Although RS-FC-based metrics can detect these changes, results from RS functional magnetic resonance imaging (RS-fMRI) studies are unclear and difficult to interpret, and the underlying dynamical mechanisms are still largely unknown. To better capture the RS dynamics, we phenomenologically extended the neural mass model of partial seizures, the Epileptor, by including two neuron subpopulations of epileptogenic and nonepileptogenic type, making it capable of producing physiological oscillations in addition to the epileptiform activity. Using the neuroinformatics platform The Virtual Brain, we reconstructed 14 epileptic and 5 healthy human (of either sex) brain network models (BNMs), based on individual anatomical connectivity and clinically defined epileptogenic heatmaps. Through systematic parameter exploration and fitting to neuroimaging data, we demonstrated that epileptic brains during interictal RS are associated with lower global excitability induced by a shift in the working point of the model, indicating that epileptic brains operate closer to a stable equilibrium point than healthy brains. Moreover, we showed that functional networks are unaffected by interictal spikes, corroborating previous experimental findings; additionally, we observed higher excitability in epileptogenic regions, in agreement with the data. We shed light on new dynamical mechanisms responsible for altered RS-FC in epilepsy, involving the following two key factors: (1) a shift of excitability of the whole brain leading to increased stability; and (2) a locally increased excitability in the epileptogenic regions supporting the mixture of hyperconnectivity and hypoconnectivity in these areas.

SIGNIFICANCE STATEMENT Advances in functional neuroimaging provide compelling evidence for epilepsy-related brain network alterations, even during the interictal resting state (RS). However, the dynamical mechanisms underlying these changes are still elusive. To identify local and network processes behind the RS-functional connectivity (FC) spatiotemporal patterns, we systematically manipulated the local excitability and the global coupling in the virtual human epileptic patient brain network models (BNMs), complemented by the analysis of the impact of interictal spikes and fitting to the neuroimaging data. Our results suggest that a global shift of the dynamic working point of the brain model, coupled with locally hyperexcitable node dynamics of the epileptogenic networks, provides a mechanistic explanation of the epileptic processes during the interictal RS period. These, in turn, are associated with the changes in FC.

Seizure onset location shapes dynamics of initiation

OBJECTIVE

Ictal electrographic patterns are widely thought to reflect underlying neural mechanisms of seizures. Here we studied the degree to which seizure patterns are consistent in a given patient, relate to particular brain regions and if two candidate biomarkers (high-frequency oscillations, HFOs; infraslow activity, ISA) and network activity, as assessed with cross-frequency interactions, can discriminate between seizure types.

METHODS

We analyzed temporal changes in low and high frequency oscillations recorded during seizures, as well as phase-amplitude coupling (PAC) to monitor the interactions between delta/theta and ripple/fast ripple frequency bands at seizure onset.

RESULTS

Seizures of multiple electrographic patterns were observed in a given patient and brain region. While there was an increase in HFO rate across different electrographic patterns, there are specific relationships between types of HFO activity and onset region. Similarly, changes in PAC dynamics were more closely related to seizure onset region than they were to electrographic patterns while ISA was a poor indicator for seizure onset.

CONCLUSIONS

Our findings suggest that the onset region sculpts neurodynamics at seizure initiation and that unique features of the cytoarchitecture and/or connectivity of that region play a significant role in determining seizure mechanism.

SIGNIFICANCE

To learn how seizures are initiated, researchers would do well to consider other aspects of their manifestation, in addition to their electrographic patterns. Examination of onset pattern in conjunction with the interactions between different oscillatory frequencies in the context of different brain regions might be more informative and lead to more reliable clinical inference as well as novel therapeutic approaches.

A mathematical model for neuronal differentiation in terms of an evolved dynamical system

We attempted to create a mathematical model for neuronal differentiation. The present study was performed within the framework of self-organization with constraints by looking for an optimized informational unit. We treated networks of individual dynamical system units with an external input, which was provided by coupled one-dimensional maps with possible forms of unidirectionally feed-forward network, random network, small-world network, and fully-connected network. We used a genetic algorithm to maximize the information transmission for each type of network. Optimized maps were obtained depending on the coupling strength and network structure. These maps can be classified into three types: passive, excitable, and oscillatory. In particular, the excitable and oscillatory types of dynamical systems possess characteristics that are quite similar to those of neurons, whereas the passive and oscillatory types of dynamical system may represent glial cells.

Active direct current (DC) shifts and "Red slow": two new concepts for seizure mechanisms and identification of the epileptogenic zone

An accurate identification of the epileptogenic zone is essential for patients with intractable epilepsy who are candidates to neurosurgery. EEG recordings can provide predictive biomarkers of the epileptogenic zone. Wide-band EEG makes it possible to record from infraslow (including DC shifts) to high frequency (HFO, over 300 Hz) oscillations for diagnostic purposes in patients with epilepsy. Although the presence of HFOs have been proposed to sign the epileptogenic zone, DC-like recordings demonstrate that DC shifts precede HFOs at seizure onset. This led to the proposal that "ictal active DC shifts" are causally related to seizure onset as opposed to "ictal passive DC shifts". Thus, active DC shifts may constitute predictive biomarkers of the epileptogenic zone in epilepsy. Since DC shift is commonly associated to a rise in extracellular potassium, potassium homeostasis regulated by Kir4.1 channels in astrocytes may play an key role at seizure onset. In addition, we hypothesize that, during the interictal period, the co-occurrence of slow events and interictal HFOs, so-called "Red slow", may also delineate an epileptogenic zone, even if a seizure would not be actually recorded.

Recording Electrical Brain Activity with Novel Stretchable Electrodes Based on Supersonic Cluster Beam Implantation Nanotechnology on Conformable Polymers

Background

Multielectrodes are implanted in central and peripheral nervous systems for rehabilitation and diagnostic purposes. The physical resistance of intracranial devices to mechanical stress is critical and fractures or electrode displacement may occur. We describe here a new recording device with stretchable properties based on Supersonic Cluster Beam Implantation (SCBI) technology with high mechanical adaptability to displacement and movement.

Results

The capability of SCBI-based multichannel electrodes to record brain electrical activity was compared to glass/silicon microelectrodes in acute in vitro experiments on the isolated guinea pig brain preparation. Field potentials and power frequency analysis demonstrated equal recording features for SCBI and standard electrodes. Chronic in vivo epidural implantation of the SCBI electrodes confirmed excellent long-term recording properties in comparison to standard EEG metal electrodes. Tissue biocompatibility was demonstrated by neuropathological evaluation of the brain tissue 2 months after the implantation of the devices in the subarachnoid space.

Conclusion

We confirm the biocompatibility of novel SCBI-based stretchable electrode devices and demonstrate their suitability for recording electrical brain activity in pre-clinical settings.

Mathematical structures for epilepsy: High-frequency oscillation and interictal epileptic slow (red slow)

In the present study, we attempted to characterize two characteristic features within the dynamic behavior of wideband electrocorticography data, which were recorded as the brain waves of epilepsy, comprising high-frequency oscillations (HFOs) and interictal epileptic slow (red slow). The results of power spectrum and nonlinear time series analysis indicate that, on one hand, HFOs at epileptic focus are characterized by one-dimensional dynamical systems in ictal onset time segments at an epileptic focus for two patients' datasets; on the other hand, an interictal epileptic slow is characterized by the residue of power spectrum. The results suggest that the degree of freedom of the brain dynamics during epileptic seizure with HFO degenerates to low-dimensional dynamics; hence, the interictal epileptic slow as the precursors of the seizure onset can be detected simply from interictal brain wave data for the dataset of one patient. Therefore, our results are essential to understand the brain dynamics in epilepsy.

DC shifts, high frequency oscillations, ripples and fast ripples in relation to the seizure onset zone

Efforts to improve epilepsy surgery outcomes have led to increased interest in the study of electroencephalographic oscillations outside the conventional EEG bands. These include fast activity above the gamma band, known as high frequency oscillations (HFOs), and infraslow activity (ISA) below the delta band, sometimes referred to as direct current (DC) or ictal baseline shifts (IBS). HFOs in particular have been extensively studied as potential biomarkers for epileptogenic tissue in light of evidence showing that resection of brain tissue containing HFOs is associated with good surgical outcomes. Not all HFOs are conclusively pathological, however, as they can be recorded in nonepileptic tissue and induced by cognitive, visual, or motor tasks. Consequently, efforts to distinguish between pathological and physiological HFOs have identified several traits specific to pathological HFOs, such as coupling with interictal spikes, association with delta waves, and stereotypical morphologies. On the opposite end of the EEG spectrum, sub-delta oscillations have been shown to co-localize with the seizure onset zones (SOZ) and appear in a narrower spatial distribution than activity in the conventional EEG frequency bands. In this report, we review studies that implicate HFOs and ISA in ictogenesis and discuss current limitations such as inter-observer variability and poor standardization of recording techniques. Furthermore, we propose that HFOs and ISA should be analyzed in addition to activity in the conventional EEG band during intracranial presurgical EEG monitoring to identify the best possible surgical margin.

Activation of nicotinamide adenine dinucleotide phosphate oxidase is the primary trigger of epileptic seizures in rodent models

OBJECTIVE

Despite decades of epilepsy research, 30% of focal epilepsies remain resistant to antiseizure drugs, with effective drug development impeded by lack of understanding on how seizures are initiated. Here, we report the mechanism of seizure onset relevant to most seizures that are characteristic of focal epilepsies.

METHODS

Electric and metabolic network parameters were measured using several seizure models in mouse hippocampal slices and acutely induced seizures in rats in vivo to determine metabolic events occurring at seizure onset.

RESULTS

We show that seizure onset is associated with a rapid release of H₂ O₂ resulting from N-methyl-D-aspartate (NMDA) receptor-mediated activation of nicotinamide adenine dinucleotide phosphate oxidase (NOX). NOX blockade prevented the fast H₂ O₂ release as well as the direct current shift and seizurelike event induction in slices. Similarly, intracerebroventricular injection of NOX antagonists prevented acutely induced seizures in rats.

INTERPRETATION

Our results show that seizures are initiated by NMDA receptor-mediated NOX-induced oxidative stress and can be arrested by NOX inhibition. We introduce a novel use for blood-brain barrier-permeable NOX inhibitor with a significant potential to become the first seizure-specific medication. Thus, targeting NOX may provide a breakthrough treatment for focal epilepsies. ANN NEUROL 2019;85:907-920.

Spectral entropy indicates electrophysiological and hemodynamic changes in drug-resistant epilepsy - A multimodal MREG study

Objective

Epilepsy causes measurable irregularity over a range of brain signal frequencies, as well as autonomic nervous system functions that modulate heart and respiratory rate variability. Imaging dynamic neuronal signals utilizing simultaneously acquired ultra-fast 10 Hz magnetic resonance encephalography (MREG), direct current electroencephalography (DC-EEG), and near-infrared spectroscopy (NIRS) can provide a more comprehensive picture of human brain function. Spectral entropy (SE) is a nonlinear method to summarize signal power irregularity over measured frequencies. SE was used as a joint measure to study whether spectral signal irregularity over a range of brain signal frequencies based on synchronous multimodal brain signals could provide new insights in the neural underpinnings of epileptiform activity.

Methods

Ten patients with focal drug-resistant epilepsy (DRE) and ten healthy controls (HC) were scanned with 10 Hz MREG sequence in combination with EEG, NIRS (measuring oxygenated, deoxygenated, and total hemoglobin: HbO, Hb, and HbT, respectively), and cardiorespiratory signals. After pre-processing, voxelwise SE_MREG was estimated from MREG data. Different neurophysiological and physiological subfrequency band signals were further estimated from MREG, DC-EEG, and NIRS: fullband (0–5 Hz, FB), near FB (0.08–5 Hz, NFB), brain pulsations in very-low (0.009–0.08 Hz, VLFP), respiratory (0.12–0.4 Hz, RFP), and cardiac (0.7–1.6 Hz, CFP) frequency bands. Global dynamic fluctuations in MREG and NIRS were analyzed in windows of 2 min with 50% overlap.

Results

Right thalamus, cingulate gyrus, inferior frontal gyrus, and frontal pole showed significantly higher SE_MREG in DRE patients compared to HC. In DRE patients, SE of cortical Hb was significantly reduced in FB (p = .045), NFB (p = .017), and CFP (p = .038), while both HbO and HbT were significantly reduced in RFP (p = .038, p = .045, respectively). Dynamic SE of HbT was reduced in DRE patients in RFP during minutes 2 to 6. Fitting to the frontal MREG and NIRS results, DRE patients showed a significant increase in SE_EEG in FB in fronto-central and parieto-occipital regions, in VLFP in parieto-central region, accompanied with a significant decrease in RFP in frontal pole and parietal and occipital (O2, Oz) regions.

Conclusion

This is the first study to show altered spectral entropy from synchronous MREG, EEG, and NIRS in DRE patients. Higher SE_MREG in DRE patients in anterior cingulate gyrus together with SE_EEG and SE_NIRS results in 0.12–0.4 Hz can be linked to altered parasympathetic function and respiratory pulsations in the brain. Higher SE_MREG in thalamus in DRE patients is connected to disturbances in anatomical and functional connections in epilepsy. Findings suggest that spectral irregularity of both electrophysiological and hemodynamic signals are altered in specific way depending on the physiological frequency range.

•

Simultaneous imaging methods indicate spectral irregularity in neurovascular and electrophysiological brain pulsations in DRE.

•

Altered spectral entropy in EEG, NIRS and BOLD indicate dysfunctional brain pulsations in respiratory frequency in epilepsy.

•

Spectral irregularity (0-5 Hz) of BOLD in right thalamus supports previous structural and functional findings in epilepsy.

Pilomotor seizures marked by infraslow activity and acetazolamide responsiveness

A patient with pilomotor seizures post anti‐LGI1 limbic encephalitis, refractory to immunotherapy and anti‐epileptic drugs, was investigated with electroencephalography and magnetoencephalography. Seizures occurred daily (14.9 ± 4.9/day), with catamenial exacerbation, inducible by hyperventilation. Anterior temporal ictal onsets were heralded (by ~15 sec) by high amplitude ipsilateral electromagnetic infraslow activity. The catamenial/ventilatory sensitivity and the infraslow activity (reflecting glial depolarization) suggested an ionic, CO₂/pH‐related glioneuronal mechanism. Furosemide decreased seizure frequency by ~33%. Acetazolamide led to immediate seizure freedom, but lost efficacy with daily treatment. A cycling acetazolamide regimen (2 days on, 4 days off) plus low‐dose topiramate maintained >95% reduction (0.5 ± 0.9/day) in seizures.

Short "Infraslow" Activity (SISA) With Burst Suppression in Acute Anoxic Encephalopathy: A Rare, Specific Ominous Sign With Acute Posthypoxic Myoclonus or Acute Symptomatic Seizures

OBJECTIVE

Slow wave with frequency <0.5 Hz are recorded in various situations such as normal sleep, epileptic seizures. However, its clinical significance has not been fully clarified. Although infra-slow activity was recently defined as activity between 0.01 and 0.1 Hz, we focus on the activity recorded with time constant of 2 seconds for practical usage. We defined short "infraslow" activity (SISA) less than 0.5 Hz recorded with time constant of 2 seconds and investigated the occurrence and clinical significance of SISA in acute anoxic encephalopathy.

METHODS

This study evaluated the findings of electroencephalography in consecutive 98 comatose patients with acute anoxic encephalopathy after cardiac arrest. We first classified electroencephalography findings conventionally, then investigated SISA by time constant of 2 second and a high-cut filter of 120 Hz, to clarify the relationship between SISA and clinical profiles, especially of clinical outcomes and occurrence of acute posthypoxic myoclonus or acute symptomatic seizures.

RESULTS

Short infra-slow activity was found in six patients (6.2%), superimposed on the burst phase of the burst-suppression pattern. All six patients showed acute posthypoxic myoclonus or acute symptomatic seizures (generalized tonic-clonic seizures) and its prognosis was poor. This 100% occurrence of acute posthypoxic myoclonus or acute symptomatic seizures was significantly higher than that in patients without SISA (39.1%; P < 0.05).

CONCLUSIONS

Short infra-slow activity in acute anoxic encephalopathy could be associated with acute posthypoxic myoclonus and acute symptomatic seizures. Short infra-slow activity could be a practically feasible biomarker for myoclonus or seizures and poor prognosis in acute anoxic encephalopathy, if it occurs with burst suppression.

How do we use in vitro models to understand epileptiform and ictal activity? A report of the TASK1-WG4 group of the ILAE/AES Joint Translational Task Force

In vitro brain tissue preparations allow the convenient and affordable study of brain networks and have allowed us to garner molecular, cellular, and electrophysiologic insights into brain function with a detail not achievable in vivo. Preparations from both rodent and human postsurgical tissue have been utilized to generate in vitro electrical activity similar to electrographic activity seen in patients with epilepsy. A great deal of knowledge about how brain networks generate various forms of epileptiform activity has been gained, but due to the multiple in vitro models and manipulations used, there is a need for a standardization across studies. Here, we describe epileptiform patterns generated using in vitro brain preparations, focusing on issues and best practices pertaining to recording, reporting, and interpretation of the electrophysiologic patterns observed. We also discuss criteria for defining in vitro seizure‐like patterns (i.e., ictal) and interictal discharges. Unifying terminologies and definitions are proposed. We suggest a set of best practices for reporting in vitro studies to favor both efficient across‐lab comparisons and translation to in vivo models and human studies.

A companion to the preclinical common data elements and case report forms for rodent EEG studies. A report of the TASK3 EEG Working Group of the ILAE/AES Joint Translational Task Force

Electroencephalography (EEG) is commonly used in epilepsy and neuroscience research to study brain activity. The principles of EEG recording such as signal acquisition, digitization, and conditioning share similarities between animal and clinical EEG systems. In contrast, preclinical EEG studies demonstrate more variability and diversity than clinical studies in the types and locations of EEG electrodes, methods of data analysis, and scoring of EEG patterns and associated behaviors. The TASK3 EEG working group of the International League Against Epilepsy/American Epilepsy Society (ILAE/AES) Joint Translational Task Force has developed a set of preclinical common data elements (CDEs) and case report forms (CRFs) for recording, analysis, and scoring of animal EEG studies. This companion document accompanies the first set of proposed preclinical EEG CRFs and is intended to clarify the CDEs included in these worksheets. We provide 7 CRF and accompanying CDE modules for use by the research community, covering video acquisition, electrode information, experimental scheduling, and scoring of EEG activity. For ease of use, all data elements and input ranges are defined in supporting Excel charts (Appendix S1).

Uncensored EEG: The role of DC potentials in neurobiology of the brain

Brain direct current (DC) potentials denote sustained shifts and slow deflections of cerebral potentials superimposed with conventional electroencephalography (EEG) waves and reflect alterations in the excitation level of the cerebral cortex and subcortical structures. Using galvanometers, such sustained displacement of the EEG baseline was recorded in the early days of EEG recordings. To stabilize the EEG baseline and eliminate artefacts, EEG was performed later by voltage amplifiers with high-pass filters that dismiss slow DC potentials. This left slow DC potential recordings as a neglected diagnostic source in the routine clinical setting over the last few decades. Brain DC waves may arise from physiological processes or pathological phenomena. Recordings of DC potentials are fundamental electro-clinical signatures of some neurological and psychological disorders and may serve as diagnostic, prognostic, and treatment monitoring tools. We here review the utility of both physiological and pathological brain DC potentials in different aspects of neurological and psychological disorders. This may enhance our understanding of the role of brain DC potentials and improve our fundamental clinical and research strategies for brain disorders.

Pathophysiological mechanisms of migraine and epilepsy: Similarities and differences

Migraine and epilepsy are episodic disorders with distinct features, but they have some clinical and pathophysiological overlaps. We review here clinical overlaps between seizures and migraine attacks, activities of neuronal networks observed during seizures and migraine attacks, and molecular and cellular mechanisms of migraine identified in genetic forms, focusing on genetic variants identified in hemiplegic migraine and their functional effects. Epilepsy and migraine can be generated by dysfunctions of the same neuronal networks, but these dysfunctions can be disease-specific, even if pathogenic mutations target the same protein. Studies of rare monogenic forms have allowed the identification of some molecular/cellular dysfunctions that provide a window on pathological mechanisms: we have begun to disclose the tip of the iceberg.

Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value

PURPOSE

Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ).

METHODS

We computed the PLV between the phase of the amplitude of high gamma activity (80-150Hz) and the phase of lower frequency rhythms (4-30Hz) from ECoG recordings obtained from 10 patients with epilepsy (21 seizures). We extracted five features from the PLV and used a machine learning approach based on logistic regression to build a model that classifies electrodes as SOZ or non-SOZ.

RESULTS

More than 96% of electrodes identified as the SOZ by our algorithm were within the resected area in six seizure-free patients. In four non-seizure-free patients, more than 31% of the identified SOZ electrodes by our algorithm were outside the resected area. In addition, we observed that the seizure outcome in non-seizure-free patients correlated with the number of non-resected SOZ electrodes identified by our algorithm.

CONCLUSION

This machine learning approach, based on features extracted from the PLV, effectively identified electrodes within the SOZ. The approach has the potential to assist clinicians in surgical decision-making when pre-surgical intracranial recordings are utilized.

Characteristics of EEG Seizure-Onset Patterns Recorded From Subdural Electrodes Over MRI-Visible Frontal Focal Cortical Dysplasia Type IIb Lesions

PURPOSE

Focal cortical dysplasia (FCD) is intrinsically epileptogenic, and an MRI-visible lesion typically constitutes the core part of the epileptogenic zone. We aimed to identify ictal EEG patterns that represent the epileptogenic zone by using subdural electrodes placed over the MRI-visible FCD lesion.

METHODS

We selected seven patients with frontal lobe epilepsy caused by pathologically proven FCD type IIb who underwent preoperative intracranial EEG evaluation with subdural electrodes followed by resection surgery with seizure-free outcome. The characteristics of ictal EEG patterns, interictal/ictal high-frequency oscillations, and ictal direct current shifts from intracranial electrodes placed over the MRI-visible lesion were analyzed.

RESULTS

Two seizure-onset patterns (low voltage fast activity and fast spike activity) were identified. Low voltage fast activity was seen in all patients with a lateral frontal lesion, and it was always preceded by preictal spikes. Fast spike activity occurred only in patients with a mesial frontal lesion. Interictal/ictal high-frequency oscillations and ictal direct current shifts were seen in all patients.

CONCLUSIONS

The epileptogenic zone of frontal FCD type IIb may be characterized by EEG seizure-onset patterns consisting of low voltage fast activity and fast spike activity accompanied by ictal high-frequency oscillations and ictal direct current shifts. Further study is needed to determine whether other seizure-onset patterns exist in patients with FCD type IIb.

Direct current electrocorticography for clinical neuromonitoring of spreading depolarizations

Spreading depolarizations cause cortical electrical potential changes over a wide spectral range that includes slow potentials approaching the direct current (or 0 Hz) level. The negative direct current shift (<0.05 Hz) is an important identifier of cortical depolarization and its duration is a measure of potential tissue injury associated with longer lasting depolarizations. To determine the feasibility of monitoring the full signal bandwidth of spreading depolarizations in patients, we performed subdural electrocorticography using platinum electrode strips and direct current-coupled amplifiers in 27 patients with acute brain injury at two neurosurgical centers. While large baseline direct current offsets developed, loss of data due to amplifier saturation was minimal and rates of baseline drift throughout recordings were generally low. Transient negative direct current shifts of spreading depolarizations were easily recognized and in 306/551 (56%) cases had stereotyped, measurable characteristics. Following a standardized training session, novice scorers achieved a high degree of accuracy and interobserver reliability in identifying depolarizations, suggesting that direct current-coupled recordings can facilitate bedside diagnosis for future trials or clinical decision-making. We conclude that intracranial monitoring of slow potentials can be achieved with platinum electrodes and that unfiltered, direct current-coupled recordings are advantageous for identifying and assessing the impact of spreading depolarizations.

Interictal Infraslow Activity in Stereoelectroencephalography: From Focus to Network

PURPOSE

Infraslow activity (ISA) occurring during the interictal state in focal epilepsy is largely unstudied. In this exploratory analysis, the authors aimed to characterize features of interictal ISA in a cohort of patients studied by stereoelectroencephography.

METHODS

The interictal stereoelectroencephography records for 15 consecutive adult patients were retrospectively analyzed, after application of both conventional (1.6-70 Hz) and infraslow (0.01-0.1 Hz) bandpass filters. Visual analysis was complemented by time-frequency analysis to quantify the change in ISA power over hours. Linear correlation coefficient (R) calculations were used to map interictal connectivity in the infraslow band.

RESULTS

Interictal ISA background fluctuations were present throughout the interictal state in all patients, manifesting as recurrent and stereotyped oscillations. These oscillations had an apparent modulatory effect on conventional-band activities and spikes ("spike-crested oscillations"). In the infraslow band, the correlations between electrode contacts were shown to have a stable structure over time.

CONCLUSIONS

Infraslow activity exists as a fundamental component of wideband cortical dynamics in focal epilepsy, with features suggestive of scale-free (1/f) dynamics: evidence of phase-amplitude coupling and functional connectivity in the infraslow band. Rather than viewed as a focal paroxysmal activity, interictal ISA may be better understood as a network process, although this requires further study.