Interictal discharges in the human brain are travelling waves arising from an epileptogenic source.

While seizure activity may be electrographically widespread, increasing evidence has suggested that ictal discharges may in fact represent travelling waves propagated from a focal seizure source. Interictal epileptiform discharges (IEDs) are an electrographic manifestation of excessive hypersynchronization of cortical activity that occur between seizures and are considered a marker of potentially epileptogenic tissue. The precise relationship between brain regions demonstrating IEDs and those involved in seizure onset, however, remains poorly understood. Here, we hypothesize that IEDs likewise reflect the receipt of travelling waves propagated from the same regions which give rise to seizures. Forty patients from our institution who underwent invasive monitoring for epilepsy, proceeded to surgery and had at least one year of follow-up were included in our study. Interictal epileptiform discharges were detected using custom software, validated by a clinical epileptologist. We show that IEDs reach electrodes in sequences with a consistent temporal ordering, and this ordering matches the timing of receipt of ictal discharges, suggesting that both types of discharges spread as travelling waves. We use a novel approach for localization of ictal discharges, in which time differences of discharge receipt at nearby electrodes are used to compute source location; similar algorithms have been used in acoustics and geophysics. We find that interictal discharges co-localize with ictal discharges. Moreover, interictal discharges tend to localize to the resection territory in patients with good surgical outcome and outside of the resection territory in patients with poor outcome. The seizure source may originate at, and also travel to, spatially distinct IED foci. Our data provide evidence that interictal discharges may represent travelling waves of pathological activity that are similar to their ictal counterparts, and that both ictal and interictal discharges emerge from common epileptogenic brain regions. Our findings have important clinical implications, as they suggest that seizure source localizations may be derived from interictal discharges, which are much more frequent than seizures.

Slow wave sleep is associated with forgetting in patients with temporal lobe epilepsy.

While time spent in slow wave sleep (SWS) after learning promotes memory consolidation in the healthy brain, it is unclear if the same benefit is obtained in patients with temporal lobe epilepsy (TLE). Interictal epileptiform discharges (IEDs) are potentiated during SWS and thus may disrupt memory consolidation processes thought to depend on hippocampal-neocortical interactions. Here, we explored the relationship between SWS, IEDs, and overnight forgetting in patients with TLE. Nineteen patients with TLE studied object-scene pairs and memory was tested across a day of wakefulness (6 hrs) and across a night of sleep (16 hrs) while undergoing continuous scalp EEG monitoring. We found that time spent in SWS after learning was related to greater forgetting overnight. Longer duration in SWS and number of IEDs were each associated with greater forgetting, although the number of IEDs did not mediate the relationship between SWS and memory. Further research, particularly with intracranial recordings, is required to identify the mechanisms by which SWS and IEDs can be pathological to sleep-dependent memory consolidation in patients with TLE.

Identification and classification of pathology and artifacts for human intracranial cognitive research.

Intracranial electroencephalography (iEEG) presents a unique opportunity to extend human neuroscientific understanding. However, typically iEEG is collected from patients diagnosed with focal drug-resistant epilepsy (DRE) and contains transient bursts of pathological activity. This activity disrupts performances on cognitive tasks and can distort findings from human neurophysiology studies. In addition to manual marking by a trained expert, numerous IED detectors have been developed to identify these pathological events. Even so, the versatility and usefulness of these detectors is limited by training on small datasets, incomplete performance metrics, and lack of generalizability to iEEG. Here, we employed a large annotated public iEEG dataset from two institutions to train a random forest classifier (RFC) to distinguish data segments as either 'non-cerebral artifact' (n = 73,902), 'pathological activity' (n = 67,797), or 'physiological activity' (n = 151,290). We found our model performed with an accuracy of 0.941, specificity of 0.950, sensitivity of 0.908, precision of 0.911, and F1 score of 0.910, averaged across all three event types. We extended the generalizability of our model to continuous bipolar data collected in a task-state at a different institution with a lower sampling rate and found our model performed with an accuracy of 0.789, specificity of 0.806, and sensitivity of 0.742, averaged across all three event types. Additionally, we created a custom graphical user interface to implement our classifier and enhance usability.

Latencies to the first interictal epileptiform discharges recorded by the electroencephalography in different epileptic patients.

PURPOSE: Interictal epileptiform discharges (IEDs) captured in electroencephalography (EEG) have a high diagnostic value for epileptic patients. Extending the recording time may increase the possibility of obtaining IEDs. The purpose of our research was to determine how long it took for various epileptic individuals to receive their first IEDs. METHODS: We retrospectively analyzed patients who were diagnosed with epilepsy and had no anti-seizure medications (ASMs) between September 2018 and March 2019 in the neurology department of the First Affiliated Hospital of Xi'an Jiaotong University. Each individual underwent a 24-h long-term video electroencephalographic monitoring (VEM) procedure. Clinical information including age, gender, age of seizure onset, frequency of seizures, the interval between last seizure and VEM, and results of neuroimaging were gathered. We also calculated the times from the start of the VEM to the first definite IEDs. RESULTS: A total of 241 patients were examined, including 191 with focal-onset epilepsy and 50 with generalized epilepsy. In individuals with focal-onset epilepsy, the median latency to the first IED was 63.0 min (IQR 19.0-299.0 min), as compared to 30.0 min (IQR 12.5-62.0 min) in patients with generalized epilepsy (p < 0.001). The latency to the first IED is significantly related to the age of seizure onset (HR = 0.988, p = 0.049), the interval between last seizure and VEM (HR = 0.998, p = 0.013). But it is not correlated with seizure frequency, gender and age. CONCLUSIONS: IEDs were discovered during 24-h EEG monitoring in 222/241(92.1%) of the epilepsy patients that were included. Compared to focal-onset epilepsy, generalized epilepsy demonstrated a much shorter latency to IED. Patients with late-onset epilepsy or those without recent episodes may require longer EEG monitoring periods.

The role of interictal discharges in ictogenesis - A dynamical perspective.

Interictal epileptiform discharge (IED) is a traditional hallmark of epileptic tissue that is generated by the synchronous activity of a population of neurons. Interictal epileptiform discharges represent a heterogeneous group of pathological activities that differ in shape, duration, spatiotemporal distribution, underlying cellular and network mechanisms, and their relationship to seizure genesis. The exact role of IEDs in epilepsy is still not well understood, and there remains a persistent dichotomy about the impact on IEDs on seizures. Proseizure, antiseizure, and no impact on ictogenesis have all been described in previous studies. In this article, we review the existing knowledge on the role of interictal discharges in seizure genesis, and we discuss how dynamical approaches to ictogenesis can explain the existing dichotomy about the multifaceted role of IEDs in ictogenesis. This article is part of the Special Issue "NEWroscience 2018".

Interictal epileptiform discharges shape large-scale intercortical communication.

Dynamic interactions between remote but functionally specialized brain regions enable complex information processing. This intercortical communication is disrupted in the neural networks of patients with focal epilepsy, and epileptic activity can exert widespread effects within the brain. Using large-scale human intracranial electroencephalography recordings, we show that interictal epileptiform discharges (IEDs) are significantly coupled with spindles in discrete, individualized brain regions outside of the epileptic network. We found that a substantial proportion of these localized spindles travel across the cortical surface. Brain regions that participate in this IED-driven oscillatory coupling express spindles that have a broader spatial extent and higher tendency to propagate than spindles occurring in uncoupled regions. These altered spatiotemporal oscillatory properties identify areas that are shaped by epileptic activity independent of IED or seizure detection. Our findings suggest that IED-spindle coupling may be an important mechanism of interictal global network dysfunction that could be targeted to prevent disruption of normal neural activity.

Diagnostic yield of seizure recordings and neuroimaging in patients with focal epilepsy without interictal epileptiform discharges.

OBJECTIVE: Repeated routine electroencephalography (EEG) or even long-term video-EEG monitoring (VEM) does not always record interictal epileptiform discharges (IEDs) in some patients with epilepsy. The present study investigated whether focal seizures detected by VEM and focal abnormalities on neuroimaging are useful for the diagnosis of patients with focal epilepsy without IEDs. METHODS: We retrospectively reviewed 409 consecutive patients with focal epilepsy (207 men, aged 9 to 76 years) who underwent 4- or 5-day VEM, magnetic resonance imaging (MRI), and fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) for diagnosis to identify patients without IEDs. The occurrence of focal seizures during VEM and the presence of focal abnormalities on neuroimaging were investigated in those patients. The occurrence rate of seizures during VEM was investigated in patients with daily, weekly, monthly, and yearly seizure frequency based on history-taking. RESULTS: Ninety-five (23.2%) of 409 patients with focal epilepsy did not have IEDs. Fifty-five (57.9%) of the 95 patients had focal seizures during VEM. Fifty-four patients (56.8%) showed focal abnormalities compatible with seizure semiology on neuroimaging investigations. Neither seizure recordings nor neuroimaging abnormalities were seen in 16 (16.8%) of the 95 patients. The occurrence rate of seizures during VEM depended on the seizure frequency at history-taking. However, 28 (45.9%) of 61 patients with monthly and yearly seizure frequency had focal seizures during 4- or 5-day VEM with seizure induction. CONCLUSIONS: Video-EEG monitoring can detect focal seizures in patients with focal epilepsy but no IEDs. Comprehensive assessment including VEM and neuroimaging study is important for the diagnosis.

Anti-epileptic drugs improved serial 7s scores on the Mini-Mental State Examination in elderly with cognitive impairment and epileptiform discharge on electroencephalography.

AIM: As the population ages, epilepsy among elderly people is increasing. Epileptic seizures in the elderly are mostly complex partial seizures without convulsions, so more caution is needed in the diagnosis of epilepsy. If epileptic seizures in the context of memory impairment are overlooked, epilepsy may be misdiagnosed as dementia. However, in older patients with epilepsy, there is a possibility that cognitive function may be impaired in the interictal phase. This study aims to investigate the efficacy of anti-epileptic drug (AED) treatment for patients with cognitive impairment and interictal epileptiform discharge (IED) on electroencephalography. METHODS: The outcome of AED administration in 50 patients who exhibited IED was retrospectively investigated. Their cognitive functions were assessed by the Mini-Mental State Examination (MMSE) at both baseline and after AED administration. RESULTS: In all patients who underwent electroencephalography, IED were temporal spikes, and re-examination of the 50 patients revealed that the frequency of temporal spikes had decreased or else disappeared in 41 patients (82%) after AED administration. In these 41 patients, the mean MMSE score significantly increased from 23.4 ± 3.7 at baseline to 24.7 ± 4.8 after AED treatment (P <0.01). Similarly, the mean serial 7s score (MMSE subscale) also improved significantly from 2.5 ± 1.8 to 3.6 ± 1.6 (P <0.01). The MMSE score was significantly improved only in the 41 patients with recovery of IED. CONCLUSION: AED treatment for elderly amnestic patients with temporal spikes was effective in improving cognitive decline and related electroencephalographic abnormalities. A more thorough search of IED is necessary in elderly amnesic patients because there is a possibility that IED modifies cognitive function.

Is it time for individualized testing in the electroencephalogram (EEG) laboratory?

BACKGROUND AND PURPOSE: The interictal electroencephalogram (EEG) has an important role in the classification and treatment of epilepsy. In busy EEG laboratories, valuable resources are used in order to comply with current recommendations regarding the length of EEG recordings. Our aim was to examine the time to first interictal epileptiform discharge (IED) in standard and sleep-deprived EEGs. METHODS: Standard and sleep-deprived EEG recordings with IEDs were retrospectively reviewed during a 2-year period. Bedside EEGs and long-term video-EEGs were excluded. IED latency according to EEG type, age group and inpatient/outpatient status was analyzed with the Kaplan-Meier estimator. RESULTS: The study group included 684 patients, 372 (54%) males, aged 0.2-89 years. Standard (n = 316) and sleep-deprived (n = 368) EEGs were performed in 245 inpatients and 439 outpatients. The EEG was requested in 96% of the inpatients following a seizure. Most IEDs were recorded whilst the patients were awake (43%) or drowsy (34%). Ninety percent of the IEDs were recorded within 18.5 min, earlier in standard (14.6 vs. 21.3 min) (P = 0.024) EEGs and in inpatients (14 vs. 21.3 min) (P = 0.002). IED latency was unaffected by age. CONCLUSIONS: Electroencephalogram type and admission status may be used for individual determination of the duration of EEG recording. Reducing the duration of standard and sleep-deprived EEGs may be considered especially in inpatients.

vEpiNet: A multimodal interictal epileptiform discharge detection method based on video and electroencephalogram data.

To enhance deep learning-based automated interictal epileptiform discharge (IED) detection, this study proposes a multimodal method, vEpiNet, that leverages video and electroencephalogram (EEG) data. Datasets comprise 24 931 IED (from 484 patients) and 166 094 non-IED 4-second video-EEG segments. The video data is processed by the proposed patient detection method, with frame difference and Simple Keypoints (SKPS) capturing patients' movements. EEG data is processed with EfficientNetV2. The video and EEG features are fused via a multilayer perceptron. We developed a comparative model, termed nEpiNet, to test the effectiveness of the video feature in vEpiNet. The 10-fold cross-validation was used for testing. The 10-fold cross-validation showed high areas under the receiver operating characteristic curve (AUROC) in both models, with a slightly superior AUROC (0.9902) in vEpiNet compared to nEpiNet (0.9878). Moreover, to test the model performance in real-world scenarios, we set a prospective test dataset, containing 215 h of raw video-EEG data from 50 patients. The result shows that the vEpiNet achieves an area under the precision-recall curve (AUPRC) of 0.8623, surpassing nEpiNet's 0.8316. Incorporating video data raises precision from 70% (95% CI, 69.8%-70.2%) to 76.6% (95% CI, 74.9%-78.2%) at 80% sensitivity and reduces false positives by nearly a third, with vEpiNet processing one-hour video-EEG data in 5.7 min on average. Our findings indicate that video data can significantly improve the performance and precision of IED detection, especially in prospective real clinic testing. It suggests that vEpiNet is a clinically viable and effective tool for IED analysis in real-world applications.

Interictal discharge traveling waves recorded from stereoelectroencephalography electrodes.

OBJECTIVE: Interictal epileptiform discharges (IEDs) are intermittent high-amplitude electrical signals that occur between seizures. They have been shown to propagate through the brain as traveling waves when recorded with epicortical grid-type electrodes and small penetrating microelectrode arrays. However, little work has been done to translate experimental IED analyses to more clinically relevant platforms such as stereoelectroencephalography (SEEG). In this pilot study, the authors aimed to define a computational method to identify and characterize IEDs recorded from clinical SEEG electrodes and leverage the directionality of IED traveling waves to localize the seizure onset zone (SOZ). METHODS: Continuous SEEG recordings from 15 patients with medically refractory epilepsy were collected, and IEDs were detected by identifying overlapping peaks of a minimum prominence. IED pathways of propagation were defined and compared to the SOZ location determined by a clinical neurologist based on the ictal recordings. For further analysis of the IED pathways of propagation, IED detections were divided into triplets, defined as a set of 3 consecutive contacts within the same IED detection. Univariate and multivariate linear regression models were employed to associate IED characteristics with colocalization to the SOZ. RESULTS: A median (range) of 22.6 (4.4-183.9) IEDs were detected per hour from 15 patients over a mean of 23.2 hours of recording. Depending on the definition of the SOZ, a median (range) of 20.8% (0.0%-54.5%) to 62.1% (19.2%-99.4%) of IEDs per patient traversed the SOZ. IEDs passing through the SOZ followed discrete pathways that had little overlap with those of the IEDs passing outside the SOZ. Contact triplets that occurred more than once were significantly more likely to be detected in an IED passing through the SOZ (p < 0.001). Per our multivariate model, patients with a greater proportion of IED traveling waves had a significantly greater proportion of IEDs that localized to the SOZ (ß = 0.64, 95% CI 0.01-1.27, p = 0.045). CONCLUSIONS: By using computational methods, IEDs can be meaningfully detected from clinical-grade SEEG recordings of patients with epilepsy. In some patients, a high proportion of IEDs are traveling waves according to multiple metrics that colocalize to the SOZ, offering hope that IED detection, with further refinement, could serve as an alternative method for SOZ localization.

Interrater reliability of interictal EEG waveforms in Lennox-Gastaut Syndrome.

OBJECTIVE: Identification of EEG waveforms is critical for diagnosing Lennox-Gastaut Syndrome (LGS) but is complicated by the progressive nature of the disease. Here, we assess the interrater reliability (IRR) among pediatric epileptologists for classifying EEG waveforms associated with LGS. METHODS: A novel automated algorithm was used to objectively identify epochs of EEG with transient high power, which were termed events of interest (EOIs). The algorithm was applied to EEG from 20 LGS subjects and 20 healthy controls during NREM sleep, and 1350 EOIs were identified. Three raters independently reviewed the EOIs within isolated 15-second EEG segments in a randomized, blinded fashion. For each EOI, the raters assigned a waveform label (spike and slow wave, generalized paroxysmal fast activity, seizure, spindle, vertex, muscle, artifact, nothing, or other) and indicated the perceived subject type (LGS or control). RESULTS: Labeling of subject type had 85% accuracy across all EOIs and an IRR of κ =0.790, suggesting that brief segments of EEG containing high-power waveforms can be reliably classified as pathological or normal. Waveform labels were less consistent, with κ =0.558, and the results were highly variable for different categories of waveforms. Label mismatches typically occurred when one reviewer selected "nothing," suggesting that reviewers had different thresholds for applying named labels. SIGNIFICANCE: Classification of EEG waveforms associated with LGS has weak IRR, due in part to varying thresholds applied during visual review. Computational methods to objectively define EEG biomarkers of LGS may improve IRR and aid clinical decision-making.

Therapeutic Strategies in Children with Epilepsy: A Quality-of-Life-Related Perspective.

Back ground: Children with epilepsy are affected by several factors, including clinical and social variables. Among these variables, cognitive decline and behavioral disturbances, perceptions of stigma, and fatigue can lead to reductions in quality of life (QOL). Epileptic activities, including seizure severity, frequent seizures, and status epilepticus (SE), have been identified as important predictors of QOL. In addition, the frequency of interictal epileptiform discharges (IEDs) on electroencephalogram (EEG) may also be an important predictor of QOL, because IEDs can lead to cognitive decline and behavioral disturbances. Moreover, frequent seizures and/or IEDs may play a role in emotional mediators, such as stigma and fatigue, in childhood epilepsy. Seizure severity and/or IEDs are, therefore, important QOL-related factors in childhood epilepsy. Seizure severity as a QOL-related factor: Frontal lobe dysfunctions, such as cognitive decline and behavioral disturbances, can result in reduced QOL for both the child and their family. Frontal and prefrontal lobe growth disturbances can be present during active-phase epilepsy in some children with neuropsychological impairments. Recovery from prefrontal lobe growth disturbances may depend on the active seizure period. Children with a shorter active seizure period can recover from disturbances in prefrontal lobe growth more rapidly. In contrast, recovery may be delayed in children with a longer active seizure period. Moreover, frequent seizures can lead to seizure-associated headaches, perceptions of self-stigma and parental stigma, and fatigue. Accordingly, severe seizures can lead to neuropsychological impairments in association with prefrontal lobe growth disturbances in children with epilepsy. EEG abnormalities as QOL-related factors: IEDs on EEG, representing persistent pathological neuronal discharges, may be associated with several pathological aspects. Frontal IEDs can be a risk factor for recurrent seizures, cognitive decline, and behavioral disturbances, and they may also play a role as emotional mediators similar to stigma. In addition, behavioral disturbances may result in the presence of secondary bilateral synchrony (SBS) on EEG. Behavioral disturbances can be improved in association with a reduction in IEDs in children with frontal IEDs and SBS. Therefore, EEG abnormalities, such as frontal IEDs and SBS, can also lead to neuropsychological impairments in children with epilepsy. Therapeutic strategies in children with epilepsy: Seizure severity and IEDs on EEG may be associated with neuropsychological impairments, leading to QOL reduction. Therapeutic management may be desirable to reduce seizures and EEG abnormalities, such as frontal IEDs and SBS, as early as possible to improve QOL in children with epilepsy. During antiseizure medication (ASM) selection and adjustment, physicians should strategize the therapeutic approach to controlling seizures and suppressing EEG abnormalities in children with epilepsy. Among various ASMs, novel ASMs, such as levetiracetam and perampanel, may suppress both clinical seizures and IEDs on EEG; thus, these novel ASMs may represent an important addition to the treatments available for epileptic children presenting with frontal IEDs and SBS.

V2IED: Dual-view learning framework for detecting events of interictal epileptiform discharges.

Interictal epileptiform discharges (IED) as large intermittent electrophysiological events are associated with various severe brain disorders. Automated IED detection has long been a challenging task, and mainstream methods largely focus on singling out IEDs from backgrounds from the perspective of waveform, leaving normal sharp transients/artifacts with similar waveforms almost unattended. An open issue still remains to accurately detect IED events that directly reflect the abnormalities in brain electrophysiological activities, minimizing the interference from irrelevant sharp transients with similar waveforms only. This study then proposes a dual-view learning framework (namely V2IED) to detect IED events from multi-channel EEG via aggregating features from the two phases: (1) Morphological Feature Learning: directly treating the EEG as a sequence with multiple channels, a 1D-CNN (Convolutional Neural Network) is applied to explicitly learning the deep morphological features; and (2) Spatial Feature Learning: viewing the EEG as a 3D tensor embedding channel topology, a CNN captures the spatial features at each sampling point followed by an LSTM (Long Short-Term Memories) to learn the evolution of these features. Experimental results from a public EEG dataset against the state-of-the-art counterparts indicate that: (1) compared with the existing optimal models, V2IED achieves a larger area under the receiver operating characteristic (ROC) curve in detecting IEDs from normal sharp transients with a 5.25% improvement in accuracy; (2) the introduction of spatial features improves performance by 2.4% in accuracy; and (3) V2IED also performs excellently in distinguishing IEDs from background signals especially benign variants.

The Clinical Utility of Finding Unexpected Subclinical Spikes Detected by High-Density EEG During Neurodiagnostic Investigations.

This study aimed to analyze the frequency of unexpected subclinical spikes (USCS) in pediatric patients who underwent high-density electroencephalogram (HD-EEG). Of the 4481 successful HD-EEG studies, 18.5% (829) were abnormal, and 49.7% of these abnormal studies showed SCS, of which 64.1% were USCS. USCS were found to be correlated with attention/concentration deficits and executive dysfunction, often accompanied by the dual psychiatric diagnosis of ADHD. MRI revealed abnormal findings in 32.6% of the subjects with USCS, such as abnormal signal or signal hyperintensity in brain parenchyma, temporal or arachnoid cysts, and vascular malformations. Moreover, the USCS group who received neuropsychiatric testing scored lower than the population mean on Full-Scale Intelligence Quotient, Working Memory Index, and Processing Speed Index. This study highlights the potential of USCS as biomarkers that can lead to changes in clinical management and outcomes, provide valuable information about pathophysiological mechanisms, and suggest potential treatment pathways.

Sensor selection and miniaturization limits for detection of interictal epileptiform discharges with wearable EEG.

Objective.The goal of this paper is to investigate the limits of electroencephalography (EEG) sensor miniaturization in a set-up consisting of multiple galvanically isolated EEG units to record interictal epileptiform discharges (IEDs), referred to as 'spikes', in people with epilepsy.Approach.A dataset of high-density EEG recordings (257 channels) was used to emulate local EEG sensor units with short inter-electrode distances. A computationally efficient sensor selection and interictal spike detection algorithm was developed and used to assess the influence of the inter-electrode distance and the number of such EEG units on spike detection performance. Signal-to-noise ratio, correlation with a clinical-grade IEDs detector and Cohen's kappa coefficient of agreement were used to quantify performance. Bayesian statistics were used to confirm the statistical significance of the observed results.Main results.We found that EEG recording equipment should be specifically designed to measure the small signal power at short inter-electrode distance by providing an input referred noise<300 nV. We also found that an inter-electrode distance of minimum 5 cm between electrodes in a setup with a minimum of two EEG units is required to obtain near equivalent performance in interictal spike detection to standard EEG.Significance.These findings provide design guidelines for miniaturizing EEG systems for long term ambulatory monitoring of interictal spikes in epilepsy patients.

Investigation of the effect and availability of ketamine on electroencephalography in cats with temporal lobe epilepsy.

In recent years, electroencephalography (EEG) in veterinary medicine has become important not only in the diagnosis of epilepsy, but also in determining the epileptogenic focus. In cats, sedation and immobilization, usually with medetomidine or dexmedetomidine, are necessary to place the electrodes and to obtain stable scalp EEG recordings. In this study, we hypothesized that, for cats with temporal lobe epilepsy (TLE), ketamine, a sedative/anesthetic and N-methyl-D-aspartate (NMDA) antagonist that activates the limbic system and is also used to treat refractory status epilepticus in dogs, would induce sufficient sedation and immobilization for EEG, as well as induce interictal epileptiform discharges (IEDs) that are more pronounced than those induced with medetomidine. We obtained EEG recordings from TLE cats and healthy cats administered either ketamine or medetomidine alone (study 1) or ketamine after medetomidine sedation (study 2). In study 1, the frequency of IEDs showed no statistically significant difference between ketamine and medetomidine in both TLE and healthy cats. Seizures were observed in 75% (9/12) cats of the TLE group with ketamine alone. When ketamine was administered after sedation with medetomidine (study 2), 3/18 cats in the TLE group developed generalized tonic-clonic seizure and 1/18 cats showed subclinical seizure activity. However, no seizures were observed in all healthy cats in both study 1 and study 2. Slow wave activity at 2-4 Hz was observed in many individuals after ketamine administration regardless studies and groups, and quantitative analysis in study 2 showed a trend toward increased delta band activities in both groups. While there was no significant difference in the count of IEDs between medetomidine and ketamine, ketamine caused seizures in cats with TLE similar to their habitual seizure type and with a higher seizure frequency. Our results suggest that ketamine may activate epileptiform discharges during EEG recordings. However, caution should be used for cats with TLE.

Effect of Lacosamide on Interictal Epileptiform Discharges in Pediatric Patients With Newly Diagnosed Focal Epilepsy.

BACKGROUND: The purpose of this study was to determine the efficacy of lacosamide (LCM) on interictal epileptiform discharges (IEDs) and evaluate the relationships between IEDs and seizure outcome in pediatric patients with focal epilepsy. METHODS: Patient inclusion criteria included (1) newly diagnosed focal epilepsy with unknown etiology; and (2) electroencephalogram recorded twice (before and after starting LCM) under the same conditions. The difference between the highest number of IEDs over five successive minutes (IEDs/5 min) and the location of IEDs was determined. Seizure outcome was evaluated one year after achieving the maintenance dose of LCM. Responders were identified as showing a ≥50% reduction in the pre-LCM seizure frequency. RESULTS: Of 22 patients, 10 showed an increase in IEDs/5 min after starting LCM. The median IEDs/5 min before and after starting LCM was not significantly different, at 1.5 (interquartile range: 0, 31.75) and 10.5 (0, 80.5), respectively. No relationship was identified between the difference in IEDs/5 min and seizure outcome. Patients with multiple regional or diffuse IEDs had significantly poorer seizure outcome compared with patients without those IEDs (P = 0.036 and P = 0.039, respectively). Of 10 patients with single regional IEDs, a tendency of IEDs to disappear was observed between patients with frontal and non-frontal IEDs. CONCLUSION: The effects of LCM on the number of IEDs may be unrelated to seizure outcome. LCM may be ineffective at improving seizure outcomes in patients with multiple regional or diffuse IEDs.

Etiology and Clinical Significance of Network Hyperexcitability in Alzheimer's Disease: Unanswered Questions and Next Steps.

Cortical network hyperexcitability related to synaptic dysfunction in Alzheimer's disease (AD) is a potential target for therapeutic intervention. In recent years, there has been increased interest in the prevalence of silent seizures and interictal epileptiform discharges (IEDs, or seizure tendency), with both entities collectively termed "subclinical epileptiform activity" (SEA), on neurophysiologic studies in AD patients. SEA has been demonstrated to be common in AD, with prevalence estimates ranging between 22-54%. Converging lines of basic and clinical evidence imply that modifying a hyperexcitable state results in an improvement in cognition. In particular, though these results require further confirmation, post-hoc findings from a recent phase II clinical trial suggest a therapeutic effect with levetiracetam administration in patients with AD and IEDs. Here, we review key unanswered questions as well as potential clinical trial avenues. Specifically, we discuss postulated mechanisms and treatment of hyperexcitability in patients with AD, which are of interest in designing future disease-modifying therapies. Criteria to prompt screening and optimal screening methodology for hyperexcitability have yet to be defined, as does timing and personalization of therapeutic intervention.

Is epileptiform activity related to developmental language disorder? Findings from the HelSLI study.

Objective: To study if interictal epileptiform discharges (IEDs) are associated with language performance or pre-/perinatal factors in children with developmental language disorder (DLD). Methods: We recorded routine EEG in wake and sleep in 205 children aged 2.9-7.1 years with DLD, without neurologic diseases or intellectual disability. We examined the language performance of the children and collected data on pre-/perinatal factors. Results: Interictal epileptiform discharges were not associated with lower language performance. Children with so-called "rolandic", i.e. centrotemporoparietal, IEDs had better language skills, but age explained this association. Most pre-/perinatal factors evaluated did not increase the risk of rolandic IEDs, except for maternal smoking (OR 4.4, 95% CI 1.4-14). We did not find electrical status epilepticus during slow-wave sleep (ESES)/spike-and-wave activation in sleep (SWAS) in any children. Conclusions: Interictal epileptiform discharges are not associated with lower language performance, and ESES/SWAS is not common in children with DLD. Significance: Routine EEGs do not bring additional information about language performance in children with DLD who do not have any neurologic diseases, seizures, intellectual disability, or regression of language development.