Long-term video-EEG Recordings Research Articles

Alterations in HCN1 expression and distribution during epileptogenesis in rats

BackgroundThe hyperpolarization-activated cyclic nucleotide-gated cation channel (HCN1) is predominantly located in key regions associated with epilepsy, such as the neocortex and hippocampus. Under normal physiological conditions, HCN1 plays a crucial role in the excitatory and inhibitory regulation of neuronal networks. In temporal lobe epilepsy, the expression of HCN1 is decreased in the hippocampi of both animal models and patients. However, whether HCN1 expression changes during epileptogenesis preceding spontaneous seizures remains unclear. ObjectiveThe aim of this study was to determine whether the expression of HCN1 is altered during the epileptic prodromal phase, thereby providing evidence for its role in epileptogenesis. MethodsWe utilized a cobalt wire-induced rat epilepsy model to observe changes in HCN1 during epileptogenesis and epilepsy. Additionally, we also compared HCN1 alterations in epileptogenic tissues between cobalt wire- and pilocarpine-induced epilepsy rat models. Long-term video EEG recordings were used to confirm seizures development. Transcriptional changes, translation, and distribution of HCN1 were assessed using high-throughput transcriptome sequencing, total protein extraction, membrane and cytoplasmic protein fractionation, western blotting, immunohistochemistry, and immunofluorescence techniques. ResultsIn the cobalt wire-induced rat epilepsy model during the epileptogenesis phase, total HCN1 mRNA and protein levels were downregulated. Specifically, the membrane expression of HCN1 was decreased, whereas cytoplasmic HCN1 expression showed no significant change. The distribution of HCN1 in the distal dendrites of neurons decreased. During the epilepsy period, similar HCN1 alterations were observed in the neocortex of rats with cobalt wire-induced epilepsy and hippocampus of rats with lithium pilocarpine-induced epilepsy, including downregulation of mRNA levels, decreased total protein expression, decreased membrane expression, and decreased distal dendrite expression. ConclusionsAlterations in HCN1 expression and distribution are involved in epileptogenesis beyond their association with seizure occurrence. Similarities in HCN1 alterations observed in epileptogenesis-related tissues from different models suggest a shared pathophysiological pathway in epileptogenesis involving HCN1 dysregulation. Therefore, the upregulation of HCN1 expression in neurons, maintenance of the HCN1 membrane, and distal dendrite distribution in neurons may represent promising disease-modifying strategies in epilepsy.

EDeeplepsy: An artificial neural framework to reveal different brain states in children with epileptic spasms

ObjectiveDespite advances, analysis and interpretation of EEG still essentially rely on visual inspection by a super-specialized physician. Considering the vast amount of data that composes the EEG, much of the detail inevitably escapes ordinary human scrutiny. Significant information may not be evident and is missed, and misinterpretation remains a serious problem. Can we develop an artificial intelligence system to accurately and efficiently classify EEG and even reveal novel information? In this study, deep learning techniques and, in particular, Convolutional Neural Networks, have been used to develop a model (which we have named eDeeplepsy) for distinguishing different brain states in children with epilepsy. MethodsA novel EEG database from a homogenous pediatric population with epileptic spasms beyond infancy was constituted by epileptologists, representing a particularly intriguing seizure type and challenging EEG. The analysis was performed on such samples from long-term video-EEG recordings, previously coded as images showing how different parts of the epileptic brain are distinctly activated during varying states within and around this seizure type. ResultsResults show that not only could eDeeplepsy differentiate ictal from interictal states but also discriminate brain activity between spasms within a cluster from activity away from clusters, usually undifferentiated by visual inspection. Accuracies between 86 % and 94 % were obtained for the proposed use cases. SignificanceWe present a model for computer-assisted discrimination that can consistently detect subtle differences in the various brain states of children with epileptic spasms, and which can be used in other settings in epilepsy with the purpose of reducing workload and discrepancies or misinterpretations. The research also reveals previously undisclosed information that allows for a better understanding of the pathophysiology and evolving characteristics of this particular seizure type. It does so by documenting a different state (interspasms) that indicates a potentially non-standard signal with distinctive epileptogenicity at that period.

First Clinical Experiences with the New DICOM Neurophysiology Standard.

Exchange of EEG data among institutions is complicated due to vendor-specific proprietary EEG file formats. The DICOM standard, which has long been used for storage and exchange of imaging studies, was expanded to store neurophysiology data in 2020. To implement DICOM as an interoperable and vendor-independent storage format for EEG recordings in the Clinic Hietzing. A pilot implementation for automated conversion of EEG data from a proprietary to standardized DICOM format was developed. Additionally, EEG review based on a central DICOM archive in a DICOM EEG viewer (encevis by AIT) was implemented. More than 200 long-term video EEG recordings and over 3000 routine EEGs were archived to the central DICOM archive of the WIGEV. Using DICOM as a storage format for EEG data is feasible and leads to a substantial improvement of interoperability and facilitates data exchange between institutions.

EEG Analysis of Eye Movement Artifact in Parietal and Occipital Lobe Seizures: A Search for Epileptic Nystagmus (P10-1.011)

<h3>Objective:</h3> To report a method of eye movement artifact analysis on EEG without EOG electrodes, and to identify a characteristic eye movement artifact in parietal and occipital lobe seizures, consistent with Epileptic nystagmus (EN). <h3>Background:</h3> EN is a rarely reported seizure semiology, most commonly associated with seizures originating in the posterior cortical regions. EN is often easily missed in long-term video-EEG (vEEG) recordings because of multiple reasons such as poor camera resolution or camera not focused on the eyes. <h3>Design/Methods:</h3> We performed a retrospective vEEG analysis of three patients with occipital and parietal lobe seizures. The eyes were not clearly visible in any of the patients. We analyzed 30 seconds of pre-ictal EEG for any unusual eye movements, followed by the ictal EEG. We identified epochs of unilaterally directed repetitive saccadic eye movement artifacts (≥5 saccades) during the ictus. We analyzed these eye movements in a longitudinal bipolar montage with increased time constant (TC) of ≥2 seconds. <h3>Results:</h3> In all three patients, there was no specific pattern of repetitive saccadic eye movement artifact in the pre-ictal period. During the ictus, all of the patients showed repetitive contralaterally directed saccadic eye movements. When analyzed with TC≥2 seconds, the saccades were alternating with linear slow phases directed ipsilateral to the seizure focus. In one patient, there was a clear prolonged slow drift ipsilateral to the seizure focus before the onset of nystagmus, consistent with type II EN. <h3>Conclusions:</h3> EN is likely under-reported because of either lack of video evidence or lack of special EOG electrodes. Our study demonstrates a specific pattern of eye movement artifact seen on EEG in parietal and occipital seizures, consistent with EN. We also report a method to identify the slow and fast phases of EN on EEG, which can also delineate the underlying mechanism of EN (type I v type II). <b>Disclosure:</b> Dr. Acar has nothing to disclose. Dr. Zampino has nothing to disclose. Dr. Kirsch has nothing to disclose. Dr. Fotedar has nothing to disclose.

Robust, long-term video EEG monitoring in a porcine model of post-traumatic epilepsy.

To date, post-traumatic epilepsy (PTE) research in large-animal models has been limited. Recent advances in neocortical microscopy have made possible new insights into neocortical PTE. However, it is very difficult to engender convincing neocortical PTE in rodents. Thus, large-animal models that develop neocortical PTE may provide useful insights that also can be more comparable to human patients. Because gyrencephalic species have prolonged latent periods, long-term video EEG recording is required. Here, we report a fully subcutaneous EEG implant with synchronized video in freely ambulatory swine for up to 13 months during epileptogenesis following bilateral cortical impact injuries or sham surgery The advantages of this system include the availability of a commercially available system that is simple to install, a low failure rate after surgery for EEG implantation, radiotelemetry that enables continuous monitoring of freely ambulating animals, excellent synchronization to video to EEG, and a robust signal-to-noise ratio. The disadvantages of this system in this species and age are the accretion of skull bone, which entirely embedded a subset of skull screws and EEG electrodes, and the inability to rearrange the EEG electrode array. These disadvantages may be overcome by splicing a subdural electrode strip to the electrode leads so that skull growth is less likely to interfere with long-term signal capture and by placing two implants for a more extensive montage. This commercially available system in this bilateral cortical impact swine model may be useful to a wide range of investigators studying epileptogenesis in PTE.

A Role for Insulin-like Growth Factor 1 in the Generation of Epileptic Spasms in a murine model.

Infantile spasms are associated with a wide variety of clinical conditions, including perinatal brain injuries. We have created a model in which prolonged infusion of tetrodotoxin (TTX) into the neocortex, beginning in infancy, produces a localized lesion and reproduces the behavioral spasms, electroencephalogram (EEG) abnormalities, and drug responsiveness seen clinically. Here, we undertook experiments to explore the possibility that the growth factor IGF-1 plays a role in generating epileptic spasms. We combined long-term video EEG recordings with quantitative immunohistochemical and biochemical analyses to unravel IGF-1's role in spasm generation. Immunohistochemistry was undertaken in surgically resected tissue from infantile spasms patients. We used viral injections in neonatal conditional IGF-1R knock-out mice to show that an IGF-1-derived tripeptide (1-3)IGF-1, acts through the IGF-1 receptor to abolish spasms. Immunohistochemical methods revealed widespread loss of IGF-1 from cortical neurons, but an increase in IGF-1 in the reactive astrocytes in the TTX-induced lesion. Very similar changes were observed in the neocortex from patients with spasms. In animals, we observed reduced signaling through the IGF-1 growth pathways in areas remote from the lesion. To show the reduction in IGF-1 expression plays a role in spasm generation, epileptic rats were treated with (1-3)IGF-1. We provide 3 lines of evidence that (1-3)IGF-1 activates the IGF-1 signaling pathway by acting through the receptor for IGF-1. Treatment with (1-3)IGF-1 abolished spasms and hypsarrhythmia-like activity in the majority of animals. Results implicate IGF-1 in the pathogenesis of infantile spasms and IGF-1 analogues as potential novel therapies for this neurodevelopmental disorder. ANN NEUROL 2022;92:45-60.

Vasovagal Syncope in Epilepsy Monitoring Unit: A Case Report and Review

ABSTRACT Falls are a common adverse event (AE) in general hospital admissions and in the epilepsy monitoring unit (EMU) and can cause serious physical injury for patients; however, fall prevention policies widely vary between epilepsy centers. Patient safety, including minimizing AEs, such as falls, continue to be a major goal of quality improvement in the EMU. The bathroom area in an EMU is highly prone for falls due to the need for patient privacy. Syncope is a physiologic non-epileptic event with high prevalence in general population and is a potential cause for fall. It is also reported in people diagnosed with epilepsy. We report a case of vasovagal syncope (VVS) associated with injury in a young female during long-term video EEG recording in our EMU facility. We also briefly address concerns for identifying patients at risk for syncope and its prevention. A multidisciplinary team including EEG technologists can play a vital role in educating patients and caretakers about the risk factors of syncopal fall and its preventive measures.

The influence of the abundance and morphology of epileptiform discharges on diagnostic accuracy: How many spikes you need to spot in an EEG

ObjectiveThe operational definition of interictal epileptiform discharges (IEDs) of the International Federation of Clinical Neurophysiology (IFCN) described six morphological criteria. Our objective was to assess the impact of pattern-repetition in the EEG-recording, on the diagnostic accuracy of using the IFCN criteria. For clinical implementation, specificity over 95% was set as target. MethodsInterictal EEG-recordings of 20-minutes, containing sharp-transients, from 60 patients (30 with epilepsy and 30 with non-epileptic paroxysmal events) were evaluated by three experts, who first marked IEDs solely based on expert opinion, and then, independently from the first session evaluated the presence of the IFCN criteria for each sharp-transient. The gold standard was derived from long-term video-EEG recordings of the patientś habitual paroxysmal episodes. ResultsPresence of at least one discharge fulfilling five criteria provided a specificity of 100% (sensitivity: 70%). For discharges fulfilling fewer criteria, a higher number of discharges was needed to keep the specificity over 95% (5 discharges, when only 3 criteria were fulfilled). A sequential combination of these sets of criteria and thresholds provided a specificity of 97% and sensitivity of 80%. ConclusionsPattern-repetition and IED morphology influence diagnostic accuracy. SignificanceSystematic application of these criteria will improve quality of clinical EEG interpretation.

Integrating old and new complexity measures toward automated seizure detection from long-term video EEG recordings

SummaryAutomated seizure detection in long-term video-EEG recordings is far from being integrated into common clinical practice. Here, we leverage classical and state-of-the-art complexity measures to robustly and automatically detect seizures from scalp recordings. Brain activity is scored through eight features, encompassing traditional time domain and novel measures of recurrence. A binary classification algorithm tailored to treat unbalanced dataset is used to determine whether a time window is ictal or non-ictal from its features. The application of the algorithm on a cohort of ten adult patients with focal refractory epilepsy indicates sensitivity, specificity, and accuracy of 90%, along with a true alarm rate of 95% and less than four false alarms per day. The proposed approach emphasizes ictal patterns against noisy background without the need of data preprocessing. Finally, we benchmark our approach against previous studies on two publicly available datasets, demonstrating the good performance of our algorithm.

Periictal electroclinical characteristics of postictal generalized electroencephalographic suppression after generalized convulsive seizures.

The aim of this study was to investigate the demographic, clinical, and electrophysiological characteristics of postictal generalized electroencephalography (EEG) suppression (PGES), thereby facilitating the recognition of PGES and providing clues regarding its risk factors, pathophysiology, and relationship with sudden unexpected death in epilepsy patients (SUDEP).We retrospectively reviewed 237 generalized convulsive seizures (GCSs) in 126 patients during long-term video-EEG (VEEG) recordings. The associations of PGES and prolonged PGES (duration >20 seconds) with person- and seizure-specific variables were evaluated independently using SPSS software.Eighty patients (63.5%, 80/126) exhibited PGES after 127 GCSs (53.6%, 127/237) with an average PGES duration of 41.31 ± 24.03 seconds. The tonic phase was significantly prolonged in patients with PGES and prolonged PGES. PGES was independently associated with ictal semiology, which was attributable to the different proportions of GCS type 1. After seizure termination, patients with PGES had a higher percentage of postictal unresponsiveness and immobility, including oropharyngeal immobility. Between prolonged and short-duration PGES, the former was more likely to phase out gradually followed by immediate body movement, whereas the latter tended to have an abrupt, evoked termination followed by delayed body movement.Prolonged tonic duration, GCS type 1, postictal unresponsiveness, and immobility were more prone to occur with PGES, which might imply that hyperactivation of inhibitory neural networks underlies the pathophysiology of PGES and subsequent SUDEP. Any form of periictal bedside care, whether it constitutes effective medical intervention or not, is advisable due to its possible contribution to the interruption of PGES. Regardless of the PGES termination pattern, the neural network resuscitation process was progressive.

Visual seizure annotation and automated seizure detection using behind‐the‐ear electroencephalographic channels

ObjectiveSeizure diaries kept by patients are unreliable. Automated electroencephalography (EEG)‐based seizure detection systems are a useful support tool to objectively detect and register seizures during long‐term video‐EEG recording. However, this standard full scalp‐EEG recording setup is of limited use outside the hospital, and a discreet, wearable device is needed for capturing seizures in the home setting. We are developing a wearable device that records EEG with behind‐the‐ear electrodes. In this study, we determined whether the recognition of ictal patterns using only behind‐the‐ear EEG channels is possible. Second, an automated seizure detection algorithm was developed using only those behind‐the‐ear EEG channels.MethodsFifty‐four patients with a total of 182 seizures, mostly temporal lobe epilepsy (TLE), and 5284 hours of data, were recorded with a standard video‐EEG at University Hospital Leuven. In addition, extra behind‐the‐ear EEG channels were recorded. First, a neurologist was asked to annotate behind‐the‐ear EEG segments containing selected seizure and nonseizure fragments. Second, a data‐driven algorithm was developed using only behind‐the‐ear EEG. This algorithm was trained using data from other patients (patient‐independent model) or from the same patient (patient‐specific model).ResultsThe visual recognition study resulted in 65.7% sensitivity and 94.4% specificity. By using those seizure annotations, the automated algorithm obtained 64.1% sensitivity and 2.8 false‐positive detections (FPs)/24 hours with the patient‐independent model. The patient‐specific model achieved 69.1% sensitivity and 0.49 FPs/24 hours.SignificanceVisual recognition of ictal EEG patterns using only behind‐the‐ear EEG is possible in a significant number of patients with TLE. A patient‐specific seizure detection algorithm using only behind‐the‐ear EEG was able to detect more seizures automatically than what patients typically report, with 0.49 FPs/24 hours. We conclude that a large number of refractory TLE patients can benefit from using this device.

EEG Source Imaging from Standard Long-term Video EEG Recording in Patients with Medically-refractory Focal Epilepsy (P4.5-006)

EEG Source Imaging from Standard Long-term Video EEG Recording in Patients with Medically-refractory Focal Epilepsy (P4.5-006)

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

PurposeTo determine the usefulness of the first-hour sleep EEG recording in identifying interictal epileptiform discharges (IEDs) during long-term video-EEG monitoring. MethodWe retrospectively reviewed 255 consecutive patients who underwent continuous long-term video-EEG monitoring in the adult epilepsy monitoring unit (EMU) at the University of Chicago. The complete video-EEG recording was reviewed, and the occurrence of IEDs was determined for each patient. We compared the occurrence of IEDs observed during the first-hour sleep EEG recordings with the occurrence of IEDs observed during the complete video-EEG recordings. ResultsOverall, IEDs were observed in 134 (53%) of 255 patients during the full long-term video-EEG recording with a mean duration of 4 days. IEDs were identified in the first-hour sleep EEG in 125 (49%) of 225 patients. Comparing to reviewing full records, the first hour sleep EEG identified IEDs in 125 (93%) of 134 patients. Of the IED subtypes, the first-hour sleep EEG identified 92 (94%) of 98 patients with temporal lobe IEDs, 11 (92%) of 12 patients with frontal lobe IEDs, 3 (100%) of 3 patients with parietal lobe IEDs, 1(50%) of the 2 patients with occipital lobe IEDs, 16 (94%) of 17 patients with generalized IEDs, and 2 (100%) 2 patients with multi-focal IEDs. ConclusionsThe first-hour sleep EEG reliably predicts the occurrence of IEDs during the long-term video-EEG recording, and therefore can be a time-efficient tool for identifying patients with IEDs during long-term video-EEG recording in the adult epilepsy monitoring unit.

S81. The first hour sleep EEG recording predicts the occurrence of interictal epileptiform discharges during long-term video-EEG monitoring

Introduction To determine the predictive value of the first hour sleep EEG recording in identifying patients with interictal epileptiform discharges (IEDs) during long-term video-EEG monitoring in an adult epilepsy monitoring unit. Methods We retrospectively reviewed 255 consecutive patients who underwent continuous long-term video-EEG monitoring in the University of Chicago EMU. The complete video-EEG recording was reviewed, and the occurrence of IEDs was determined for each patient. We compared the occurrence of IEDs observed during the first hour sleep EEG recordings with the occurrence of IEDs observed during the complete long-term video-EEG recordings; inclusive of the first hour of sleep. Results Overall, IEDs were observed in 134(53%) of 255 patients during the full long-term video-EEG recording with a duration of 4 ± 0.8 days. IEDs were identified in the first hour sleep EEG recording in 125 (sensitivity 93%) of the 134 patients. IEDs were found in the first hour sleep EEG recording in 92 (94%) of 98 patients with temporal lobe epilepsy, 11 (92%) of 12 patients with frontal lobe epilepsy, 3 (100%) of 3 patients with parietal lobe epilepsy, 1 (50%) of the 2 patients with occipital lobe epilepsy, and 15 (88%) of the 17 patients with generalized epilepsy. The ictal onset in remaining 2 patients with multi-focal IEDs could not be localized due to muscle artifacts. The negative predictive value of the first hour EEG was 93%. Conclusion The first hour of sleep EEG recording reliably predicts the occurrence of interictal epileptiform activity in a long-term video-EEG recording, and therefore can be used efficiently for identifying patients with IEDs during long-term video-EEG recording in the adult epilepsy monitoring unit.

RNA sequencing of synaptic and cytoplasmic Upf1-bound transcripts supports contribution of nonsense-mediated decay to epileptogenesis

The nonsense mediated decay (NMD) pathway is a critical surveillance mechanism for identifying aberrant mRNA transcripts. It is unknown, however, whether the NMD system is affected by seizures in vivo and whether changes confer beneficial or maladaptive responses that influence long-term outcomes such the network alterations that produce spontaneous recurrent seizures. Here we explored the responses of the NMD pathway to prolonged seizures (status epilepticus) and investigated the effects of NMD inhibition on epilepsy in mice. Status epilepticus led to increased protein levels of Up-frameshift suppressor 1 homolog (Upf1) within the mouse hippocampus. Upf1 protein levels were also higher in resected hippocampus from patients with intractable temporal lobe epilepsy. Immunoprecipitation of Upf1-bound RNA from the cytoplasmic and synaptosomal compartments followed by RNA sequencing identified unique populations of NMD-associated transcripts and altered levels after status epilepticus, including known substrates such as Arc as well as novel targets including Inhba and Npas4. Finally, long-term video-EEG recordings determined that pharmacologic interference in the NMD pathway after status epilepticus reduced the later occurrence of spontaneous seizures in mice. These findings suggest compartment-specific recruitment and differential loading of transcripts by NMD pathway components may contribute to the process of epileptogenesis.

Increased Epileptiform EEG Activity and Decreased Seizure Threshold in Arctic APP Transgenic Mouse Model of Alzheimer's Disease.

Several Alzheimer model mice carrying transgenic amyloid precursor protein (APP) with the Swedish mutation have been reported to exhibit spontaneous seizures and/or increased epileptiform EEG activity. The primary cause for the epilepsy phenotype is still under debate. In contrast to mice with APPswe mutation that develop extracellular amyloid plaques, mice with APP Arctic mutation (E693G) have no bias toward β-secretase cleavage and display intracellular amyloid deposits but not plaques. We conducted a systematic long-term video-EEG recording in three two-week sessions on 21 APParc and 11 wild-type control mice between 3.5 and 8 months of age. Spontaneous seizures were not detected more often in APParc mice than in their wild-type control mice. Long (1 - 5 s) epileptiform discharges were occasionally detected in both APParc and wild-type mice, but short (0.5 - <1 s) epileptiform discharges were more common in APParc mice than in wild-types. However, they were far less frequent than in 6 APPswe/PS1dE9 mice recorded in parallel. In pentylenetetrazole test for seizure susceptibility, APParc mice displayed a shorter latency to sharp-wave discharges than wildtype mice but no increase in seizure duration. These data speak for a relatively mild epilepsy phenotype in APParc mice compared to APPswe mice despite even higher extent of APP overexpression. Thus extracellular amyloid plaques or increased β-secretase cleavage products appear important for the epilepsy phenotype in APPswe mice.

Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures.

Muscle activity during seizures is in electroencephalographical (EEG) praxis often considered an irritating artefact. This article discusses ways by surface electromyography (EMG) to turn it into a valuable tool of epileptology. Muscles are in direct synaptic contact with motor neurons. Therefore, EMG signals provide direct information about the electric activity in the motor cortex. Qualitative analysis of EMG has traditionally been a part of the long-term video-EEG recordings. Recent development in quantitative analysis of EMG signals yielded valuable information on the pathomechanisms of convulsive seizures, demonstrating that it was different from maximal voluntary contraction, and different from convulsive psychogenic non-epileptic seizures. Furthermore, the tonic phase of the generalised tonic-clonic seizures (GTCS) proved to have different quantitative features than tonic seizures. The high temporal resolution of EMG allowed detailed characterisation of temporal dynamics of the GTCS, suggesting that the same inhibitory mechanisms that try to prevent the build-up of the seizure activity, contribute to ending the seizure. These findings have clinical implications: the quantitative EMG features provided the pathophysiologic substrate for developing neurophysiologic biomarkers that accurately identify GTCS. This proved to be efficient both for seizure detection and for objective, automated distinction between convulsive and non-convulsive epileptic seizures.

Can an exercise bicycle be safely used in the epilepsy monitoring unit?: An exercise method to provoke epileptic seizures and the related safety issues

Background and purposeLong-term videoelectroencephalogram (video-EEG) monitoring is performed to diagnose an epileptic seizure and to investigate the differential diagnosis of paroxysmal events. To provoke an epileptic seizure, an exercise method is performed in some cases during long-term video-EEG recording in the epilepsy monitoring unit (EMU). The purpose of this study was two-fold: to assess the frequency and severity of adverse events associated with the use of an exercise bicycle and to find a way to safely use it in the EMU. MethodsA retrospective survey was performed on all epileptic seizure videos recorded in the EMU from January 2012 to December 2013. Three hundred and fifty patients were included in this study. ResultsEleven patients experienced an epileptic seizure while riding the exercise bicycle in the EMU. One patient's foot got stuck between the cycling pedal and its strap, and one patient fell off the exercise bicycle during the epileptic seizure. However, there were no serious adverse events over two years. ConclusionEpileptic seizures were not frequent while riding the exercise bicycle, and serious injuries did not occur. But, there is a need to improve the safety in the EMU to control the potentially dangerous factors associated with the use of the exercise bicycle and to continuously monitor the patients with help from the staff.

Latency of interictal epileptiform discharges in long-term EEG recordings in epilepsy patients

PurposeTo assess the latency of interictal epileptiform discharges (IED) and seizures in long-term EEG recordings of patients with epilepsy. MethodIED latency was measured in 210 consecutive patients (mean (SD) age 38.6±13.9 years) with active epilepsy and the relationship to clinical variables was analyzed retrospectively. Median duration of EEG recording was 101.5h (95% confidence interval [CI] 92 to 117h). ResultsIEDs were absent in 45 (21.4%) and present in 165 (78.6%) patients who had a longer duration (p<0.001) and early onset (p<0.01) of epilepsy and more often had IEDs in prior standard EEGs (p<0.01), a structural etiology (OR 2.4, CI: 2.1–2.7), or temporal lobe epilepsy (OR 9.6, CI: 9.0–10.2). IED latency did not correlate with other clinical variables. Median latency to the emergence of the first IED was 9.3h (CI: 7.5–11.4) occurring in 7.3%, 9.7%, 74.6%, 87.9%, and 96.4% within 20min, 30min, 24h, 48h, and 72h, respectively. Seizure frequency was higher in patients with (n=165) than without IEDs (n=45) (72.1% vs. 46.6%, p<0.01) and seizure latency (median 21.6h, CI: 16.8–27.3) was influenced by the presence of IEDs, whereas the presence of seizures did not influence the latency and frequency of IEDs. ConclusionIf present, in the majority of epilepsy patients IEDs occurred during the first 72h of long-term video-EEG recording. Repeated video-EEG or video recordings of habitual seizures are needed to minimize false negative studies.

Concept of epilepsy surgery and presurgical evaluation.

Epilepsy surgery is a well-accepted treatment for drug-resistant epilepsy. The success of the epilepsy surgery depends upon an appropriate presurgical evaluation process which should ensure the selection of suitable patients who are likely to become seizure-free following surgery without any unacceptable deficit. The two basic goals of the presurgical evaluation are the accurate localization and delineation of the extent of the epileptogenic zone, and its complete and safe resection. The process of the presurgical evaluation requires a multimodality approach wherein each modality provides unique and complimentary information which is combined with the information provided by other modalities to generate a hypothesis with regard to the likely epileptogenic zone. The basic modalities for the presurgical evaluation are clinical history, long-term video-EEG recording, high-resolution MRI, and neuropsychological evaluation. The additional modalities include functional imaging studies, electrical and magnetic source imaging, functional MRI, and intracranial monitoring. Each modality has its own limitations and the information provided by none of them is absolute. Hence, a concordance among the different modalities is the key to surgical success. The presurgical evaluation is a step-wise process starting form the most basic and most reliable tests and progressing to more complex and invasive modalities. The number of tests required varies according to the complexity involved and may include very basic minimum investigations in a given case, to the use of all the available investigations in more complex cases. The proper selection of various investigations and their accurate interpretation at each stage is required to ensure a successful outcome. In this article, we intend to review some of these basic concepts of presurgical evaluation and epilepsy surgery, and try to provide a frame work of the presurgical evaluation process.