Focal Interictal Epileptiform Discharges Research Articles

Idiopathic generalized epilepsies in the epilepsy monitoring unit: Systematic quantification of focal EEG and semiological signs

ObjectiveFocal seizure symptoms (FSS) and focal interictal epileptiform discharges (IEDs) are common in patients with idiopathic generalized epilepsies (IGEs), but dedicated studies systematically quantifying them both are lacking. We used automatic IED detection and localization algorithms and correlated these EEG findings with clinical FSS for the first time in IGE patients. Methods32 patients with IGEs undergoing long-term video EEG monitoring were systematically analyzed regarding focal vs. generalized IEDs using automatic IED detection and localization algorithms. Quantitative EEG findings were correlated with FSS. ResultsWe observed FSS in 75% of patients, without significant differences between IGE subgroups. Mostly varying/shifting lateralizations of FSS across successive recorded seizures were seen. We detected a total of 81,949 IEDs, whereof 19,513 IEDs were focal (23.8%). Focal IEDs occurred in all patients (median 13% focal IEDs per patient, range 1.1 – 51.1%). Focal IED lateralization and localization predominance had no significant effect on FSS. ConclusionsAll included patients with IGE showed focal IEDs and three-quarter had focal seizure symptoms irrespective of the specific IGE subgroup. Focal IED localization had no significant effect on lateralization and localization of FSS. SignificanceOur findings may facilitate diagnostic and treatment decisions in patients with suspected IGE and focal signs.

Focal electroclinical features in generalized tonic-clonic seizures: Decision flowchart for a diagnostic challenge.

Bilateral tonic-clonic seizures with focal semiology or focal interictal electroencephalography (EEG) can occur in both focal and generalized epilepsy types, leading to diagnostic errors and inappropriate therapy. We investigated the prevalence and prognostic values of focal features in patients with idiopathic generalized epilepsy (IGE), and we propose a decision flowchart to distinguish between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal EEG or semiology. We retrospectively analyzed video-EEG recordings of 101 bilateral tonic-clonic seizures from 60 patients (18 with IGE, 42 with focal epilepsy). Diagnosis and therapeutic response were extracted after ≥1-year follow-up. The decision flowchart was based on previous observations and assessed concordance between interictal and ictal EEG. Focal semiology in IGE was observed in 75% of seizures and 77.8% of patients, most often corresponding to forced head version (66.7%). In patients with multiple seizures, direction of head version was consistent across seizures. Focal interictal epileptiform discharges (IEDs) were observed in 61.1% of patients with IGE, whereas focal ictal EEG onset only occurred in 13% of seizures and 16.7% of patients. However, later during the seizures, a reproducible pattern of 7-Hz lateralized ictal rhythm was observed in 56% of seizures, associated with contralateral head version. We did not find correlation between presence of focal features and therapeutic response in IGE patients. Our decision flowchart distinguished between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal features with an accuracy of 96.6%. Focal semiology associated with bilateral tonic-clonic seizures and focal IEDs are common features in patients with IGE, but focal ictal EEG onset is rare. None of these focal findings appears to influence therapeutic response. By assessing the concordance between interictal and ictal EEG findings, one can accurately distinguish between focal and generalized epilepsies.

Seizures and electrophysiological features in familial cortical myoclonic tremor with epilepsy 1.

To investigate and characterize epileptic seizures and electrophysiological features of familial cortical myoclonic tremor with epilepsy (FCMTE) type 1 patients in a large Chinese cohort. We systematically evaluated 125 FCMTEtype 1 patients carrying the pentanucleotide (TTTCA) repeat expansion in the SAMD12 gene in China. Among the 28 probands, epileptic seizures (96.4%, 27/28) were the most common reason for an initial clinic visit. Ninety-seven (77.6%, 97/125) patients had experienced seizures. The seizures onset age was 36.5 ± 9.0 years, which was 6.9 years later than cortical tremors. The seizures were largely rare (<1/year, 58.8%) and occasional (1-6/year, 37.1%). Prolonged prodromes were reported in 57.7% (56/97). Thirty-one patients (24.8%, 31/125) reported photosensitivity history, and 79.5% (31/39) had a photoparoxysmal response. Interictal epileptiform discharges (IEDs) were recorded in 69.1% (56/81) of patients. Thirty-three patients showed generalized IEDs and 72.7% (24/33) were occipitally dominant, while 23 patients presented with focal IEDs with 65.2% (15/23) taking place over the occipital lobe. Overnight EEG of FCMTE patients displayed paradoxical sleep-wake fluctuation, with a higher average IED index of 0.82 ± 0.88/min during wakefulness and a lower IED index of 0.04 ± 0.06/min during non-rapid eye movement sleep stages I-II. FCMTE type 1 has a benign course of epilepsy and distinct clinical and electrophysiological features. In addition to a positive family history and cortical myoclonus tremor, the seizure prodromes, specific seizure triggers, photosensitivity, distribution of IEDs, and unique fluctuations during sleep-wake cycle are cues for proper genetic testing and an early diagnosis of FCMTE.

The differing effects of sleep on ictal and interictal network dynamics in drug-resistant epilepsy.

Sleep has important influences on focal interictal epileptiform discharges (IEDs), and the rates and spatial extent of IEDs are increased in non-rapid eye movement (NREM) sleep. In contrast, the influence of sleep on seizures is less clear and its effects on seizure topography are poorly documented. We evaluated the influences of NREM sleep on ictal spatiotemporal dynamics and contrasted these with interictal network dynamics. We included patients with drug-resistant focal epilepsy who underwent continuous intracranial EEG with depth electrodes. Patients were selected if they had 1-3 seizures from each vigilance state, wakefulness and NREM sleep, within a 48-hour window and under the same anti-seizure medication. A 10-min epoch of the interictal iEEG was selected per state, and IEDs were detected automatically. Twenty-five patients (13 females; 32.5±7.1 years) were included. The seizure onset pattern, duration, spatiotemporal propagation and latency of ictal high-frequency activity did not differ significantly between wakefulness and NREM sleep (all p>0.05). In contrast, IED rates and spatial distribution were increased in NREM compared to wakefulness (p<0.001, Cliff's d=0.48 and 0.49). The spatial overlap between vigilance states was higher for seizures (57.1±40.1%) than IEDs (41.7±46.2%) (p=0.001, Cliff's d=0.51). In contrast to its effects on IEDs, NREM sleep does not affect ictal spatiotemporal dynamics. This suggests that once the brain surpasses the seizure threshold, it will follow the underlying epileptic network irrespective of the vigilance state. These findings offer valuable insights into neural network dynamics in epilepsy and have important clinical implications for localizing seizure foci. This article is protected by copyright. All rights reserved.

Predictive Power of Interictal Epileptiform Discharges in Fitness-to-Drive Evaluation.

This study aimed to evaluate and predict the effects of interictal epileptiform discharges (IEDs) on driving ability using simple reaction tests and a driving simulator. Patients with various epilepsies were evaluated with simultaneous EEGs during their response to visual stimuli in a single-flash test, a car-driving video game, and a realistic driving simulator. Reaction times (RTs) and missed reactions or crashes (miss/crash) during normal EEG and IEDs were measured. IEDs, as considered in this study, were a series of epileptiform potentials (>1 potential) and were classified as generalized typical, generalized atypical, or focal. RT and miss/crash in relation to IED type, duration, and test type were analyzed. RT prolongation, miss/crash probability, and odds ratio (OR) of miss/crash due to IEDs were calculated. Generalized typical IEDs prolonged RT by 164 ms, compared with generalized atypical IEDs (77.0 ms) and focal IEDs (48.0 ms) (p < 0.01). Generalized typical IEDs had a session miss/crash probability of 14.7% compared with a zero median for focal and generalized atypical IEDs (p < 0.01). Long repetitive bursts of focal IEDs lasting >2 seconds had a 2.6% miss/crash probabilityIED. Cumulated miss/crash probability could be predicted from RT prolongation: 90.3 ms yielded a 20% miss/crash probability. All tests were nonsuperior to each other in detecting miss/crash probabilitiesIED (zero median for all 3 tests) or RT prolongations (flash test: 56.4 ms, car-driving video game: 75.5 ms, simulator 86.6 ms). IEDs increased the OR of miss/crash in the simulator by 4.9-fold compared with normal EEG. A table of expected RT prolongations and miss/crash probabilities for IEDs of a given type and duration was created. IED-associated miss/crash probability and RT prolongation were comparably well detected by all tests. Long focal IED bursts carry a low risk, while generalized typical IEDs are the primary cause of miss/crash. We propose a cumulative 20% miss/crash risk at an RT prolongation of 90.3 ms as a clinically relevant IED effect. The IED-associated OR in the simulator approximates the effects of sleepiness or low blood alcohol level while driving on real roads. A decision aid for fitness-to-drive evaluation was created by providing the expected RT prolongations and misses/crashes when IEDs of a certain type and duration are detected in routine EEG.

Deep learning-based automated detection and multiclass classification of focal interictal epileptiform discharges in scalp electroencephalograms

Detection and spatial distribution analyses of interictal epileptiform discharges (IEDs) are important for diagnosing, classifying, and treating focal epilepsy. This study proposes deep learning-based models to detect focal IEDs in electroencephalography (EEG) recordings of the frontal, temporal, and occipital scalp regions. This study included 38 patients with frontal (n = 15), temporal (n = 13), and occipital (n = 10) IEDs and 232 controls without IEDs from a single tertiary center. All the EEG recordings were segmented into 1.5-s epochs and fed into 1- or 2-dimensional convolutional neural networks to construct binary classification models to detect IEDs in each focal region and multiclass classification models to categorize IEDs into frontal, temporal, and occipital regions. The binary classification models exhibited accuracies of 79.3–86.4%, 93.3–94.2%, and 95.5–97.2% for frontal, temporal, and occipital IEDs, respectively. The three- and four-class models exhibited accuracies of 87.0–88.7% and 74.6–74.9%, respectively, with temporal, occipital, and non-IEDs F1-scores of 89.9–92.3%, 84.9–90.6%, and 84.3–86.0%; and 86.6–86.7%, 86.8–87.2%, and 67.8–69.2% for the three- and four-class (frontal, 50.3–58.2%) models, respectively. The deep learning-based models could help enhance EEG interpretation. Although they performed well, the resolution of region-specific focal IED misinterpretations and further model improvement are needed.

On-Scalp Optically Pumped Magnetometers versus Cryogenic Magnetoencephalography for Diagnostic Evaluation of Epilepsy in School-aged Children.

Background Magnetoencephalography (MEG) is an established method used to detect and localize focal interictal epileptiform discharges (IEDs). Current MEG systems house hundreds of cryogenic sensors in a rigid, one-size-fits-all helmet, which results in several limitations, particularly in children. Purpose To determine if on-scalp MEG based on optically pumped magnetometers (OPMs) alleviates the main limitations of cryogenic MEG. Materials and Methods In this prospective single-center study conducted in a tertiary university teaching hospital, participants underwent cryogenic (102 magnetometers, 204 planar gradiometers) and on-scalp (32 OPMs) MEG. The two modalities for the detection and localization of IEDs were compared. The t test was used to compare IED amplitude and signal-to-noise ratio (SNR). Distributed source modeling was performed on OPM-based and cryogenic MEG data. Results Five children (median age, 9.4 years [range, 5-11 years]; four girls) with self-limited idiopathic (n = 3) or refractory (n = 2) focal epilepsy were included. IEDs were identified in all five children with comparable sensor topographies for both MEG devices. IED amplitudes were 2.3 (7.2 of 3.1) to 4.6 (3.2 of 0.7) times higher (P < .001) with on-scalp MEG, and the SNR was 27% (16.7 of 13.2) to 60% (12.8 of 8.0) higher (P value range: .001-.009) with on-scalp MEG in all but one participant (P = .93), whose head movements created pronounced motion artifacts. The neural source of averaged IEDs was located at approximately 5 mm (n = 3) or higher (8.3 mm, n = 1; 15.6 mm, n = 1) between on-scalp and cryogenic MEG. Conclusion Despite the limited number of sensors and scalp coverage, on-scalp magnetoencephalography (MEG) based on optically pumped magnetometers helped detect interictal epileptiform discharges in school-aged children with epilepsy with a higher amplitude, higher signal-to-noise ratio, and similar localization value compared with conventional cryogenic MEG. Online supplemental material is available for this article. © RSNA, 2022 See also the editorial by Widjaja in this issue.

A New Score for Sharp Discharges in the EEG Predicts Epilepsy.

A challenge in EEG interpretation is to correctly classify suspicious focal sharp activity as epileptiform or not. A predictive score was developed from morphologic features of the first focal sharp discharge, which can help in this decision. From a clinical standard EEG database, the authors identified 2,063 patients without a previous epilepsy diagnosis who had a focal sharp discharge in their EEG. Morphologic features (amplitude, area of slow wave, etc.) were extracted using an open source one-click algorithm in EEGLAB, masked to clinical classification. A score was developed from these features and validated with the clinical diagnosis of epilepsy over 2 to 6 years of follow-up. Independent external validation was performed in Kural long-term video-EEG monitoring dataset. The score for the first focal sharp discharge had a moderate predictive performance for the clinical designation as the EEG being epileptiform (area under the receiver operating characteristics curve = 0.86). Best specificity was 91% and sensitivity 55%. The score also predicted a future epilepsy diagnosis (area under the receiver operating characteristics curve = 0.70). Best specificity was 86% and sensitivity 38%. Validation on the external dataset had an area under the receiver operating characteristics curve = 0.80. Clinical EEG identification of focal interictal epileptiform discharges had an area under the receiver operating characteristics curve = 0.73 for prediction of epilepsy. The score was based on amplitude, slope, difference from background, slow after-wave area, and age. Interrater reproducibility was high (ICC = 0.91). The designation of the first focal sharp discharge as epileptiform depends on reproducible morphologic features. Characteristic features were amplitude, slope, slow after-wave area, and difference from background. The score was predictive of future epilepsy. Halford semiquantitative scale had similar diagnostic performance but lower reproducibility.

Indications and yield of ambulatory EEG recordings.

To study the yield of prolonged ambulatory electroencephalogram (aEEG). A retrospective chart review of all patients who underwent aEEG studies between 2013 and 2017 was performed. Reasons for aEEG were classified into five categories: detection of interictal epileptiform discharges (IEDs), capturing clinical events, detection of unrecognized seizures, monitoring IEDs during treatment, and unclassifiable. Ambulatory EEG reports were reviewed to evaluate whether the study answered the clinical question. A total of 1,264 patients were included. Forty studies were excluded for incomplete data and 234 for being a repeat study. The average number of recording days was 1.57 ± 0.73. Based on initial clinical evaluation, patients carried the following presumptive diagnosis: 61% epilepsy, 11% single unprovoked or acute symptomatic seizure and 28% non-epileptic paroxysmal events (PEs). Overall, focal IEDs were seen in 16.1% of studies, generalized IEDs in 10.8%, focal seizures in 4.1%, and generalized seizures in 1.9%. The most frequent reason for ordering aEEG was to detect IEDs for diagnostic purposes (48.1%). For this indication, additional information was provided by the aEEG in 19.1% of cases (58.6% focal IEDs, 33.5% generalized IEDs, 7.9% seizures without IEDs). Ambulatory EEG was ordered with the intent to capture and characterize clinical events in 18.9%, mostly in patients who reported daily or weekly events. In these, aEEG captured either epileptic seizures or PEs in 102 (42.7%) of the studies (83.3% PEs, 16.7% epileptic seizures). Ambulatory EEG was ordered to evaluate unrecognized seizures in 17.8% of patients, and electrographic seizures were identified in 13.3% of these studies. The yield of aEEG varies based on the indication for the study. Ambulatory EEG can be a useful tool for recording IEDs in the outpatient setting and in a select group of patients to capture clinical events or unrecognized seizures.

Infants routine video electroencephalogram findings in a Saudi tertiary hospital.

Objectives:To report the existence and describe the non-epileptic abnormalities, interictal epileptiform discharges, and seizures in routine electroencephalograms (EEGs) of infants in a tertiary hospital out-patient neurophysiology clinics.Methods:This is a non-interventional, retrospective descriptive study that involved the review of 172 infants’ EEGs conducted from July 2018 to June 2019 in King Fahad Medical City, Riyadh, Kingdom of Saudi Arabia.Results:Total of 172 EEGs were reviewed; 152 routine EEGs for infants and 20 neonatal EEGs. Seventy-six (50%) EEGs were reported to be normal. Among the remaining EEGs, 54 were characterized by generalized slow background abnormalities (31.3 %), seven (4%) by background asymmetry, one (0.5%) by generalized low amplitude, and one (0.5 %) by an alternate trace that was dysmature for age. Interictal epileptiform discharges (IED) were present in 75 (43.6%) EEGs and they were focal in 72 (41.8%) EEGs, and generalized spike wave discharges were seen in only 3 (1.7%) EEGs with focal interictal epileptiform discharges. A diagnosis of hypsarrythmia was made from 15 (8.7%) EEGs. There were seizures in 11 (6.4%) EEGs, of which three were in neonates (15% of neonatal EEGs), and 8 in infants (4.6 % of infant EEGs).Conclusions:Fifty % of routine infants‘ EEGs had abnormalities and hypsarrythmia was the most common abnormal background associated with seizures. Ictal discharges in form of generalized electrodecremental pattern associated clinically with epileptic spasm was the most common type of seizures

Alterations of intracerebral connectivity in epilepsy patients with secondary bilateral synchrony

IntroductionThe aim of our study was to evaluate intracerebral network changes in epilepsy patients demonstrating secondary bilateral synchrony (SBS) in EEG by applying a new Diffusion Tensor Imaging (DTI) method using an energy-based global tracking algorithm. Materials and methods10 MRI negative epilepsy patients demonstrating SBS in 10–20 surface EEG were included. EEG findings were analyzed for irritative zones characterized by focal interictal epileptiform discharges (IEDs) triggering SBS. In addition, DTI including an energy-based global tracking algorithm was applied to analyze fiber tract alterations in irritative zones. To measure the deviation of a certain cortical connection in comparison to healthy controls, normalized differences of fiber tract streamline counts (SC) and their p-values were evaluated in comparison to corresponding fibers of the control group. ResultsIn 6 patients the irritative zone initiating SBS was located in the frontal lobe, in 3 patients in the temporal lobe and in 1 patient in the region surrounding the right central sulcus. All patients demonstrated significantly altered SC in brain lobes where the irritative zone triggering SBS was located (p ≤ 0.05). Seven out of 10 patients demonstrated SC alterations in tracts connecting brain lobes between the ipsilateral and the contralateral hemisphere (p ≤ 0.05). ConclusionOur data demonstrate that alterations in fiber tracts in irritative zones triggering SBS are not necessarily associated with intracerebral lesions visible in high resolution MRI. Our study gives evidence that diffusion tensor imaging is a promising non-invasive additive tool for intracerebral network analyses even in MRI-negative epilepsy patients.

Electroencephalographic Findings and Clinical Behavior During Induction of Anesthesia With Sevoflurane in Human Infants: A Prospective Observational Study.

Seizures and interictal epileptiform discharges (IEDs) have been described during sevoflurane. We prospectively estimated their incidence in 54 otherwise neurologically healthy infants by obtaining the full-head video electroencephalogram (EEG). No infants had clinical seizures, but 1 had an electrographic seizure; 3 others had focal IEDs (7.4%; 95% confidence interval [CI], 2.1%-17.9%). We detected no differences in demographic or clinical characteristics between normal and abnormal EEG groups. Diffuse slowing was the most common initial EEG change followed by fast (α, β) activity in all head leads. Larger studies with more statistical power are needed to further investigate the hypotheses generated with this research.

Interictal epileptiform discharges vary across age groups

ObjectiveTo investigate whether the occurrence and morphology of interictal epileptiform discharges (IEDs) in scalp-EEG change by age. Methods10,547 patients who had a standard or sleep deprived EEG recording reported using the SCORE standard were included. 875 patients had at least one EEG with focal IEDs. Focal IED morphology was analyzed by age using quantitative measures in EEGLAB and by visual classification based on the SCORE standard. We present distributions of IED measures by age group, with medians, interquartiles, 5th and 95th percentiles. ResultsFocal IEDs occurred most frequently in children and elderly. IED morphology and localization depended on age (p < 0.001). IEDs had higher amplitudes, sharper peaks, larger slopes, shorter durations, larger slow-wave areas and wider distributions in children. These morphological characteristics diminished and the IEDs became more lateralized with increasing age. Spike asymmetry was stable across all age groups. ConclusionsIEDs have age-dependent characteristics. A spike detector, human or computer, should not operate with the same set of thresholds for patients at various age. With increasing age, focal IEDs are less sharp, have lower amplitudes, have less prominent slow-waves and they become more lateralized. Our findings can help EEG readers in detecting and correctly describing IEDs in patients of various age. SignificanceEEG readers should always consider patient age when interpreting interictal epileptiform discharges.

Magnetic Resonance Imaging and Interictal Electroencephalography Findings in Newly Diagnosed Epileptic Children

Introduction: Epilepsy is one of the most frequently diagnosed chronic neurological disorders in children. Diagnosis is often based on seizure history and electroencephalography (EEG) assessment. Magnetic resonance imaging (MRI) is recommended for etiologic workup and intervention requirements. We aimed to detect by MRI if focal structural abnormalities are present in the brain in relation to interictal epileptiform discharges (IED). Material and Methods: The study was designed retrospectively. The data were collected from patients admitted to Near East University, Department of Pediatric Neurology, who were aged between 3 months and 18 years and who were diagnosed with epilepsy. The cases considered in the current study, however, were patients that had an EEG record prior to initiating treatment and an MRI within the first six months following diagnosis. Results: Among 222 patients, 212 (95.5%) had IED, and 92 (41.4%) had abnormal MRI results. The most frequently seen abnormalities detected by MRI were encephalomalacia, hydrocephaly, and atrophy. Among patients who had IED, the ones with multifocal IED were documented to have a statistically significant higher rate of abnormalities in MRI scans. In other patients, IED had no significant correlation with structural lesions detected by MRI. Conclusion: IED can be unrelated to MRI findings. Focal IED were not statistically concordant with the structural lesions detected by MRI. However, for the cases with multifocal discharges revealed by interictal EEG, the rate of abnormalities detected using MRI was 68%. Therefore, the likelihood of detecting abnormalities using MRI in patients with multifocal IED does support the necessity of the use of MRI in early diagnosis stages.

P1-3-10. Effect of hyperventilation on seizures and EEG findings during routine EEG

Hyperventilation (HV) is widely used to induce EEG abnormalities and epileptic seizures. However, it is still controversial how long it should be done in routine EEG. We analyzed 1,184 routine EEG data recorded in our institution between October, 2016 and September, 2017. Among them, 970 patients tried to perform HV lasting 4 min, and 949 patients completed it age mean, range. During HV, interictal epileptiform discharges (IED) were induced in 82 patients (9%). Generalized IED were seen in 70 patients, focal IED in eight, bi-temporal slow wave in three, and rhythmic theta activity (focal) in one. IED appeared only after 3-min HV in 11 patients (13%) out of 82. Epileptic seizures were induced by HV in 25 patients (3%). Absence seizures occurred in 23 patients, and focal seizures in two. Two patients (12%) had seizures after 3-min HV. No adverse event occurred during 4-min HV, not only during this study period, but also more than 40 years of our practice. We concluded that 4-min HV is effective and safe for epilepsy patients.

The relation between cortisol and functional connectivity in people with and without stress-sensitive epilepsy.

The most common reported seizure-precipitant is stress. We recently showed a biologic basis for stress sensitivity of seizures: cortisol levels in people with stress-sensitive epilepsy correlated with focal interictal epileptiform discharges (IEDs) on electroencephalography (EEG). Here we aimed to determine whether the effect of cortisol on the epileptic brain is global or focal, and whether cortisol affects all brains or just those of stress-sensitive people. Because epilepsy is associated with changes in functional brain connectivity, we studied the relationship between cortisol and changes in global and focal (node-centered) functional connectivity measures for individuals with stress-sensitive and non-stress-sensitive epilepsy. Seventeen people with epilepsy underwent long-term (>24h) EEG recording. During the first 5h after waking, saliva was collected every 15min for cortisol measurements. Theta-band functional connectivity was assessed for every 15min of the recording. We calculated the average phase-lag index (PLI) between all channels as a measure of global functional connectivity. We used network Strength, the averaged PLI per channel, as focal functional connectivity measure. We correlated cortisol, global, and focal functional connectivity (Strength) with IED frequency using linear mixed models. Analyses were split for people with and without stress-sensitivity of seizures. Cortisol was negatively correlated with global functional connectivity in people with stress-sensitive seizures (estimate -0.0020; P<.01), whereas not in those without stress-sensitivity (estimate -0.0003; P=.46). This relationship occurred irrespective of the presence of IEDs on a channel (channels without IEDs and stress-sensitivity: estimate -0.0019; P<.01, non-stress-sensitive -0.0003; P=.41). Global and focal functional connectivity were negatively correlated with IED frequency, irrespective of stress sensitivity of seizures or channel type. People with stress-sensitive epilepsy have a whole-brain neuronal response to cortisol that is different from that of people with non-stress-sensitive epilepsy. This offers a basis for understanding seizure genesis in stress-sensitive epilepsy, which might require a different treatment approach.

The yield of video-EEG telemetry evaluation for non-surgical candidate children.

Video EEG (VEEG) is performed for most pediatric patients in order to evaluate unclear paroxysmal events and improve our understanding of difficult to control epileptic patients. To characterize the video EEG studies on children who are not candidates for surgery in order to identify the parameters that affect results in level of improving the rate of acquisition, as well as improving the ability to expect the likelihood of epilepsy and of gathering new information as a result of the VEEG. Retrospective chart analysis of all consecutive patients who underwent VEEG in two VEEG monitoring units. 323 children of a mean age of 7 years (STD 4.73, range 0-17 years) were monitored for a mean duration of 2 days (STD 1.65, range 1-10 days). The main reasons for monitoring were: evaluation of unclear events (n=234), evaluation of previously diagnosed epilepsy (n=36) and confirmation of Electrical Status Epilepticus in Sleep (ESES) (n=34). The main event types for evaluation were: staring episodes (n=67), myoclonic jerks (n=35) and abnormal eye movement (n=22). Suspected events were captured in 70% of the patients. There was a positive correlation between acquisition of suspected events and each of the following: duration of the monitoring, the frequency of investigated events per history, the type of investigated events. A prior interictal epileptic activity on routine EEG was a positive predictor of an event to be epileptic (p=0.003). Amongst the group of known epileptic patients, VEEG had role in changing diagnosis in 53% of patients. Many of them had focal interictal epileptiform activity in their routine EEG. Selecting patients with frequent events and longer monitoring periods increase the yield of VEEG. Looking carefully into clinical characteristics of the patient prior to VEEG can clarify diagnosis therefore render the VEEG test superfluous to subgroups of patients. Prior routine epileptic EEG, coexistence of other seizure types, behaviors accompanying the investigated habitual behavior and abnormalities in other investigations (MRI, cognitive function and EEG) are the parameters that can predict diagnosis of epilepsy. Precise diagnosis in known epileptic patients as a result of VEEG is more likely for those with focal interictal epileptiform discharges in routine EEG.

Focal interictal epileptiform discharges in idiopathic generalized epilepsy

Are idiopathic generalized epilepsies (IGEs) truly generalized? Do IGEs representa continuum or rather distinct syndromes? Focal changes in the electroencephalography (EEG) have been reported inIGEs. The aim of this work is to investigate focal interictal epileptiform discharges (IEDs) in IGEs, and their relation to clinical variables. Forty-one IGE patients (classified according to ILAE, 2001) were recruited from a tertiary center (age 23±10.938years). Their files were reviewed and they were subjected to clinical examination and interictal EEG. Patients with focal IEDs were compared to those without focal IEDs. Nine patients had juvenile myoclonic epilepsy (JME) and 32 had idiopathic epilepsy with generalized tonic-clonic seizures only (EGTCSA). Focal IEDs were found in 20 patients, mostly in the frontal (45.5%) and temporal (31.8%) distribution. Patients with focal IEDs were treated witha larger number of combined antiepileptic drugs (AEDs) (p value=0.022). No significant difference was found between the two groups regarding age, sex, age at onset, epilepsy syndrome, seizure frequency, family history, AEDs used (sodium valproate and carbamazepine) and their doses. Seventeen EGTCSA patients had focal IEDs. They were treated with larger number of combined AEDs (p value=0.0142). No significant difference was found between the EGTCSA patients with and those without focal IEDs regarding age, sex, age at onset, seizure frequency, family history and AEDs doses. Caution must be applied in the interpretation of interictal focal IEDs. These focal changes may be related to prognosis, however this needs further investigation.

Spatiotemporal mapping of interictal epileptiform discharges in human absence epilepsy: A MEG study

PurposeAlthough absence epilepsy is considered to be a prototypic type of generalized epilepsy, it is still under debate whether generalized 3Hz spike-and-wave discharges (SWDs) might have a cortical focal origin. Here it is investigated whether focal interictal epileptiform discharges (IEDs), which typically occur in the electro- (EEG) and magnetoencephalogram (MEG) in case of focal epilepsy, are present in the MEG of children with absence epilepsy. Next, the location of the sources of the IEDs is established, and it is investigated whether the location is concordant to the earlier established focal cortical regions involved in the generalized SWDs of these children. MethodsWhole head MEG recordings of seven children with absence epilepsy were reviewed with respect to the presence of IEDs (spikes and sharp waves). These IEDs were grouped into distinct clusters, in which each contribution to a cluster yields a comparable magnetic field distribution. Source localization was then performed onto the average signal of each cluster using an equivalent current dipole model and a realistic head model of the cortical surface. ResultsIEDs were detected in 6 out of 7 patients. Source reconstruction indicated most often frontal, central or parietal origins of the IED in either the left and or right hemisphere. Spatiotemporal assessment of the IEDs indicated a stable location of the averages of these discharges, indicating a single underlying cortical source. DiscussionThe outcome of this pilot study shows that MEG is well suited for the detection of IEDs and suggests that their estimated sources coincide rather well with the cortical regions involved during the spikes of the SWDs. It is discussed whether the presence of IEDs, classically seen as a marker of focal epilepsies, indicate that absence epilepsy should be considered as a focal type of epilepsy, in which changes in the network are evolving rapidly.

A Comparison of Independent Component Analysis (ICA) of fMRI and Electrical Source Imaging (ESI) in Focal Epilepsy Reveals Misclassification Using a Classifier.

Interictal epileptiform discharges (IEDs) can produce haemodynamic responses that can be detected by electroencephalography-functional magnetic resonance imaging (EEG-fMRI) using different analysis methods such as the general linear model (GLM) of IEDs or independent component analysis (ICA). The IEDs can also be mapped by electrical source imaging (ESI) which has been demonstrated to be useful in presurgical evaluation in a high proportion of cases with focal IEDs. ICA advantageously does not require IEDs or a model of haemodynamic responses but its use in EEG-fMRI of epilepsy has been limited by its ability to separate and select epileptic components. Here, we evaluated the performance of a classifier that aims to filter all non-BOLD responses and we compared the spatial and temporal features of the selected independent components (ICs). The components selected by the classifier were compared to those components selected by a strong spatial correlation with ESI maps of IED sources. Both sets of ICs were subsequently compared to a temporal model derived from the convolution of the IEDs (derived from the simultaneously acquired EEG) with a standard haemodynamic response. Selected ICs were compared to the patients' clinical information in 13 patients with focal epilepsy. We found that the misclassified ICs clearly related to IED in 16/25 cases. We also found that the classifier failed predominantly due to the increased spectral range of fMRIs temporal responses to IEDs. In conclusion, we show that ICA can be an efficient approach to separate responses related to epilepsy but that contemporary classifiers need to be retrained for epilepsy data. Our findings indicate that, for ICA to contribute to the analysis of data without IEDs to improve its sensitivity, classification strategies based on data features other than IC time course frequency is required.