Decrease in Propagation of Interictal Epileptiform Activity After Introduction of Levetiracetam Visualized with Electric Source Imaging

Larsson, Pål G.; Eeg‐Olofsson, Orvar; Michel, Christoph M.; Seeck, Margitta; Lantz, Goeran

doi:10.1007/s10548-010-0150-1

Cited by 11 publications

(6 citation statements)

References 37 publications

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“…We have confirmed that interictal spikes can involve widespread networks, in line with previous studies showing that interictal epileptic activities can propagate rapidly in IEEG (Alarcon et al 1994) or in non-invasive electrophysiology (Larsson et al 2010;Tanaka et al 2010). Furthermore, we have shown that this is also the case for epileptic oscillations in the beta/low gamma band.…”

Section: Discussionsupporting

confidence: 90%

Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG

et al. 2016

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Electromagnetic source localization in electroencephalography (EEG) and magnetoencephalography (MEG) allows finding the generators of transient interictal epileptiform discharges ('interictal spikes'). In intracerebral EEG (iEEG), oscillatory activity (above 30 Hz) has also been shown to be a marker of neuronal dysfunction. Still, the difference between networks involved in transient and oscillatory activities remains largely unknown. Our goal was thus to extract and compare the networks involved in interictal oscillations and spikes, and to compare the non-invasive results to those obtained directly within the brain. In five patients with both MEG and iEEG recordings, we computed correlation graphs across regions, for (1) interictal spikes and (2) epileptic oscillations around 30 Hz. We show that the corresponding networks can involve a widespread set of regions (average of 10 per patient), with only partial overlap (38 % of the total number of regions in MEG, 50 % in iEEG). The non-invasive results were concordant with intracerebral recordings (79 % for the spikes and 50 % for the oscillations). We compared our interictal results to iEEG ictal data. The regions labeled as seizure onset zone (SOZ) belonged to interictal networks in a large proportion of cases: 75 % (resp. 58 %) for spikes and 58 % (resp. 33 %) for oscillations in iEEG (resp. MEG). A subset of SOZ regions were detected by one type of discharges but not the other (25 % for spikes and 8 % for oscillations). Our study suggests that spike and oscillatory activities involve overlapping but distinct networks, and are complementary for presurgical mapping.

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Section: Discussionsupporting

confidence: 90%

Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG

et al. 2016

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“…Also, it is noteworthy that frontal localisation was absent in our cases with focal ESES. It is possible that this contradictory finding obtained in our series may be due to the utilisation of dipole analysis and voltage mapping for source localisation which were applied on ESES spikes in a few previous studies [29, 31]. Self‐limited CECTS is the most frequent idiopathic focal epilepsy of childhood and is the most frequent epilepsy syndrome in school‐aged children. An increasing number of reports have previously shown a not so “benign” outcome and atypical evolution of this type of epilepsy.…”

Section: Resultsmentioning

confidence: 67%

“…Such authors have suggested that an improved combination of clinical data and computer-aided EEG analysis will offer an opportunity to recognize "dangerous" EEG features early in the course of the syndrome, and thus it may be possible to foresee (and possibly prevent) evolution into ESES in patients at risk, but without overt encephalopathy [10,21]. Although dipole analysis and source localisation have already been used in many previous studies for other childhood epileptic syndromes, such as Panayiotopoulos syndrome and self-limited CECTS [22][23][24][25][26][27][28], there are only very few studies in the literature that have utilised source analysis and spatio-temporal dynamics in ESES [19][20][21][22][23][24][25][26][27][28][29][30][31]. To our knowledge, until now, no serious efforts have been taken to classify EEG patterns in ESES based on the spatio-temporal dynamics of their spikes, in order to simplify the interpretation of these complicated EEG patterns.…”

mentioning

confidence: 99%

Classification of electrical status epilepticus in sleep based on EEG patterns and spatiotemporal mapping of spikes

Balaram¹,

Jose²,

Gafoor³

et al. 2022

Epileptic Disorders

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Objective. We firstly aimed to describe and classify EEG patterns in electrical status epilepticus in sleep (ESES), and secondly subclassify EEG patterns based on analysis of spikes using spatio‐temporal mapping and electrical source analysis. Methods. Overnight EEGs (minimum: eight hours) of 30 children, aged 2‐12 years, with ESES (spike‐wave index: at least 50%) were selected. Average reference montage was used for dipole analysis and mapping. The location and orientation of the dipoles were determined by mapping positive and negative poles and applying the rules of mapping. The onset and propagation of the spikes and the latency between the two hemispheres (for bisynchronous spikes) were determined (based on source analysis using BESA research 7.1). Results. (1) ESES was classified as “generalised” (80%) and focal (20%) patterns; (2) the bisynchronous subtype in the “generalised” pattern was due to apparently synchronous bilateral activation of spikes (with lead‐in of 20‐60 ms from one hemisphere) with a tangential/oblique dipole (source analysis localised these spikes to around the peri‐rolandic cortex); (3) the classic description of ESES spikes as “diffuse” spikes with bifrontal maxima is a misinterpretation using the 10‐20 EEG system. Using voltage mapping and source analysis, cortical activation in the rolandic cortex was identified which imparts diffuse frontal negativity and parieto‐occipital positivity; (4) ESES spikes showed intraspike and interspike dipole instability and the orientation of dipoles changed due to local spike propagation around the source and into the depth of the sulcus (which we refer to herein as “dancing dipoles”); and (5) focal ESES were classified as parietal, occipital and temporo‐occipital patterns; a frontal ESES pattern was not seen. Significance. Based on detailed mapping and source analysis of ESES, we have successfully reinterpreted various misconceptions in the literature. We have simplified the interpretation of complicated EEG patterns by extracting the primary and propagated sources which aid the classification of ESES. As the dipole is always stable in self‐limited childhood epilepsy with centrotemporal spikes, we believe that the phenomenon of an intrinsically unstable dipole is a reliable qualitative EEG marker of ESES.

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“…Clinical studies showed similar results emphasizing the large influence of LEV on seizure propagation. Larsson et al demonstrated that LEV significantly reduced the ratio of patients with epileptic spikes propagations from 22/24 to 7/15 (75). This may be due to the widespread expression of SV2A in the brain especially at regions vital for activity spreading and propagation including the dentate gyrus, entorhinal cortex, frontal cortex, several thalamic nuclei, and mesencephalon (106)(107)(108).…”

Section: Levetiracetam (Lev)mentioning

confidence: 99%

The Effect of Anti-seizure Medications on the Propagation of Epileptic Activity: A Review

2021

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The propagation of epileptiform events is a highly interesting phenomenon from the pathophysiological point of view, as it involves several mechanisms of recruitment of neural networks. Extensive in vivo and in vitro research has been performed, suggesting that multiple networks as well as cellular candidate mechanisms govern this process, including the co-existence of wave propagation, coupled oscillator dynamics, and more. The clinical importance of seizure propagation stems mainly from the fact that the epileptic manifestations cannot be attributed solely to the activity in the seizure focus itself, but rather to the propagation of epileptic activity to other brain structures. Propagation, especially when causing secondary generalizations, poses a risk to patients due to recurrent falls, traumatic injuries, and poor neurological outcome. Anti-seizure medications (ASMs) affect propagation in diverse ways and with different potencies. Importantly, for drug-resistant patients, targeting seizure propagation may improve the quality of life even without a major reduction in simple focal events. Motivated by the extensive impact of this phenomenon, we sought to review the literature regarding the propagation of epileptic activity and specifically the effect of commonly used ASMs on it. Based on this body of knowledge, we propose a novel classification of ASMs into three main categories: major, minor, and intermediate efficacy in reducing the propagation of epileptiform activity.

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Decrease in Propagation of Interictal Epileptiform Activity After Introduction of Levetiracetam Visualized with Electric Source Imaging

Cited by 11 publications

References 37 publications

Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG

Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG

Classification of electrical status epilepticus in sleep based on EEG patterns and spatiotemporal mapping of spikes

The Effect of Anti-seizure Medications on the Propagation of Epileptic Activity: A Review

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