Magnetoencephalographic signatures of insular epileptic spikes based on functional connectivity

Failure to recognize insular cortex seizures has recently been identified as a cause of epilepsy surgeries targeting the temporal, parietal, or frontal lobe. Such failures are partly due to the fact that current noninvasive localization techniques fare poorly in recognizing insular epileptic foci. Our group recently demonstrated that magnetoencephalography (MEG) is sensitive to epileptiform spikes generated by the insula. In this study, we assessed the potential of distributed source imaging and functional connectivity analyses to distinguish insular networks underlying the generation of spikes. Nineteen patients with operculo‐insular epilepsy were investigated. Each patient underwent MEG as well as T1‐weighted magnetic resonance imaging (MRI) as part of their standard presurgical evaluation. Cortical sources of MEG spikes were reconstructed with the maximum entropy on the mean algorithm, and their time courses served to analyze source functional connectivity. The results indicate that the anterior and posterior subregions of the insula have specific patterns of functional connectivity mainly involving frontal and parietal regions, respectively. In addition, while their connectivity patterns are qualitatively similar during rest and during spikes, couplings within these networks are much stronger during spikes. These results show that MEG can establish functional connectivity‐based signatures that could help in the diagnosis of different subtypes of insular cortex epilepsy. Hum Brain Mapp 37:3250–3261, 2016. © 2016 Wiley Periodicals, Inc .     

sLORETA-qm for interictal MEG epileptic spike analysis: comparison of location and quantity with equivalent dipole estimation

ObjectiveTo determine whether quantitative modification of a standardised low-resolution brain electromagnetic tomography (sLORETA-qm) could be used as a reliable tool for quantitative analysis of magnetoencephalography (MEG) for analysis of the interictal epileptic spike. To verify the performance of sLORETA-qm, magnetic source location and quantity were compared with the equivalent current dipole (ECD) method.MethodsA total of 50 sources from 10 patients with epilepsy were obtained. Analyses were performed after the MEG data were 3–70 Hz band-pass filtered. Time points for analysis were selected referring to waveform patterns and the isofield contour map. With the same spherical model, source estimation was conducted with two methods of analysis: ECD and sLORETA-qm. Distance from the centre of the spherical model and intensities were compared between the methods.ResultsThere were no significant differences between the methods in the distance from the spherical model (paired t-test, p = 0.8761). Source intensities between the methods were strongly correlated (Spearman’s Rho = 0.9803, p < 0.001).ConclusionssLORETA-qm was closely correlated with ECD concerning point source location and quantity in analysis of the interictal epileptic spike.SignificancesLORETA-qm is a reliable quantifiable method without arbitrariness for analysis of the interictal epileptic spike.     

MEG detection of high frequency oscillations and intracranial-EEG validation in pediatric epilepsy surgery

ObjectiveTo assess the feasibility of automatically detecting high frequency oscillations (HFOs) in magnetoencephalography (MEG) recordings in a group of ten paediatric epilepsy surgery patients who had undergone intracranial electroencephalography (iEEG).MethodsA beamforming source-analysis method was used to construct virtual sensors and an automatic algorithm was applied to detect HFOs (80–250 Hz). We evaluated the concordance of MEG findings with the sources of iEEG HFOs, the clinically defined seizure onset zone (SOZ), the location of resected brain structures, and with post-operative outcome.ResultsIn 8/9 patients there was good concordance between the sources of MEG HFOs and iEEG HFOs and the SOZ. Significantly more HFOs were detected in iEEG relative to MEG t(71) = 2.85, p < .05. There was good concordance between sources of MEG HFOs and the resected area in patients with good and poor outcome, however HFOs were also detected outside of the resected area in patients with poor outcome.ConclusionOur findings demonstrate the feasibility of automatically detecting HFOs non-invasively in MEG recordings in paediatric patients, and confirm compatibility of results with invasive recordings.SignificanceThis approach provides support for the non-invasive detection of HFOs to aid surgical planning and potentially reduce the need for invasive monitoring, which is pertinent to paediatric patients.     

Temporal lobe epilepsy: Decreased thalamic resting-state functional connectivity and their relationships with alertness performance

ObjectivesStudies have provided evidence regarding the pathology of the thalamus in patients with temporal lobe epilepsy (TLE). The thalamus, particularly the right thalamus, is one of the subcortical structures that are most uniformly accepted as being significantly involved in alertness. Moreover, alertness impairment in epilepsy has been reported. This study aimed to investigate alterations in thalamic resting-state functional connectivity (FC) and their relationships with alertness performance in patients with TLE; an issue that has not yet been addressed.MethodsA total of 15 patients with right TLE (rTLE) and 16 healthy controls were recruited for the present study. All of the participants underwent a resting-state functional magnetic resonance imaging (fMRI) scan and the attention network test (ANT). Whole-brain voxel-wise FC analyses were applied to extract the thalamic resting-state functional networks in the patients with rTLE and healthy controls, and the differences between the two groups were evaluated. Correlation analyses were employed to examine the relationships between alterations in thalamic FC and alertness performance in patients with rTLE.ResultsCompared to the healthy controls, the FC within and between the bilateral thalamus was decreased in the patients with rTLE. Moreover, in the patient group, the bilateral anterior cingulate cortex (ACC) and subcortical regions, including the bilateral brainstem, cerebellum, putamen, right caudate nucleus, and amygdala, exhibited decreased FC with the ipsilateral thalamus (p < 0.05, AlphaSim corrected, cluster size > 44) but not with the contralateral thalamus (p < 0.05, AlphaSim corrected, cluster size > 43). The intrinsic and phasic alertness performances of the patients were impaired (p = 0.001 and p < 0.001, respectively) but not correlated with decreased thalamic FC. Meanwhile, the alertness performance was not altered in right TLE but was negatively correlated with decreased thalamic FC with ACC (p < 0.05).ConclusionsOur findings highlight the functional importance of the thalamus in TLE pathology and suggest that damage to the thalamic resting-state functional networks, particularly ipsilateral to the epileptogenic focus, is present in patients with TLE.     

Altered attention networks in benign childhood epilepsy with centrotemporal spikes (BECTS): A resting-state fMRI study

It is noteworthy that some children with benign childhood epilepsy with centrotemporal spikes (BECTS) show attention problems despite their favorable seizure outcome. Resting-state functional magnetic resonance imaging (fMRI) is a method widely used to detect brain network alterations in neuropsychiatric diseases. We used resting-state functional magnetic resonance imaging (fMRI) to investigate specific brain networks related to attention deficit in children with BECTS. Resting-state fMRI was performed in patients with BECTS with ADHD (n = 15) and those with BECTS without ADHD (n = 15) and in healthy controls (n = 15). Unbiased seed-based whole-brain functional connectivity analysis was used to study the connectivity pattern of three resting-state networks, including the ventral attention network (VAN) and the dorsal attention network (DAN) and the default mode network (DMN). Patients with BECTS with ADHD displayed decreased functional connectivity in the DAN compared with other two groups, while patients with BECTS without ADHD showed increased functional connectivity in the DAN. Moreover, we found increased functional connectivity in the VAN and in the DMN in patients with BECTS with or without ADHD when comparing with controls. These results showed that the newly-diagnosed children with BECTS displayed brain activity alterations in the ventral and dorsal attention networks. The difference in the extent of impairment in the dorsal attention network of patients with BECTS with ADHD and patients with BECTS without ADHD may lead to improved understanding of the underlying neuropathophysiology and treatment of BECTS with ADHD and BECTS without ADHD.     

Interictal high‐frequency oscillations (HFOs) as predictors of high frequency and conventional seizure onset zones

We investigated the relationship between the interictal high‐frequency oscillations (HFOs) and the seizure onset zones (SOZs) defined by the ictal HFOs or conventional frequency activity (CFA), and evaluated the usefulness of the interictal HFOs as spatial markers of the SOZs. We analysed seizures showing discrete HFOs at onset on intracranial EEGs acquired at ≥1000‐Hz sampling rate in a training cohort of 10 patients with temporal and extratemporal epilepsy. We classified each ictal channel as: HFO+ (HFOs at onset with subsequent evolution), HFO‐ (HFOs at onset without evolution), CFA (1.6–70‐Hz activity at onset with evolution), or non‐ictal. We defined the SOZs as: hSOZ (HFO+ channels only), hfo+&‐SOZ (HFO+ and HFO‐ channels), and cSOZ (CFA channels). Using automated methods, we detected the interictal HFOs and extracted five features: density, connectivity, peak frequency, log power, and amplitude. We created logistic regression models using these features, and tested their performance in a separate replication cohort of three patients. The models containing the five interictal HFO features reliably differentiated the channels located inside the SOZ from those outside in the training cohort (p<0.001), reaching the highest accuracy for the classification of hSOZ. Log power and connectivity had the highest odds ratios, both being higher for the channels inside the SOZ compared with those outside the SOZ. In the replication cohort of novel patients, the same models differentiated the HFO+ from HFO‐ channels, and predicted the extents of the hSOZ and hfo+&‐SOZ (F1 measure >0.5) but not the cSOZ. Our study shows that the interictal HFOs are useful in defining the spatial extent of the SOZ, and predicting whether or not a given channel in a novel patient would be involved in the seizure. The findings support the existence of an abnormal network of tightly‐linked ictal and interictal HFOs in patients with intractable epilepsy.     

Resting state connectivity in neocortical epilepsy: The epilepsy network as a patient-specific biomarker

ObjectiveLocalization related epilepsy (LRE) is increasingly accepted as a network disorder. To better understand the network specific characteristics of LRE, we defined individual epilepsy networks and compared them across patients.MethodsThe epilepsy network was defined in the slow cortical potential frequency band in 10 patients using intracranial EEG data obtained during interictal periods. Cortical regions were included in the epilepsy network if their connectivity pattern was similar to the connectivity pattern of the seizure onset electrode contact. Patients were subdivided into frontal, temporal, and posterior quadrant cohorts according to the anatomic location of seizure onset. Jaccard similarity was calculated within each cohort to assess for similarity of the epilepsy network between patients within each cohort.ResultsAll patients exhibited an epilepsy network in the slow cortical potential frequency band. The topographic distribution of this correlated network activity was found to be unique at the single subject level.ConclusionsThe epilepsy network was unique at the single patient level, even between patients with similar seizure onset locations.SignificanceWe demonstrated that the epilepsy network is patient-specific. This is in keeping with our current understanding of brain networks and identifies the patient-specific epilepsy network as a possible biomarker in LRE.     

Automatic 80-250Hz "ripple" high frequency oscillation detection in invasive subdural grid and strip recordings in epilepsy by a radial basis function neural network

ObjectiveRecent studies give evidence that high frequency oscillations (HFOs) in the range between 80 Hz and 500 Hz in invasive recordings of epilepsy patients have the potential to serve as reliable markers of epileptogenicity. This study presents an algorithm for automatic HFO detection.MethodsThe presented HFO detector uses a radial basis function neural network. Input features of the detector were energy, line length and instantaneous frequency. Visual marked “ripple” HFOs (80–250 Hz) of 3 patients were used to train the neural network, and a further 8 patients served for the detector evaluation.ResultsDetector sensitivity and specificity were 49.1% and 36.3%. The linear and rank correlation between visual and automatic marked “ripple” HFO counts over the channels were significant for all recordings. A reference detector based on the line length achieved a sensitivity of 35.4% and a specificity of 46.8%.ConclusionsAutomatic detections corresponded only partly to visual markings for single events but the relative distribution of brain regions displaying “ripple” HFO activity is reflected by the automated system.SignificanceThe detector allows the automatic evaluation of brain areas with high HFO frequency, which is of high relevance for the demarcation of the epileptogenic zone.     

Improving the identification of High Frequency Oscillations

ObjectiveHigh Frequency Oscillations (HFOs), including Ripples (80–250 Hz) and Fast Ripples (250–500 Hz), can be recorded from intracranial macroelectrodes in patients with intractable epilepsy. We implemented a procedure to establish the duration for which a stable measurement of rate of HFOs is achieved.MethodsTo determine concordance, Kappa coefficient was computed. The information gained when increasing the duration was analyzed in terms of HFO rates and ranking of channels with respect to HFO and spike rates.ResultsIn a group of 30 patients, Kappa was 0.7 for ripples, 0.7 for fast ripples and 0.67 for spikes. Five minutes provided the same information as 10 min in terms of rates in 9/10 patients and with respect to ranking of channels in 8/10 patients; 5/30 patients did not achieve stable measurements of HFOs or spikes and needed marking for 10 min.ConclusionWe propose that 5 min provides in most cases the same information as a longer interval when identifying HFOs and spikes in slow wave sleep, and present methods to identify when this is not the case.SignificanceThis procedure is useful to control for consistency between readers and to evaluate if the selected interval provides stable information, for automatic and visual identification of events.     

Pitfalls of high-pass filtering for detecting epileptic oscillations: A technical note on “false” ripples

ObjectivesTo analyze interictal High frequency oscillations (HFOs) as observed in the medial temporal lobe of epileptic patients and animals (ripples, 80–200 Hz and fast ripples, 250–600 Hz). To show that the identification of interictal HFOs raises some methodological issues, as the filtering of sharp transients (e.g., epileptic spikes or artefacts) or signals with harmonics can result in “false” ripples. To illustrate and quantify the occurrence of false ripples on filtered EEG traces.MethodsWe have performed high-pass filtering on both simulated and real data. We have also used two alternate methods: time-frequency analysis and matching pursuit.ResultsTwo types of events were shown to produce oscillations after filtering that could be confounded with actual oscillatory activity: sharp transients and harmonics of non-sinusoidal signals.ConclusionsHigh-pass filtering of EEG traces for detection of oscillatory activity should be performed with great care. Filtered traces should be compared to original traces for verification of presence of transients. Additional techniques such as time-frequency transforms or sparse decompositions are highly beneficial.SignificanceOur study draws the attention on an issue of great importance in the marking of HFOs on EEG traces. We illustrate complementary methods that can help both researchers and clinicians.     

Hippocampal high frequency oscillations in unilateral and bilateral mesial temporal lobe epilepsy

ObjectiveThe main aim of this study was to investigate the potential differences in terms of interictal high frequency oscillations (HFOs) between both hippocampi in unilateral (U-MTLE) and bilateral mesial temporal lobe epilepsy (B-MTLE).MethodsSixteen patients with MTLE underwent bilateral hippocampal depth electrode implantation as part of epilepsy surgery evaluation. Interictal HFOs were detected automatically. The analyses entail comparisons of the rates and spatial distributions of ripples and fast ripples (FR) in hippocampi and amygdalae, with respect to the eventual finding of hippocampal sclerosis (HS).ResultsIn U-MTLE, higher ripple and FR rates were found in the hippocampi ipsilateral to the seizure onset than in the contralateral hippocampi. Non-epileptic hippocampi in U-MTLE were distinguished by significantly lower ripple rate than in the remaining analyzed hippocampi. There were not differences between the hippocampi in B-MTLE. In the hippocampi with proven HS, higher FR rates were observed in the ventral than in the dorsal parts.ConclusionsNon-epileptic hippocampi in U-MTLE demonstrated significantly lower ripple rates than those epileptic in U-MTLE and B-MTLE.SignificanceLow interictal HFO occurrence might be considered as a marker of the non-epileptic hippocampi in MTLE.     

Effect of interictal epileptiform discharges on EEG-based functional connectivity networks

ObjectiveFunctional connectivity networks (FCNs) based on interictal electroencephalography (EEG) can identify pathological brain networks associated with epilepsy. FCNs are altered by interictal epileptiform discharges (IEDs), but it is unknown whether this is due to the morphology of the IED or the underlying pathological activity. Therefore, we characterized the impact of IEDs on the FCN through simulations and EEG analysis.MethodsWe introduced simulated IEDs to sleep EEG recordings of eight healthy controls and analyzed the effect of IED amplitude and rate on the FCN. We then generated FCNs based on epochs with and without IEDs and compared them to the analogous FCNs from eight subjects with infantile spasms (IS), based on 1340 visually marked IEDs. Differences in network structure and strength were assessed.ResultsIEDs in IS subjects caused increased connectivity strength but no change in network structure. In controls, simulated IEDs with physiological amplitudes and rates did not alter network strength or structure.ConclusionsIncreases in connectivity strength in IS subjects are not artifacts caused by the interictal spike waveform and may be related to the underlying pathophysiology of IS.SignificanceDynamic changes in EEG-based FCNs during IEDs may be valuable for identification of pathological networks associated with epilepsy.     

Electro- and magneto-encephalographic spike source localization of small focal cortical dysplasia in the dorsal peri-rolandic region

ObjectiveSmall focal cortical dysplasia (FCD) may be ambiguous or overlooked on magnetic resonance (MR) imaging. Source localization of EEG and magnetoencephalography (MEG) spikes was evaluated to confirm the diagnosis of small FCD.MethodsThis study included 6 epilepsy patients with a single small lesion on MR imaging suggesting FCD within a single gyrus among 181 consecutive epilepsy patients admitted to our epilepsy monitoring unit over 27 months. Stereotypical interictal spikes were detected on simultaneous EEG and MEG recordings and the onset-related source of averaged spikes was estimated.ResultsAll 6 patients had unique clinical characteristics as follows: leg sensori-motor seizures in 5 patients and eye version in 1 patient; a small MR imaging lesion suggesting FCD in the dorsal peri-rolandic region, which had been overlooked until our evaluation; and both EEG and MEG dipoles were estimated adjacent to the MR imaging lesion.ConclusionsSource localization of EEG and MEG spikes can confirm the diagnosis of FCD based on a single small MR imaging lesion, which was overlooked by previous examination of MR images.SignificanceExamination of MR images should be based on spike source localization as well as seizure semiology to identify subtle MR imaging abnormalities.     

High-frequency (80-500 Hz) oscillations and epileptogenesis in temporal lobe epilepsy

High-frequency oscillations (HFOs), termed ripples (80-200 Hz) and fast ripples (250-600 Hz), are recorded in the EEG of epileptic patients and in animal epilepsy models; HFOs are thought to reflect pathological activity and seizure onset zones. Here, we analyzed the temporal and spatial evolution of interictal spikes with and without HFOs in the rat pilocarpine model of temporal lobe epilepsy. Depth electrode recordings from dentate gyrus (DG), CA3 region, subiculum and entorhinal cortex (EC), were obtained from rats between the 4th and 15th day after a status epilepticus (SE) induced by i.p. injection of pilocarpine. The first seizure occurred 6.1 ± 2.5 days after SE (n = 7 rats). Five of 7 animals exhibited interictal spikes that co-occurred with fast ripples accounting for 4.9 ± 4.6% of all analyzed interictal spikes (n = 12,886) while all rats showed interictal spikes co-occurring with ripples, accounting for 14.3 ± 3.4% of all events. Increased rates of interictal spikes without HFOs in the EC predicted upcoming seizures on the following day, while rates of interictal spikes with fast ripples in CA3 reflected periods of high seizure occurrence. Finally, interictal spikes co-occurring with ripples did not show any specific relation to seizure occurrence. Our findings identify different temporal and spatial developmental patterns for the rates of interictal spikes with or without HFOs in relation with seizure occurrence. These distinct categories of interictal spikes point at dynamic processes that should bring neuronal networks close to seizure generation.     

Altered resting‐state connectivity during interictal generalized spike‐wave discharges in drug‐naïve childhood absence epilepsy

Purpose: To investigate the intrinsic brain connections at the time of interictal generalized spike‐wave discharges (GSWDs) to understand their mechanism of effect on brain function in untreated childhood absence epilepsy (CAE). Methods: The EEG‐functional MRI (fMRI) was used to measure the resting state functional connectivity during interictal GSWDs in drug‐naïve CAE, and three different brain networks—the default mode network (DMN), cognitive control network (CCN), and affective network (AN)—were investigated. Results: Cross‐correlation functional connectivity analysis with priori seed revealed decreased functional connectivity within each of these three networks in the CAE patients during interictal GSWDS. It included precuneus‐dorsolateral prefrontal cortex (DLPFC), dorsomedial prefrontal cortex (DMPFC), and inferior parietal lobule in the DMN; DLPFC‐inferior frontal junction (IFJ), and pre‐supplementary motor area (pre‐SMA) subregions connectivity disruption in CCN; ACC‐ventrolateral prefrontal cortex (VLPFC) and DMPFC in AN; There were also some regions, primarily the parahippcampus, paracentral in AN, and the left frontal mid orb in the CCN, which showed increased connectivity. Conclusions: The current findings demonstrate significant alterations of resting‐state networks in drug naïve CAE subjects during interictal GSWDs and interictal GSWDs can cause dysfunction in specific networks important for psychosocial function. Impairment of these networks may cause deficits both during and between seizures. Our study may contribute to the understanding of neuro‐pathophysiological mechanism of psychosocial function impairments in patients with CAE. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.     

Effects of the noncompetitive AMPA receptor antagonist perampanel on thalamo-cortical excitability: A study of high-frequency oscillations in somatosensory evoked potentials

ObjectiveWe designed a longitudinal cohort study on People with Epilepsy (PwE) with the aim of assessing the effect of Perampanel (PER) on cortico-subcortical networks, as measured by high-frequency oscillations of somatosensory evoked potentials (SEP-HFOs). SEP-HFOs measure the excitability of both thalamo-cortical projections (early HFOs) and intracortical GABAergic synapses (late HFOs), thus they could be used to study the anti-glutamatergic action of PER, a selective antagonist of the AMPA receptor.Methods15 PwE eligible for PER add-on therapy, were enrolled prospectively. Subjects underwent SEPs recording from the dominant hand at two times: PwE_T0 (baseline, before PER titration) and PwE_T1 (therapeutic dose of 4 mg). HFOs were obtained by filtering N20 scalp response in the 400–800 Hz range. Patients were compared with a normative population of 15 healthy controls (HC) matched for age and sex.ResultsWe found a significant reduction of Total HFOs and mostly early HFOs area between PwE_T0 and PwE_T1 (p = 0.05 and p = 0.045 respectively) and between HC and PwE_T1 (p = 0.01). Furthermore, we found a significant reduction of P24/N24 Amplitude between PwE_T0 and HC and between PwE_T0 and PwE_T1 (p = 0.006 and p = 0.032, respectively).ConclusionsIntroduction of PER as add-on therapy reduced the area of total HFOs, acting mainly on the early burst, related to thalamo-cortical pathways. Furthermore P24/N24 amplitude, which seems to reflect a form of cortico-subcortical integration, resulted increased in PwE at T0 and normalized at T1.SignificanceOur findings suggest that PER acts on cortico-subcortical excitability. This could explain the broad spectrum of PER and its success in forms of epilepsy characterized by thalamo-cortical hyperexcitability.     

The network integration of epileptic activity in relation to surgical outcome

ObjectiveEpilepsy is a network disease with epileptic activity and cognitive impairment involving large-scale brain networks. A complex network is involved in the seizure and in the interictal epileptiform discharges (IEDs). Directed connectivity analysis, describing the information transfer between brain regions, and graph analysis are applied to high-density EEG to characterise networks.MethodsWe analysed 19 patients with focal epilepsy who had high-density EEG containing IED and underwent surgery. We estimated cortical activity during IED using electric source analysis in 72 atlas-based cortical regions of the individual brain MRI. We applied directed connectivity analysis (information Partial Directed Coherence) and graph analysis on these sources and compared patients with good vs poor post-operative outcome at global, hemispheric and lobar level.ResultsWe found lower network integration reflected by global, hemispheric, lobar efficiency during the IED (p < 0.05) in patients with good post-surgical outcome, compared to patients with poor outcome. Prediction was better than using the IED field or the localisation obtained by electric source imaging.ConclusionsAbnormal network patterns in epilepsy are related to seizure outcome after surgery.SignificanceOur finding may help understand networks related to a more “isolated” epileptic activity, limiting the extent of the epileptic network in patients with subsequent good post-operative outcome.     

High frequency oscillations in intra-operative electrocorticography before and after epilepsy surgery

ObjectiveRemoval of brain tissue showing high frequency oscillations (HFOs; ripples: 80–250 Hz and fast ripples: 250–500 Hz) in preresection electrocorticography (preECoG) in epilepsy patients seems a predictor of good surgical outcome. We analyzed occurrence and localization of HFOs in intra-operative preECoG and postresection electrocorticography (postECoG).MethodsHFOs were automatically detected in one-minute epochs of intra-operative ECoG sampled at 2048 Hz of fourteen patients. Ripple, fast ripple, spike, ripples on a spike (RoS) and not on a spike (RnoS) rates were analyzed in pre- and postECoG for resected and nonresected electrodes.ResultsRipple, spike and fast ripple rates decreased after resection. RnoS decreased less than RoS (74% vs. 83%; p = 0.01). Most fast ripples in preECoG were located in resected tissue. PostECoG fast ripples occurred in one patient with poor outcome. Patients with good outcome had relatively high postECoG RnoS rates, specifically in the sensorimotor cortex.ConclusionsOur observations show that fast ripples in intra-operative ECoG, compared to ripples, may be a better biomarker for epileptogenicity. Further studies have to determine the relation between resection of epileptogenic tissue and physiological ripples generated by the sensorimotor cortex.SignificanceFast ripples in intra-operative ECoG can help identify the epileptogenic zone, while ripples might also be physiological.     

Sleep before and after temporal lobe epilepsy surgery

PurposePatients with epilepsy often complain of non-restorative sleep. This is the consequence of the acute effect of seizures and the chronic effect of epilepsy responsible for disrupting sleep architecture. Other factors such as antiepileptic drugs (AEDs), also play a role in the alteration of sleep organization. The aim of this study was to evaluate the specific effect of seizures and interictal epileptiform abnormalities (IEAs) on sleep, in particular to see whether reducing seizure frequency by epilepsy surgery might improve sleep organization in these patients.MethodsEleven patients with refractory mesial temporal lobe epilepsy, who underwent surgical treatment and who were seizure free at the follow-up, were included in the study. Treatment with AEDs was not significantly modified before the second year of follow-up. Patients were evaluated before surgery, at 1-year and 2-year follow-up visits with a videoEEG monitoring (24 h/24). At each follow-up visit, interictal epileptiform abnormalities and sleep macrostructure parameters were assessed.ResultsAll patients showed a reduction of their IEAs. At 1-year follow-up, total sleep time and REM sleep increased significantly (p = 0.032 and p = 0.006, respectively). At 2-year follow-up, an important increase of REM sleep was observed (p = 0.028). Most significant variations were noted 1 year after surgery. No significant variations were observed between the first and the second year after surgery.ConclusionsSurgical treatment of temporal lobe epilepsy may improve sleep macrostructure by reducing the number of seizures and of IEAs. These results indirectly confirm the role of epilepsy in disrupting sleep organization chronically.     

Orbitofrontal epilepsy: Case series and review of literature

BackgroundOrbitofrontal epilepsy (OFE) is less known and is poorly characterized in comparison with temporal lobe epilepsy, partly because it is rare and possibly because it is unrecognized and therefore underestimated.ObjectiveThis paper aimed to better characterize seizure semiology, presurgical findings, and surgical outcomes in patients with OFE.MethodsWe retrospectively reviewed all confidently established OFE cases from six Canadian epilepsy monitoring units between 1988 and 2014, and in the literature between 1972 and 2017. Inclusion criteria were identification of an epileptogenic lesion localized in the OFC or if the patient was seizure-free after surgical removal of the OFC in nonlesional cases.ResultsSixteen cases were identified from our databases. Fifty percent had predominantly sleep-related seizures; 56% had no aura (the remaining had nonspecific or vegetative auras), and 62.5% featured hypermotor (mostly hyperkinetic) behaviors. Interictal epileptiform discharges over frontal and temporal derivations always allowed lateralization. Magnetic resonance imaging (MRI) identified an orbitofrontal lesion in 8/16, positron emission tomography (PET) identified a hypometabolism extending outside the orbital cortex in 4/9, ictal single-photon emission computed tomography (SPECT) identified an orbital hyperperfusion in 1/5, magnetoencephalography (MEG) identified lateral orbital sources in 2/4, and intracranial electroencephalography (EEG) identified an orbitofrontal onset in 9/10. Fourteen patients underwent surgery, all reaching a favorable outcome (71.4% Engel 1; 28.6% Engel 2; mean FU = 5.6 years). Pre- and postoperative neuropsychological assessments revealed heterogeneous findings. Our review of literature identified 71 possible cases of OFE, 32 with confident focus localization. Extracted data from these cumulated cases supported observations made from our case series.ConclusionsOrbitofrontal epilepsy should be suspected with sleep-related, hyperkinetic seizures with no specific aura, and frontotemporal interictal discharges. Several patients have nonmotor seizures with or without auras which may resemble temporal lobe seizures. Postoperative seizure outcome was favorable, but there is inherent bias as we only included patients with a seizure-free outcome if the MRI was negative. A larger study is required to address identified gaps in knowledge such as identifying discriminative features between medial and lateral OFE, evaluating the value of more recent diagnostic tools, and assessing the neuropsychological outcome of orbital epilepsy surgery.