Patients with normal MR imaging (nonlesional) findings and medically refractory extratemporal epilepsy make up a disproportionate number of nonexcellent outcomes after epilepsy surgery. In this paper, the authors investigated the usefulness of intracranial electroencephalography (iEEG) in the identification of surgical candidates.
Between 1992 and 2002, 51 consecutive patients with normal MR imaging findings and extratemporal epilepsy underwent intracranial electrode monitoring. The implantation of intracranial electrodes was determined by seizure semiology, interictal and ictal scalp EEG, SPECT, and in some patients PET studies. The demographics of patients at the time of surgery, lobar localization of electrode implantation, duration of follow-up, and Engel outcome score were abstracted from the Mayo Rochester Epilepsy Surgery Database. A blinded independent review of the iEEG records was conducted for this study.
Thirty-one (61%) of the 51 patients who underwent iEEG ultimately underwent resection for their epilepsy. For 28 (90.3%) of the 31 patients who had epilepsy surgery, adequate information regarding follow-up (> 1 year), seizure frequency, and iEEG recordings was available. Twenty-six (92.9%) of 28 patients had frontal lobe resections, and 2 had parietal lobe resections. The most common iEEG pattern at seizure onset in the surgically treated group was a focal high-frequency discharge (in 15 [53.6%] of 28 patients). Ten (35.7%) of the 28 surgically treated patients were seizure free. Fourteen (50%) had Engel Class I outcomes, and overall, 17 (60.7%) had significant improvement (Engel Class I and IIAB with ≥ 80% seizure reduction). Focal high-frequency oscillation at seizure onset was associated with Engel Class I surgical outcome (12 [85.7%] of 14 patients, p = 0.02), and it was uncommon in the nonexcellent outcome group (3 [21.4%] of 14 patients).
A focal high-frequency oscillation (> 20 Hz) at seizure onset on iEEG may identify patients with nonlesional extratemporal epilepsy who are likely to have an Engel Class I outcome after epilepsy surgery. The prospect of excellent outcome in nonlesional extratemporal lobe epilepsy prior to intracranial monitoring is poor (14 [27.5%] of 51 patients). However, iEEG can further stratify patients and help identify those with a greater likelihood of Engel Class I outcome after surgery.
electroencephalography; epilepsy surgery; high-frequency oscillation
To investigate the feasibility of using noninvasive EEG source imaging approach to image continuous seizure activity in pediatric epilepsy patients.
Nine pediatric patients with medically intractable epilepsy were included in this study. Eight of the patients had extratemporal lobe epilepsy and one had temporal lobe epilepsy. All of the patients underwent resective surgery and seven of them underwent intracranial EEG (iEEG) monitoring. The ictal EEG was analyzed using a noninvasive dynamic seizure imaging (DSI) approach. The DSI approach separates scalp EEGs into independent components and extracts the spatio-temporal ictal features to achieve dynamic imaging of seizure sources. Surgical resection and intracranial recordings were used to validate the noninvasive imaging results.
The DSI determined seizure onset zones (SOZs) in these patients were localized within or in close vicinity to the surgically resected region. In the seven patients with intracranial monitoring, the estimated seizure onset sources were concordant with the seizure onset zones of iEEG. The DSI also localized the multiple foci involved in the later seizure propagation, which were confirmed by the iEEG recordings.
Dynamic seizure imaging can noninvasively image the seizure activations in pediatric patients with both temporal and extratemporal lobe epilepsy.
EEG seizure imaging can potentially be used to noninvasively image the SOZs and aid the pre-surgical planning in pediatric epilepsy patients.
Pediatric patients; Epilepsy; EEG; Dynamic seizure imaging; Intracranial recording; Surgical resection
The unpredictability of re-occurring seizures dramatically impacts the quality of life and autonomy of people with epilepsy. Reliable early seizure detection could open new therapeutic possibilities and thus substantially improve quality of life and autonomy. Though many seizure detection studies have shown the potential of scalp electroencephalogram (EEG) and intracranial EEG (iEEG) signals, reliable early detection of human seizures remains elusive in practice. Here, we examined the use of intracortical local field potentials (LFPs) recorded from 4×4-mm2 96-microelectrode arrays (MEA) for early detection of human epileptic seizures. We adopted a framework consisting of (1) sampling of intracortical LFPs; (2) denoising of LFPs with the Kalman filter; (3) spectral power estimation in specific frequency bands using 1-sec moving time windows; (4) extraction of statistical features, such as the mean, variance, and Fano factor (calculated across channels) of the power in each frequency band; and (5) cost-sensitive support vector machine (SVM) classification of ictal and interictal samples. We tested the framework in one-participant dataset, including 4 seizures and corresponding interictal recordings preceding each seizure. The participant was a 52-year-old woman suffering from complex partial seizures. LFPs were recorded from an MEA implanted in the participant’s left middle temporal gyrus. In this participant, spectral power in 0.3–10 Hz, 20–55 Hz, and 125–250 Hz changed significantly between ictal and interictal epochs. The examined seizure detection framework provided an event-wise sensitivity of 100% (4/4) and only one 20-sec-long false positive event in interictal recordings (likely an undetected subclinical event under further visual inspection), and a detection latency of 4.35 ± 2.21 sec (mean ± std) with respect to iEEG-identified seizure onsets. These preliminary results indicate that intracortical MEA recordings may provide key signals to quickly and reliably detect human seizures.
Improved non-invasive localization of the epileptogenic foci prior to epilepsy surgery would improve surgical outcome in patients with partial seizure disorders. A critical component for the identification of the epileptogenic brain is the analysis of electrophysiological data obtained during ictal activity from prolonged intracranial recordings. The development of a noninvasive means to identify the seizure onset zone (SOZ) would thus play an important role in treating patients with intractable epilepsy. In the present study, we have investigated non-invasive imaging of epileptiform activity in patients with medically intractable epilepsy by means of a cortical potential imaging (CPI) technique. Eight pediatric patients (1M/7F, ages 4–14 year) with intractable partial epilepsy were studied. Each patient had multiple (6 to 14) interictal spikes (IIS) subjected to the CPI analysis. Realistic geometry boundary element head models were built using each individual’s MRI in order to maximize the imaging precision. CPI analysis was performed on the IISs, and extrema in the estimated CPI images were compared with SOZs as determined from the ictal electrocorticogram (ECoG) recordings, as well as the resected areas in the patients and surgical outcomes. The distances between the maximum cortical activities of the IISs reflected by the estimated cortical potential distributions and the SOZs were determined to quantitatively evaluate the performance of the CPI in localizing the epileptogenic zone. Ictal ECoG recordings revealed that six patients exhibited a single epileptogenic focus while two patients had multiple foci. In each patient, the CPI results revealed an area of activity overlapping with the SOZs as identified by ictal ECoG. The distance from the extreme of the CPI images at the peak of IIS to the nearest intracranial electrode associated with the onset of the ictal activity was evaluated for each patient and the averaged distance was 4.6 mm. In the group of patients studied, the CPI imaged epileptogenic foci were within the resected areas. According to the follow-up of the eight patients included, two were seizure free and six had substantial reduction in seizure frequency. These promising results demonstrate the potential for noninvasive localization of the epileptogenic focus from interictal scalp EEG recordings. Confirmation of our results may have a significant impact on the process of presurgical planning in pediatric patients with intractable epilepsy by dramatically reducing or potentially eliminating the use of intracranial recording.
Cortical imaging; localization; epileptogenic focus; interictal spike; pediatric
The purpose of this study is to assess the accuracy of spatiotemporal source analysis of magnetoencephalography (MEG) and scalp electroencephalography (EEG) for representing the propagation of frontotemporal spikes in patients with partial epilepsy. This study focuses on frontotemporal spikes, which are typically characterized by a preceding anterior temporal peak followed by an ipsilateral inferior frontal peak. Ten patients with frontotemporal spikes on MEG/EEG were studied. We analyzed the propagation of temporal to frontal epileptic spikes on both MEG and EEG independently by using a cortically-constrained minimum norm estimate (MNE). Spatiotemporal source distribution of each spike was obtained on the cortical surface derived from the patient’s MRI. All patients underwent an extraoperative intracranial EEG (IEEG) recording covering temporal and frontal lobes after presurgical evaluation. We extracted source waveforms of MEG and EEG from the source distribution of interictal spikes at the sites corresponding to the location of intracranial electrodes. The time differences of the ipsilateral temporal and frontal peaks as obtained by MEG, EEG and IEEG were statistically compared in each patient. In all patients, MEG and IEEG showed similar time differences between temporal and frontal peaks. The time differences of EEG spikes were significantly smaller than those of IEEG in nine of ten patients. Spatiotemporal analysis of MEG spikes models the time course of frontotemporal spikes as observed on IEEG more adequately than EEG in our patients. Spatiotemporal source analysis may be useful for planning epilepsy surgery, by predicting the pattern of IEEG spikes.
epilepsy; magnetoencephalography; electroencephalography; propagation; spatiotemporal source analysis; minimum norm estimate
The hypothesis that focal scalp EEG and MEG interictal epileptiform activity can be modelled by single dipoles or by a limited number of dipoles was examined. The time course and spatial distribution of interictal activity recorded simultaneously by surface electrodes and by electrodes next to mesial temporal structures in 12 patients being assessed for epilepsy surgery have been studied to estimate the degree of confinement of neural activity present during interictal paroxysms, and the degree to which volume conduction and neural propagation take part in the diffusion of interictal activity. Also, intrapatient topographical correlations of ictal onset zone and deep interictal activity have been studied. Correlations between the amplitudes of deep and surface recordings, together with previous reports on the amplitude of scalp signals produced by artificially implanted dipoles suggest that the ratio of deep to surface activity recorded during interictal epileptiform activity on the scalp is around 1:2000. This implies that most such activity recorded on the scalp does not arise from volume conduction from deep structures but is generated in the underlying neocortex. Also, time delays of up to 220 ms recorded between interictal paroxysms at different recording sites show that interictal epileptiform activity can propagate neuronally within several milliseconds to relatively remote cortex. Large areas of archicortex and neocortex can then be simultaneously or sequentially active via three possible mechanisms: (1) by fast association fibres directly, (2) by fast association fibres that trigger local phenomena which in turn give rise to sharp/slow waves or spikes, and (3) propagation along the neocortex. The low ratio of deep-to-surface signal on the scalp and the simultaneous activation of large neocortical areas can yield spurious equivalent dipoles localised in deeper structures. Frequent interictal spike activities can also take place independently in areas other than the ictal onset zone and their interictal propagation to the surface is independent of their capacity to trigger seizures. It is concluded that: (1) the deep-to-surface ratios of electromagnetic fields from deep sources are extremely low on the scalp; (2) single dipoles or a limited number of dipoles are not adequate for surgical assessment; (3) the correct localisation of the onset of interictal activity does not necessarily imply the onset of seizures in the region or in the same hemisphere. It is suggested that, until volume conduction and neurophysiological propagation can be distinguished, semiempirical correlations between symptomatology, surgical outcome, and detailed presurgical modeling of the neocortical projection patterns by combined MEG, EEG, and MRI could be more fruitful than source localization with unrealistic source models.
In this paper, we study temporal couplings between interictal events of spatially remote regions in order to localize the leading epileptic regions from intracerebral electroencephalogram (iEEG). We aim to assess whether quantitative epileptic graph analysis during interictal period may be helpful to predict the seizure onset zone of ictal iEEG. Using wavelet transform, cross-correlation coefficient, and multiple hypothesis test, we propose a differential connectivity graph (DCG) to represent the connections that change significantly between epileptic and non-epileptic states as defined by the interictal events. Post-processings based on mutual information and multi-objective optimization are proposed to localize the leading epileptic regions through DCG. The suggested approach is applied on iEEG recordings of five patients suffering from focal epilepsy. Quantitative comparisons of the proposed epileptic regions within ictal onset zones detected by visual inspection and using electrically stimulated seizures, reveal good performance of the present method.
Epilepsy; functional connectivity graph; intracerebral EEG; permutation-based multiple hypothesis test; wavelet cross-correlation coefficient.
Scalp electroencephalography (EEG) has been established as a major component of the pre-surgical evaluation for epilepsy surgery. However, its ability to localize seizure onset zones (SOZ) has been significantly restricted by its low spatial resolution and indirect correlation with underlying brain activities. Here we report a novel non-invasive dynamic seizure imaging (DSI) approach based upon high-density EEG recordings. This novel approach was particularly designed to image the dynamic changes of ictal rhythmic discharges that evolve through time, space and frequency. This method was evaluated in a group of 8 epilepsy patients and results were rigorously validated using intracranial EEG (iEEG) (n = 3) and surgical outcome (n = 7). The DSI localized the ictal activity in concordance with surgically resected zones and ictal iEEG recordings in the cohort of patients. The present promising results support the ability to precisely and accurately image dynamic seizure activity from non-invasive measurements. The successful establishment of such a non-invasive seizure imaging modality for surgical evaluation will have a significant impact in the management of medically intractable epilepsy.
High-resolution EEG; Dynamic seizure imaging; Pre-surgical planning
Electrode arrays are sometimes implanted in the brains of patients with intractable epilepsy to better localize seizure foci before epilepsy surgery. Analysis of intracranial EEG (iEEG) recordings is typically performed in the electrode channel domain without explicit separation of the sources that generate the signals. However, intracranial EEG signals, like scalp EEG signals, could be linear mixtures of local activity and volume-conducted activity arising in multiple source areas. Independent component analysis (ICA) has recently been applied to scalp EEG data, and shown to separate the signal mixtures into independently generated brain and non-brain source signals. Here, we applied ICA to unmix source signals from intracranial EEG recordings from four epilepsy patients during a visually cued finger movement task in the presence of background pathological brain activity. This ICA decomposition demonstrated that the iEEG recordings were not maximally independent, but rather are linear mixtures of activity from multiple sources. Many of the independent component (IC) projections to the iEEG recording grid were consistent with sources from single brain regions, including components exhibiting classic movement-related dynamics. Notably, the largest IC projection to each channel accounted for no more than 20–80% of the channel signal variance, implying that in general intracranial recordings cannot be accurately interpreted as recordings of independent brain sources. These results suggest that ICA can be used to identify and monitor major field sources of local and distributed functional networks generating iEEG data. ICA decomposition methods are useful for improving the fidelity of source signals of interest, likely including distinguishing the sources of pathological brain activity.
ICA; intracranial; EEG; electrocorticography; ECoG; epilepsy; mu
Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such as providing patient warnings and delivering preemptive therapy. Progress on seizure forecasting, however, has been hindered by lack of sufficient data to rigorously evaluate the hypothesis that seizures are preceded by physiological changes, and are not simply random events. We investigated seizure forecasting in three dogs with naturally occurring focal epilepsy implanted with a device recording continuous intracranial EEG (iEEG). The iEEG spectral power in six frequency bands: delta (0.1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), low-gamma (30–70 Hz), and high-gamma (70–180 Hz), were used as features. Logistic regression classifiers were trained to discriminate labeled pre-ictal and inter-ictal data segments using combinations of the band spectral power features. Performance was assessed on separate test data sets via 10-fold cross-validation. A total of 125 spontaneous seizures were detected in continuous iEEG recordings spanning 6.5 to 15 months from 3 dogs. When considering all seizures, the seizure forecasting algorithm performed significantly better than a Poisson-model chance predictor constrained to have the same time in warning for all 3 dogs over a range of total warning times. Seizure clusters were observed in all 3 dogs, and when the effect of seizure clusters was decreased by considering the subset of seizures separated by at least 4 hours, the forecasting performance remained better than chance for a subset of algorithm parameters. These results demonstrate that seizures in canine epilepsy are not randomly occurring events, and highlight the feasibility of long-term seizure forecasting using iEEG monitoring.
Epilepsy affects 50 million people worldwide, and seizures in 30% of the cases remain drug resistant. This has increased interest in responsive neurostimulation, which is most effective when administered during seizure onset. We propose a novel framework for seizure onset detection that involves (i) constructing statistics from multichannel intracranial EEG (iEEG) to distinguish nonictal versus ictal states; (ii) modeling the dynamics of these statistics in each state and the state transitions; you can remove this word if there is no room. (iii) developing an optimal control-based “quickest detection” (QD) strategy to estimate the transition times from nonictal to ictal states from sequential iEEG measurements. The QD strategy minimizes a cost function of detection delay and false positive probability. The solution is a threshold that non-monotonically decreases over time and avoids responding to rare events that normally trigger false positives. We applied QD to four drug resistant epileptic patients (168 hour continuous recordings, 26–44 electrodes, 33 seizures) and achieved 100% sensitivity with low false positive rates (0.16 false positive/hour). This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction.
► A control-theoretical framework for automatic online seizure detection is proposed. ► This framework combines iEEGs, network-based statistics, and optimization tools. ► The detection algorithm minimizes detection delays and probability of false alarms. ► Reported results show 100% sensitivity and low false positive rates.
Quickest detection; Bayesian estimation; Multivariate analysis; Intracranial electroencephalogram; Optimal control; Hidden Markov model; Dynamic programming; Networks
Rationale: Dense array EEG (dEEG) evenly covers the whole head surface with over 100 channels contributing to more accurate electrical source imaging due to the higher spatial and temporal resolution. Several studies have shown the clinical utility of dEEG in presurgical clinical evaluation of epilepsy. However validation studies measuring the accuracy of dEEG source imaging are still needed. This can be achieved through simultaneously recording both scalp dEEG with intracranial electrodes (icEEG), which is considered as the true measure of cortical activity at the source. The purpose of this study is to evaluate the accuracy of 256-channel dEEG electrical source estimation for interictal spikes.
Methods: Four patients with medically refractory neocortical epilepsy, all surgical candidates, underwent subdural electrode implantation to determine ictal onset and define functional areas. One patient showed a lesion on the magnetic resonance imaging in the right parietal lobe. The patient underwent simultaneous recording of interictal spikes by both scalp 256-channelsvdEEG and icEEG. The dEEG was used to non-invasively estimate the source of the interictal spikes detected by the 256-channel dEEG array, which was then compared to the activity measured directly at the source by the icEEG.
Results: From the four patients, a total of 287 interictal spikes were measured with the icEEG. One hundred fifty-five of the 287 spikes (54%) were visually detected by the dEEG upon examination of the 256 channel head surface array. The spike amplitudes detected by the 256-channel dEEG correlated with icEEG spike amplitudes (p < 0.01). All spikes detected in dEEG were localized to the same lobe correctly.
Conclusion: Our study demonstrates that 256-channel dEEG can reliably detect interictal spikes and localize them with reasonable accuracy. Two hundred fifty-six-channel dEEG may be clinically useful in the presurgical workup for epilepsy and also reduce the need for invasive EEG evaluation.
dense array EEG; source estimation; neocortical epilepsy; interictal spike; intracranial EEG
Electroencephalography (EEG) remains a “gold standard” for defining seizures; hence identification of epileptogenic zone for surgical treatment of epilepsy requires precise electrographic localization of the seizures. Routine scalp EEG recording is not sufficient in many instances, such as extratemporal lobe epilepsy or non-lesional temporal lobe epilepsy. In these individuals EEG recording from proximity of the seizure focus is necessary, which can be achieved by placing electrodes on the surface or in the substance of the brain. As this process requires invasive procedures (usually necessitating surgical intervention) EEG obtained via these electrodes is defined as invasive electroencephalography (iEEG). As only limited areas of the brain can be covered by these electrodes in an individual, precise targeting of the presumed seizure onset location is crucial. The presurgical planning includes where to place electrodes, which type of the electrodes to choose and planned duration of the intracranial recording. Though there are general principles that guide such endeavor, each center does it slightly differently depending upon the various technologies available to them and expertise and preferences of the epilepsy surgery team. Here we describe our approach to iEEG recording. We briefly describe the background, types of iEEG recording and rationale for each, various electrode types, and scenarios where iEEG might be useful. We also describe planning of iEEG recording once the need has been established as well as our decision making process of deciding about location of electrode placement, type of electrodes to use, length of recording, choice of arrays, mapping of eloquent cortex and finally surgical planning and decisions.
Depth electrodes; electrocorticography; epidural peg electrodes; epilepsy surgery; intracranial electroencephalography; invasive electroencephalography; subdural electrodes
Intracranial electroencephalography (EEG) is performed as part of an epilepsy surgery evaluation when noninvasive tests are incongruent or the putative seizure-onset zone is near eloquent cortex. Determining the seizure-onset zone using intracranial EEG has been conventionally based on identification of specific ictal patterns with visual inspection. High-frequency oscillations (HFOs, >80 Hz) have been recognized recently as highly correlated with the epileptogenic zone. However, HFOs can be difficult to detect because of their low amplitude. Therefore, the prevalence of ictal HFOs and their role in localization of epileptogenic zone on intracranial EEG are unknown.
We identified 48 patients who underwent surgical treatment after the surgical evaluation with intracranial EEG, and 44 patients met criteria for this retrospective study. Results were not used in surgical decision making. Intracranial EEG recordings were collected with a sampling rate of 2,000 Hz. Recordings were first inspected visually to determine ictal onset and then analyzed further with time-frequency analysis. Forty-one (93%) of 44 patients had ictal HFOs determined with time-frequency analysis of intracranial EEG.
Twenty-two (54%) of the 41 patients with ictal HFOs had complete resection of HFO regions, regardless of frequency bands. Complete resection of HFOs (n = 22) resulted in a seizure-free outcome in 18 (82%) of 22 patients, significantly higher than the seizure-free outcome with incomplete HFO resection (4/19, 21%).
Our study shows that ictal HFOs are commonly found with intracranial EEG in our population largely of children with cortical dysplasia, and have localizing value. The use of ictal HFOs may add more promising information compared to interictal HFOs because of the evidence of ictal propagation and followed by clinical aspect of seizures. Complete resection of HFOs is a favorable prognostic indicator for surgical outcome.
High-frequency oscillations; Intracranial EEG; Time-frequency analysis; Surgical outcome; Nonlesional epilepsy
High frequency oscillations (HFOs) can be recorded with depth electrodes in focal epilepsy patients. They occur during seizures and interictally and seem important in seizure genesis. We investigated whether interictal and ictal HFOs occur in the same regions and how they relate to epileptiform spikes.
In 25 patients, spikes, ripples (80–250 Hz) and fast ripples (FR: 250–500 Hz) and their co-occurrences were marked during interictal slow wave sleep (5–10 min), during 10 preictal seconds and 5 s following seizure onset. We compared occurrence and spatial distribution between these periods.
HFOs and spikes increased from interictal to ictal periods: the percentage of time occupied by ripples increased from 2.3% to 6.5%, FR from 0.2% to 0.8%, spikes from 1.1% to 4.8%. HFOs increased from interictal to preictal periods in contrast to spikes. Spikes were in different channels in the interictal, preictal and ictal periods whereas HFOs largely remained in the same channels.
HFOs remain confined to the same, possibly epileptogenic, area, during interictal and ictal periods, while spikes are more widespread during seizures than interictally.
Ictal and interictal HFOs represent the same (epileptogenic) area and are probably similar phenomena.
PMID: 21030302 CAMSID: cams3344
High frequency oscillations; Focal epilepsy; Epilepsy surgery; Depth EEG; Ictogenesis
To evaluate the diagnostic value of individual noninvasive presurgical modalities and to study their role in surgical management of nonlesional pediatric epilepsy patients.
We retrospectively studied 14 children (3–18 years) with nonlesional intractable focal epilepsy. Clinical characteristics, surgical outcome, localizing features on 3 presurgical diagnostic tests (subtraction peri-ictal SPECT coregistered to MRI [SISCOM], statistical parametric mapping [SPM] analysis of [18F] FDG-PET, magnetoencephalography [MEG]), and intracranial EEG (iEEG) were reviewed. The localization of each individual test was determined for lobar location by visual inspection. Concordance of localization between each test and iEEG was scored as follows: 2 = lobar concordance; 1 = hemispheric concordance; 0 = discordance or nonlocalization. Total concordance score in each patient was measured by the summation of concordance scores for all 3 tests.
Seven (50%) of 14 patients were seizure-free for at least 12 months after surgery. One (7%) had only rare seizures and 6 (43%) had persistent seizures. MEG (79%, 11/14) and SISCOM (79%, 11/14) showed greater lobar concordance with iEEG than SPM-PET (13%, 3/14) (p < 0.05). SPM-PET provided hemispheric lateralization (71%, 10/14) more often than lobar localization. Total concordance score tended to be greater for seizure-free patients (4.7) than for non–seizure-free patients (3.9).
Our data suggest that MEG and SISCOM are better tools for lobar localization than SPM analysis of FDG-PET in children with nonlesional epilepsy. A multimodality approach may improve surgical outcome as well as selection of surgical candidates in patients without MRI abnormalities.
Focality in electro-clinical or neuroimaging data often motivates epileptologists to consider epilepsy surgery in patients with medically-uncontrolled seizures, while not all focal findings are causally associated with the generation of epileptic seizures. With the help of Hill's criteria, we have discussed how to establish causality in the context of the presurgical evaluation of epilepsy. The strengths of EEG include the ability to determine the temporal relationship between cerebral activities and clinical events; thus, scalp video-EEG is necessary in the evaluation of the majority of surgical candidates. The presence of associated ictal discharges can confirm the epileptic nature of a particular spell and whether an observed neuroimaging abnormality is causally associated with the epileptic seizure. Conversely, one should be aware that scalp EEG has a limited spatial resolution and sometimes exhibits propagated epileptiform discharges more predominantly than in situ discharges generated at the seizure-onset zone. Intraoperative or extraoperative electrocorticography (ECoG) is utilized when noninvasive presurgical evaluation, including anatomical and functional neuroimaging, fails to determine the margin between the presumed epileptogenic zone and eloquent cortex. Retrospective as well as prospective studies have reported that complete resection of the seizure-onset zone on ECoG was associated with a better seizure outcome, but not all patients became seizure-free following such resective surgery. Some retrospective studies suggested that resection of sites showing high-frequency oscillations (HFOs) at >80 Hz on interictal or ictal ECoG was associated with a better seizure outcome. Others reported that functionally-important areas may generate HFOs of a physiological nature during rest as well as sensorimotor and cognitive tasks. Resection of sites showing task-related augmentation of HFOs has been reported to indeed result in functional loss following surgery. Thus, some but not all sites showing interictal HFOs are causally associated with seizure generation. Furthermore, evidence suggests that some task-related HFOs can be transiently suppressed by the prior occurrence of interictal spikes. The significance of interictal HFOs should be assessed by taking into account the eloquent cortex, seizure-onset zone, and cortical lesions. Video-EEG and ECoG generally provide useful but still limited information to establish causality in presurgical evaluation. A comprehensive assessment of data derived from multiple modalities is ultimately required for successful management.
infantile spasms; pediatric epilepsy surgery; concept of the epileptogenic zone; eloquent cortex; functional brain mapping; language; in-vivo animation of event-related gamma activity; Hill's criteria for causality; high-frequency oscillations (HFOs)
Epilepsy surgery has improved over the last decade, but non-seizure-free outcome remains at 10%–40% in temporal lobe epilepsy (TLE) and 40%–60% in extratemporal lobe epilepsy (ETLE). This paper reports a complex multifocal case. With a normal magnetic resonance imaging (MRI) result and nonlocalizing electroencephalography (EEG) findings (bilateral TLE and ETLE, with more interictal epileptiform discharges [IEDs] in the right frontal and temporal regions), a presurgical EEG-functional MRI (fMRI) was performed before the intraoperative intracranial EEG (icEEG) monitoring (icEEG with right hemispheric coverage). Our previous EEG-fMRI analysis results (IEDs in the left hemisphere alone) were contradictory to the EEG and icEEG findings (IEDs in the right frontal and temporal regions). Thus, the EEG-fMRI data were reanalyzed with newly identified IED onsets and different fMRI model options. The reanalyzed EEG-fMRI findings were largely concordant with those of EEG and icEEG, and the failure of our previous EEG-fMRI analysis may lie in the inaccurate identification of IEDs and wrong usage of model options. The right frontal and temporal regions were resected in surgery, and dual pathology (hippocampus sclerosis and focal cortical dysplasia in the extrahippocampal region) was found. The patient became seizure-free for 3 months, but his seizures restarted after antiepileptic drugs (AEDs) were stopped. The seizures were not well controlled after resuming AEDs. Postsurgical EEGs indicated that ictal spikes in the right frontal and temporal regions reduced, while those in the left hemisphere became prominent. This case suggested that (1) EEG-fMRI is valuable in presurgical evaluation, but requires caution; and (2) the intact seizure focus in the remaining brain may cause the non-seizure-free outcome.
EEG-fMRI; focus localization; presurgical evaluation; epilepsy surgery
Non-invasive studies to predict regions of seizure onset are important for planning intracranial grid locations for invasive cortical recordings prior to resective surgery for patients with medically intractable epilepsy. The neurosurgeon needs to know both the seizure onset zone (SOZ) and the region of immediate cortical spread to determine the epileptogenic zone to be resected. The immediate zone of spread may be immediately adjacent, on a nearby gyrus, in a different lobe, and sometimes even in the contralateral cerebral hemisphere. We reviewed consecutive simultaneous EEG/MEG recordings on 162 children with medically intractable epilepsy. We analyzed the MEG signals in the bandwidth 20–70 Hz with a beamformer algorithm, synthetic aperture magnetometry, at a 2.5 mm voxel spacing throughout the brain (virtual sensor locations, VSLs) with the kurtosis statistic (g2) to determine presence of excess kurtosis (γ2) consistent with intermittent increased high frequency spikiness of the background. The MEG time series was reconstructed (virtual sensor signals) at each of these VSLs. The VS signals were further examined with a relative peak amplitude spike detection algorithm. The time of VS spike detection was compared to the simultaneous EEG and MEG sensor signals for presence of conventional epileptiform spike morphology in the latter signals. The time of VS spike detection was compared across VSLs to determine earliest and last VSL to show a VS spike. Seven subjects showed delay in activation across VS locations detectable on visual examination. We compared the VS locations that showed earliest and later VS spikes with the locations on intracranial grid locations by electrocorticography (ECoG) that showed spikes and both onset and spread of seizures. We compared completeness of resection of VS locations to postoperative outcome. The VS locations for spike onset and spread were similar to locations for ictal onset and spread by ECoG.
magnetoencephalography; beamformer; children; adolescents; intracranial EEG; outcome; network; localization
In the present study, we have developed a novel patient-specific rule-based seizure prediction system for focal neocortical epilepsy.
Five univariate measures including correlation dimension, correlation entropy, noise level, Lempel-Ziv complexity, and largest Lyapunov exponent as well as one bivariate measure, nonlinear interdependence, were extracted from non-overlapping 10-second segments of intracranial electroencephalogram (iEEG) data recorded using electrodes implanted deep in the brain and/or placed on the cortical surface. The spatio-temporal information was then integrated by using rules established based on patient-specific changes observed in the period prior to a seizure sample for each patient. The system was tested on 316 h of iEEG data containing 49 seizures recorded in eleven patients with medically intractable focal neocortical epilepsy.
For seizure occurrence periods of 30 and 50 min our method showed an average sensitivity of 79.9% and 90.2% with an average false prediction rate of 0.17 and 0.11/h, respectively. In terms of sensitivity and false prediction rate, the system showed superiority to random and periodical predictors.
The nonlinear analysis of iEEG in the period prior to seizures revealed patient-specific spatio-temporal changes that were significantly different from those observed within baselines in the majority of the seizures analyzed in this study.
The present results suggest that the patient specific rule-based approach may become a potentially useful approach for predicting seizures prior to onset.
Focal epilepsy; intracranial EEG; nonlinear dynamics; seizure prediction
Purpose. To investigate EEG and SPECT in the surgical outcome of patients with normal MRI (nonlesional) and extratemporal lobe epilepsy. Methods. We retrospectively identified 41 consecutive patients with nonlesional extratemporal epilepsy who underwent epilepsy surgery between 1997 and 2007. The history, noninvasive diagnostic studies (scalp EEG, MRI, and SPECT) and intracranial EEG (iEEG) monitoring was reviewed. Scalp and iEEG ictal onset patterns were defined. The association of preoperative studies and postoperative seizure freedom was analyzed using Kaplan-Meier analysis, log-rank test, and Cox proportional hazard. Results. Thirty-six of 41 patients had adequate information with a minimum of 1-year followup. Favorable surgical outcome was identified in 49% of patients at 1 year, and 35% at 4-year. On scalp EEG, an ictal onset pattern consisting of focal beta-frequency discharge (>13–125 Hz) was associated with favorable surgical outcome (P = 0.02). Similarly, a focal fast-frequency oscillation (>13–125 Hz) on iEEG at ictal onset was associated with favorable outcome (P = 0.03). Discussion. A focal fast-frequency discharge at ictal onset identifies nonlesional MRI, extratemporal epilepsy patients likely to have a favorable outcome after resective epilepsy surgery.
Analysis of intracranial electroencephalographic (iEEG) recordings in patients with temporal lobe epilepsy (TLE) has revealed characteristic dynamical features that distinguish the interictal, ictal, and postictal states and inter-state transitions. Experimental investigations into the mechanisms underlying these observations require the use of an animal model. A rat TLE model was used to test for differences in iEEG dynamics between well-defined states and to test specific hypotheses: 1) the short-term maximum Lyapunov exponent (STLmax), a measure of signal order, is lowest and closest in value among cortical sites during the ictal state, and highest and most divergent during the postictal state; 2) STLmax values estimated from the stimulated hippocampus are the lowest among all cortical sites; and 3) the transition from the interictal to ictal state is associated with a convergence in STLmax values among cortical sites. iEEGs were recorded from bilateral frontal cortices and hippocampi. STLmax and T-index (a measure of convergence/divergence of STLmax between recorded brain areas) were compared among the four different periods. Statistical tests (ANOVA and multiple comparisons) revealed that ictal STLmax was lower (p < 0.05) than other periods, STLmax values corresponding to the stimulated hippocampus were lower than those estimated from other cortical regions, and T-index values were highest during the postictal period and lowest during the ictal period. Also, the T-index values corresponding to the preictal period were lower than those during the interictal period (p < 0.05). These results indicate that a rat TLE model demonstrates several important dynamical signal characteristics similar to those found in human TLE and support future use of the model to study epileptic state transitions.
Seizures; Temporal lobe epilepsy; EEG dynamics
In human partial epilepsies, as well as in experimental models of chronic and/or acute epilepsy, the role of inhibition and the relationship between the inhibition and excitation and epileptogenesis has long been questioned. Besides experimental methods carried out either in vitro (human or animal tissue) or in vivo (animals), pathophysiological mechanisms can be approached by direct recording of brain electrical activity in human epilepsy. Indeed, in some clinical pre-surgical investigation methods like stereoelectroencephalopraphy (SEEG), intracerebral electrodes are used in patients suffering from drug resistant epilepsy to directly record paroxysmal activities with excellent temporal resolution (in the order of one millisecond). The study of neurophysiological mechanisms underlying such depth-EEG activities is crucial to progress in the understanding of the interictal to ictal transition.
In this study, we relate electrophysiological patterns typically observed during the transition from interictal to ictal activity in human mesial temporal lobe epilepsy (MTLE) to mechanisms (at a neuronal population level) involved in seizure generation through a computational model of EEG activity. Intracerebral EEG signals recorded from hippocampus in five patients with MTLE during four periods (during interictal activity, just before seizure onset, during seizure onset and during ictal activity) were used to identify the three main parameters of a model of hippocampus EEG activity (related to excitation, slow dendritic inhibition and fast somatic inhibition). The identification procedure used optimization algorithms to minimize a spectral distance between real and simulated signals. Results demonstrated that the model generates very realistic signals for automatically identified parameters. They also showed that the transition from interictal to ictal activity can not be simply explained by an increase in excitation and a decrease in inhibition but rather by time-varying ensemble interactions between pyramidal cells and local interneurons projecting to either their dendritic or perisomatic region (with slow and fast GABAA kinetics). Particularly, during preonset activity, an increasing dendritic GABAergic inhibition compensates a gradually increasing excitation up to a brutal drop at seizure onset when faster oscillations (beta and low gamma band, 15 to 40 Hz) are observed. These faster oscillations are then explained by the model feedback loop between pyramidal cells and interneurons targeting their perisomatic region. These findings obtained from model identification in human TLE are in agreement with some results obtained experimentally, either on animal models of epilepsy or on the human epileptic tissue.
Human TLE; Hippocampus; Intracerebral EEG; Neuronal population model; Parameter identification; Ictogenesis mechanisms.
There is inherent difficulty in identifying the epileptogenic zone in nonlesional neocortical epilepsy, which leads to the incomplete resection. However, with careful interpretation of other studies including functional neuroimaging and the presence of concordant results, surgical treatment can benefit selected patients with nonlesional neocortical epilepsy. Two recent large studies including ours demonstrated that seizure free outcomes were 47 and 55% for nonlesional TLE, and 41 and 43% for nonlesional extratemporal lobe epilepsy patients. Concordance with two or more presurgical evaluations among interictal EEG, ictal EEG, FDG-PET, and ictal SPECT was significantly related to a seizure-free outcome. However, we should be cautious to the possibility of false localization of ictal EEG or functional neuroimaging in nonlesional neocortical epilepsy. Careful placement of intracranial electrodes on the presumed epileptogenic zone and the adjacent areas should be needed for these patients. The repositioning of intracranial electrodes after the failure in identifying ictal onset zone at the initial intracranial study might identify a new ictal onset zone. Consideration of one-week interval repositioning of intracranial electrodes could be helpful in selected patients. Intracranial EEG is one of the most important procedures in planning surgery and achieving a good surgical outcome in resective epilepsy surgery. Slow propagation and focal or regional ictal onset rather than widespread onset were associated with a seizure-free outcome. Complete resection including the area with initial three second ictal rhythm and interictal abnormalities predicts a good surgical outcome.
Epilepsy surgery; Nonlesion; Neocortical
Epileptic cortex is characterized by paroxysmal electrical discharges. Analysis of these interictal discharges typically manifests as spike–wave complexes on electroencephalography, and plays a critical role in diagnosing and treating epilepsy. Despite their fundamental importance, little is known about the neurophysiological mechanisms generating these events in human focal epilepsy. Using three different systems of microelectrodes, we recorded local field potentials and single-unit action potentials during interictal discharges in patients with medically intractable focal epilepsy undergoing diagnostic workup for localization of seizure foci. We studied 336 single units in 20 patients. Ten different cortical areas and the hippocampus, including regions both inside and outside the seizure focus, were sampled. In three of these patients, high density microelectrode arrays simultaneously recorded between 43 and 166 single units from a small (4 mm × 4 mm) patch of cortex. We examined how the firing rates of individual neurons changed during interictal discharges by determining whether the firing rate during the event was the same, above or below a median baseline firing rate estimated from interictal discharge-free periods (Kruskal–Wallis one-way analysis, P<0.05). Only 48% of the recorded units showed such a modulation in firing rate within 500 ms of the discharge. Units modulated during the discharge exhibited significantly higher baseline firing and bursting rates than unmodulated units. As expected, many units (27% of the modulated population) showed an increase in firing rate during the fast segment of the discharge (±35 ms from the peak of the discharge), while 50% showed a decrease during the slow wave. Notably, in direct contrast to predictions based on models of a pure paroxysmal depolarizing shift, 7.7% of modulated units recorded in or near the seizure focus showed a decrease in activity well ahead (0–300 ms) of the discharge onset, while 12.2% of units increased in activity in this period. No such pre-discharge changes were seen in regions well outside the seizure focus. In many recordings there was also a decrease in broadband field potential activity during this same pre-discharge period. The different patterns of interictal discharge-modulated firing were classified into more than 15 different categories. This heterogeneity in single unit activity was present within small cortical regions as well as inside and outside the seizure onset zone, suggesting that interictal epileptiform activity in patients with epilepsy is not a simple paroxysm of hypersynchronous excitatory activity, but rather represents an interplay of multiple distinct neuronal types within complex neuronal networks.
microelectrodes; focal epilepsy; spike–wave; single unit; microphysiology