Sudden phase changes are related to cortical phase transitions, which likely change in frequency and spatial distribution as epileptogenic activity evolves. A 100 s long section of micro-ECoG data obtained before and during a seizure was selected and analyzed. In addition, nine other short-duration epileptic events were also examined. The data was collected at 420 Hz, imported into MATLAB, downsampled to 200 Hz, and filtered in the 1–50 Hz band. The Hilbert transform was applied to compute the analytic phase, which was then unwrapped, and detrended to look for sudden phase changes. The phase slip rate (counts/s) and its acceleration (counts/s2) were computed with a stepping window of 1-s duration and with a step size of 5 ms. The analysis was performed for theta (3–7 Hz), alpha (7–12 Hz), and beta (12–30 Hz) bands. The phase slip rate on all electrodes in the theta band decreased while it increased for the alpha and beta bands during the seizure period. Similar patterns were observed for isolated epileptogenic events. Spatiotemporal contour plots of the phase slip rates were also constructed using a montage layout of 8 × 8 electrode positions. These plots exhibited dynamic and oscillatory formation of phase cone-like structures which were higher in the theta band and lower in the alpha and beta bands during the seizure period and epileptogenic events. These results indicate that the formation of phase cones might be an excellent biomarker to study the evolution of a seizure and also the cortical dynamics of isolated epileptogenic events.

We found that phase cone clustering patterns in EEG ripple bands demonstrate an increased turnover rate in epileptogenic zones compared to adjacent regions. We employed 256 channel EEG data collected in four adult subjects with refractory epilepsy. The analysis was performed in the 80–150 and 150–250 Hz ranges. Ictal onsets were documented with intracranial EEG recordings. Interictal scalp recordings, free of epileptiform patterns, of 240-s duration, were selected for analysis for each subject. The data was filtered, and the instantaneous phase was extracted after the Hilbert transformation. Spatiotemporal contour plots of the unwrapped instantaneous phase with 1.0 ms intervals were constructed using a montage layout of the 256 electrode positions. Stable phase cone patterns were selected based on criteria that the sign of spatial gradient did not change for a minimum of three consecutive time samples and the frame velocity was consistent with known propagation velocities of cortical axons. These plots exhibited increased dynamical formation and dissolution of phase cones in the ictal onset zones, compared to surrounding cortical regions, in all four patients. We believe that these findings represent markers of abnormally increased cortical excitability. They are potential tools that may assist in localizing the epileptogenic zone.

We examined the effects of slow-pulsed transcranial electrical stimulation (TES) in suppressing epileptiform discharges in seven adults with refractory epilepsy. An MRI-based realistic head model was constructed for each subject and co-registered with 256-channel dense EEG (dEEG). Interictal spikes were localized, and TES targeted the cortical source of each subject's principal spike population. Targeted spikes were suppressed in five subject's (29/35 treatment days overall), and nontargeted spikes were suppressed in four subjects. Epileptiform activity did not worsen. This study suggests that this protocol, designed to induce long-term depression (LTD), is safe and effective in acute suppression of interictal epileptiform discharges.

Our objective was to determine if there are any distinguishable phase cone clustering patterns present near to epileptic spikes. These phase cones arise from episodic phase shifts due to the coordinated activity of cortical neurons at or near to state transitions and can be extracted from the high-density scalp EEG recordings. The phase cone clustering activities in the low gamma band (30–50 Hz) and in the ripple band (80–150 Hz) were extracted from the analytic phase after taking Hilbert transform of the 256-channel high density (dEEG) data of adult patients. We used three subjects in this study. Spatiotemporal contour plots of the unwrapped analytic phase with 1.0 ms intervals were constructed using a montage layout of 256 electrode positions. Stable phase cone patterns were selected based on the criteria that the sign of the spatial gradient did not change for at least three consecutive time samples and the frame velocity was within the range of propagation velocities of cortical axons. These plots exhibited dynamical formation of phase cones which were higher in the seizure area as compared with the nearby surrounding brain areas. Spatiotemporal oscillatory patterns were also visible during ±5 sec period from the location of the spike. These results suggest that the phase cone activity might be useful for noninvasive localization of epileptic sites and also for examining the cortical neurodynamics near to epileptic spikes.

Surgical resection of the seizure onset zone (SOZ) requires that this region of the cortex is accurately localized. The onset of a seizure may be marked by transient discharges, but it also may be accompanied by oscillatory, sinusoidal electrographic activity, such as the EEG theta rhythm. However, because of the superposition of the seizure signal with other electrical signals, including noise artifacts and non-seizure brain activity, noninvasive Electrical Source Imaging (ESI) of the ictal EEG activity at seizure onset remains a challenging task for surgical planning. In the present study, we localize the SOZ from oscillatory features of the EEG at the ictal onset using 256-channel high density electroencephalography (HD-EEG), exact sensor positions, and individual electrical head models constructed from the patient's T1 magnetic resonance image (MRI). Epileptic activities at the seizure onset were characterized with joint time-frequency analysis and source estimated by standardized low resolution electromagnetic tomography (sLORETA) inverse method. The consistency of this localization was examined across multiple seizures for individual patients. For validation, results were compared to three clinical criteria: (1) epileptogenic lesions, (2) seizure onset observed in intracranial EEG, and (3) successful surgical outcomes. In this set of 84 seizures, the onsets of 56 seizures could be localized. For the lateralization measure, the results from HD-EEG with interictal spikes (8/10) and with ictal onset (10/10) were more accurate than international 10-20 EEG for interictal spikes (5/10) and ictal onset (5/10). ESI from HD-EEG with ictal onset (9/10) had greater concordance to the clinical criteria than HD-EEG with interictal spikes (6/10). Noninvasive ESI of oscillatory features at ictal onset using 256-channel HD-EEG and high-resolution individual head models can make a useful contribution to the clinical localization of the SOZ in presurgical planning.

About one-third of patients with epilepsy, which affects at least 1–2% of all persons, will prove to have medically refractory seizures [1]. Some refractory patients can be successfully treated with surgery [2], while others may experience an amelioration of seizures with dietary measures [3], or with vagal nerve [4] and other forms of neuro-stimulation [5]. However, it also is true that many, if not most, of all subjects with refractory epilepsy will continue to have seizures, either because they are not candidates for alternative therapy or such treatment simply does not result in adequate seizure control. There is a definite need for the development and implementation of more effective and safe anti-seizure medications to manage difficult to control epilepsy. Over the last two decades, the medical armamentarium available to clinicians to treat persons with epilepsy has expanded to include several new agents, which have generally been shown to be both as effective as the older agents, and less likely to produce medication-related side effects. Perhaps the most clinically useful of the newer generation of medications are also those, which are “broad-spectrum” in terms of efficacy, meaning that multiple seizure types may be responsive to a single agent. One of the most recent anti-seizure drugs now available is rufinamide (1-[(2,6-diflourophenyl)methyl]1-hydro-1,23-triazole-4carboximide, with empirical formula C10H8F2N4O). Rufinamide is approved by both the United States Food and Drug Administation and the EuropeanMedicines Agency (which recognizes the medication as an “orphan drug”) for the adjunctive treatment for seizures associated with the Lennox-Gastaut syndrome. Experimentally, rufinamide has been shown to block voltage sensitive sodium channels, and prevents these channels from returning to an activated from an inactivated state, thus aborting the generation of sustained bursts of high frequency action potentials [6]. This understanding of the presumed mechanism of action, as well as other data from animal studies, suggests that rufinamide should be effective against a wider range seizure types than those limited to the Lennox-Gastaut syndrome [7]. Many clinicians who manage patients with difficult epilepsy have been impressed by observations that rufinamide may indeed have a role in the management of seizures in multiple epilepsy syndromes [8]. The current report by Lee et al. [9] clearly supports this belief. Lee et al. [9] examined the effectiveness of the drug in a retrospective review of 88 patients, mainly children, with refractory epilepsy and found that nearly half of the patients had a 50% or more reduction in seizure frequency compared to baseline following the institution of the drug. Of the patients studied, only 18% had seizures related to Lennox-Gastaut syndrome, while one third had *Address for correspondence: Mark D. Holmes, Regional Epilepsy Center, Department of Neurology, University of Washington, 325 Ninth Avenue, Box 359745, Seattle, WA 98105, USA. Tel.: +1 206 744 3576/3539; Fax: +1 206 744 4409; E-mail: mdholmes@ u.washington.edu. Journal of Pediatric Epilepsy 2 (2012) 75–76 DOI 10.3233/PEP-2012-013 IOS Press 75

High density scalp EEG and subdural ECoG recordings provide an opportunity to map the electrical activity of the cortex with high spatial resolution. The spatial power spectral densities conform to a power law distribution with some nonlinear variations. The spatiotemporal patterns of phase derived from these data sets have unique features, such as, amplitude and phase modulation waves and also exhibited formation of spatial phase cluster patterns. These unique features represent different cognitive states and are different between normal and diseased states. Reported results show that the rate of formation of phase cluster patterns derived from the seizure-free interictal EEG data are higher in epileptogenic zones as compared with nearby normal areas of the brain.

OBJECTIVE: To examine the utility of early EEG for treatment decisions in comatose patients following return of spontaneous circulation (RoSC) from cardiac arrest (CA) in a population-based randomized trial cohort. BACKGROUND: The literature is conflicting on the prognostic value and utility of early EEG in the setting of RoSC following CA. DESIGN/METHODS: 1359 eligible adults with out-of-hospital non-traumatic CA (both ventricular fibrillation (VF) and non-VF) were randomized to standard care with or without prehospital cooling with IV 4°C normal saline following RoSC. Inclusion criteria were RoSC, intubation, intravenous access, placement of esophageal temperature probe and unconsciousness. Here we report clinical EEG use and findings from the first 364 charts retrospectively reviewed. Descriptive statistics were used. RESULTS: In the 364 patients, mean age was 61 years, 34% were female and 43% were VF arrests. At least one EEG was performed in 33% (120/364) patients: during TH (TH-EEG) in 19% (68/364) and otherwise (nTH-EEG) in 27% (100/364). Of the 68 TH-EEGs, 44 (65%) were continuous, and the rest, standard EEGs. In the 68 TH-EEGs included 19 (28%) with burst-suppression, 24 (35%) severe generalized slowing, 3 (4.4%) seizures (including 3 (4.4%) status epilepticus). Of the 100 nTH-EEGs, 68% were continuous. In the 100 nTH-EEGs included 18% with burst-suppression, 38% severe generalized slowing, 8% seizures (including 5 (5%) status epilepticus). At the patient level, 43% had EEG interpretations suggesting severe brain injury, and 21% an implied a poor prognosis. In 28% EEG may have factored into end-of-life decisions. CONCLUSIONS: In this subset of patients, EEG was performed in 1/3 after RoSC. EEG identified abnormalities leading to an interpretation of severe brain injury in a substantial portion of patients, and seemed to factor into end-of-life decisions in 1/4 patients where EEG was performed. Results from the entire cohort, with outcome correlations, are planned. Study Supported by: NHLBI R01-HL089554 and the Seattle Medic One Foundation. Disclosure: Dr. Cahill has nothing to disclose. Dr. Tirschwell has received personal compensation for activities with Bristol-Myers Squibb Co., Sanofi-Aventis Pharmaceuticals Inc., and Boehringer Inbelheim Pharmaceuticals Inc. as a speaker, and with Axio Research as a consultant. Dr. Tirschwell has received research support from Amplatzer Corp. and Novo Nordisk. Dr. Schubert has nothing to disclose. Dr. Holmes has nothing to disclose. Dr. Hakimian has nothing to disclose. Dr. Longstreth has nothing to disclose. Dr. Olsufka has nothing to disclose. Dr. Francis has nothing to disclose.

Purpose Pulmonary aspergillosis is a significant cause of morbidity and predictor of all-cause mortality post lung transplantation (LTx), including potentially contributing to development of bronchiolitis obliterans syndrome (BOS), despite prophylactic strategies and advances in immunosuppression and surgical technique. Specific treatment exists, but side effects are significant, while delay in diagnosis and treatment can worsen outcomes. Analysis of the risk-benefit ratio of commencing treatment is important. Galactomannan (GM) is a major constituent of Aspergillus cell walls released during hyphal growth, indicating active replication. Serum GM is widely used in immunocompromised haematology patients to diagnose invasive aspergillosis, but limited sensitivity has been observed in LTx recipients. There are few studies on BAL GM (and optimal optical density {OD}) post LTx. AIMS: Evaluate utility and determine optimal OD of BAL GM in diagnosis of aspergillosis post-LTx. Methods and Materials LTx recipients undergoing bronchoscopy for surveillance or clinical indications between September 2010 and November 2012 were assessed. BAL specimens were analysed for GM using ELISA. OD > 1.5 and 0.5 were compared with the current gold standard - direct microscopy and fungal cultures (FC). Results 76 bronchoscopies performed. Fungal elements were negative in all patients. At GM OD > 1.5 Sensitivity, specificity, PPV and NPV were 72, 100, 100 and 95% respectively. At OD > 0.5, Sensitivity, specificity, PPV and NPV were 100, 64, 32, 100% respectively. Conclusions BAL GM increases accuracy of early detection of pulmonary aspergillosis in LTx patients, with minimal additional risk. In this study, OD > 1.5 was the optimal cut-off. Results GM OD > 1.5 FC + FC - Total GM + 8 0 8 GM - 3 65 68 Total 11 65 76 Results GM OD > 0.5 FC + FC - Total GM + 11 23 34 GM - 0 42 42 Total 11 65 76

The objective of this study was to determine whether unimodal auditory stimuli evoke event-related potentials (ERPs) in brain areas normally designated as the visual cortex (VC). The topographical distribution of ERPs evoked by auditory click stimuli was measured from (a) electroencephalographic electrodes on the scalp of six neurologically normal adult human participants and (b) intracranial electrodes implanted on the cortex of one epileptic adult human participant. In all participants, unimodal click stimuli evoked ERPs over both the auditory cortex (AC) and the VC. Relative amplitudes of ERPs at different scalp electrodes did not support the idea that the ERPs over VC were volume-conducted versions of those over AC, and intracranial records confirmed the origin of some click-evoked ERPs in both V1 and other regions of VC. We conclude that unimodal auditory stimuli can evoke ERPs in VC. This finding adds to the earlier evidence for the effect of visual stimuli on AC by providing new evidence for bidirectional functional connectivity in the audio-visual network of the human brain. The implication is that not only do visual stimuli affect hearing; auditory stimuli also affect visual perception.

Progress in characterizing the functional networks of the normal human brain is now rapid, with evidence from both regional correlational patterns from functional MRI and fiber tractography from diffusion MRI. Increasingly, the tools of cerebral network analysis are being applied to understand the derangement of specific cortical and subcortical networks in epileptic disorders. In this approach, the clinical manifestations of epilepsy are viewed as the consequence of the pathologies of network dynamics and functional connectivity that may involve abnormal network pathways. Importantly, concepts of epileptic networks are supplanting the older, and more simplistic, notion that epileptic seizures must be either “focal” (or partial) or “generalized” in nature. Rather, seizures can be understood to result from the paroxysmal and pathological activation of specific neuronal connections. The characteristics of these may not fit with conventional assumptions, and could include widespread and bilateral involvement during seizures which classically are considered as focal, or could involve restricted cortical/subcortical regions during some seizures that are typically considered as generalized in nature. We believe that identifying patient-specific epileptic networks will provide critical insights into epilepsy syndromes, and more importantly, these insights will lead the way to novel forms of treatment for affected individuals. Technological improvements in several fields have contributed to the tools applied to understanding epileptic networks, particularly in neuroimaging (MRI, FDG-PET, fMRI), and in electromagnetic recordings (dense array EEG, MEG). Investigators are also finding that combining these methodologies may have a synergistic effect in regard to enhancing our understanding of the involved cortical networks. In this volume we have assembled contributions from an international group of investigators, each of whom has approached the problem of identifying the epileptic network from somewhat different perspectives. The unifying theme in all cases is the question of how the application of a specific technology, or a simultaneous combination of technologies, may enhance our insight into the recognition of the epileptogenic zone in the resting state. This book opens with a chapter by Stefan and Lopes da Silva (1), who review the evidence for the concept of epileptic networks. These authors discuss the structure and dynamics of cortical networks, describe how these connections can be analyzed through linear and non-linear methodologies, and outline the dynamics of neuronal networks in the context of combined EEG/MEG and EEG/fMRI signals analysis. They conclude that the resulting network analysis has clear relevance to understanding the nature of seizures occurring with focal cortical dysplasia and with temporal lobe epilepsy. Remarkably, they suggest that an absence seizure, often considered the prototypical generalized seizure, is actually a fast-spreading localized event. In a similar vein, Leite et al. (2) propose a novel method for linkage of EEG and fMRI signals in network analysis by describing in their report a “transfer function” between these divergent measures. They perform independent component analysis of EEG and extract metrics that express models of EEG-fMRI function from resulting time courses. These metrics are then used to predict fMRI activity and thus the brain regions associated with epileptic activity. The authors illustrate the methodology in a proof of concept report on the application of this function to fMRI-EEG data obtained during both ictal and interictal states in one subject with a hypothalamic hamartoma. In the next two chapters, by Constable et al. (3) and Weaver et al. (4) the focus is on using resting state fMRI to assess functional connectivity in the human brain, and how this approach can be applied to epilepsy. These two groups describe the functional reorganization that occurs in epilepsy, and the potential that connectivity measures have in identifying a network of seizure-generating tissues. Both groups stress the importance of focal connectivity measures as adjunctive tools in the identification of the epileptogenic zone in patients with refractory epilepsy who are being considered for resective surgery. On the other hand, Kerr et al. (5) find that the interictal FDG-PET, by visualization of the metabolic changes that take place across the whole brain in epilepsy patients, offer another method to observe abnormal brain networks in the resting state. These authors report that in temporal lobe epilepsy, examination of patterns of metabolic dysfunction may assist in lateralizing the onset of seizures. They report on the development of a computerized assisted diagnostic tool for implementing the metabolic analysis in clinical practice. Rose et al. (6) studied simultaneous MEG-EEG activity in a series of children with refractory epilepsy. They studied the MEG signals throughout the brain using a beamformer algorithm, and they determined virtual MEG spike locations with a spike detection program. Comparisons of the MEG results with intracranial EEG recordings were conducted both for EEG spikes and for the onset and spread of seizures. By demonstrating similarities with the invasive electrographic findings, the authors conclude that the pattern of interictal MEG findings has the potential to define the distribution of the epileptic network, thereby providing a non-invasive method to analyze abnormal neuronal connections. Yamazaki et al. (7) have pioneered the ability to simultaneously record 256 channel dense EEG (dEEG) and invasive subdural EEG recordings in temporal lobe epilepsy, thus helping to establish the validity of dEEG recordings. In their chapter in this volume, Yamazaki et al. (7) extend this work to cases of neocortical epilepsy by demonstrating that dEEG, by covering the whole head with sufficient sensor density, can reliably localize epileptiform discharges when compared to invasive studies. The final two chapters concern the application of analytic techniques to examine abnormal synchronization of the interictal dEEG data to establish the presumptive epileptogenic zone. Song et al. (8) discuss the use of coherence measures in the examination of interictal spikes to determine the extent and distribution of epileptic networks. In their contribution, Ramon and Holmes (9) provide evidence that brief segments of interictal dEEG, free of classical epileptiform patterns, nevertheless may contain stable markers that reveal the likely epileptic network. These markers are identified through analysis of localized patterns of phase synchronization and cross-frequency coupling that appear specific to the epileptogenic region as proven by later intracranial recordings. The topics covered in this volume present an introduction to the study of identifying epileptic networks. They are only a sample of the many current approaches to cerebral network analysis that could be applied to epilepsy. Nevertheless, we are hopeful that the material presented here will provide encouragement for additional work to clarify – and treat – the pathological dynamics of human cerebral networks in epilepsy.

Our objective is to examine if spatial phase clustering patterns are different in epileptogenic zones derived from high density interictal scalp EEG. We studied two patients with refractory epilepsy who underwent intracranial EEG to establish the localization of seizures. One patient had seizures originating from frontal and parietal areas; the other patient had seizures arising from right temporal parietal areas. Prior to invasive EEG studies, the subjects underwent dense array 256 channel EEG (dEEG) recordings. Three minutes of interictal dEEG data was selected for analysis. The selected segment was at least two hours from an epileptic seizure and, based on visual analysis, free of interictal epileptiform patterns. Data was imported into MATLAB for analysis. The EEG data was filtered in the appropriate EEG band. The phase was computed after taking Hilbert transform of the EEG data. Contour plots with 4 ms intervals were constructed using a montage layout of 256 electrode positions. Spatial plots revealed formation of cone-like structures which changed in spatial shapes from one frame to the next. In addition, the peak intensity varied from one frame to the next. In general, more stronger and stable patterns were observed in the seizure area as compared with nearby surrounding brain areas. A clustering of spatial patterns was also observed which was denser in the seizure areas as compared with nearby surrounding areas. These preliminary results show that the spatiotemporal dynamics and clustering of phase cone patterns have a potential to localize the epileptic zones from the scalp dEEG data.

The stochastic behavior of the phase synchronization index (SI) and cross-frequency couplings on different days during a hospital stay of three epileptic patients was studied for non-invasive localization of the epileptogenic areas from high density, 256-channel, scalp EEG (dEEG) recordings. The study was performed with short-duration (0-180s), seizure-free, epileptiform-free, and spike-free interictal dEEG data on different days of three subjects. The seizure areas were localized with subdural recordings with an 8 x 8 macro-electrode grid array and strip electrodes. The study was performed in theta (3-7 Hz), alpha (7-12 Hz), beta (12-30 Hz), and low gamma (30-50 Hz) bands. A detrended fluctuation analysis was used to find the long range temporal correlations in the SI that reveals the stochastic behavior of the SI in a given time period. The phase synchronization was computed after taking Hilbert transform of the EEG data. Contour plots were constructed with 20s time-frames using a montage of the layout of 256 electrode positions. It was found that the stochastic behavior of the SI was higher in epileptogenic areas and in nearby areas on different days for each subject. The low gamma band was found to be the best to localize the epileptic sites. Also, a stable higher pattern of SI emerged after 60-120s in the epileptogenic areas. The cross-frequency couplings of SI in theta gamma, beta gamma, and alpha gamma bands were decreased and spatial patterns were fragmented in epileptogenic areas. Combinations of an increase in the stochastic behavior of the SI and decrease in cross-frequency couplings are potential markers to assist in localizing epileptogenic areas. These findings suggest that it is possible to localize the epileptogenic areas non-invasively from a short-duration (similar to 180s), seizure-free and spike-free interictal scalp dEEG recordings.

The stochastic behavior of the phase synchronization index (SI) on different days during a hospital stay of epileptic patients was studied for noninvasive localization of the epileptogenic areas from high density (256 channel) scalp EEG recordings. The study was performed on three subjects with interictal EEG data on different days. The seizure areas were localized with subdural recordings with an 8 × 8 grid electrode array. The study was performed in low gamma (30–50 Hz) band with short duration (0–180 s), seizure-free and spike-free scalp EEG data. A detrended fluctuation analysis was used to find the averaged stochastic fluctuations in the SI. The phase synchronization was computed after taking Hilbert transform of the EEG data. Contour plots were constructed with 20 s time–frames using a montage of the layout of 256 electrode positions. It was found that the stochastic behavior of the SI was higher in epileptogenic areas on different days for each subject. Also, a stable higher pattern of SI emerged after 60–100 s in the epileptogenic areas. These findings suggest that it is possible to localize the epileptogenic areas from the short duration (60–100 s), seizure-free and spike-free high density scalp EEG recordings.

Epilepsy may reflect a focal abnormality of cerebral tissue, but the generation of seizures typically involves propagation of abnormal activity through cerebral networks. We examined epileptiform discharges (spikes) with dense array electroencephalography (dEEG) in five patients to search for the possible engagement of pathological networks. Source analysis was conducted with individual electrical head models for each patient, including sensor position measurement for registration with MRI with geodesic photogrammetry; tissue segmentation and skull conductivity modeling with an atlas skull warped to each patient’s MRI; cortical surface extraction and tessellation into 1 cm2 equivalent dipole patches; inverse source estimation with either minimum norm or cortical surface Laplacian constraints; and spectral coherence computed among equivalent dipoles aggregated within Brodmann areas with 1 Hz resolution from 1 to 70 Hz. These analyses revealed characteristic source coherence patterns in each patient during the pre-spike, spike, and post-spike intervals. For one patient with both spikes and seizure onset localized to a single temporal lobe, we observed a cluster of apparently abnormal coherences over the involved temporal lobe. For the other patients, there were apparently characteristic coherence patterns associated with the discharges, and in some cases these appeared to reflect abnormal temporal lobe synchronization, but the coherence patterns for these patients were not easily related to an unequivocal epileptogenic zone. In contrast, simple localization of the site of onset of the spike discharge, and/or the site of onset of the seizure, with non-invasive 256 dEEG was useful in predicting the characteristic site of seizure onset for those cases that were verified by intracranial EEG and/or by surgical outcome.

Epilepsy surgery is common in the face of benign brain tumors, but rarely for patients with a history of malignant brain tumors. Seizures are a common sequelae in survivors of malignant pediatric brain tumors. Medical management alone may not adequately treat epilepsy, including in this group. We report four cases of patients who previously underwent gross total resection, radiation therapy, and chemotherapy for successful treatment of malignant brain neoplasia, yet suffered from medically intractable seizures. All underwent surgery for treatment of epilepsy with extension of the original resection. Despite the aggressive primary treatment of the neoplasm, and the potential for diffuse cerebral insults, all benefited from focal surgical resection. Aggressive surgical management of intractable epilepsy can be considered in survivors of malignant brain tumors.