Localization Of Seizure Onset Zone Research Articles

Improved Localization of Seizure Onset Zones Using Spatiotemporal Constraints and Time-Varying Source Connectivity.

Presurgical evaluation of brain neural activity is commonly carried out in refractory epilepsy patients to delineate as accurately as possible the seizure onset zone (SOZ) before epilepsy surgery. In practice, any subjective interpretation of electroencephalographic (EEG) recordings is hindered mainly because of the highly stochastic behavior of the epileptic activity. We propose a new method for dynamic source connectivity analysis that aims to accurately localize the seizure onset zones by explicitly including temporal, spectral, and spatial information of the brain neural activity extracted from EEG recordings. In particular, we encode the source nonstationarities in three critical stages of processing: Inverse problem solution, estimation of the time courses extracted from the regions of interest, and connectivity assessment. With the aim to correctly encode all temporal dynamics of the seizure-related neural network, a directed functional connectivity measure is employed to quantify the information flow variations over the time window of interest. Obtained results on simulated and real EEG data confirm that the proposed approach improves the accuracy of SOZ localization.

Utility of gray-matter segmentation of ictal-Interictal perfusion SPECT and interictal 18F-FDG-PET in medically refractory epilepsy

PurposeWe present a method of gray-matter segmentation of functional neuroimaging for localization of seizure onset zone (SOZ) in epilepsy surgery. 18F-FDG-PET hypometabolism and ictal SPECT hyperperfusion may correspond to SOZ. We hypothesize that limiting functional images to gray matter improves identification of small, subtle, or obscure cortical volumes of 18F-FDG-PET hypometabolism and eliminates hyperperfused seizure propagation pathways within white matter in ictal perfusion SPECT. MethodsTwenty-five adult and pediatric patients age 2–48 years with epilepsy surgery evaluations consisting of MRI, 18F-FDG-PET, ictal and interictal perfusion SPECT, and intracranial EEG (iEEG) monitoring were selected. MRI gray matter segmentation was used to identify cortical regions in coregistered 18F-FDG-PET and Ictal-Interictal SPECT Analysis by SPM (ISAS) as volumes of interest (VOI). VOIs in 18F-FDG-PET and SPECT perfusion clusters were compared to iEEG localization. The level of VOI concordance between two modalities was recorded as the same subgyrus (highest concordance), gyrus, sublobe, lobe, hemisphere, or no concordance. ResultsWith segmentation, 84% (21/25) of cases had at least one area identified on 18F-FDG-PET scan concordant with iEEG SOZ at sublobar or higher levels, and 72% (18/25) of cases had subgyral concordance with iEEG SOZ. Without segmentation, 60% (15/25) of cases had at least one area in 18F-FDG-PET scan concordant with iEEG SOZ at sublobar or higher levels, and 32% (8/25) with subgyral concordance. 83% (10/12) of seizure free patients had subgyral concordance on segmented 18F-FDG-PET. Both segmented and nonsegmented ictal-interictal SPECT perfusion clusters had 56% (14/25) of cases with at least sublobar concordance. Subgyral concordance was achieved by 28% (7/25) of segmented and 20% (5/25) of nonsegmented SPECTs. DiscussionSegmented 18F-FDG-PET scans frequently result in high correspondence to iEEG onset zones with localizations exactly concordant with iEEG SOZ- more than twice as often as without segmentation. Segmentation allows for the identification of small or subtle areas of hypometabolism that are often unappreciated or are obscured by normally hypometabolic white matter. Segmentation of ictal-interictal SPECT clusters did not significantly increase localization with iEEG SOZ over nonsegmented clusters.

Co-occurrence of high-frequency oscillations and delayed responses evoked by intracranial electrical stimulation in stereo-EEG studies.

To perform a side-by-side comparison of two epileptogenicity biomarkers, high frequency oscillations (HFOs) and delayed responses (DRs), as a result of single-pulse electrical stimulation. We have recorded stimulation-evoked HFOs and DRs in 16 epileptic patients undergoing presurgical evaluation using the stereoelectroencephalographic method. To evaluate converging and complementary information provided by the biomarkers, we analyzed them individually and for logical "and"/"or" combinations between them. 3D maps of the biomarkers' distributions by recording location (inbound maps) and by stimulation location (outbound maps) were created to analyze their relationship with the epileptogenic structures. HFOs occur less frequently than DRs, by 18.7%, when counting by recording contacts, and more frequently, by 7.4%, when counting by stimulation contacts. 40.6% of the contacts exhibiting HFOs also exhibit DRs, and 44.1% of the contacts exhibiting DRs also exhibit HFOs. When combining biomarkers, there was a tradeoff between increased seizure onset zone (SOZ) sensitivity, from 21.3% to 73%, and decreased specificity, from 87.2% to 34.3%. There is a moderate similarity in the information provided by the DRs and HFOs. The biomarkers complement each other, but there is a tradeoff between different metrics for SOZ localization.

Seizure Onset Zone Localization from Ictal High-Density EEG in Refractory Focal Epilepsy.

Epilepsy surgery is the most efficient treatment option for patients with refractory epilepsy. Before surgery, it is of utmost importance to accurately delineate the seizure onset zone (SOZ). Non-invasive EEG is the most used neuroimaging technique to diagnose epilepsy, but it is hard to localize the SOZ from EEG due to its low spatial resolution and because epilepsy is a network disease, with several brain regions becoming active during a seizure. In this work, we propose and validate an approach based on EEG source imaging (ESI) combined with functional connectivity analysis to overcome these problems. We considered both simulations and real data of patients. Ictal epochs of 204-channel EEG and subsets down to 32 channels were analyzed. ESI was done using realistic head models and LORETA was used as inverse technique. The connectivity pattern between the reconstructed sources was calculated, and the source with the highest number of outgoing connections was selected as SOZ. We compared this algorithm with a more straightforward approach, i.e. selecting the source with the highest power after ESI as the SOZ. We found that functional connectivity analysis estimated the SOZ consistently closer to the simulated EZ/RZ than localization based on maximal power. Performance, however, decreased when 128 electrodes or less were used, especially in the realistic data. The results show the added value of functional connectivity analysis for SOZ localization, when the EEG is obtained with a high-density setup. Next to this, the method can potentially be used as objective tool in clinical settings.

Localizing seizure onset zone by convolutional transfer entropy from iEEG.

Automatic localization of the seizure onset zone (SOZ) is able to output an objective result and help clinical doctors greatly in epilepsy therapy. Transfer entropy is one of the most frequently used measures based on information theory to localize the SOZ. However, if only using transfer entropy to localize the SOZ, different results can be obtained during different periods, thus humans still need to identify which one is most reasonable. This paper proposes a new method to output only a few (e.g. 1 or 2) results along a long time slot. Based on the results of traditional transfer entropy, we use a 3D convolution method to enhance the connection between the spatial channels and also between different temporal positions. After that, a connected component method is used to extract the stable blocks that indicate the SOZ. To evaluate the effectiveness of our method, preliminary experiments on a short iEEG signals are conducted. The experimental results show that our method can achieve a sensitivity of 100% and a false positive rate of 1.79% for SOZ localization.

Seizure-onset zone localization by statistical parametric mapping in visually normal (18) F-FDG PET studies.

Neuroimaging is crucial in the presurgical evaluation of patients with medically refractory epilepsy. To improve the moderate sensitivity of [(18) F]fluorodeoxyglucose-positron emission tomography ((18) F-FDG-PET), our aim was to evaluate the usefulness of statistical parametric mapping (SPM) to localize the seizure-onset zone (SOZ) in PET studies deemed normal by visual assessment. Fifty-five patients with medically refractory epilepsy whose (18) F-FDG-PET was visually evaluated as normal were retrospectively included. Twenty of these patients had undergone surgical intervention. PET images were analyzed by SPM8 using a corrected p-value of p < 0.05 and three uncorrected p-values of p < 0.0001, p < 0.001, and p < 0.005, matched with minimum cluster sizes of k > 0, k > 20, k > 100, and k > 200, respectively. The SPM-identified potential seizure zone (SZ) was compared to the SOZ, which was determined by consensus during patient management meetings in the epilepsy unit, taking into account presurgical tests. Studies in which the SPM-identified potential SZ was concordant with the SOZ were considered "correctly localizing." The SPM threshold combination with the least restrictive p-value and greatest minimum cluster size achieved the highest rate of correctly localizing studies. When p < 0.005/k > 200 was used, 40% (22/55) of studies were correctly localizing, and the concordance obtained in the surgically intervened subgroup was substantial (к = 0.607, 95% confidence interval [CI] 0.258-0.957), which was comparable to the concordance obtained by magnetic resonance imaging (MRI) (к = 0.783, 95% CI 0.509-1.000). SPM offers improved SOZ localization in (18) F-FDG-PET studies that are negative on visual assessment. For this purpose, statistical parametric maps could be thresholded with liberal p-values and restrictive cluster sizes.

Differences between mesial and neocortical magnetic-resonance-imaging-negative temporal lobe epilepsy.

The aim of this study was to assess clinical and electrophysiological differences within a group of patients with magnetic-resonance-imaging-negative temporal lobe epilepsy (MRI-negative TLE) according to seizure onset zone (SOZ) localization in invasive EEG (IEEG). According to SOZ localization in IEEG, 20 patients with MRI-negative TLE were divided into either having mesial SOZ-mesial MRI-negative TLE or neocortical SOZ-neocortical MRI-negative TLE. We evaluated for differences between these groups in demographic data, localization of interictal epileptiform discharges (IEDs), and the ictal onset pattern in semiinvasive EEG and in ictal semiology. Thirteen of the 20 patients (65%) had mesial MRI-negative TLE and 7 of the 20 patients (35%) had neocortical MRI-negative TLE. The differences between mesial MRI-negative TLE and neocortical MRI-negative TLE were identified in the distribution of IEDs and in the ictal onset pattern in semiinvasive EEG. The patients with neocortical MRI-negative TLE tended to have more IEDs localized outside the anterotemporal region (p=0.031) and more seizures without clear lateralization of ictal activity (p=0.044). No other differences regarding demographic data, seizure semiology, surgical outcome, or histopathological findings were found. According to the localization of the SOZ, MRI-negative TLE had two subgroups: mesial MRI-negative TLE and neocortical MRI-negative TLE. The groups could be partially distinguished by an analysis of their noninvasive data (distribution of IEDs and lateralization of ictal activity). This differentiation might have an impact on the surgical approach.

Exploring the time–frequency content of high frequency oscillations for automated identification of seizure onset zone in epilepsy

Objective. High frequency oscillations (HFOs) in intracranial electroencephalography (iEEG) recordings are considered as promising clinical biomarkers of epileptogenic regions in the brain. The aim of this study is to improve and automatize the detection of HFOs by exploring the time–frequency content of iEEG and to investigate the seizure onset zone (SOZ) detection accuracy during the sleep, awake and pre-ictal states in patients with epilepsy, for the purpose of assisting the localization of SOZ in clinical practice. Approach. Ten-minute iEEG segments were defined during different states in eight patients with refractory epilepsy. A three-stage algorithm was implemented to detect HFOs in these segments. First, an amplitude based initial detection threshold was used to generate a large pool of HFO candidates. Then distinguishing features were extracted from the time and time–frequency domain of the raw iEEG and used with a Gaussian mixture model clustering to isolate HFO events from other activities. The spatial distribution of HFO clusters was correlated with the seizure onset channels identified by neurologists in seven patient with good surgical outcome. Main results. The overlapping rates of localized channels and seizure onset locations were high in all states. The best result was obtained using the iEEG data during sleep, achieving a sensitivity of 81%, and a specificity of 96%. The channels with maximum number of HFOs identified epileptogenic areas where the seizures occurred more frequently. Significance. The current study was conducted using iEEG data collected in realistic clinical conditions without channel pre-exclusion. HFOs were investigated with novel features extracted from the entire frequency band, and were correlated with SOZ in different states. The results indicate that automatic HFO detection with unsupervised clustering methods exploring the time–frequency content of raw iEEG can be efficiently used to identify the epileptogenic zone with an accurate and efficient manner.

Understanding Hyper Motor Seizures

Introduction: Hyper Motor Seizures [HMS] are characterized by complex high amplitude movements involving proximal segments of the body resulting violent and inappropriate to the context. Objective: To review the possible ictal onset zones related to HMS and the cortical areas that would be covered if invasive recording are needed. Development: Semiology can predict the localization of ictal onset zone. Two subtypes of HMS [type 1 and 2] have been described. HMS1 is associated with an epileptogenic zone on the ventromedial frontal cortex and HMS2 has been associated with a more dorsal epileptogenic zone than those resulting in HSM1. However, HMS can also be originated in temporal lobe [mesial, neocortical or in the pole], in insular cortex or even in parietal lobe. The origin of HMS can be suspected by the associated signs. Thus, HMS originating in the insula–operculum regions can be associated with various somatosensory auras; in parietal seizures, propioceptive sensations may precede hyper motor behavior [HM], whereas autonomic and emotional auras prompt to think in the temporal lobe origin. Conclusion: Except in cases of lesional temporal lobe epilepsy with concordant prersurgical results, all patients with HMS should be evaluated through intracranial recordings. The auras, the HMS subtype, the hypometabolic areas showed by PET study, and the localization and lesion type seeing on MRI can help to decide what structures should be covered with depth electrodes during invasive recordings.

Connectivity of epileptic brain regions in wake and sleep.

Focal epileptic brain is characterized by a region of pathological tissue seizure onset zone (SOZ) - the pathologic tissue generating seizures. During the interictal period (nonseizure) the SOZ is characterized by epileptiform activity - interictal spikes & high-frequency oscillations (HFO). The SOZ also exhibits hyper-synchrony and functional disconnection from the surrounding areas. Recent studies have described the synchrony inside the SOZ and surrounding tissue for just small sets of patients (2-4) and without any distinction in behavioral states. Wake and sleep cycles can, however, have a significant influence on SOZ activity. Here we show the results of connectivity analysis in three fundamental areas of the epileptic brain - inside SOZ, outside SOZ and bridging areas in 7 patients during wake and sleep. We observed increased synchrony inside SOZ and decreased synchrony on its edges (bridging areas) in specific frequency bands. We also detected significant differences of synchrony levels between wake and sleep periods in HFO frequencies. Our results provide additional insight into the properties of SOZ connectivity. Knowledge of these principles may prove useful for SOZ localization and understanding epileptic brain function in general.

Automatic segmentation of deep intracerebral electrodes in computed tomography scans.

BackgroundInvasive monitoring of brain activity by means of intracerebral electrodes is widely practiced to improve pre-surgical seizure onset zone localization in patients with medically refractory seizures. Stereo-Electroencephalography (SEEG) is mainly used to localize the epileptogenic zone and a precise knowledge of the location of the electrodes is expected to facilitate the recordings interpretation and the planning of resective surgery. However, the localization of intracerebral electrodes on post-implant acquisitions is usually time-consuming (i.e., manual segmentation), it requires advanced 3D visualization tools, and it needs the supervision of trained medical doctors in order to minimize the errors. In this paper we propose an automated segmentation algorithm specifically designed to segment SEEG contacts from a thresholded post-implant Cone-Beam CT volume (0.4 mm, 0.4 mm, 0.8 mm). The algorithm relies on the planned position of target and entry points for each electrode as a first estimation of electrode axis. We implemented the proposed algorithm into DEETO, an open source C++ prototype based on ITK library.ResultsWe tested our implementation on a cohort of 28 subjects in total. The experimental analysis, carried out over a subset of 12 subjects (35 multilead electrodes; 200 contacts) manually segmented by experts, show that the algorithm: (i) is faster than manual segmentation (i.e., less than 1s/subject versus a few hours) (ii) is reliable, with an error of 0.5 mm ± 0.06 mm, and (iii) it accurately maps SEEG implants to their anatomical regions improving the interpretability of electrophysiological traces for both clinical and research studies. Moreover, using the 28-subject cohort we show here that the algorithm is also robust (error < 0.005 mm) against deep-brain displacements (< 12 mm) of the implanted electrode shaft from those planned before surgery.ConclusionsOur method represents, to the best of our knowledge, the first automatic algorithm for the segmentation of SEEG electrodes. The method can be used to accurately identify the neuroanatomical loci of SEEG electrode contacts by a non-expert in a fast and reliable manner.

Whole-brain functional connectivity increases with extended duration of focal epileptiform activity

The analysis of interictal epileptiform discharges (IEDs) using magnetoencephalography (MEG) is utilized for the localization of seizure onset zones in the presurgical planning of epilepsy patients. Additionally, resting-state functional connectivity analyses using the IED area may provide novel insight into the underlying brain networks. In this study, we evaluate whether chronicity of seizures is related to whole-brain functional connectivity metrics using the area of IED generation (derived from MEG) as the seed region. We found a positive correlation between the duration of seizures and beta-band functional connectivity between the epileptogenic zone and other brain areas. This suggests the presence of inhibitory GABAergic modulation of distal brain regions in response to chronic epileptiform activity.

LOCALIZATION OF EPILEPTIC FOCI USING MULTIMODALITY NEUROIMAGING

Approximately 30% of epilepsy patients are medically intractable. Epilepsy surgery may offer cure or palliation, and neuromodulation and direct drug delivery are being developed as alternatives. Successful treatment requires correct localization of seizure onset zones and understanding surrounding functional cortex to avoid iatrogenic disability. Several neurophysiologic and imaging localization techniques have inherent individual weaknesses which can be overcome by multimodal analysis. We review common noninvasive techniques, then illustrate the value of multimodal analysis to localize seizure onset for targeted treatment.

Stability of synchronization clusters and seizurability in temporal lobe epilepsy.

PurposeIdentification of critical areas in presurgical evaluations of patients with temporal lobe epilepsy is the most important step prior to resection. According to the “epileptic focus model”, localization of seizure onset zones is the main task to be accomplished. Nevertheless, a significant minority of epileptic patients continue to experience seizures after surgery (even when the focus is correctly located), an observation that is difficult to explain under this approach. However, if attention is shifted from a specific cortical location toward the network properties themselves, then the epileptic network model does allow us to explain unsuccessful surgical outcomes.MethodsThe intraoperative electrocorticography records of 20 patients with temporal lobe epilepsy were analyzed in search of interictal synchronization clusters. Synchronization was analyzed, and the stability of highly synchronized areas was quantified. Surrogate data were constructed and used to statistically validate the results. Our results show the existence of highly localized and stable synchronization areas in both the lateral and the mesial areas of the temporal lobe ipsilateral to the clinical seizures. Synchronization areas seem to play a central role in the capacity of the epileptic network to generate clinical seizures. Resection of stable synchronization areas is associated with elimination of seizures; nonresection of synchronization clusters is associated with the persistence of seizures after surgery.DiscussionWe suggest that synchronization clusters and their stability play a central role in the epileptic network, favoring seizure onset and propagation. We further speculate that the stability distribution of these synchronization areas would differentiate normal from pathologic cases.

Cambios en la memoria verbal y no verbal asociados a la implantación de electrodos hipocampales bilaterales en cirugía de la epilepsia

An appropriate localization of ictal onset zone in refractory temporal lobe epilepsy favors an adequate outcome associated with surgical treatment. When video-electroencephalogram (video-EEG) and magnetic resonance imaging do not provide accurate data to locate ictal onset zone, the use of subdural or deep intracranial electrodes is indicated. Hippocampal electrode placement could generate functional changes in an unaffected hippocampus. To describe mnesic changes in patients admitted for epilepsy surgery, with previous bilateral hippocampal implantation using depth electrodes. We identified eight patients undergoing video-EEG using bilateral hippocampal electrodes. Verbal and nonverbal mnesic performance was evaluated before/after the procedure. The following aspects were considered for the analysis: memory lateralization according to intracarotid amobarbital test (Wada test), invasive ictal onset zone, side of resection and pattern of electrocorticographic dissemination. In patients with memory dominance, contralateral to the ictal onset zone, there was an improvement in verbal and nonverbal memory, suggesting that invasive recordings did not impair mnesic skills of the unaffected hippocampus. In patients with bilateral representation of memory, ipsilateral mnesic impairment was associated with the resection. Contralateral improvement in memory was seen when the right side was resected, as opposed to no changes with resections made on the left side, indicating that electrode implantation of unaffected hippocampus did not generate a functional decline. Based on the preservation of verbal and nonverbal memory after depth electrode placement, invasive recordings of the hippocampus seem to be safe.

Seizure source imaging by means of FINE spatio-temporal dipole localization and directed transfer function in partial epilepsy patients

ObjectiveTo investigate the usage of a high-density EEG recording system and source imaging technique for localizing seizure activity in patients with medically intractable partial epilepsy. MethodsHigh-density, 76-channel scalp EEG signals were recorded in 10 patients with partial epilepsy. The patients underwent routine clinical pre-surgical evaluation and all had resective surgery with seizure free outcome. After applying a FINE (first principle vectors) spatio–temporal source localization and DTF (directed transfer function) connectivity analysis approach, ictal sources were imaged. Effects of number of scalp EEG electrodes on the seizure localization were also assessed using 76, 64, 48, 32, and 21 electrodes, respectively. ResultsSurgical resections were used to assess the source imaging results. Results from the 76-channel EEG in the 10 patients showed high correlation with the surgically resected brain regions. The localization of seizure onset zone from 76-channel EEG showed improved source detection accuracy compared to other EEG configurations with fewer electrodes. ConclusionsFINE together with DTF was able to localize seizure onset zones of partial epilepsy patients. High-density EEG recording can help achieve improved seizure source imaging. SignificanceThe present results suggest the promise of high-density EEG and electrical source imaging for noninvasively localizing seizure onset zones.

Time-frequency characterization of electrocorticographic recordings of epileptic patients using frequency-entropy similarity: A comparison to other bi-variate measures

Expert evaluation of electrocorticographic (ECoG) recordings forms the linchpin of seizure onset zone localization in the evaluation of epileptic patients for surgical resection. Numerous methods have been developed to analyze these complex recordings, including uni-variate (characterizing single channels), bi-variate (comparing channel pairs) and multivariate measures. Developing reliable algorithms may be helpful in clinical tasks such as localization of epileptogenic zones and seizure anticipation, as well as enabling better understanding of neuronal function and dynamics. Recently we have developed the frequency-entropy (F-E) similarity measure, and have tested its capability in mapping the epileptogenic zones. The F-E similarity measure compares time-frequency characterizations of two recordings. In this study, we examine the method's principles and utility and compare it to previously described bi-variate correspondence measures such as correlation, coherence, mean phase coherence and spectral comparison methods. Specially designed synthetic signals were used for illuminating theoretical differences between the measures. Intracranial recordings of four epileptic patients were then used for the measures’ comparative analysis by creating a mean inter-electrode matrix for each of the correspondence measures and comparing the structure of these matrices during the inter-ictal and ictal periods. We found that the F-E similarity measure is able to discover spectral and temporal features in data which are hidden for the other measures and are important for foci localization.

The Impact of Cerebral Source Area and Synchrony on Recording Scalp Electroencephalography Ictal Patterns

To determine the cerebral electroencephalography (EEG) substrates of scalp EEG seizure patterns, such as source area and synchrony, and in so doing assess the limitations of scalp seizure recording in the localization of seizure onset zones in patients with temporal lobe epilepsy. We recorded simultaneously 26 channels of scalp EEG with subtemporal supplementary electrodes and 46-98 channels of intracranial EEG in presurgical candidates with temporal lobe epilepsy. We correlated intracranial EEG source area and synchrony at seizure onset with the corresponding scalp EEG. Eighty-six simultaneous intracranial- and scalp-recorded seizures from 23 patients were evaluated. Thirty-four intracranial ictal discharges (40%) from 9 patients (39%) had sufficient cortical source area (namely > 10 cm(2)) and synchrony at seizure onset to produce a simultaneous or nearly simultaneous focal scalp EEG ictal pattern. Forty-one intracranial ictal discharges (48%) from 10 patients (43%) gradually achieved the necessary source area and synchrony over several seconds to generate a scalp EEG ictal pattern. These scalp rhythms were lateralized, but not localizable as to seizure origin. Eleven intracranial ictal discharges (13%) from 4 patients (17%) recruited the necessary source area, but lacked sufficient synchrony to result in a clearly localized or lateralized scalp ictal pattern. Sufficient source area and synchrony are mandatory cerebral EEG requirements for generating scalp-recordable ictal EEG patterns. The dynamic interaction of cortical source area and synchrony at the onset and during a seizure is a primary reason for heterogeneous scalp ictal EEG patterns.

GRAPH THEORETICAL CHARACTERIZATION AND TRACKING OF THE EFFECTIVE NEURAL CONNECTIVITY DURING EPISODES OF MESIAL TEMPORAL EPILEPTIC SEIZURE

Via a detailed case study of mesial temporal lobe epilepsy, we show that a method of determining the direction of information flow among signals is able to provide focal localization via the simultaneous analysis of multiple EEG channels. This determination is accomplished by representing information flow direction via directed graphs, where focal electrodes are associated with high observed rates of pertinence to strongly connected subgraphs. Further clinical support to this finding is provided by results for an additional 9 cases of focal epilepsy cases. The graph theoretical approach is a tool for describing and analyzing the effective connectivity dynamics behind epileptic seizures and may provide a common language for studying other complex dynamic relationships between neural structures.