Measurable transitions during seizures in intracranial EEG: A stereoelectroencephalography and SPECT study.

OBJECTIVE: Ictal Single Photon Emission Computed Tomography (SPECT) and stereo-electroencephalography (SEEG) are diagnostic techniques used for the management of patients with drug-resistant focal epilepsies. While hyperperfusion patterns in ictal SPECT studies reveal seizure onset and propagation pathways, the role of ictal hypoperfusion remains poorly understood. The goal of this study was to systematically characterize the spatio-temporal information flow dynamics between differently perfused brain regions using stereo-EEG recordings. METHODS: We identified seizure-free patients after resective epilepsy surgery who had prior ictal SPECT and SEEG investigations. We estimated directional connectivity between the epileptogenic-zone (EZ), non-resected areas of hyperperfusion, hypoperfusion, and baseline perfusion during the interictal, preictal, ictal, and postictal periods. RESULTS: Compared to the background, we noted significant information flow (1) during the preictal period from the EZ to the baseline and hyperperfused regions, (2) during the ictal onset from the EZ to all three regions, and (3) during the period of seizure evolution from the area of hypoperfusion to all three regions. CONCLUSIONS: Hypoperfused brain regions were found to indirectly interact with the EZ during the ictal period. SIGNIFICANCE: Our unique study, combining intracranial electrophysiology and perfusion imaging, presents compelling evidence of dynamic changes in directional connectivity between brain regions during the transition from interictal to ictal states.

Decoding executed and imagined grasping movements from distributed non-motor brain areas using a Riemannian decoder.

Using brain activity directly as input for assistive tool control can circumventmuscular dysfunction and increase functional independence for physically impaired people. The motor cortex is commonly targeted for recordings, while growing evidence shows that there exists decodable movement-related neural activity outside of the motor cortex. Several decoding studies demonstrated significant decoding from distributed areas separately. Here, we combine information from all recorded non-motor brain areas and decode executed and imagined movements using a Riemannian decoder. We recorded neural activity from 8 epilepsy patients implanted with stereotactic-electroencephalographic electrodes (sEEG), while they performed an executed and imagined grasping tasks. Before decoding, we excluded all contacts in or adjacent to the central sulcus. The decoder extracts a low-dimensional representation of varying number of components, and classified move/no-move using a minimum-distance-to-geometric-mean Riemannian classifier. We show that executed and imagined movements can be decoded from distributed non-motor brain areas using a Riemannian decoder, reaching an area under the receiver operator characteristic of 0.83 ± 0.11. Furthermore, we highlight the distributedness of the movement-related neural activity, as no single brain area is the main driver of performance. Our decoding results demonstrate a first application of a Riemannian decoder on sEEG data and show that it is able to decode from distributed brain-wide recordings outside of the motor cortex. This brief report highlights the perspective to explore motor-related neural activity beyond the motor cortex, as many areas contain decodable information.

Successful epilepsy surgery in two cases with multiple sclerosis.

Brain surgery is the only curative treatment for people with focal epilepsy, but it is unclear whether this induces active disease in multiple sclerosis (MS). This creates a barrier to evaluate MS patients for epilepsy surgery. We present two cases of successful epilepsy surgery in patients with pharmacoresistant epilepsy and stable MS and give an overview of the existing literature. (1) a 28-year-old woman with seizures arising from a right basal temporo-occipital ganglioglioma was seizure-free after surgery, without MS relapse but with one new MS lesion postsurgically. (2) a 46-year-old woman with seizures arising from a natalizumab-associated progressive multifocal leukoencephalopathy (PML) lesion in the right frontal lobe was seizure-free after surgery preceded by extraoperative subdural electrocorticography, with new subclinical MS lesions. We are the first to report brain surgery in a PML survivor. Both patients stabilized radiologically after initiating second-line therapies. Successful epilepsy surgery can substantially increase the quality of life in patients with pharmacoresistant epilepsy and MS. With increasing survival rates of brain tumors and PML, the risk-benefit ratio of epilepsy surgery compared to a potential MS relapse after surgery becomes critically important. Shared decision-making is valuable for balancing the risks related to both diseases.

Novel noninvasive identification of patient-specific epileptic networks in focal epilepsies: Linking single-photon emission computed tomography perfusion during seizures with resting-state magnetoencephalography dynamics.

Single-photon emission computed tomography (SPECT) during seizures and magnetoencephalography (MEG) during the interictal state are noninvasive modalities employed in the localization of the epileptogenic zone in patients with drug-resistant focal epilepsy (DRFE). The present study aims to investigate whether there exists a preferentially high MEG functional connectivity (FC) among those regions of the brain that exhibit hyperperfusion or hypoperfusion during seizures. We studied MEG and SPECT data in 30 consecutive DRFE patients who had resective epilepsy surgery. We parcellated each ictal perfusion map into 200 regions of interest (ROIs) and generated ROI time series using source modeling of MEG data. FC between ROIs was quantified using coherence and phase-locking value. We defined a generalized linear model to relate the connectivity of each ROI, ictal perfusion z score, and distance between ROIs. We compared the coefficients relating perfusion z score to FC of each ROI and estimated the connectivity within and between resected and unresected ROIs. We found that perfusion z scores were strongly correlated with the FC of hyper-, and separately, hypoperfused ROIs across patients. High interictal connectivity was observed between hyperperfused brain regions inside and outside the resected area. High connectivity was also observed between regions of ictal hypoperfusion. Importantly, the ictally hypoperfused regions had a low interictal connectivity to regions that became hyperperfused during seizures. We conclude that brain regions exhibiting hyperperfusion during seizures highlight a preferentially connected interictal network, whereas regions of ictal hypoperfusion highlight a separate, discrete and interconnected, interictal network.

Dataset of Speech Production in intracranial.Electroencephalography.

Speech production is an intricate process involving a large number of muscles and cognitive processes. The neural processes underlying speech production are not completely understood. As speech is a uniquely human ability, it can not be investigated in animal models. High-fidelity human data can only be obtained in clinical settings and is therefore not easily available to all researchers. Here, we provide a dataset of 10 participants reading out individual words while we measured intracranial EEG from a total of 1103 electrodes. The data, with its high temporal resolution and coverage of a large variety of cortical and sub-cortical brain regions, can help in understanding the speech production process better. Simultaneously, the data can be used to test speech decoding and synthesis approaches from neural data to develop speech Brain-Computer Interfaces and speech neuroprostheses.

Continuously Decoding Grasping Movements using Stereotactic Depth Electrodes.

Brain-Computer Interfaces (BCIs) that decode a patient's movement intention to control a prosthetic device could restore some independence to paralyzed patients. An important step on the road towards naturalistic prosthetic control is to decode movement continuously with low-latency. BCIs based on intracortical micro-arrays provide continuous control of robotic arms, but require a minor craniotomy. Surface recordings of neural activity using EEG have made great advances over the last years, but suffer from high noise levels and large intra-session variance. Here, we investigate the use of minimally invasive recordings using stereotactically implanted EEG (sEEG). These electrodes provide a sparse sampling across many brain regions. So far, promising decoding results have been presented using data measured from the subthalamic nucleus or trial-to-trial based methods using depth electrodes. In this work, we demonstrate that grasping movements can continuously be decoded using sEEG electrodes, as well. Beta and high-gamma activity was extracted from eight participants performing a grasping task. We demonstrate above chance level decoding of movement vs rest and left vs right, from both frequency bands with accuracies up to 0.94 AUC. The vastly different electrode locations between participants lead to large variability. In the future, we hope that sEEG recordings will provide additional information for the decoding process in neuroprostheses.

Neurovascular networks in epilepsy: Correlating ictal blood perfusion with intracranial electrophysiology.

Perfusion patterns observed in Subtraction Ictal SPECT Co-registered to MRI (SISCOM) assist in focus localization and surgical planning for patients with medically intractable focal epilepsy. While the localizing value of SISCOM has been widely investigated, its relationship to the underlying electrophysiology has not been extensively studied and is therefore not well understood. In the present study, we set to investigate this relationship in a cohort of 70 consecutive patients who underwent ictal and interictal SPECT studies and subsequent stereo-electroencephalography (SEEG) monitoring for localization of the epileptogenic focus and surgical intervention. Seizures recorded during SEEG evaluation (SEEG seizures) were matched to semiologically-similar seizures during the preoperative ictal SPECT evaluation (SPECT seizures) by comparing the semiological changes in the course of each seizure. The spectral changes of the ictal SEEG with respect to interictal ones over 7 traditional frequency bands (0.1 to 150Hz) were analyzed at each SEEG site. Neurovascular (SEEG/SPECT) relations were assessed by comparing the estimated spectral power density changes of the SEEG at each site with the perfusion changes (SISCOM z-scores) estimated from the acquired SISCOM map at that site. Across patients, a significant correlation (p<0.05) was observed between spectral changes during the SEEG seizure and SISCOM perfusion z-scores. Brain sites with high perfusion z-score exhibited higher increased SEEG power in theta to ripple frequency bands with concurrent suppression in delta and theta frequency bands compared to regions with lower perfusion z-score. The dynamics of the correlation of SISCOM perfusion and SEEG spectral power from ictal onset to seizure end and immediate postictal period were also derived. Forty-six (46) of the 70 patients underwent resective epilepsy surgery. SISCOM z-score and power increase in beta to ripple frequency bands were significantly higher in resected than non-resected sites in the patients who were seizure-free following surgery. This study provides for the first time concrete evidence that both hyper-perfusion and hypo-perfusion patterns observed in SISCOM maps have strong electrophysiological underpinnings, and that integration of the information from SISCOM and SEEG can shed light on the location and dynamics of the underlying epileptic brain networks, and thus advance our anatomo-electro-clinical understanding and approaches to targeted diagnostic and therapeutic interventions.

Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data.

EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular 'bridge' between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response's variability over brain regions. By analyzing interictal data from twelve patients, we show that the extracted source signatures provide a sensitive localization of the ictal onset zone (10/12). Moreover, complementary parts of the IOZ can be uncovered by inspecting those regions with the most deviant neurovascular coupling, as quantified by two entropy-like metrics of the hemodynamic response function waveforms (9/12). Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can assist the presurgical evaluation of epilepsy. We make all code required to perform the computations available at https://github.com/svaneynd/structured-cmtf.

Epilepsy and Neurodevelopmental Comorbidities in Tuberous Sclerosis Complex: A Natural History Study.

BACKGROUND: We studied the natural history, genotype influence, and inter-relationship of epilepsy and neuropsychiatric disorders in tuberous sclerosis complex. METHODS: Patients were identified using the TSC Natural History Database, the largest repository of longitudinally studied patients enrolled by the TSC Clinics Consortium. RESULTS: A cohort of 1657 TSC Natural History Database patients was analyzed. Eighty-eight percent patients (91% TSC2 vs 82% TSC1; P = 0.002) had epilepsy; TSC2 was more frequent with epilepsy onset at age less than two years (TSC2 82% vs TSC1 54%; P < 0.001) and infantile spasms (TSC2 56% vs TSC1 27%; P < 0.001). Frequency of intellectual disability (intelligence quotient less than 70) was higher when epilepsy coexisted (P < 0.001), but was not impacted by genotype (P = 0.08). Severe intellectual disability (intelligence quotient less than 50) was associated with epilepsy onset at age less than two years (P = 0.007), but not with the epilepsy duration (P = 0.45). Autism was diagnosed in 23% and was associated with epilepsy (P < 0.001), particularly with epilepsy onset at age less than two years (P = 0.02) but not with genotype (P = 0.06). Attention-deficit/hyperactivity disorder (age greater than four years) was diagnosed in 18% and was associated with epilepsy (P < 0.001), but genotype made no difference. Nine percent had anxiety (age greater than seven years) and 6% had depression (age greater than nine years), but neither showed association with epilepsy or genotype. CONCLUSIONS: Epilepsy is associated with intellectual disability, and when epilepsy begins before age two years the frequency and severity of intellectual disability is much higher. Epilepsy is also associated with autism and attention-deficit/hyperactivity disorder but not with anxiety and depression. Additional trials, blinded, prospective, and adequately powered, will help clarify if early and effective treatment of epilepsy may also mitigate intellectual disability, autism, and attention-deficit/hyperactivity disorder.

Magnetoencephalography and ictal SPECT in patients with failed epilepsy surgery.

OBJECTIVE: Selected patients with intractable focal epilepsy who have failed a previous epilepsy surgery can become seizure-free with reoperation. Preoperative evaluation is exceedingly challenging in this cohort. We aim to investigate the diagnostic value of two noninvasive approaches, magnetoencephalography (MEG) and ictal single-photon emission computed tomography (SPECT), in patients with failed epilepsy surgery. METHODS: We retrospectively included a consecutive cohort of patients who failed prior resective epilepsy surgery, underwent re-evaluation including MEG and ictal SPECT, and had another surgery after the re-evaluation. The relationship between resection and localization from each test was determined, and their association with seizure outcomes was analyzed. RESULTS: A total of 46 patients were included; 21 (46%) were seizure-free at 1-year followup after reoperation. Twenty-seven (58%) had a positive MEG and 31 (67%) had a positive ictal SPECT. The resection of MEG foci was significantly associated with seizure-free outcome (p = 0.002). Overlap of ictal SPECT hyperperfusion zones with resection was significantly associated with seizure-free outcome in the subgroup of patients with injection time ≤20 seconds(p = 0.03), but did not show significant association in the overall cohort (p = 0.46) although all injections were ictal. Patients whose MEG and ictal SPECT were concordant on a sublobar level had a significantly higher chance of seizure freedom (p = 0.05). CONCLUSIONS: MEG alone achieved successful localization in patients with failed epilepsy surgery with a statistical significance. Only ictal SPECT with early injection (≤20 seconds) had good localization value. Sublobar concordance between both tests was significantly associated with seizure freedom. SPECT can provide essential information in MEG-negative cases and vice versa. SIGNIFICANCE: Our results emphasize the importance of considering a multimodal presurgical evaluation including MEG and SPECT in all patients with a previous failed epilepsy surgery.

Connectivity in ictal single photon emission computed tomography perfusion: a cortico-cortical evoked potential study.

Subtraction ictal and interictal single photon emission computed tomography can demonstrate complex ictal perfusion patterns. Regions with ictal hyperperfusion are suggested to reflect seizure onset and propagation pathways. The significance of ictal hypoperfusion is not well understood. The aim of this study was to verify whether ictal perfusion changes, both hyper- and hypoperfusion, correspond to electrically connected brain networks. A total of 36 subtraction ictal and interictal perfusion studies were analysed in 31 consecutive medically refractory focal epilepsy patients, evaluated by stereo-electroencephalography that demonstrated a single focal onset. Cortico-cortical evoked potential studies were performed after repetitive electrical stimulation of the ictal onset zone. Evoked responses at electrode contacts outside the stimulation site were used as a measure of connectivity. The evoked responses at these electrodes were compared to ictal perfusion values noted at these locations. In 67% of studies, evoked responses were significantly larger in hyperperfused compared to baseline-perfused areas. The majority of hyperperfused contacts also had significantly increased evoked responses relative to pre-stimulus electroencephalogram. In contrast, baseline-perfused and hypoperfused contacts mainly demonstrated non-significant evoked responses. Finally, positive significant correlations (P < 0.05) were found between perfusion scores and evoked responses in 61% of studies. When the stimulated ictal onset area was hyperperfused, 82% of studies demonstrated positive significant correlations. Following stimulation of hyperperfused areas outside seizure onset, positive significant correlations between perfusion changes and evoked responses could be seen, suggesting bidirectional connectivity. We conclude that strong connectivity was demonstrated between the ictal onset zone and hyperperfused regions, while connectivity was weaker in the direction of baseline-perfused or hypoperfused areas. In trying to understand a patient's epilepsy, one should consider the contribution of all hyperperfused regions, as these are likely not random, but represent an electrically connected epileptic network.

A prospective fMRI-based technique for localising the epileptogenic zone in presurgical evaluation of epilepsy.

There is growing evidence for the benefits of simultaneous EEG-fMRI as a non-invasive localising tool in the presurgical evaluation of epilepsy. However, many EEG-fMRI studies fail due to the absence of interictal epileptic discharges (IEDs) on EEG. Here we present an algorithm which makes use of fMRI as sole modality to localise the epileptogenic zone (EZ). Recent studies using various model-based or data-driven fMRI analysis techniques showed that it is feasible to find activation maps which are helpful in the detection of the EZ. However, there is lack of evidence that these techniques can be used prospectively, due to (a) their low specificity, (b) selecting multiple activation maps, or (c) a widespread epileptic network indicated by the selected maps. In the current study we present a method based on independent component analysis and a cascade of classifiers that exclusively detects a single map related to interictal epileptic brain activity. In order to establish the sensitivity and specificity of the proposed method, it was evaluated on a group of 18 EEG-negative patients with a single well-defined EZ and 13 healthy controls. The results show that our method provides maps which correctly indicate the EZ in several (N=4) EEG-negative cases but at the same time maintaining a high specificity (92%). We conclude that our fMRI-based approach can be used in a prospective manner, and can extend the applicability of fMRI to EEG-negative cases.

Correspondence between large-scale ictal and interictal epileptic networks revealed by single photon emission computed tomography (SPECT) and electroencephalography (EEG)-functional magnetic resonance imaging (fMRI).

OBJECTIVE: Epilepsy is increasingly recognized as a network disorder, but the spatial relationship between ictal and interictal networks is still largely unexplored. In this work, we compared hemodynamic changes related to seizures and interictal spikes on a whole brain scale. METHODS: Twenty-eight patients with refractory focal epilepsy (14 temporal and 14 extratemporal lobe) underwent both subtraction ictal single photon emission computed tomography (SPECT) coregistered to magnetic resonance imaging (MRI) (SISCOM) and spike-related electroencephalography (EEG-functional MRI (fMRI). SISCOM visualized relative perfusion changes during seizures, whereas EEG-fMRI mapped blood oxygen level-dependent (BOLD) changes related to spikes. Similarity between statistical maps of both modalities was analyzed per patient using the following two measures: (1) correlation between unthresholded statistical maps (Pearson's correlation coefficient) and (2) overlap between thresholded images (Dice coefficient). Overlap was evaluated at a regional level, for hyperperfusions and activations and for hypoperfusions and deactivations separately, using different thresholds. Nonparametric permutation tests were applied to assess statistical significance (p ≤ 0.05). RESULTS: We found significant and positive correlations between hemodynamic changes related to seizures and spikes in 27 (96%) of 28 cases (median correlation coefficient 0.29 [range -0.12 to 0.62]). In 20 (71%) of 28 cases, spatial overlap between hyperperfusion on SISCOM and activation on EEG-fMRI was significantly larger than expected by chance. Congruent changes were not restricted to the territory of the presumed epileptogenic zone, but could be seen at distant sites (e.g., cerebellum and basal ganglia). Overlap between ictal hypoperfusion and interictal deactivation was statistically significant in 22 (79%) of 28 patients. Despite the high rate of congruence, discrepancies were observed for both modalities. SIGNIFICANCE: We conclude that hemodynamic changes related to seizures and spikes varied spatially with the same sign and within a common network. Overlap was present in regions nearby and distant from discharge origin.

A reliable and time-saving semiautomatic spike-template-based analysis of interictal EEG-fMRI.

OBJECTIVE: A prerequisite for the implementation of interictal electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) in the presurgical work-up for epilepsy surgery is straightforward processing. We propose a new semi-automatic method as alternative for the challenging and time-consuming visual spike identification. METHODS: Our method starts from a patient-specific spike-template, built by averaging spikes recorded on the EEG outside the scanner. Spatiotemporal cross-correlations between the template and the EEG measured during fMRI were calculated. To minimize false-positive detections, this time course of cross-correlations was binarized by means of a spike-template-specific threshold determined in healthy controls. To inform our model for statistical parametric mapping, this binarized regressor was convolved with the canonical hemodynamic response function. We validated our "template-based" method in 21 adult patients with refractory focal epilepsy with a well-defined epileptogenic zone and interictal spikes during EEG-fMRI. Sensitivity and specificity for detecting the epileptogenic zone were calculated and represented in receiver operating characteristic (ROC) curves. Our approach was compared with a previously proposed semiautomatic "topography-based" method that used the topographic amplitude distribution of spikes as a starting point for correlation-based fitting. RESULTS: Good diagnostic performance could be reached with our template-based method. The optimal area under the ROC curve was 0.77. Diagnostic performance of the topography-based method was overall low. SIGNIFICANCE: Our new template-based method is more standardized and time-saving than visual spike identification on intra-scanner EEG recordings, and preserves good diagnostic performance for detecting the epileptogenic zone.

Sensitivity and Specificity of Interictal EEG-fMRI for Detecting the Ictal Onset Zone at Different Statistical Thresholds.

There is currently a lack of knowledge about electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) specificity. Our aim was to define sensitivity and specificity of blood oxygen level dependent (BOLD) responses to interictal epileptic spikes during EEG-fMRI for detecting the ictal onset zone (IOZ). We studied 21 refractory focal epilepsy patients who had a well-defined IOZ after a full presurgical evaluation and interictal spikes during EEG-fMRI. Areas of spike-related BOLD changes overlapping the IOZ in patients were considered as true positives; if no overlap was found, they were treated as false-negatives. Matched healthy case-controls had undergone similar EEG-fMRI in order to determine true-negative and false-positive fractions. The spike-related regressor of the patient was used in the design matrix of the healthy case-control. Suprathreshold BOLD changes in the brain of controls were considered as false positives, absence of these changes as true negatives. Sensitivity and specificity were calculated for different statistical thresholds at the voxel level combined with different cluster size thresholds and represented in receiver operating characteristic (ROC)-curves. Additionally, we calculated the ROC-curves based on the cluster containing the maximal significant activation. We achieved a combination of 100% specificity and 62% sensitivity, using a Z-threshold in the interval 3.4-3.5 and cluster size threshold of 350 voxels. We could obtain higher sensitivity at the expense of specificity. Similar performance was found when using the cluster containing the maximal significant activation. Our data provide a guideline for different EEG-fMRI settings with their respective sensitivity and specificity for detecting the IOZ. The unique cluster containing the maximal significant BOLD activation was a sensitive and specific marker of the IOZ.

Automatic selection of epileptic independent fMRI components.

EEG-correlated fMRI analysis has proven to be useful in localizing regions of BOLD activation related to epileptic activity. However, as EEG does not always provide reliable information, purely fMRI-based data-driven techniques are invaluable. Recently, we have shown that independent component analysis (ICA) can extract sources related to the epileptic network even in such EEG-negative cases [1]. Moreover, these sources were shown to be informative with respect to the seizure onset zone (SOZ). In order to utilize this concept in clinical practice in a prospective manner, this work aims at developing an automatic technique for selecting the epileptic sources. The proposed approach applies a cascade of two classifiers. In the first step artifact related sources are discarded. In the second step the sources are characterized by four discriminative features and epileptic sources are selected from among other BOLD-related components. Our technique reaches a promising 77% specificity and provides concordant sources with the EEG-correlated fMRI activation maps or with the SOZ in 71% of the cases.

ICA extracts epileptic sources from fMRI in EEG-negative patients: a retrospective validation study.

Simultaneous EEG-fMRI has proven to be useful in localizing interictal epileptic activity. However, the applicability of traditional GLM-based analysis is limited as interictal spikes are often not seen on the EEG inside the scanner. Therefore, we aim at extracting epileptic activity purely from the fMRI time series using independent component analysis (ICA). To our knowledge, we show for the first time that ICA can find sources related to epileptic activity in patients where no interictal spikes were recorded in the EEG. The epileptic components were identified retrospectively based on the known localization of the ictal onset zone (IOZ). We demonstrate that the selected components truly correspond to epileptic activity, as sources extracted from patients resemble significantly better the IOZ than sources found in healthy controls. Furthermore, we show that the epileptic components in patients with and without spikes recorded inside the scanner resemble the IOZ in the same degree. We conclude that ICA of fMRI has the potential to extend the applicability of EEG-fMRI for presurgical evaluation in epilepsy.