Hemodynamic changes preceding the interictal EEG spike in patients with focal epilepsy investigated using simultaneous EEG-fMRI

Negative BOLD response to interictal epileptic discharges in focal epilepsy

In EEG-fMRI studies, BOLD responses related to interictal epileptic discharges (IEDs) are most often the expected positive response (activation) but sometimes a surprising negative response (deactivation). The significance of deactivation in the region of IED generation is uncertain. The aim of this study was to determine if BOLD deactivation was caused by specific IED characteristics. Among focal epilepsy patients who underwent 3T EEG-fMRI from 2006 to 2011, those with negative BOLD having a maximum t-value in the IED generating region were selected. As controls, subjects with maximum activation in the IED generating region were selected. We established the relationship between the type of response (activation/deactivation) and (1) presence of slow wave in the IEDs, (2) lobe of epileptic focus, (3) occurrence as isolated events or bursts, (4) spatial extent of the EEG discharge. Fifteen patients with deactivation and 15 with activation were included. The IEDs were accompanied by a slow wave in 87 % of patients whose primary BOLD was a deactivation and only in 33 % of patients with activation. In the deactivation group, the epileptic focus was more frequently in the posterior quadrant and involved larger cortical areas, whereas in the activation group it was more frequently temporal. IEDs were more frequently of long duration in the deactivation group. The main factor responsible for focal deactivations is the presence of a slow wave, which is the likely electrographic correlate of prolonged inhibition. This adds a link to the relationship between electrophysiological and BOLD activities.

Simultaneous EEG and fMRI recordings (EEG-fMRI) in children with epilepsy

By combining electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) it is possible to describe blood oxygenation level-dependent (BOLD) signal changes related to EEG patterns. This way, EEG-pattern-associated networks of hemodynamic changes can be detected anywhere in the brain with good spatial resolution. This review summarizes EEG-fMRI studies that have been performed in children with epilepsy. EEG-fMRI studies in focal epilepsy (structural and nonlesional cases, benign epilepsy with centrotemporal spikes), generalized epilepsy (especially absence epilepsy), and epileptic encephalopathies (West syndrome, Lennox-Gastaut syndrome, continuous spike and waves during slow sleep, and Dravet syndrome) are presented. Although EEG-fMRI was applied mainly to localize the region presumably generating focal interictal discharges in focal epilepsies, EEG-fMRI identified underlying networks in patients with generalized epilepsies and thereby contributed to a better understanding of these epilepsies. In epileptic encephalopathies a specific fingerprint of hemodynamic changes associated with the particular syndrome was detected. The value of the EEG-fMRI technique for diagnosis and investigation of pathogenetic mechanisms of different forms of epilepsy is discussed.

Epileptic neuronal networks: methods of identification and clinical relevance

The main objective of this paper is to examine evidence for the concept that epileptic activity should be envisaged in terms of functional connectivity and dynamics of neuronal networks. Basic concepts regarding structure and dynamics of neuronal networks are briefly described. Particular attention is given to approaches that are derived, or related, to the concept of causality, as formulated by Granger. Linear and non-linear methodologies aiming at characterizing the dynamics of neuronal networks applied to EEG/MEG and combined EEG/fMRI signals in epilepsy are critically reviewed. The relevance of functional dynamical analysis of neuronal networks with respect to clinical queries in focal cortical dysplasias, temporal lobe epilepsies, and "generalized" epilepsies is emphasized. In the light of the concepts of epileptic neuronal networks, and recent experimental findings, the dichotomic classification in focal and generalized epilepsy is re-evaluated. It is proposed that so-called "generalized epilepsies," such as absence seizures, are actually fast spreading epilepsies, the onset of which can be tracked down to particular neuronal networks using appropriate network analysis. Finally new approaches to delineate epileptogenic networks are discussed.

EEG-fMRI correlation patterns in the presurgical evaluation of focal epilepsy: a comparison with electrocorticographic data and surgical outcome measures

EEG-correlated functional MRI (EEG-fMRI) visualizes brain regions associated with interictal epileptiform discharges (IEDs). This technique images the epileptiform network, including multifocal, superficial and deeply situated cortical areas. To understand the role of EEG-fMRI in presurgical evaluation, its results should be validated relative to a gold standard. For that purpose, EEG-fMRI data were acquired for a heterogeneous group of surgical candidates (n=16) who were later implanted with subdural grids and strips (ECoG). The EEG-fMRI correlation patterns were systematically compared with brain areas involved in IEDs ECoG, using a semi-automatic analysis method, as well as to the seizure onset zone, resected area, and degree of seizure freedom. In each patient at least one of the EEG-fMRI areas was concordant with an interictally active ECoG area, always including the early onset area of IEDs in the ECoG data. This confirms that EEG-fMRI reflects a pattern of onset and propagation of epileptic activity. At group level, 76% of the BOLD regions that were covered with subdural grids, were concordant with interictally active ECoG electrodes. Due to limited spatial sampling, 51% of the BOLD regions were not covered with electrodes and could, therefore, not be validated. From an ECoG perspective it appeared that 29% of the interictally active ECoG regions were missed by EEG-fMRI and that 68% of the brain regions were correctly identified as inactive with EEG-fMRI. Furthermore, EEG-fMRI areas included the complete seizure onset zone in 83% and resected area in 93% of the data sets. No clear distinction was found between patients with a good or poor surgical outcome: in both patient groups, EEG-fMRI correlation patterns were found that were either focal or widespread. In conclusion, by comparison of EEG-fMRI with interictal invasive EEG over a relatively large patient population we were able to show that the EEG-fMRI correlation patterns are spatially accurate at the level of neurosurgical units (i.e. anatomical brain regions) and reflect the underlying network of IEDs. Therefore, we expect that EEG-fMRI can play an important role for the determination of the implantation strategy.

Mapping preictal and ictal haemodynamic networks using video-electroencephalography and functional imaging

Ictal patterns on scalp-electroencephalography are often visible only after propagation, therefore rendering localization of the seizure onset zone challenging. We hypothesized that mapping haemodynamic changes before and during seizures using simultaneous video-electroencephalography and functional imaging will improve the localization of the seizure onset zone. Fifty-five patients with ≥2 refractory focal seizures/day, and who had undergone long-term video-electroencephalography monitoring were included in the study. 'Preictal' (30 s immediately preceding the electrographic seizure onset) and ictal phases, 'ictal-onset'; 'ictalestablished' and 'late ictal', were defined based on the evolution of the electrographic pattern and clinical semiology. The functional imaging data were analysed using statistical parametric mapping to map ictal phase-related haemodynamic changes consistent across seizures. The resulting haemodynamic maps were overlaid on co-registered anatomical scans, and the spatial concordance with the presumed and invasively defined seizure onset zone was determined. Twenty patients had typical seizures during functional imaging. Seizures were identified on video-electroencephalography in 15 of 20, on electroencephalography alone in two and on video alone in three patients. All patients showed significant ictal-related haemodynamic changes. In the six cases that underwent invasive evaluation, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone for all patients. The most statistically significant haemodynamic cluster within the presumed seizure onset zone was between 1.1 and 3.5 cm from the invasively defined seizure onset zone, which was resected in two of three patients undergoing surgery (Class I post-surgical outcome) and was not resected in one patient (Class III post-surgical outcome). In the remaining 14 cases, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone in six of eight patients with structural-lesions and five of six non-lesional patients. The most statistically significant haemodynamic cluster was localizable at sub-lobar level within the presumed seizure onset zone in six patients. The degree of concordance of haemodynamic maps was significantly better (P < 0.05) for the ictal-onset phase [entirely concordant/concordant plus (13/20; 65%) + some concordance (4/20; 20%) = 17/20; 85%] than ictal-established [entirely concordant/concordant plus (5/13; 38%) + some concordance (4/13; 31%) = 9/13; 69%] and late ictal [concordant plus (1/9; 11%) + some concordance (4/9; 44%) = 5/9; 55%] phases. Ictal propagation-related haemodynamic changes were also seen in symptomatogenic areas (9/20; 45%) and the default mode network (13/20; 65%). A common pattern of preictal changes was seen in 15 patients, starting between 98 and 14 s before electrographic seizure onset, and the maps had a degree of concordance with the presumed seizure onset zone in 10 patients. In conclusion, preictal and ictal haemodynamic changes in refractory focal seizures can non-invasively localize seizure onset at sub-lobar/gyral level when ictal scalp-electroencephalography is not helpful.

Mapping brain activity using event-related independent components analysis (eICA): specific advantages for EEG-fMRI

Event-related analyses of functional MRI (fMRI) typically assume that the onset and offset of neuronal activity match stimuli onset and offset, and that evoked fMRI signal changes follow the canonical haemodynamic response function (HRF). Some event types, however, may be unsuited to this approach: brief stimuli might elicit an extended neuronal response; anticipatory effects might result in activity preceding the event; or altered neurovascular coupling may result in a non-canonical HRF. An example is interictal epileptiform discharges (IEDs), which may show a non-canonical HRF and fMRI signal changes preceding their onset as detected on EEG. In such cases, less constrained analyses - capable of detecting early, non-canonical responses - may be necessary. A consequence of less constrained analyses, however, is that artefactual sources of signal change - motion or physiological noise for example - may also be detected and mixed with the neuronally-generated signals. In this paper, to address this issue, we describe an event-related independent components analysis (eICA) that identifies different sources of event-related signal change that can then be separately assessed to identify likely artefacts and separate primary from propagated activity. We also describe a group analysis that identifies eICA components that are spatially and temporally consistent across subjects and provides an objective approach for selecting group-specific components likely to be of neural origin. We apply eICA to patients with rolandic epilepsy - with stereotypical IEDs arising from a focus in the rolandic fissure - and demonstrate that a single event-related component, concordant with this source location, is detected.

Mapping interictal epileptic discharges using mutual information between concurrent EEG and fMRI

OBJECTIVE

The mapping of haemodynamic changes related to interictal epileptic discharges (IED) in simultaneous electroencephalography (EEG) and functional MRI (fMRI) studies is usually carried out by means of EEG-correlated fMRI analyses where the EEG information specifies the model to test on the fMRI signal. The sensitivity and specificity critically depend on the accuracy of EEG detection and the validity of the haemodynamic model. In this study we investigated whether an information theoretic analysis based on the mutual information (MI) between the presence of epileptic activity on EEG and the fMRI data can provide further insights into the haemodynamic changes related to interictal epileptic activity. The important features of MI are that: 1) both recording modalities are treated symmetrically; 2) no requirement for a-priori models for the haemodynamic response function, or assumption of a linear relationship between the spiking activity and BOLD responses, and 3) no parametric model for the type of noise or its probability distribution is necessary for the computation of MI.

METHODS

Fourteen patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI and intracranial EEG and/or surgical resection with positive postoperative outcome (seizure freedom or considerable reduction in seizure frequency) was available in 7/14 patients. We used nonparametric statistical assessment of the MI maps based on a four-dimensional wavelet packet resampling method. The results of MI were compared to the statistical parametric maps obtained with two conventional General Linear Model (GLM) analyses based on the informed basis set (canonical HRF and its temporal and dispersion derivatives) and the Finite Impulse Response (FIR) models.

RESULTS

The MI results were concordant with the electro-clinically or surgically defined epileptogenic area in 8/14 patients and showed the same degree of concordance as the results obtained with the GLM-based methods in 12 patients (7 concordant and 5 discordant). In one patient, the information theoretic analysis improved the delineation of the irritative zone compared with the GLM-based methods.

DISCUSSION

Our findings suggest that an information theoretic analysis can provide clinically relevant information about the BOLD signal changes associated with the generation and propagation of interictal epileptic discharges. The concordance between the MI, GLM and FIR maps support the validity of the assumptions adopted in GLM-based analyses of interictal epileptic activity with EEG-fMRI in such a manner that they do not significantly constrain the localization of the epileptogenic zone.

Spontaneous EEG-Functional MRI in Mesial Temporal Lobe Epilepsy: Implications for the Neural Correlates of Consciousness

The combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has been shown to have great potential for providing a greater understanding of normal and diseased states in both human and animal studies. Simultaneous EEG-fMRI is particularly well suited for the study of epilepsy in that it may reveal the neurobiology of ictal and interictal epileptiform discharges and noninvasively localize epileptogenic foci. Spontaneous, coherent fluctuations of neuronal activity and the coupled hemodynamic responses have also been shown to provide diagnostic markers of disease, extending our understanding of intrinsically structured ongoing brain activity. Following a short summary of the hardware and software development of simultaneous EEG-fMRI, this paper reviews a unified framework of integrating neuronal and hemodynamic processes during epileptic seizures and discusses the role and impact of spontaneous activity in the mesial temporal lobe epilepsies with particular emphasis on the neural and physiological correlates of consciousness.

Detection of epileptic activity in fMRI without recording the EEG

EEG-fMRI localizes epileptic foci by detecting cerebral hemodynamic changes that are correlated to epileptic events visible in EEG. However, scalp EEG is insensitive to activity restricted to deep structures and recording the EEG in the scanner is complex and results in major artifacts that are difficult to remove. This study presents a new framework for identifying the BOLD manifestations of epileptic discharges without having to record the EEG. The first stage is based on the detection of epileptic events for each voxel by sparse representation in the wavelet domain. The second stage is to gather voxels according to proximity in time and space of detected activities. This technique was evaluated on data generated by superposing artificial responses at different locations and responses amplitude in the brain for 6 control subject runs. The method was able to detect effectively and consistently for responses amplitude of at least 1% above baseline. 46 runs from 15 patients with focal epilepsy were investigated. The results demonstrate that the method detected at least one concordant event in 37/41 runs. The maps of activation obtained from our method were more similar to those obtained by EEG-fMRI than to those obtained by the other method used in this context, 2D-Temporal Cluster Analysis. For 5 runs without event read on scalp EEG, 3 runs showed an activation concordant with the patient's diagnostic. It may therefore be possible, at least when spikes are infrequent, to detect their BOLD manifestations without having to record the EEG.

Nonlinear hemodynamic responses in human epilepsy: a multimodal analysis with fNIRS-EEG and fMRI-EEG

Functional magnetic resonance imaging (fMRI) combined with electroencephalography (fMRI-EEG) is a neuroimaging technique based on the blood oxygenation level dependent (BOLD) signal which has been shown to be useful in the study of epilepsy for the localization of the epileptogenic focus. Functional near-infrared spectroscopy (fNIRS) combined with EEG (fNIRS-EEG) is another imaging technique based on the measurement of oxygenated and deoxygenated hemoglobin with complementary clinical potential in epilepsy, for continuous patient monitoring, language lateralization, and focus localization. In this work fMRI-EEG and fNIRS-EEG are used to quantify nonlinear hemodynamic responses in three cases of human refractory focal epilepsy, by using the Volterra kernel expansion up to second order. Prior to analyzing real data, extensive simulations are carried out to show that nonlinearities are estimable. The Volterra methodology is then applied to multimodal data recorded from 3 epileptic patients selected for their frequent spiking activity. Care is taken to account for variability of hemodynamic responses due to other causes than Volterra nonlinearities. Statistically significant nonlinearities are observed for all patients and all modalities. Good concordance between fNIRS and fMRI is found for both the amplitude of the Volterra responses, and, with limitations, in the localization of the epileptic focus and regions of inverted responses (negative BOLD signals). In one patient, Volterra nonlinearities allowed epileptic focus identification with fMRI, while analyses without nonlinearities failed to see it. In simulations when nonlinearities were included, analysis without Volterra nonlinearities performed poorly. These two observations suggest routinely checking for nonlinearities in functional imaging of patients presenting with frequent spikes.

Mapping hemodynamic correlates of seizures using fMRI: A review

Functional magnetic resonance imaging (fMRI) is able to detect changes in blood oxygenation level associated with neuronal activity throughout the brain. For more than a decade, fMRI alone or in combination with simultaneous EEG recording (EEG-fMRI) has been used to investigate the hemodynamic changes associated with interictal and ictal epileptic discharges. This is the first literature review to focus on the various fMRI acquisition and data analysis methods applied to map epileptic seizure-related hemodynamic changes from the first report of an fMRI scan of a seizure to the present day. Two types of data analysis approaches, based on temporal correlation and data driven, are explained and contrasted. The spatial and temporal relationship between the observed hemodynamic changes using fMRI and other non-invasive and invasive electrophysiological and imaging data is considered. We then describe the role of fMRI in localizing and exploring the networks involved in spontaneous and triggered seizure onset and propagation. We also discuss that fMRI alone and combined with EEG hold great promise in the investigation of seizure-related hemodynamic changes non-invasively in humans. We think that this will lead to significant improvements in our understanding of seizures with important consequences for the treatment of epilepsy.

Quantifying hemodynamic refractory bold effects in normal subjects at the single-subject level using an inverse logit fitting procedure

PURPOSE

To evaluate whether hemodynamic refractory effects provoked by repeated visual stimulation can be detected and quantified at the single-subject level using a recently described hemodynamic response function (HRF) fitting algorithm.

MATERIALS AND METHODS

Hemodynamic refractory effects were induced with an easily applicable functional MRI (fMRI) paradigm. A fitting method with inverse logit (IL) functions was applied to quantify net HRFs at the single-subject level with three interstimulus intervals (ISI; 1, 2, and 6 s). The model yielded amplitude, latencies, and width for each HRF.

RESULTS

HRF fitting was possible in 44 of 51 healthy volunteers, with excellent goodness-of-fit (R(2) = 0.9745 ± 0.0241). Refractory effects were most pronounced for the 1-s ISI (P < 0.001) and had nearly disappeared for the 6-s ISI.

CONCLUSION

Quantifying refractory effects in individuals was possible in 86.3% of normal subjects using the IL fitting algorithm. This setup may be suitable to explore such effects in individual patients.

Combining EEG and fMRI in the study of epileptic discharges

The combining of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a unique noninvasive method for investigating the brain regions involved at the time of epileptic discharges. The neuronal discharges taking place during an interictal spike or spike-wave burst result in an increase in metabolism and blood flow, which is reflected in the blood oxygen-level dependent (BOLD) signal measured by fMRI. This increase is most intense in the region generating the discharge but is also present in regions affected by the discharge. On occasion, epileptic discharges result in decreased metabolism, the origin of which is only partially understood. EEG-fMRI applied to focal epilepsy results in maxima of the BOLD signal most often concordant with other methods of localization and has been shown to help in localizing epileptic foci in nonlesional frontal lobe epilepsy. It has also demonstrated the involvement of the thalamus in generalized epileptic discharges. In patients with new-onset epilepsy it could be used to evaluate the source and extent of the brain structures involved during discharges and their evolution as the disease progresses.

Preictal changes in cerebral haemodynamics: review of findings and insights from intracerebral EEG

The possibility of recording changes in brain signals occurring before epileptic seizures is of considerable interest, both as markers for seizure anticipation and as a window into the mechanisms of seizure generation. Several studies have reported preictal changes on electrophysiological traces. More recently, observations have been made of changes occurring on haemodynamic signals before interictal events or before seizures, often without concurrent changes observed on electrophysiology. We present here a critical review of these findings, in optical imaging, SPECT and fMRI, followed by a discussion based on data from intracerebral EEG.

With or without spikes: localization of focal epileptic activity by simultaneous electroencephalography and functional magnetic resonance imaging

In patients with medically refractory focal epilepsy who are candidates for epilepsy surgery, concordant non-invasive neuroimaging data are useful to guide invasive electroencephalographic recordings or surgical resection. Simultaneous electroencephalography and functional magnetic resonance imaging recordings can reveal regions of haemodynamic fluctuations related to epileptic activity and help localize its generators. However, many of these studies (40-70%) remain inconclusive, principally due to the absence of interictal epileptiform discharges during simultaneous recordings, or lack of haemodynamic changes correlated to interictal epileptiform discharges. We investigated whether the presence of epilepsy-specific voltage maps on scalp electroencephalography correlated with haemodynamic changes and could help localize the epileptic focus. In 23 patients with focal epilepsy, we built epilepsy-specific electroencephalographic voltage maps using averaged interictal epileptiform discharges recorded during long-term clinical monitoring outside the scanner and computed the correlation of this map with the electroencephalographic recordings in the scanner for each time frame. The time course of this correlation coefficient was used as a regressor for functional magnetic resonance imaging analysis to map haemodynamic changes related to these epilepsy-specific maps (topography-related haemodynamic changes). The method was first validated in five patients with significant haemodynamic changes correlated to interictal epileptiform discharges on conventional analysis. We then applied the method to 18 patients who had inconclusive simultaneous electroencephalography and functional magnetic resonance imaging studies due to the absence of interictal epileptiform discharges or absence of significant correlated haemodynamic changes. The concordance of the results with subsequent intracranial electroencephalography and/or resection area in patients who were seizure free after surgery was assessed. In the validation group, haemodynamic changes correlated to voltage maps were similar to those obtained with conventional analysis in 5/5 patients. In 14/18 patients (78%) with previously inconclusive studies, scalp maps related to epileptic activity had haemodynamic correlates even when no interictal epileptiform discharges were detected during simultaneous recordings. Haemodynamic changes correlated to voltage maps were spatially concordant with intracranial electroencephalography or with the resection area. We found better concordance in patients with lateral temporal and extratemporal neocortical epilepsy compared to medial/polar temporal lobe epilepsy, probably due to the fact that electroencephalographic voltage maps specific to lateral temporal and extratemporal epileptic activity are more dissimilar to maps of physiological activity. Our approach significantly increases the yield of simultaneous electroencephalography and functional magnetic resonance imaging to localize the epileptic focus non-invasively, allowing better targeting for surgical resection or implantation of intracranial electrode arrays.

The diagnostic value of clinical EEG in detecting abnormal synchronicity in panic disorder

Electroencephalographic (EEG) findings repeatedly reported abnormal synchronous or even epileptiform discharges in panic disorder. Although less frequently occurring in patients with panic disorder, these deviant EEG features during panic attacks were also observed in intracranial EEG. For this purpose, our article reviews the consideration of abnormal synchronous neuronal activity in different neurocircuits, particularly limbic, as a suggested condition of panic attacks. Therapeutic approaches of anticonvulsants have shown reductions of symptoms and frequency of attacks in numerous patients suffering from panic disorder, supporting the presumption of underlying abnormal synchronous neuronal activity. Thus, scalp EEG recordings are still recommended for discovering indications of abnormal synchronous neuronal activity in panic patients.

A characteristic time sequence of epileptic activity in EEG during dynamic penicillin-induced focal epilepsy--a preliminary study

Penicillin-induced focal epilepsy is a well-known model in experimental epilepsy. However, the dynamic evolution of waveforms, DC-level changes, spectral content and coherence are rarely reported. Stimulated by earlier fMRI findings, we also seek for the early signs preceding spiking activity from frequency domain of EEG signal. In this study, EEG data is taken from previous EEG/fMRI series (six pigs, 20-24kg) of an experimental focal epilepsy model, which includes dynamic induction of epileptic activity with penicillin (6000IU) injection into the somatosensory cortex during deep isoflurane anaesthesia. No ictal discharges were recorded with this dose. Spike waveforms, DC-level, time-frequency content and coherence of EEG were analysed. Development of penicillin induced focal epileptic activity was not preceded with specific spectral changes. The beginning of interictal spiking was related to power increase in the frequencies below 6Hz or 20Hz, and continued to a widespread spectral increase. DC-level and coherence changes were clear in one animal. Morphological evolution of epileptic activity was a collection of the low-amplitude monophasic, bipolar, triple or double spike-wave forms, with an increase in amplitude, up to large monophasic spiking. In conclusion, in the time sequence of induced epileptic activity, immediate shifts in DC-level EEG are plausible, followed by the spike activity-related widespread increase in spectral content. Morphological evolution does not appear to follow a clear continuum; rather, intermingled and variable spike or multispike waveforms generally lead to stabilised activity of high-amplitude monophasic spikes.

Changes preceding interictal epileptic EEG abnormalities: comparison between EEG/fMRI and intracerebral EEG

PURPOSE

In simultaneous scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), blood oxygen level dependent (BOLD) changes occurring before the spike have been sometimes described but could not be explained. To characterize the origin of this prespike BOLD signal change, we looked for electrographic changes in stereo-EEG (SEEG) possibly preceding the scalp spike in patients that showed early BOLD response in EEG/fMRI.

METHODS

We studied four patients with drug-resistant focal epilepsy who underwent EEG/fMRI, showed a prespike BOLD response, and were then studied with depth electrodes for presurgical localization of the epileptic generator. Early BOLD responses in the region of the spike field were analyzed using models with hemodynamic response functions (HRFs) peaking from -9 to +9 s around the spike. SEEG recordings in the period and location corresponding to the early HRF responses were analyzed to detect if electrographic changes were present in the SEEG before the scalp abnormality.

KEY FINDINGS

One of the four patients presented a SEEG interictal discharge in the period corresponding to the early BOLD response. In the other three, no electrographic changes were detected in the SEEG in the period corresponding to early BOLD changes.

SIGNIFICANCE

Although the early BOLD activity may sometimes be explained by a synchronized neural discharge detectable with SEEG but not visible on the scalp EEG, in most cases the early BOLD response reflects a metabolic phenomenon that does not appear to result from a synchronized neuronal discharge. Prespike metabolic responses can result from synchronized or nonsynchronized neuronal activity, or from nonneuronal mechanisms including glia.

Neuroimaging biomarkers of epileptogenesis

Much progress has been made in the field studying the process of epileptogenesis via neuroimaging techniques. Conventional imaging methods include magnetic resonance imaging with morphometric analysis, magnetic resonance spectroscopy and positron emission tomography. Newer network-based methods such as diffusion tensor imaging and functional magnetic resonance imaging with resting functional connectivity are being developed and applied to clinical use. This review provides a brief summary of the major human and animal studies in both partial and generalized epilepsies that demonstrate the potential of these imaging modalities to serve as biomarkers of epileptogenesis.

Reproducibility of interictal EEG-fMRI results in patients with epilepsy

PURPOSE

Combined electroencephalography (EEG) and functional MRI (EEG-fMRI) can be useful in the evaluation of epilepsy patients. The reproducibility of EEG-fMRI findings needs to be established to consider it as a clinically valuable method. We addressed the intrasubject reproducibility of EEG-fMRI and the possible superiority of higher magnetic field strength in patients who were scanned twice.

METHODS

Fifteen patients were studied: Seven had one 1.5T and one 3T scan and eight had two 3T EEG-fMRI studies. Equal numbers of events of the same interictal epileptic discharge (IED) were included, and IED-related blood oxygenation level dependent (BOLD) results were compared.

KEY FINDINGS

In 1.5T-3T comparisons, five patients had BOLD responses in both studies, but in four there was a better response (higher maximum t-score and larger cluster) in 3T studies. One patient had a BOLD response in the 3T study only. The remaining patient had no BOLD response in either study. In 3T-3T comparisons, results were reproducible in five of eight patients, and one patient had no response in both studies. The two remaining patients had previous extensive surgery and extremely frequent IEDs. Some of the reproduced patterns in other patients, however, differed in terms of maximum t-score and cluster size.

SIGNIFICANCE

EEG-fMRI appears to provide reasonable reproducibility, although repeated studies may show differences. The absence of BOLD response seems to be reproducible as well. EEG-fMRI results tend to benefit from higher field scanners (3T over 1.5T). Further studies are needed to determine if reproducibility depends on specific clinical, electrographic, or anatomic findings.

Subdural electrodes

Subdural electrodes are frequently used to aid in the neurophysiological assessment of patients with intractable seizures. We review the indications for these, their uses for localizing epileptogenic regions and for localizing cortical regions supporting movement, sensation, and language.

Absence seizures: individual patterns revealed by EEG-fMRI

PURPOSE

Absences are characterized by an abrupt onset and end of generalized 3-4 Hz spike and wave discharges (GSWs), accompanied by unresponsiveness. Although previous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) studies showed that thalamus, default mode areas, and caudate nuclei are involved in absence seizures, the contribution of these regions throughout the ictal evolution of absences remains unclear. Furthermore, animal models provide evidence that absences are initiated by a cortical focus with a secondary involvement of the thalamus. The aim of this study was to investigate dynamic changes during absences.

METHODS

Seventeen absences from nine patients with absence epilepsy and classical pattern of 3-4 Hz GSWs during EEG-fMRI recording were included in the study. The absences were studied in a sliding window analysis, providing a temporal sequence of blood oxygen-level dependent (BOLD) response maps.

RESULTS

Thalamic activation was found in 16 absences (94%), deactivation in default mode areas in 15 (88%), deactivation of the caudate nuclei in 10 (59%), and cortical activation in patient-specific areas in 10 (59%) of the absences. Cortical activations and deactivations in default mode areas and caudate nucleus occurred significantly earlier than thalamic responses.

DISCUSSION

Like a fingerprint, patient-specific BOLD signal changes were remarkably consistent in space and time across different absences of one patient but were quite different from patient to patient, despite having similar EEG pattern and clinical semiology. Early frontal activations could support the cortical focus theory, but with an addition: This early activation is patient specific.

BOLD signal changes preceding negative responses in EEG-fMRI in patients with focal epilepsy

PURPOSE

In simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), increased neuronal activity from epileptiform spikes commonly elicits positive blood oxygenation level-dependent (BOLD) responses. Negative responses are also occasionally seen and have not been explained. Recent studies describe BOLD signal changes before focal EEG spikes. We aimed to systematically study if the undershoot of a preceding positive response might explain the negative BOLD seen in the focus.

METHODS

Eighty-two patients with focal epilepsy who underwent EEG-fMRI at 3T were retrospectively studied. Studies with a focal negative BOLD response in the region of the spike field were reanalyzed using models with hemodynamic response functions (HRFs) peaking from -9 to +9 s around the spike.

RESULTS

Eight patients met the inclusion criteria, showing negative BOLD responses in the spike field on standard analysis. None had positive BOLD responses immediately adjacent to the areas of deactivation. Regions of deactivation were found to have congruent preceding positive responses in two cases. These early activations were seen at the combined maps of -5 to -9 s.

DISCUSSION

This study indicates that in a small proportion of patients with focal epilepsy in whom the standard analysis reveals focal negative responses, an earlier positive BOLD response is probably the cause. The origin of negative BOLD signal changes in the focus as a result of an epileptic event remains, however, unexplained in most of the patients in whom it occurs.

Modulation by EEG features of BOLD responses to interictal epileptiform discharges

INTRODUCTION

EEG-fMRI of interictal epileptiform discharges (IEDs) usually assumes a fixed hemodynamic response function (HRF). This study investigates HRF variability with respect to IED amplitude fluctuations using independent component analysis (ICA), with the goal of improving the specificity of EEG-fMRI analyses.

METHODS

We selected EEG-fMRI data from 10 focal epilepsy patients with a good quality EEG. IED amplitudes were calculated in an average reference montage. The fMRI data were decomposed by ICA and a deconvolution method identified IED-related components by detecting time courses with a significant HRF time-locked to the IEDs (F-test, p<0.05). Individual HRF amplitudes were then calculated for each IED. Components with a significant HRF/IED amplitude correlation (Spearman test, p<0.05) were compared to the presumed epileptogenic focus and to results of a general linear model (GLM) analysis.

RESULTS

In 7 patients, at least one IED-related component was concordant with the focus, but many IED-related components were at distant locations. When considering only components with a significant HRF/IED amplitude correlation, distant components could be discarded, significantly increasing the relative proportion of activated voxels in the focus (p=0.02). In the 3 patients without concordant IED-related components, no HRF/IED amplitude correlations were detected inside the brain. Integrating IED-related amplitudes in the GLM significantly improved fMRI signal modeling in the epileptogenic focus in 4 patients (p<0.05).

CONCLUSION

Activations in the epileptogenic focus appear to show significant correlations between HRF and IED amplitudes, unlike distant responses. These correlations could be integrated in the analysis to increase the specificity of EEG-fMRI studies in epilepsy.

Functional epileptic network in left mesial temporal lobe epilepsy detected using resting fMRI

The purpose of this study was to determine transient functional signal activity in a small, homogeneous group of left temporal lobe epilepsy (TLE) patients, without the use of EEG; and to use one of these activated regions to identify a possible epileptogenic network across the whole brain in this group. Resting functional MRI scanning was performed on five left TLE patients who underwent selective amygdalohippocampectomy resulting in seizure control and 10 healthy control subjects. Activation maps of functional signal peaks were calculated using a data-driven analysis, 2dTCA, across the group of patients. In addition to the expected region of activation in the left anterior hippocampus, the results of the 2dTCA analysis revealed activity in the bilateral insular cortex and default-mode network which are not commonly reported using fMRI, but are supported by other electrical and functional changes. The region of activation corresponding to the anterior hippocampal region of resection (presumably the epileptogenic region) was used as a seed region for fMRI functional connectivity analysis. This revealed increased negative connectivity in the patients as compared to controls across a network including thalamic, brainstem, frontal and parietal regions consistent with theories of inhibited function in subcortical and cortical structures during ictal propagation.

Independent component analysis reveals dynamic ictal BOLD responses in EEG-fMRI data from focal epilepsy patients

INTRODUCTION

Seizures occur rarely during EEG-fMRI acquisitions of epilepsy patients, but can potentially offer a better estimation of the epileptogenic zone than interictal activity. Independent component analysis (ICA) is a data-driven method that imposes minimal constraints on the hemodynamic response function (HRF). In particular, the investigation of HRFs with clear peaks, but varying latency, may be used to differentiate the ictal focus from propagated activity.

METHODS

ICA was applied on ictal EEG-fMRI data from 15 patients. Components related to seizures were identified by fitting an HRF to the component time courses at the time of the ictal EEG events. HRFs with a clear peak were used to derive maps of significant BOLD responses and their associated peak delay. The results were then compared with those obtained from a general linear model (GLM) method. Concordance with the presumed epileptogenic focus was also assessed.

RESULTS

The ICA maps were significantly correlated with the GLM maps for each patient (Spearman's test, p<0.05). The ictal BOLD responses identified by ICA always included the presumed epileptogenic zone, but were also more widespread, accounting for 20.3% of the brain volume on average. The method provided a classification of the components as a function of peak delay. BOLD response clusters associated with early HRF peaks were concordant with the suspected epileptogenic focus, while subsequent HRF peaks may correspond to ictal propagation.

CONCLUSION

ICA applied to EEG-fMRI can detect areas of significant BOLD response to ictal events without having to predefine an HRF. By estimating the HRF peak time in each identified region, the method could also potentially provide a dynamic analysis of ictal BOLD responses, distinguishing onset from propagated activity.