Firas Fahoum

Widespread epileptic networks in focal epilepsies: EEG‐fMRI study

Purpose:  To assess the extent of brain involvement during focal epileptic activity, we studied patterns of cortical and subcortical metabolic changes coinciding with interictal epileptic discharges (IEDs) using group analysis of simultaneous electroencephalography and functional magnetic resonance imaging (EEG‐fMRI) scans in patients with focal epilepsy.

Electroencephalography/functional magnetic resonance imaging responses help predict surgical outcome in focal epilepsy

Simultaneous electroencephalography/functional magnetic resonance imaging (EEG/fMRI) recording can noninvasively map in the whole brain the hemodynamic response following an interictal epileptic discharge. EEG/fMRI is gaining interest as a presurgical evaluation tool. This study aims to determine how hemodynamic responses related to epileptic activity can help predict surgical outcome in patients considered for epilepsy surgery.

Epileptic Discharges Affect the Default Mode Network – fMRI and Intracerebral EEG Evidence

Functional neuroimaging studies of epilepsy patients often show, at the time of epileptic activity, deactivation in default mode network (DMN) regions, which is hypothesized to reflect altered consciousness. We aimed to study the metabolic and electrophysiological correlates of these changes in the DMN regions. We studied six epilepsy patients that underwent scalp EEG-fMRI and later stereotaxic intracerebral EEG (SEEG) sampling regions of DMN (posterior cingulate cortex, Pre-cuneus, inferior parietal lobule, medial prefrontal cortex and dorsolateral frontal cortex) as well as non-DMN regions. SEEG recordings were subject to frequency analyses comparing sections with interictal epileptic discharges (IED) to IED-free baselines in the IED-generating region, DMN and non-DMN regions. EEG-fMRI and SEEG were obtained at rest. During IEDs, EEG-fMRI demonstrated deactivation in various DMN nodes in 5 of 6 patients, most frequently the pre-cuneus and inferior parietal lobule, and less frequently the other DMN nodes. SEEG analyses demonstrated decrease in gamma power (50–150 Hz), and increase in the power of lower frequencies (<30 Hz) at times of IEDs, in at least one DMN node in all patients. These changes were not apparent in the non-DMN regions. We demonstrate that, at the time of IEDs, DMN regions decrease their metabolic demand and undergo an EEG change consisting of decreased gamma and increased lower frequencies. These findings, specific to DMN regions, confirm in a pathological condition a direct relationship between DMN BOLD activity and EEG activity. They indicate that epileptic activity affects the DMN, and therefore may momentarily reduce the consciousness level and cognitive reserve.

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 patients diagnostic. It may therefore be possible, at least when spikes are infrequent, to detect their BOLD manifestations without having to record the EEG.

Resting-State Connectivity of the Sustained Attention Network Correlates with Disease Duration in Idiopathic Generalized Epilepsy

Introduction In idiopathic generalized epilepsy (IGE), a normal electroencephalogram between generalized spike and wave (GSW) discharges is believed to reflect normal brain function. However, some studies indicate that even excluding GSW-related errors, IGE patients perform poorly on sustained attention task, the deficit being worse as a function of disease duration. We hypothesized that at least in a subset of structures which are normally involved in sustained attention, resting-state functional connectivity (FC) is different in IGE patients compared to controls and that some of the changes are related to disease duration. Method Seeds were selected based on a sustained attention study in controls. Resting-state functional magnetic resonance imaging (fMRI) data was obtained from 14 IGE patients and 14 matched controls. After physiological noise removal, the mean time-series of each seed was used as a regressor in a general linear model to detect regions that showed correlation with the seed. In patients, duration factor was defined based on epilepsy duration. Between-group differences weighted by the duration factor were evaluated with mixed-effects model. Correlation was then evaluated in IGE patients between the FC, averaged over each significant cluster, and the duration factor. Results Eight of 18 seeds showed significant difference in FC across groups. However, only for seeds in the medial superior frontal and precentral gyri and in the medial prefrontal area, average FC taken over significant clusters showed high correlation with the duration factor. These 3 seeds showed changes in FC respectively with the premotor and superior frontal gyrus, the dorsal premotor, and the supplementary motor area plus precentral gyrus. Conclusion Alterations of FC in IGE patients are not limited to the frontal areas. However, as indicated by specificity analysis, patients with long history of disease show changes in FC mainly within the frontal areas.

Specific resting-state brain networks in mesial temporal lobe epilepsy

We studied with functional magnetic resonance imaging (fMRI) differences in resting-state networks between patients with mesial temporal lobe epilepsy (MTLE) and healthy subjects. To avoid any a priori hypothesis, we use a data-driven analysis assessing differences between groups independently of structures involved. Shared and specific independent component analysis (SSICA) is an exploratory method based on independent component analysis, which performs between-group network comparison. It extracts and classifies components (networks) in those common between groups and those specific to one group. Resting fMRI data were collected from 10 healthy subjects and 10 MTLE patients. SSICA was applied multiple times with altered initializations and different numbers of specific components. This resulted in many components specific to patients and to controls. Spatial clustering identified the reliable resting-state networks among all specific components in each group. For each reliable specific network, power spectrum analysis was performed on reconstructed time-series to estimate connectivity in each group and differences between groups. Two reliable networks, corresponding to statistically significant clusters robustly detected with clustering were labeled as specific to MTLE and one as specific to the control group. The most reliable MTLE network included hippocampus and amygdala bilaterally. The other MTLE network included the postcentral gyri and temporal poles. The control-specific network included bilateral precuneus, anterior cingulate, thalamus, and parahippocampal gyrus. Results indicated that the two MTLE networks show increased connectivity in patients, whereas the control-specific network shows decreased connectivity in patients. Our findings complement results from seed-based connectivity analysis (1). The pattern of changes in connectivity between mesial temporal lobe structures and other areas may help us understand the cognitive impairments often reported in patients with MTLE.

Epileptic scalp ripples are associated with corticothalamic BOLD changes

Interictal high frequency oscillations (HFOs) in the 40–200 Hz range have been identified in scalp electroencephalography (EEG) recordings of patients with focal epilepsy. HFOs usually co‐occur with interictal epileptiform discharges (IEDs), and are specific and accurate markers for the epileptic focus, but the brain regions involved when HFOs are generated are unknown. We investigated this question with combined EEG–functional magnetic resonance imaging (fMRI), measuring the blood oxygenation level–dependent (BOLD) signal, and examined HFOs in the gamma (40–80 Hz) and ripple (80–200 Hz) bands.

Limits of 2D-TCA in detecting BOLD responses to epileptic activity.

Two-dimensional temporal clustering analysis (2D-TCA) is a relatively new functional MRI (fMRI) based technique that breaks blood oxygen level dependent activity into separate components based on timing and has shown potential for localizing epileptic activity independently of electroencephalography (EEG). 2D-TCA has only been applied to detect epileptic activity in a few studies and its limits in detecting activity of various forms (i.e. activation size, amplitude, and frequency) have not been investigated. This study evaluated 2D-TCAs ability to detect various forms of both simulated epileptic activity and EEG-fMRI activity detected in patients. When applied to simulated data, 2D-TCA consistently detected activity in 6min runs containing 5 spikes/run, 10 spikes/run, and one 5s long event with hemodynamic response function amplitudes of at least 1.5%, 1.25%, and 1% above baseline respectively. When applied to patient data, while detection of interictal spikes was inconsistent, 2D-TCA consistently produced results similar to those obtained by EEG-fMRI when at least 2 prolonged interictal events (a few seconds each) occurred during the run. However, even for such cases it was determined that 2D-TCA can only be used to validate localization by other means or to create hypotheses as to where activity may occur, as it also detects changes not caused by epileptic activity.

Contributions of EEG-fMRI to Assessing the Epileptogenicity of Focal Cortical Dysplasia

Purpose: To examine the ability of the BOLD response to EEG spikes to assess the epileptogenicity of the lesion in patients with focal cortical dysplasia (FCD). Method: Patients with focal epilepsy and FCD who underwent 3T EEG-fMRI from 2006 to 2010 were included. Diagnosis of FCD was based on neuroradiology (MRI+), or histopathology in MRI-negative cases (MRI−). Patients underwent 120 min EEG-fMRI recording session. Spikes similar to those recorded outside the scanner were marked in the filtered EEG. The lesion (in MRI+) or the removed cortex (in MRI−) was marked on the anatomical T1 sequence, blindly to the BOLD response, after reviewing the FLAIR images. For each BOLD response we assessed the concordance with the spike field and with the lesion in MRI+ or the removed cortex in MRI−. BOLD responses were considered “concordant” if the maximal t-value was inside the marking. Follow-up after resection was used as gold-standard. Results: Twenty patients were included (13 MRI+, 7 MRI−), but in seven the EEG was not active or there were artifacts during acquisition. In all 13 studied patients, at least one BOLD response was concordant with the spike field; in 9/13 (69%) at least one BOLD response was concordant with the lesion: in 6/7 (86%) MRI+ and in 3/6 (50%) MRI− patients. Conclusions: Our study shows a high level of concordance between FCD and BOLD response. This data could provide useful information especially for MRI negative patients. Moreover, it shows in almost all FCD patients, a metabolic involvement of remote cortical or subcortical structures, corroborating the concept of epileptic network.