Louise Tyvaert

Different structures involved during ictal and interictal epileptic activity in malformations of cortical development: an EEG-fMRI study

Malformations of cortical development (MCDs) are commonly complicated by intractable focal epilepsy. Epileptogenesis in these disorders is not well understood and may depend on the type of MCD. The cellular mechanisms involved in interictal and ictal events are notably different, and could be influenced independently by the type of pathology. We evaluated the relationship between interictal and ictal zones in eight patients with different types of MCD in order to better understand the generation of these activities: four had nodular heterotopia, two focal cortical dysplasia and two subcortical band heterotopia (double-cortex). We used the non-invasive EEG-fMRI technique to record simultaneously all cerebral structures with a high spatio-temporal resolution. We recorded interictal and ictal events during the same session. Ictal events were either electrical only or clinical with minimal motion. BOLD changes were found in the focal cortical dysplasia during interictal and ictal epileptiform events in the two patients with this disorder. Heterotopic and normal cortices were involved in BOLD changes during interictal and ictal events in the two patients with double cortex, but the maximum BOLD response was in the heterotopic band in both patients. Only two of the four patients with nodular heterotopia showed involvement of a nodule during interictal activity. During seizures, although BOLD changes affected the lesion in two patients, the maximum was always in the overlying cortex and never in the heterotopia. For two patients intracranial recordings were available and confirm our findings. The dysplastic cortex and the heterotopic cortex of band heterotopia were involved in interictal and seizure processes. Even if the nodular gray matter heterotopia may have the cellular substrate to produce interictal events, the often abnormal overlying cortex is more likely to be involved during the seizures. The non-invasive BOLD study of interictal and ictal events in MCD patients may help to understand the role of the lesion in epileptogenesis and also determine the potential surgical target.

EEG-fMRI Adding to standard evaluations of patients with nonlesional frontal lobe epilepsy

Objective: In patients with nonlesional frontal lobe epilepsy (FLE), the delineation of the epileptogenic zone is difficult. Therefore these patients are often not considered for surgery due to an unclear seizure focus. The aim of this study was to investigate whether EEG-fMRI can add useful information in the preoperative evaluation of these patients. Methods: Nine nonlesional FLE patients were studied with EEG-fMRI using a 3 T scanner. Spike-related blood oxygen level dependent (BOLD) signal changes were compared to the topography of the spikes and to PET and SPECT results if available. The structural MRIs were reviewed for subtle abnormalities in areas that showed BOLD responses. For operated patients, postoperative resection and histology were compared to BOLD responses. Results: Concordance between spike localization and positive BOLD response was found in 8 patients. PET and SPECT investigations corresponded with BOLD signal changes in 6 of 7 investigations. In 2 cases, reviewing the structural MRI guided by EEG-fMRI data resulted in considering a suspicious deep sulcus. Two patients were operated. In 1, the resected cortex corresponded with the suspicious sulcus and fMRI results and histology showed cortical dysplasia. In another, histology revealed an extended microdysgenesis not visible on structural MRI. EEG-fMRI had shown activation just adjacent to the resected pathologic area. Conclusions: Our study provides different types of support (topography, concordance with PET and SPECT, structural peculiarities, postoperative histology) that EEG-fMRI may help to delineate the epileptic focus in patients with nonlesional frontal lobe epilepsy, a challenging group in the preoperative evaluation.

Thalamic nuclei activity in idiopathic generalized epilepsy An EEG-fMRI study

Objective: Idiopathic generalized epilepsies (IGE) are characterized by specific EEG changes including 3- to 5-Hz generalized spike-and-wave discharges. The thalamus and its cortical interactions are considered essential in the production and propagation of spike-and-wave discharges. In animal studies, corticoreticular and limbic system property changes have been observed in absence seizures and during spike-and-wave discharges and suggest the involvement of different types of thalamic nuclei. With the development of deep brain stimulation in epilepsy, the role of the thalamic nuclei needs to be clarified in human IGE. Methods: Ten patients with IGE were recorded using 3T EEG-fMRI during spike-and-wave discharges. Hemodynamic response functions were calculated for 4 regions of interest corresponding to the anterior thalamic and centromedian and parafascicular (CM-Pf) nuclei of each thalamus. The time to peak of the hemodynamic response function was compared within thalamic structures (left compared to right) and between structures (anterior thalamic compared to CM-Pf nucleus). Results: CM-Pf and anterior nucleus are both activated during GSWDs. However, the positive time to peak in the CM-Pf (4.4 ± 2.5 s) occurred significantly earlier than in the anterior nucleus (7.6 ± 3.2 s). Conclusions: We demonstrated in humans the involvement of the centromedian and parafascicular part of the corticoreticular system and of the anterior nucleus part of the limbic system during generalized spike-and-wave discharges. The different time courses suggest that the posterior intralaminar nuclei may be involved in epileptic discharge initiation or early propagation, while the anterior nucleus may only play a role in its maintenance. These results may help to understand the clinical effect of deep brain stimulation within thalamic nuclei in intractable idiopathic generalized epilepsy patients.

Noninvasive Dynamic Imaging of Seizures in Epileptic Patients

Epileptic seizures are due to abnormal synchronized neuronal discharges. Techniques measuring electrical changes are commonly used to analyze seizures. Neuronal activity can be also defined by concomitant hemodynamic and metabolic changes. Simultaneous electroencephalogram (EEG)‐functional MRI (fMRI) measures noninvasively with a high‐spatial resolution BOLD changes during seizures in the whole brain. Until now, only a static image representing the whole seizure was provided. We report in 10 focal epilepsy patients a new approach to dynamic imaging of seizures including the BOLD time course of seizures and the identification of brain structures involved in seizure onset and discharge propagation. The first activation was observed in agreement with the expected location of the focus based on clinical and EEG data (three intracranial recordings), thus providing validity to this approach. The BOLD signal preceded ictal EEG changes in two cases. EEG‐fMRI may detect changes in smaller and deeper structures than scalp EEG, which can only record activity form superficial cortical areas. This method allowed us to demonstrate that seizure onset zone was limited to one structure, thus supporting the concept of epileptic focus, but that a complex neuronal network was involved during propagation. Deactivations were also found during seizures, usually appearing after the first activation in areas close or distant to the activated regions. Deactivations may correspond to actively inhibited regions or to functional disconnection from normally active regions. This new noninvasive approach should open the study of seizure generation and propagation mechanisms in the whole brain to groups of patients with focal epilepsies. Hum Brain Mapp, 2009.

Effects of fluctuating physiological rhythms during prolonged EEG-fMRI studies

OBJECTIVE We evaluated BOLD correlates of alertness fluctuations commonly seen during prolonged EEG-fMRI studies to better define the brain areas active at different phases of vigilance and to assess the contribution of these fluctuations to the BOLD signal. METHODS We evaluated BOLD changes specifically related to the main physiological EEG rhythms (alpha, beta, theta, delta, spindles) in 15 epilepsy patients with rare discharges (all the regressors were included in the same general linear model to improve specificity). RESULTS We found a consistent effect of spindles, alpha and theta. For alpha, BOLD was positively correlated in thalami and putamen, and negatively correlated in the occipital, parietal and frontal lobes. For theta, a negative correlation was found over the parietal, temporal and frontal lobes. Spindles were correlated with a positive BOLD in thalami and putamen. Rhythm regressors added as confounds in the fMRI analysis explained at least 5% of BOLD signal variance in 6.8+/-8.9% of gray matter voxels, a contribution which is of the order of typical changes in fMRI studies. CONCLUSION First, we found specific cerebral structures involved in each main EEG rhythm generation. Second, fluctuations of these rhythms following vigilance changes are responsible for noteworthy BOLD changes. SIGNIFICANCE Physiological EEG rhythms may be integrated to the analysis of EEG-fMRI in studies with fluctuation of alertness, to eliminate possible confounding factors.

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 (Spearmans 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.

Structures involved at the time of temporal lobe spikes revealed by interindividual group analysis of EEG/fMRI data.

Purpose:  We measured metabolic changes associated with temporal lobe (TL) spikes using combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). We selected 18 patients with temporal lobe epilepsy (TLE) who underwent a 2‐h simultaneous EEG–fMRI and had unilateral or bilateral independent TL spikes for interindividual group analysis, in order to identify consistent blood oxygenation level dependent (BOLD) responses to TL spikes.

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.

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 magnetic resonance imaging suggests automatization of the cortical response to inspiratory threshold loading in humans

Inspiratory threshold loading (ITL) induces cortical activation. It is sustained over time and is resistant to distraction, suggesting automaticity. We hypothesized that ITL-induced changes in cerebral activation may differ between single-breath ITL and continuous ITL, with differences resembling those observed after cortical automatization of motor tasks. We analyzed the brain blood oxygen level dependent (BOLD) signal of 11 naive healthy volunteers during 5 min of random, single-breath ITL and 5 min of continuous ITL. Single-breath ITL increased BOLD in many areas (premotor cortices, bilateral insula, cerebellum, reticular formation of the lateral mesencephalon) and decreased BOLD in regions co-localizing with the default mode network. Continuous ITL induced signal changes in a limited number of areas (supplementary motor area). These differences are comparable to those observed before and after overlearning of motor tasks. We conclude that the respiratory-related cortical activation observed in response to ITL is likely due to automated, attention-independent mechanisms. Also, ITL activates cortical circuits right from the first breath.