Variability of the hemodynamic response as a function of age and frequency of epileptic discharge in children with epilepsy

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.

fMRI functional networks for EEG source imaging

The brain exhibits temporally coherent networks (TCNs) involving numerous cortical and sub-cortical regions both during the rest state and during the performance of cognitive tasks. TCNs represent the interactions between different brain areas, and understanding such networks may facilitate electroencephalography (EEG) source estimation. We propose a new method for examining TCNs using scalp EEG in conjunction with data obtained by functional magnetic resonance imaging (fMRI). In this approach, termed NEtwork based SOurce Imaging (NESOI), multiple TCNs derived from fMRI with independent component analysis (ICA) are used as the covariance priors of the EEG source reconstruction using Parametric Empirical Bayesian (PEB). In contrast to previous applications of PEB in EEG source imaging with smoothness or sparseness priors, TCNs play a fundamental role among the priors used by NESOI. NESOI achieves an efficient integration of the high temporal resolution EEG and TCN derived from the high spatial resolution fMRI. Using synthetic and real data, we directly compared the performance of NESOI with other distributed source inversion methods, with and without the use of fMRI priors. Our results indicated that NESOI is a potentially useful approach for EEG source imaging.

Incorporating FMRI functional networks in EEG source imaging: a Bayesian model comparison approach

Brain functional networks extracted from fMRI can improve the accuracy of EEG source localization. However, the coupling between EEG and fMRI remains poorly understood, i.e., whether fMRI networks provide information about the magnitude of neural activity, and whether neural sources demonstrate temporal correlations within each network. In this paper, we present an improved version of the NEtwork-based SOurce Imaging method (iNESOI) through Bayesian model comparison. Different models correspond to various matching between EEG and fMRI, and the appropriate one is selected by data with the model evidence. Synthetic and real data tests show that iNESOI has potential to select the appropriate fMRI priors to reach a better source reconstruction than some other typical approaches.

Independent component analysis (ICA) of generalized spike wave discharges in fMRI: comparison with general linear model-based EEG-fMRI

Most EEG-fMRI studies in epileptic patients are analyzed using the general linear model (GLM), which assumes a known hemodynamic response function (HRF) to epileptic spikes. In contrast, independent component analysis (ICA) can extract blood-oxygenation level dependent (BOLD) responses without imposing constraints on the HRF. ICA might therefore detect responses that vary in time and shape, and that are not detected in the GLM analysis. In this study, we compared the findings of ICA and GLM analyses in 12 patients with idiopathic generalized epilepsy. Spatial ICA was used to extract independent components from the functional magnetic resonance imaging (fMRI) data. A deconvolution method identified component time courses significantly related to the generalized EEG discharges, without constraining the shape of the HRF. The results from the ICA analysis were compared to those from the GLM analysis. GLM maps and ICA maps showed significant correlation and revealed BOLD responses in the thalamus, caudate nucleus, and default mode areas. In patients with a low rate of discharges per minute, the GLM analysis detected BOLD signal changes within the thalamus and the caudate nucleus that were not revealed by the ICA. In conclusion, ICA is a viable alternative technique to GLM analyses in EEG-fMRI studies related to generalized discharges. This study demonstrated that the BOLD response largely resembles the standard HRF and that GLM analysis is adequate. However, ICA is more dependent on a sufficient number of events than GLM analysis.

EEG-fMRI reveals activation of brainstem and thalamus in patients with Lennox-Gastaut syndrome

PURPOSE

Even if etiologies of Lennox-Gastaut syndrome (LGS) are diverse, the multiple causes converge into a final common pathway that results in this specific epilepsy phenotype. There is little knowledge, however, about neuronal networks that may be a part of this pathway.

METHODS

To investigate these networks, 11 children with LGS and 9 control children with multifocal epileptic activity were investigated using simultaneous recordings of EEG and functional MRI (EEG-fMRI) in a 3 Tesla scanner.

KEY FINDINGS

Individual and group analyses revealed significant activation of brainstem and thalamus (especially centromedian and anterior thalamus) associated with epileptiform discharges in patients with LGS. None of the patients with multifocal epileptic activity presented with the same hemodynamic activation pattern.

SIGNIFICANCE

Because brainstem activation has been associated with infantile spasms, which often evolve into LGS, and thalamus activation has been observed in patients with primary (idiopathic generalized syndromes) and secondary (focal epilepsies) bilateral synchrony, the described network in LGS may represent the common pathogenetic pathway of these different conditions.

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.

Cerebral hemodynamic responses to seizure in the mouse brain: simultaneous near-infrared spectroscopy-electroencephalography study

We applied near-infrared spectroscopy (NIRS) and electroencephalography (EEG) simultaneously on the mouse brain and investigated the hemodynamic response to epileptic episodes under pharmacologically driven seizure. gamma-butyrolactone (GBL) and 4-aminopyridine (4-AP) were applied to induce absence and tonic-clonic seizures, respectively. The epileptic episodes were identified from the single-channel EEG, and the corresponding hemodynamic changes in different regions of the brain were characterized by multichannel frequency-domain NIRS. Our results are the following: (i) the oxyhemoglobin level increases in the case of GBL-treated mice but not 4-AP-treated mice compared to the predrug state; (ii) the dominant response to each absence seizure is a decrease in deoxyhemolobin; (iii) the phase shift between oxy- and deoxyhemoglobin reduces in GBL-treated mice but no 4-AP-treated mice; and (iv) the spatial correlation of hemodynamics increased significantly in 4-AP-treated mice but not in GBL-treated mice. Our results shows that spatiotemporal tracking of cerebral hemodynamics using NIRS can be successfully applied to the mouse brain in conjunction with electrophysiological recording, which will support the study of molecular, cellular, and network origin of neurovascular coupling in vivo.

Independent component analysis as a model-free approach for the detection of BOLD changes related to epileptic spikes: a simulation study

EEG-fMRI in epileptic patients is commonly analyzed using the general linear model (GLM), which assumes a known hemodynamic response function (HRF) to epileptic spikes in the EEG. In contrast, independent component analysis (ICA) can extract Blood-Oxygenation Level Dependent (BOLD) responses without imposing constraints on the HRF. This technique was evaluated on data generated by superimposing artificial responses on real background fMRI signals. Simulations were run using a wide range of EEG spiking rates, HRF amplitudes, and activation regions. The data were decomposed by spatial ICA into independent components. A deconvolution method then identified component time courses significantly related to the simulated spikes, without constraining the shape of the HRF. Components matching the simulated activation regions ("concordant components") were found in 84.4% of simulations, while components at discordant locations were found in 12.2% of simulations. These false activations were often related to large artifacts that coincidentally occurred simultaneously with some of the random simulated spikes. The performance of the method depended closely on the simulation parameters; when the number of spikes was low, concordant components could only be identified when HRF amplitudes were large. Although ICA did not depend on the shape of the HRF, data processed with the GLM did not reveal the appropriate activation region when the HRF varied slightly from the canonical shape used in the model. ICA may thus be able to extract BOLD responses from EEG-fMRI data in epileptic patients, in a way that is robust to uncertainty and variability in the shape of the HRF.

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.