Network perspectives on epilepsy using EEG/MEG source connectivity

The evolution of EEG/MEG source connectivity is both, a promising, and controversial advance in the characterization of epileptic brain activity. In this narrative review we elucidate the potential of this technology to provide an intuitive view of the epileptic network at its origin, the different brain regions involved in the epilepsy, without the limitation of electrodes at the scalp level. Several studies have confirmed the added value of using source connectivity to localize the seizure onset zone and irritative zone or to quantify the propagation of epileptic activity over time. It has been shown in pilot studies that source connectivity has the potential to obtain prognostic correlates, to assist in the diagnosis of the epilepsy type even in the absence of visually noticeable epileptic activity in the EEG/MEG, and to predict treatment outcome. Nevertheless, prospective validation studies in large and heterogeneous patient cohorts are still lacking and are needed to bring these techniques into clinical use. Moreover, the methodological approach is challenging, with several poorly examined parameters that most likely impact the resulting network patterns. These fundamental challenges affect all potential applications of EEG/MEG source connectivity analysis, be it in a resting, spiking, or ictal state, and also its application to cognitive activation of the eloquent area in presurgical evaluation. However, such method can allow unique insights into physiological and pathological brain functions and have great potential in (clinical) neuroscience

EEG source connectivity to localize the seizure onset zone in patients with drug resistant epilepsy

Visual inspection of the EEG to determine the seizure onset zone (SOZ) in the context of the presurgical evaluation in epilepsy is time-consuming and often challenging or impossible. We offer an approach that uses EEG source imaging (ESI) in combination with functional connectivity analysis (FC) to localize the SOZ from ictal EEG. Ictal low-density-scalp EEG from 111 seizures in 27 patients who were rendered-seizure free after surgery was analyzed. For every seizure, ESI (LORETA) was applied on an artifact-free epoch selected around the seizure onset. Additionally, FC was applied on the reconstructed sources. We estimated the SOZ in two ways: (i)the source with highest power after ESI and (ii)the source with the most outgoing connections after ESI and FC. For both approaches, the distance between the estimated SOZ and the resected zone (RZ) of the patient were calculated. Using ESI alone, the SOZ was estimated inside the RZ in 31% of the seizures and within 10mm from the border of the RZ in 42%. For 18.5% of the patients, all seizures were estimated within 10mm of the RZ. Using ESI and FC, 72% of the seizures were estimated inside the RZ, and 94% within 10mm. For 85% of the patients, all seizures were estimated within 10mm of the RZ. FC provided a significant added value to ESI alone (p<0.001). ESI combined with subsequent FC is able to localize the SOZ in a non-invasive way with high accuracy. Therefore it could be a valuable tool in the presurgical evaluation of epilepsy

Dynamic imaging of coherent sources reveals different network connectivity underlying the generation and perpetuation of epileptic seizures

The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone) and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS), an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity) between coherent sources was investigated using the renormalized partial directed coherence (RPDC) method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis

Multimodal imaging of human brain activity: rational, biophysical aspects and modes of integration

Until relatively recently the vast majority of imaging and electrophysiological studies of human brain activity have relied on single-modality measurements usually correlated with readily observable or experimentally modified behavioural or brain state patterns. Multi-modal imaging is the concept of bringing together observations or measurements from different instruments. We discuss the aims of multi-modal imaging and the ways in which it can be accomplished using representative applications. Given the importance of haemodynamic and electrophysiological signals in current multi-modal imaging applications, we also review some of the basic physiology relevant to understanding their relationship

Causal hierarchy within the thalamo-cortical network in spike and wave discharges

Background: Generalised spike wave (GSW) discharges are the electroencephalographic (EEG) hallmark of absence seizures, clinically characterised by a transitory interruption of ongoing activities and impaired consciousness, occurring during states of reduced awareness. Several theories have been proposed to explain the pathophysiology of GSW discharges and the role of thalamus and cortex as generators. In this work we extend the existing theories by hypothesizing a role for the precuneus, a brain region neglected in previous works on GSW generation but already known to be linked to consciousness and awareness. We analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between precuneus, thalamus and prefrontal cortex in patients with GSW discharges. Methodology and Principal Findings: We analysed fMRI data from seven patients affected by Idiopathic Generalized Epilepsy (IGE) with frequent GSW discharges and significant GSW-correlated haemodynamic signal changes in the thalamus, the prefrontal cortex and the precuneus. Using DCM we assessed their effective connectivity, i.e. which region drives another region. Three dynamic causal models were constructed: GSW was modelled as autonomous input to the thalamus (model A), ventromedial prefrontal cortex (model B), and precuneus (model C). Bayesian model comparison revealed Model C (GSW as autonomous input to precuneus), to be the best in 5 patients while model A prevailed in two cases. At the group level model C dominated and at the population-level the p value of model C was ∼1. Conclusion: Our results provide strong evidence that activity in the precuneus gates GSW discharges in the thalamo-(fronto) cortical network. This study is the first demonstration of a causal link between haemodynamic changes in the precuneus - an index of awareness - and the occurrence of pathological discharges in epilepsy. © 2009 Vaudano et al

Seizure onset zone localization from ictal high-density EEG in five patients

Rationale Because epilepsy is a network disease, localization of the exact seizure onset zone (SOZ) is difficult because the epileptic activity can spread to other regions within milliseconds. Functional connectivity metrics quantify how the activity in different brain regions is interrelated. In the past, it has been shown that functional connectivity analysis of ictal intracranial EEG (icEEG) recordings can help with SOZ localization in patients with focal epilepsy (van Mierlo et al., 2014). However, it would be of high clinical value to be able to localize the SOZ based on non-invasive ictal EEG recordings to optimize the icEEG implantation scheme or to avoid invasive monitoring and improve surgical outcome. In this work, we propose an approach to localize the SOZ based on non-invasive ictal high-density EEG (hd-EEG) recordings. Methods We considered retrospective ictal epochs of 2.4 s up to 10 s recorded with hd-EEG (256 electrodes) in five patients who were rendered seizure free after surgery. From the 256 electrodes, the facial electrodes were removed, resulting in a subset of 204 electrodes. A 28-channel subset was constructed to mimic a low-density (ld) electrode setup used in clinical practice. EEG source imaging (ESI) was performed in the CARTOOL software using an individual head model (LSMAC) to calculate the forward model (Brunet et al., 2011). We considered sources uniformly distributed in the brain with a spacing of 5 mm. LORETA (Pascal-Marqui et al., 1994) was used as inverse solution method. In each cluster of activity, we determined a central source based on the criterion that there was no higher power in its neighborhood. The time-varying connectivity pattern between the time series of these sources was calculated using Granger causality (van Mierlo et al., 2013). This was done in the frequency band containing the fundamental seizure frequency, 3-30Hz. The outdegree of each selected dipole was determined as the sum over time of all outgoing connections. Around the dipole with the highest outdegree, we determined a region of dipoles that had a power that was at least 90% of the power of the center dipole. This region was then considered as the SOZ. Results We were able to successfully localize the driver in the resected zone for all patients based on ESI followed by connectivity analysis of the hd-EEG (mean localization error (LE) = 0 mm). If we chose the cluster with the highest power as driver, the mean LE was 59.69 mm. For the ld-EEG, ESI followed by connectivity analysis resulted in a mean LE of 23.30 mm and when selecting the cluster with the highest power as driver, the mean LE was 31.21 mm. Conclusions ESI in combination with connectivity analysis can successfully localize the SOZ in non-invasive ictal hd-EEG recordings and greatly outperforms localization based on power. For ld-EEG recordings, the localization error remains significant but still outperforms localization based on power. This could have important clinical relevance for the presurgical evaluation in focal epilepsy

Physiological consequences of abnormal connectivity in a developmental epilepsy

Objective Many forms of epilepsy are associated with aberrant neuronal connections, but the relationship between such pathological connectivity and the underlying physiological predisposition to seizures is unclear. We sought to characterize the cortical excitability profile of a developmental form of epilepsy known to have structural and functional connectivity abnormalities. Methods We employed transcranial magnetic stimulation (TMS) with simultaneous electroencephalographic (EEG) recording in 8 patients with epilepsy from periventricular nodular heterotopia and matched healthy controls. We used connectivity imaging findings to guide TMS targeting and compared the evoked responses to single-pulse stimulation from different cortical regions. Results Heterotopia patients with active epilepsy demonstrated a relatively augmented late cortical response that was greater than that of matched controls. This abnormality was specific to cortical regions with connectivity to subcortical heterotopic gray matter. Topographic mapping of the late response differences showed distributed cortical networks that were not limited to the stimulation site, and source analysis in 1 subject revealed that the generator of abnormal TMS-evoked activity overlapped with the spike and seizure onset zone. Interpretation Our findings indicate that patients with epilepsy from gray matter heterotopia have altered cortical physiology consistent with hyperexcitability, and that this abnormality is specifically linked to the presence of aberrant connectivity. These results support the idea that TMS-EEG could be a useful biomarker in epilepsy in gray matter heterotopia, expand our understanding of circuit mechanisms of epileptogenesis, and have potential implications for therapeutic neuromodulation in similar epileptic conditions associated with deep lesions

Seizure-onset mapping based on time-variant multivariate functional connectivity analysis of high-dimensional intracranial EEG : a Kalman filter approach

The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (< 60). The aim of this study was to test two Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach

White Matter Abnormalities in Patients with Treatment-Resistant Genetic Generalized Epilepsies.

BACKGROUND Genetic generalized epilepsies (GGEs) are associated with microstructural brain abnormalities that can be evaluated with diffusion tensor imaging (DTI). Available studies on GGEs have conflicting results. Our primary goal was to compare the white matter structure in a cohort of patients with video/EEG-confirmed GGEs to healthy controls (HCs). Our secondary goal was to assess the potential effect of age at GGE onset on the white matter structure. MATERIAL AND METHODS A convenience sample of 23 patients with well-characterized treatment-resistant GGEs (13 female) was compared to 23 HCs. All participants received MRI at 3T. DTI indices, including fractional anisotropy (FA) and mean diffusivity (MD), were compared between groups using Tract-Based Spatial Statistics (TBSS). RESULTS After controlling for differences between groups, abnormalities in DTI parameters were observed in patients with GGEs, including decreases in functional anisotropy (FA) in the hemispheric (left&gt;right) and brain stem white matter. The examination of the effect of age at GGE onset on the white matter integrity revealed a significant negative correlation in the left parietal white matter region FA (R=-0.504; p=0.017); similar trends were observed in the white matter underlying left motor cortex (R=-0.357; p=0.103) and left posterior limb of the internal capsule (R=-0.319; p=0.148). CONCLUSIONS Our study confirms the presence of widespread white matter abnormalities in patients with GGEs and provides evidence that the age at GGE onset may have an important effect on white matter integrity