Neuronal networks in epileptic encephalopathies with CSWS.

OBJECTIVE: The aim of our study was to investigate the neuronal networks underlying background oscillations of epileptic encephalopathy with continuous spikes and waves during slow sleep (CSWS). METHODS: Sleep electroencephalography (EEG) studies before and after the treatment were investigated in 15 patients with CSWS. To investigate functional and effective connectivity within the network generating the delta activity in the background sleep EEG, the methods of dynamic imaging of coherent sources (DICS) and renormalized partial directed coherence (RPDC) were applied. RESULTS: Independent of etiology and severity of epilepsy, background EEG pattern in patients with CSWS before treatment is associated with the complex network of coherent sources in medial prefrontal cortex, somatosensory association cortex/posterior cingulate cortex, medial prefrontal cortex, middle temporal gyrus/parahippocampal gyrus/insular cortex, thalamus, and cerebellum. The analysis of information flow within this network revealed that the medial parietal cortex, the precuneus, and the thalamus act as central hubs, driving the information flow to other areas, especially to the temporal and frontal cortex. The described CSWS-specific pattern was no longer observed in patients with normalized sleep EEG. In addition, frequency of spiking showed a strong linear correlations with absolute source power, source coherence strength, and source RPDC strength at both time points: (1) Spike and wave index (SWI) versus absolute source power at EEG1 (r = 0.56; p = 0.008) and at EEG2 (r = 0.45; p = 0.009); (2) SWI versus source coherence strength at EEG1 (r = 0.71; p = 0.005) and at EEG2 (r = 0.52; p = 0.006); and (3) SWI versus source RPDC strength at EEG1 (r = 0.65; p = 0.003) and at EEG2 (r = 0.47; p = 0.009). SIGNIFICANCE: The leading role of the precuneus and thalamus in the hierarchical organization of the network underlying the background EEG points toward the significance of fluctuations of vigilance in the generation of CSWS. This hierarchical network organization appears to be specific for CSWS as it is resolved after successful treatment.

Neuronal networks in west syndrome as revealed by source analysis and renormalized partial directed coherence.

West syndrome is a severe epileptic encephalopathy of infancy with a poor developmental outcome. This syndrome is associated with the pathognomonic EEG feature of hypsarrhythmia. The aim of the study was to describe neuronal networks underlying hypsarrhythmia using the source analysis method (dynamic imaging of coherent sources or DICS) which represents an inverse solution algorithm in the frequency domain. In order to investigate the interaction within the detected network, a renormalized partial directed coherence (RPDC) method was also applied as a measure of the directionality of information flow between the source signals. Both DICS and RPDC were performed for EEG delta activity (1-4 Hz) in eight patients with West syndrome and in eight patients with partial epilepsies (control group). The brain area with the strongest power in the given frequency range was defined as the reference region. The coherence between this reference region and the entire brain was computed using DICS. After that, the RPDC was applied to the source signals estimated by DICS. The results of electrical source imaging were compared to results of a previous EEG-fMRI study which had been carried out using the same cohort of patients. As revealed by DICS, delta activity in hypsarrhythmia was associated with coherent sources in the occipital cortex (main source) as well as the parietal cortex, putamen, caudate nucleus and brainstem. In patients with partial epilepsies, delta activity could be attributed to sources in the occipital, parietal and sensory-motor cortex. In West syndrome, RPDC showed the strongest and most significant direction of ascending information flow from the brainstem towards the putamen and cerebral cortex. The neuronal network underlying hypsarrhythmia in this study resembles the network which was described in previous EEG-fMRI and PET studies with involvement of the brainstem, putamen and cortical regions in the generation of hypsarrhythmia. The RPDC suggests that brainstem could have a key role in the pathogenesis of West syndrome. This study supports the theory that hypsarrhythmia results from ascending brainstem pathways that project widely to basal ganglia and cerebral cortex.

Neuronal networks underlying ictal and subclinical discharges in childhood absence epilepsy.

Childhood absence epilepsy (CAE), involves 3 Hz generalized spikes and waves discharges (GSWDs) on the electroencephalogram (EEG), associated with ictal discharges (seizures) with clinical symptoms and impairment of consciousness and subclinical discharges without any objective clinical symptoms or impairment of consciousness. This study aims to comparatively characterize neuronal networks underlying absence seizures and subclinical discharges, using source localization and functional connectivity (FC), to better understand the pathophysiological mechanism of these discharges. Routine EEG data from 12 CAE patients, consisting of 45 ictal and 42 subclinical discharges were selected. Source localization was performed using the exact low-resolution electromagnetic tomography (eLORETA) algorithm, followed by FC based on the imaginary part of coherency. FC based on the thalamus as the seed of interest showed significant differences between ictal and subclinical GSWDs (p < 0.05). For delta (1-3 Hz) and alpha bands (8-12 Hz), the thalamus displayed stronger connectivity towards other brain regions for ictal GSWDs as compared to subclinical GSWDs. For delta band, the thalamus was strongly connected to the posterior cingulate cortex (PCC), precuneus, angular gyrus, supramarginal gyrus, parietal superior, and occipital mid-region for ictal GSWDs. The strong connections of the thalamus with other brain regions that are important for consciousness, and with components of the default mode network (DMN) suggest the severe impairment of consciousness in ictal GSWDs. However, for subclinical discharges, weaker connectivity between the thalamus and these brain regions may suggest the prevention of impairment of consciousness. This may benefit future therapeutic targets and improve the management of CAE patients.

EEG-Findings during long-term treatment with everolimus in TSC-associated and therapy-resistant epilepsies in children.

AIM: This prospective observational study evaluated the long-term EEG changes in children treated with everolimus (EVO) for refractory TSC-associated epilepsy. Changes in EEG-abnormalities were related to developmental outcomes. METHODS: Thirteen children treated with EVO were examined for EEG-recorded seizures and interictal epileptic discharges (IED) during a 72-hour-video-EEG-monitoring, which was performed at baseline and repeated at follow-up intervals of at least 9 months. Antiseizure medication was left unchanged for at least 27 months. Changes in cognitive developmental parameters were related to reduction of seizures and IED at the last monitoring. RESULTS: We found a significant reduction of recorded seizures and IED during sleep at the first as well as the last follow-up recording. The reduction of IED was especially prominent during sleep. For patients who continued for more than one monitoring under EVO (n = 8), number of seizures further decreased. In patients with developmental examination (n = 9), we observed that only (nearly) full cessation of IED was related to acquisition of new skills. DISCUSSION: In children with TSC, EVO was effective in reducing recorded seizures and IED; long-term EVO treatment led to a more pronounced reduction and an improvement of nocturnal IED even when the patient was initially not seizure-free. Cessation of IED in children with developmental improvement may point to the importance of healthy sleep for cognition.

Differentiating ictal/subclinical spikes and waves in childhood absence epilepsy by spectral and network analyses: A pilot study.

OBJECTIVE: Childhood absence epilepsy (CAE) is a disease with distinct seizure semiology and electroencephalographic (EEG) features. Differentiating ictal and subclinical generalized spikes and waves discharges (GSWDs) in the EEG is challenging, since they appear to be identical upon visual inspection. Here, spectral and functional connectivity (FC) analyses were applied to routine EEG data of CAE patients, to differentiate ictal and subclinical GSWDs. METHODS: Twelve CAE patients with both ictal and subclinical GSWDs were retrospectively selected for this study. The selected EEG epochs were subjected to frequency analysis in the range of 1-30 Hz. Further, FC analysis based on the imaginary part of coherency was used to determine sensor level networks. RESULTS: Delta, alpha and beta band frequencies during ictal GSWDs showed significantly higher power compared to subclinical GSWDs. FC showed significant network differences for all frequency bands, demonstrating weaker connectivity between channels during ictal GSWDs. CONCLUSION: Using spectral and FC analyses significant differences between ictal and subclinical GSWDs in CAE patients were detected, suggesting that these features could be used for machine learning classification purposes to improve EEG monitoring. SIGNIFICANCE: Identifying differences between ictal and subclinical GSWDs using routine EEG, may improve understanding of this syndrome and the management of patients with CAE.

Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter.

BACKGROUND AND OBJECTIVE: The human brain displays rich and complex patterns of interaction within and among brain networks that involve both cortical and subcortical brain regions. Due to the limited spatial resolution of surface electroencephalography (EEG), EEG source imaging is used to reconstruct brain sources and investigate their spatial and temporal dynamics. The majority of EEG source imaging methods fail to detect activity from subcortical brain structures. The reconstruction of subcortical sources is a challenging task because the signal from these sources is weakened and mixed with artifacts and other signals from cortical sources. In this proof-of-principle study we present a novel EEG source imaging method, the regional spatiotemporal Kalman filter (RSTKF), that can detect deep brain activity. METHODS: The regional spatiotemporal Kalman filter (RSTKF) is a generalization of the spatiotemporal Kalman filter (STKF), which allows for the characterization of different regional dynamics in the brain. It is based on state-space modeling with spatially heterogeneous dynamical noise variances, since models with spatial and temporal homogeneity fail to describe the dynamical complexity of brain activity. First, RSTKF is tested using simulated EEG data from sources in the frontal lobe, putamen, and thalamus. After that, it is applied to non-averaged interictal epileptic spikes from a presurgical epilepsy patient with focal epileptic activity in the amygdalo-hippocampal complex. The results of RSTKF are compared to those of low-resolution brain electromagnetic tomography (LORETA) and of standard STKF. RESULTS: Only RSTKF is successful in consistently and accurately localizing the sources in deep brain regions. Additionally, RSTKF shows improved spatial resolution compared to LORETA and STKF. CONCLUSIONS: RSTKF is a generalization of STKF that allows for accurate, focal, and consistent localization of sources, especially in the deeper brain areas. In contrast to standard source imaging methods, RSTKF may find application in the localization of the epileptogenic zone in deeper brain structures, such as mesial frontal and temporal lobe epilepsies, especially in EEG recordings for which no reliable averaged spike shape can be obtained due to lack of the necessary number of spikes required to reach a certain signal-to-noise ratio level after averaging.

Convulsions associated with gastroenteritis in the spectrum of benign focal epilepsies in infancy: 30 cases including four cases with ictal EEG recording.

Benign convulsions associated with gastroenteritis are now recognized as a clinical entity, characterized by an acute cluster of afebrile seizures during an episode of mild diarrhoea with excellent prognosis. We observed 30 children who each experienced at least two seizures associated with mild gastroenteritis. The inclusion criteria were: afebrile seizures during gastroenteritis, dehydration at ≤ 5%, normal neurological findings, normal psychomotor development and no underlying pathology according to laboratory and neuroimaging studies. Mean age was 21 months (range: 6-38). Familial history for epilepsy was positive in 3/30 (10%) and for febrile convulsions in 11/30 (36.6%). Seizure onset was mainly on the third day of gastroenteritis. Seizures were described as generalised by parents in 16/30 patients (53.3%). We directly observed seizures in 14/30 patients (47.7%), and the semiology was partial with secondary generalisation. Focal onset was confirmed in two patients by EEG and in two patients by video-EEG recording. Twenty of 30 patients (66.6%) received antiepileptic drugs during the acute phase. Ten patients (33.3%) received no treatment. During follow-up (mean duration: 53 months), one patient had an isolated afebrile seizure and two others a febrile seizure. At the end of follow-up, antiepileptic treatment was withdrawn for all but two patients. None developed epilepsy. Although the pathogenesis of this clinical entity is unknown, we hypothesize that mild gastroenteritis may provoke a transient brain dysfunction which in turn provokes seizures in children with genetically determined susceptibility.

Spatial projection as a preprocessing step for EEG source reconstruction using spatiotemporal Kalman filtering.

The reconstruction of brain sources from non-invasive electroencephalography (EEG) or magnetoencephalography (MEG) via source imaging can be distorted by information redundancy in case of high-resolution recordings. Dimensionality reduction approaches such as spatial projection may be used to alleviate this problem. In this proof-of-principle paper we apply spatial projection to solve the problem of information redundancy in case of source reconstruction via spatiotemporal Kalman filtering (STKF), which is based on state-space modeling. We compare two approaches for incorporating spatial projection into the STKF algorithm and select the best approach based on its performance in source localization with respect to accurate estimation of source location, lack of spurious sources, computational speed and small number of required optimization steps in state-space model parameter estimation. We use state-of-the-art simulated EEG data based on neuronal population models, for which the number and location of sources is known, to validate the source reconstruction results of the STKF. The incorporation of spatial projection into the STKF algorithm solved the problem of information redundancy, resulting in correct source localization with no spurious sources, and decreased the overall computational time in STKF analysis. The results help make STKF analyses of high-density EEG, MEG or simultaneous MEG-EEG data more feasible.

Source reconstruction via the spatiotemporal Kalman filter and LORETA from EEG time series with 32 or fewer electrodes.

The clinical routine of non-invasive electroencephalography (EEG) is usually performed with 8-40 electrodes, especially in long-term monitoring, infants or emergency care. There is a need in clinical and scientific brain imaging to develop inverse solution methods that can reconstruct brain sources from these low-density EEG recordings. In this proof-of-principle paper we investigate the performance of the spatiotemporal Kalman filter (STKF) in EEG source reconstruction with 9-, 19- and 32- electrodes. We used simulated EEG data of epileptic spikes generated from lateral frontal and lateral temporal brain sources using state-of-the-art neuronal population models. For validation of source reconstruction, we compared STKF results to the location of the simulated source and to the results of low-resolution brain electromagnetic tomography (LORETA) standard inverse solution. STKF consistently showed less localization bias compared to LORETA, especially when the number of electrodes was decreased. The results encourage further research into the application of the STKF in source reconstruction of brain activity from low-density EEG recordings.

The performance of the spatiotemporal Kalman filter and LORETA in seizure onset localization.

The assumption of spatial-smoothness is often used to solve the bioelectric inverse problem during electroencephalographic (EEG) source imaging, e.g., in low resolution electromagnetic tomography (LORETA). Since the EEG data show a temporal structure, the combination of the temporal-smoothness and the spatial-smoothness constraints may improve the solution of the EEG inverse problem. This study investigates the performance of the spatiotemporal Kalman filter (STKF) method, which is based on spatial and temporal smoothness, in the localization of a focal seizure's onset and compares its results to those of LORETA. The main finding of the study was that the STKF with an autoregressive model of order two significantly outperformed LORETA in the accuracy and consistency of the localization, provided that the source space consists of a whole-brain volumetric grid. In the future, these promising results will be confirmed using data from more patients and performing statistical analyses on the results. Furthermore, the effects of the temporal smoothness constraint will be studied using different types of focal seizures.

The choice of the source space and the Laplacian matrix in LORETA and the spatio-temporal Kalman filter EEG inverse methods.

The discretization of the brain and the definition of the Laplacian matrix influence the results of methods based on spatial and spatio-temporal smoothness, since the Laplacian operator is used to define the smoothness based on the neighborhood of each grid point. In this paper, the results of low resolution electromagnetic tomography (LORETA) and the spatiotemporal Kalman filter (STKF) are computed using, first, a greymatter source space with the standard definition of the Laplacian matrix and, second, using a whole-brain source space and a modified definition of the Laplacian matrix. Electroencephalographic (EEG) source imaging results of five inter-ictal spikes from a pre-surgical patient with epilepsy are used to validate the two aforementioned approaches. The results using the whole-brain source space and the modified definition of the Laplacian matrix were concentrated in a single source activation, stable, and concordant with the location of the focal cortical dysplasia (FCD) in the patient's brain compared with the results which use a grey-matter grid and the classical definition of the Laplacian matrix. This proof-of-concept study demonstrates a substantial improvement of source localization with both LORETA and STKF and constitutes a basis for further research in a large population of patients with epilepsy.

Neuronal Networks during Burst Suppression as Revealed by Source Analysis.

INTRODUCTION: Burst-suppression (BS) is an electroencephalography (EEG) pattern consisting of alternant periods of slow waves of high amplitude (burst) and periods of so called flat EEG (suppression). It is generally associated with coma of various etiologies (hypoxia, drug-related intoxication, hypothermia, and childhood encephalopathies, but also anesthesia). Animal studies suggest that both the cortex and the thalamus are involved in the generation of BS. However, very little is known about mechanisms of BS in humans. The aim of this study was to identify the neuronal network underlying both burst and suppression phases using source reconstruction and analysis of functional and effective connectivity in EEG. MATERIAL/METHODS: Dynamic imaging of coherent sources (DICS) was applied to EEG segments of 13 neonates and infants with burst and suppression EEG pattern. The brain area with the strongest power in the analyzed frequency (1-4 Hz) range was defined as the reference region. DICS was used to compute the coherence between this reference region and the entire brain. The renormalized partial directed coherence (RPDC) was used to describe the informational flow between the identified sources. RESULTS/CONCLUSION: Delta activity during the burst phases was associated with coherent sources in the thalamus and brainstem as well as bilateral sources in cortical regions mainly frontal and parietal, whereas suppression phases were associated with coherent sources only in cortical regions. Results of the RPDC analyses showed an upwards informational flow from the brainstem towards the thalamus and from the thalamus to cortical regions, which was absent during the suppression phases. These findings may support the theory that a "cortical deafferentiation" between the cortex and sub-cortical structures exists especially in suppression phases compared to burst phases in burst suppression EEGs. Such a deafferentiation may play a role in the poor neurological outcome of children with these encephalopathies.

Risk factors of cognitive outcome in patients with atypical benign partial epilepsy/pseudo-Lennox syndrome (ABPE/PLS) and continues spike and wave during sleep (CSWS).

BACKGROUND: Atypical benign partial epilepsy/pseudo-Lennox syndrome (ABPE/PLS) and continues spike and wave during sleep (CSWS) belong to a spectrum of idiopathic focal epilepsy syndromes ranging from benign Rolandic epilepsy to more severe seizure disorders, which are commonly characterized by the association of various epileptic seizure types, aggravation of spike-wave discharges during slow sleep, and cognitive and/or behavioral disturbances. The Aim of our study was to evaluate the risk factors that influence cognitive outcome in patients with ABPE/PLS and CSWS in a retrospective analysis. METHODS: Thirty patients fulfilled the diagnostic criteria for ABPE/PLS and 12 for CSWS and were chosen for the descriptive analysis. Cognitive achievement was evaluated according to psychological tests and school performances. RESULTS: Severe global and specific cognitive disturbances occurred almost regularly in cases of ABPE. Already at the time of epilepsy presentation the level of cognitive performance was lower than that of the normal population. At the time of disease presentation only 56% of the children had IQ within the standard range (≥85). We observed that the level of cognitive developmental delay did not change significantly during the disease process. We were not able to observe any statistically significant connection between the development of EEG abnormalities and cognitive development. The conclusion can be drawn that many patients exhibit cognitive impairment at disease presentation which is not affected significantly during the treatment process. Judging from the observed data, we assume that EEG abnormalities, duration of active epilepsy, and antiepileptic medication have less influence on the cognitive development than was previously assumed.

Altered information processing in children with focal epilepsies with and without intellectual disability.

The aim of this exploratory study was to investigate the relationship between focal interictal epileptiform discharges (IEDs), intellectual disability and cortical information processing in children with partial epilepsy. Two groups of patients--Group 1 (n = 9 patients) with focal IEDs and normal IQ and Group 2 (n = 10 patients) with focal IEDs and intellectual disability--were compared with 14 healthy control participants. A computerized choice reaction time task (go/no-go paradigm) was performed and event-related potentials (ERPs) were recorded. When an IED occurred during the period between the presentation of the stimulus and the response, the response was defined as a response with IED. Omission errors, commission errors and reaction time were evaluated in temporal relationship to IEDs. The Group 1 patients did not differ from the healthy children in neurophysiological functions and ERP amplitudes. The Group 2 children showed inferior Altered information processing in children with focal epilepsies with and without intellectual disability performances in verbal learning and memory, cognitive flexibility and selective attention, and were characterized by low ERP amplitudes compared with the epilepsy patients with normal IQ and the healthy children. We were not able to identify any significant relationship between IEDs and cognitive functions in either group of patients. Our findings suggest that the impact of IEDs on the overall intellectual abilities of epilepsy patients may not be as significant as previously thought. Moreover, it is likely that abnormalities in cognitive information processing as revealed by lower ERP amplitudes, occurrence of IEDs, and intellectual disabilities may represent common abnormal processes and may not be causally related to each other.

Electroencephalographic features in dravet syndrome: five-year follow-up study in 22 patients.

The aim of the study was to evaluate interictal electroencephalogram features in 22 patients with Dravet syndrome from the onset of the disease through the next 5 years. Electroencephalogram was abnormal in 5 patients (22.7%) at onset, and in 17 (77.3%) at the end of the study. Epileptiform abnormalities (focal, multifocal, or generalized) were seen in 6 patients at the onset and in 14 (27% vs 64%) at the end of the study. Photoparoxysmal response was present in 41% of patients at the end of follow-up. No statistical differences were found between mutated and nonmutated groups regarding evolution of background activity, interictal abnormalities, and presence of photoparoxysmal response. Electroencephalogram findings seemed to be age dependent, variable among different patients, and not influenced by the presence of sodium channel, voltage-gated, type I, alpha subunit (SCN1A) mutation. The lack of specific epileptiform abnormalities contributes to the difficulty of patients' management in Dravet syndrome.