EEG background activity is abnormal in the temporal and inferior parietal cortex in benign rolandic epilepsy of childhood: a LORETA study

Disrupted functional connectivity patterns of the left inferior frontal gyrus subregions in benign childhood epilepsy with centrotemporal spikes

BACKGROUND

Benign epilepsy with centrotemporal spikes (BECTS) is one of the most common pediatric epileptic syndromes. Recent studies have shown that BECTS can lead to significant language dysfunction. Although research supports the role of the left inferior frontal gyrus (LIFG) in BECTS, it is unclear whether the subregions of the LIFG show different change patterns in patients with this syndrome.

METHODS

Using resting-state functional magnetic resonance imaging (fMRI) data in a group of 49 BECTS patients and 49 healthy controls, we investigated whether the BECTS patients show abnormal connectivity patterns of the LIFG subregions.

RESULTS

Compared with healthy controls, the BECTS patients exhibited higher connectivity between the following: the inferior frontal sulcus (IFS) and the right anterior cingulate cortex (ACC), and the ventral area 44 (A44v) region and the left hippocampus/parahippocampus. Also, a decreased connectivity was found between the IFS and the left inferior temporal gyrus (ITG). No other significant differences in functional connectivity were found in the other 4 functional subregions of the LIFG in the BECTS.

CONCLUSIONS

These findings provide evidence for BECTS-related functional connectivity patterns of the LIFG subregions and suggest that different subregions may be involved in different neural circuits associated with language function in the BECTS.

Source EEG reveals that Rolandic epilepsy is a regional epileptic encephalopathy

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Children with RE have fewer spindles but they have typical time–frequency features.

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Spindle deficits extend to multiple cortical regions in Rolandic epilepsy.

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Cognitive deficits are predicted by spindle rate in Rolandic epilepsy.

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Regional spindle rate predicts motor deficits better than Rolandic spindle deficit.

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Spindle features in RE identify a regional thalamocortical epileptic encephalopathy.

Rolandic epilepsy is the most common form of epileptic encephalopathy, characterized by sleep-potentiated inferior Rolandic epileptiform spikes, seizures, and cognitive deficits in school-age children that spontaneously resolve by adolescence. We recently identified a paucity of sleep spindles, physiological thalamocortical rhythms associated with sleep-dependent learning, in the Rolandic cortex during the active phase of this disease. Because spindles are generated in the thalamus and amplified through regional thalamocortical circuits, we hypothesized that: 1) deficits in spindle rate would involve but extend beyond the inferior Rolandic cortex in active epilepsy and 2) regional spindle deficits would better predict cognitive function than inferior Rolandic spindle deficits alone. To test these hypotheses, we obtained high-resolution MRI, high-density EEG recordings, and focused neuropsychological assessments in children with Rolandic epilepsy during active (n = 8, age 9–14.7 years, 3F) and resolved (seizure free for > 1 year, n = 10, age 10.3–16.7 years, 1F) stages of disease and age-matched controls (n = 8, age 8.9–14.5 years, 5F). Using a validated spindle detector applied to estimates of electrical source activity in 31 cortical regions, including the inferior Rolandic cortex, during stages 2 and 3 of non-rapid eye movement sleep, we compared spindle rates in each cortical region across groups. Among detected spindles, we compared spindle features (power, duration, coherence, bilateral synchrony) between groups. We then used regression models to examine the relationship between spindle rate and cognitive function (fine motor dexterity, phonological processing, attention, and intelligence, and a global measure of all functions). We found that spindle rate was reduced in the inferior Rolandic cortices in active but not resolved disease (active P = 0.007; resolved P = 0.2) compared to controls. Spindles in this region were less synchronous between hemispheres in the active group (P = 0.005; resolved P = 0.1) compared to controls; but there were no differences in spindle power, duration, or coherence between groups. Compared to controls, spindle rate in the active group was also reduced in the prefrontal, insular, superior temporal, and posterior parietal regions (i.e., “regional spindle rate”, P < 0.039 for all). Independent of group, regional spindle rate positively correlated with fine motor dexterity (P < 1e-3), attention (P = 0.02), intelligence (P = 0.04), and global cognitive performance (P < 1e-4). Compared to the inferior Rolandic spindle rate alone, models including regional spindle rate trended to improve prediction of global cognitive performance (P = 0.052), and markedly improved prediction of fine motor dexterity (P = 0.006). These results identify a spindle disruption in Rolandic epilepsy that extends beyond the epileptic cortex and a potential mechanistic explanation for the broad cognitive deficits that can be observed in this epileptic encephalopathy.

Electroencephalography source localization analysis in epileptic children during a visual working-memory task

We localize the sources of brain activity of children with epilepsy based on electroencephalograph (EEG) recordings acquired during a visual discrimination working memory task. For the numerical solution of the inverse problem, with the aid of age-specific MRI scans processed from a publicly available database, we use and compare three regularization numerical methods, namely the standardized low resolution brain electromagnetic tomography (sLORETA), the weighted minimum norm estimation (wMNE) and the dynamic statistical parametric mapping (dSPM). We show that all three methods provide the same spatio-temporal patterns of differences between the groups of epileptic and control children. In particular, our analysis reveals statistically significant differences between the two groups in regions of the parietal cortex indicating that these may serve as "biomarkers" for diagnostic purposes and ultimately localized treatment.

Changes in background electroencephalographic activity in benign childhood epilepsy with centrotemporal spikes after oxcarbazepine treatment: a standardized low-resolution brain electromagnetic tomography (sLORETA) study

Background

Several neuroimaging studies have reported neurophysiological alterations in patients with benign childhood epilepsy with centrotemporal spikes (BCECTS). However, reported outcomes have been inconsistent, and the progression of these changes in the brain remains unresolved. Moreover, background electroencephalography (EEG) in cases of BCECTS has not been performed often.

Methods

We investigated background EEG activity changes after six months of oxcarbazepine treatment to better understand the neurophysiological alterations and progression that occur in BCECTS. In 18 children with BCECTS, non-parametric statistical analyses using standardized low resolution brain electromagnetic tomography (sLORETA) were performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between untreated and treated conditions.

Results

Background EEG activity for the delta frequency band was significantly decreased in the fronto-temporal and limbic regions of the left hemisphere after oxcarbazepine treatment (threshold log-F-ratio = ±2.729, P < 0.01). The maximum current density difference was found in the parahippocampal gyrus of the left limbic lobe (Montreal Neurological Institute coordinate [x, y, z = 25, − 20, − 10], Brodmann area 28) (log-F-ratio = 3.081, P < 0.01).

Conclusions

Our results indicate the involvement of the fronto-temporal and limbic cortices in BCECTS, and limbic lobe involvement, including the parahippocampal gyrus, was noted. In addition to evidence of the involvement of the fronto-temporal and limbic cortices in BCECTS, this study also found that an antiepileptic drug could reduce the delta frequency activity of the background EEG in these regions.

The Clinical Spectrum of Benign Epilepsy with Centro-Temporal Spikes: a Challenge in Categorization and Predictability

Benign epilepsy with centro-temporal spikes (BECTS) is the most common type of focal epilepsy in children; it is age-dependent and presumably genetic. Traditionally, children with BECTS have a very good prognosis, even without medical treatment, and are thought to show no neurological symptoms or cognitive deficits. However, many previous studies have shown that BECTS can present with various clinical and electroencephalographic characteristics that are commonly associated with neuropsychological deficits, including linguistic, cognitive, and behavioral impairment. The degree of the neuropsychological deficits appears to depend on the sleep cycle and the localization of epileptiform discharges. Furthermore, based on neurobiological studies, a complex interplay between the processes of brain maturation and the involvement of genes that confer susceptibility may contribute to a variety of different childhood epileptic syndromes with various neuropsychological deficits. Thus, BECTS, atypical benign focal epilepsy during childhood, status epilepticus of BECTS, Landau-Kleffner syndrome, and epileptic encephalopathy with continuous spike-and-wave during sleep are all considered different entities, but are part of a single spectrum of disorders. In clinical practice, we have to consider BECTS as benign only when there are no or only mild neuropsychological deficits before medical treatment.

Local and Distant Dysregulation of Synchronization Around Interictal Spikes in BECTS

Objective: High Density electroencephalography (HD EEG) is the reference non-invasive technique to investigate the dynamics of neuronal networks in Benign Epilepsy with Centro-Temporal Spikes (BECTS). Analysis of local dynamic changes surrounding Interictal Epileptic Spikes (IES) might improve our knowledge of the mechanisms that propel neurons to the hypersynchronization of IES in BECTS. Transient distant changes in the dynamics of neurons populations may also interact with neuronal networks involved in various functions that are impaired in BECTS patients.

Methods: HD EEG (64 electrodes) of eight well-characterized BECTS patients (8 males; mean age: 7.2 years, range: 5–9 years) were analyzed. Unilateral IES were selected in 6 patients. They were bilateral and independent in 2 other patients. This resulted in a total of 10 groups of IES. Time-frequency analysis was performed on HD EEG epochs around the peak of the IES (±1000 ms), including phase-locked and non-phase-locked activities to the IES. The time frequency analyses were calculated for the frequencies between 4 and 200 Hz.

Results: Time-frequency analysis revealed two patterns of dysregulation of the synchronization between neuronal networks preceding and following hypersynchronization of interictal spikes (±400 ms) in the epileptogenic zone. Dysregulation consists of either desynchronization (n = 6) or oscillating synchronization (n = 4) (4–50 Hz) surrounding the IES. The 2 patients with bilateral IES exhibited only local desynchronization whatever the IES considered. Distant desynchronization in low frequencies within the same window occurs simultaneously in bilateral frontal, temporal and occipital areas (n = 7).

Significance: Using time-frequency analysis of HD EEG data in a well-defined population of BECTS, we demonstrated repeated complex changes in the dynamics of neuronal networks not only during, but also, before and after the IES. In the epileptogenic zone, our results found more complex reorganization of the local network than initially thought. In line with previous results obtained at a microscopic or macroscopic level, these changes suggested the variability strategies of neuronal assemblies to raise IES. Distant changes from the epileptogenic zone in desynchronization observed in the same time window suggested interactions between larger embedded networks and opened new avenues about their possible role in the underlying mechanism leading to cognitive deficits.

Resting-state oscillatory dynamics in sensorimotor cortex in benign epilepsy with centro-temporal spikes and typical brain development

Benign Epilepsy with Centro-Temporal Spikes (BECTS) is a common childhood epilepsy associated with deficits in several neurocognitive domains. Neurophysiological studies in BECTS often focus on centro-temporal spikes, but these correlate poorly with morphology and cognitive impairments. To better understand the neural profile of BECTS, we studied background brain oscillations, thought to be integrally involved in neural network communication, in sensorimotor areas. We used independent component analysis of temporally correlated sources on magnetoencephalography recordings to assess sensorimotor resting-state network activity in BECTS patients and typically developing controls. We also investigated the variability of oscillatory characteristics within focal primary motor cortex (M1), localized with a separate finger abduction task. We hypothesized that background oscillations would differ between patients and controls in the sensorimotor network but not elsewhere, especially in the beta band (13-30 Hz) because of its role in network communication and motor processing. The results support our hypothesis: in the sensorimotor network, patients had a greater variability in oscillatory amplitude compared to controls, whereas there was no difference in the visual network. Network measures did not correlate with age. The coefficient of variation of resting M1 peak frequency correlated negatively with age in the beta band only, and was greater than average for a number of patients. Our results point toward a "disorganized" functional sensorimotor network in BECTS, supporting a neurodevelopmental delay in sensorimotor cortex. Our findings further suggest that investigating the variability of oscillatory peak frequency may be a useful tool to investigate deficits of disorganization in neurodevelopmental disorders.

Remission of benign epilepsy with rolandic spikes: an EEG-based connectivity study at the onset of the disease and at remission

PURPOSE

The neuronal mechanisms of remission of epilepsy are not known. Based on the principles of the "network theory of epilepsy" we postulated the existence of abnormal cortico-cortical interactions at the onset of epilepsy (Hypothesis-1), and postulated that remission is associated with the decrease or disappearance of the abnormal quantitative EEG findings (Hypothesis-2).

METHODS

Four children with benign epilepsy with rolandic sharp waves (BERS) were investigated. 21-channel EEG was recorded at the onset of the disease (Setting No. 1) and in remission (Setting No. 2). Local EEG synchronization was estimated by LORETA (low resolution electromagnetic tomography). Remote EEG synchronization (intra-hemispheric, cortico-cortical EEG functional connectivity, EEGfC) was computed by the LSC (LORETA Source Correlation) method, among 23 regions of interest (ROI) in both hemispheres. Both local and remote EEG synchronization were evaluated in very narrow frequency bands of 1Hz bandwidth (VNB), from 1 to 25Hz.

RESULTS

Individual results were presented. Abnormal but topographically very dissimilar LORETA and LSC findings were found at the onset of the disease. The disappearance of the initial abnormalities was found in Setting No. 2. An unforeseen finding was the presence of abnormal EEGfC results in Setting No. 2.

DISCUSSION

The authors confirmed both hypotheses. The dissimilarity of the initial abnormalities is in accord with the network concept of epilepsy and the etiology of BERS. The disappearance of the initial abnormalities reflects "normalization" of network dynamics while the emergence of new EEGfC abnormalities is interpreted as "compensation".

CONCLUSION

EEG-based local and remote connectivity (EEGfC) are appropriate tools to describe network dynamics in the active state of BERS and in remission.