Changes of Ictal-Onset Epileptic Network Synchronicity in Childhood Absence Epilepsy: A Magnetoencephalography Study

Impact of interictal epileptiform discharges on brain network in self-limited epilepsy with centrotemporal spikes: A magnetoencephalography study

OBJECTIVE

This study aimed to investigate the differences on resting-state brain networks between the interictal epileptiform discharge (IED) group with self-limited epilepsy with centrotemporal spikes (SeLECTS), the non-IED group with SeLECTS, and the healthy control (HC) group.

METHODS

Patients were divided into the IED and non-IED group according to the presence or absence of IED during magnetoencephalography (MEG). We used Wechsler Intelligence Scale for Children, fourth edition (WISC-IV) to assess cognition in 30 children with SeLECTS and 15 HCs. Functional networks were constructed at the whole-brain level and graph theory (GT) analysis was used to quantify the topology of the brain network.

RESULTS

The IED group had the lowest cognitive function scores, followed by the non-IED group and then HCs. Our MEG results showed that the IED group had more dispersed functional connectivity (FC) in the 4-8 Hz frequency band, and more brain regions were involved compared to the other two groups. Furthermore, the IED group had fewer FC between the anterior and posterior brain regions in the 12-30 Hz frequency band. Both the IED group and the non-IED group had fewer FC between the anterior and posterior brain regions in the 80-250 Hz frequency band compared to the HC group. GT analysis showed that the IED group had a higher clustering coefficient compared to the HC group and a higher degree compared to the non-IED group in the 80-250 Hz frequency band. The non-IED group had a lower path length in the 30-80 Hz frequency band compared to the HC group.

CONCLUSIONS

The study data obtained in this study suggested that intrinsic neural activity was frequency-dependent and that FC networks of the IED group and the non-IED group underwent changes in different frequency bands. These network-related changes may contribute to cognitive dysfunction in children with SeLECTS.

Alternations of neuromagnetic activity across neurocognitive core networks among benign childhood epilepsy with centrotemporal spikes: A multi-frequency MEG study

Objective

We aimed to investigate the alternations of neuromagnetic activity across neurocognitive core networks among early untreated children having benign childhood epilepsy with centrotemporal spikes (BECTS).

Methods

We recorded the Magnetoencephalography (MEG) resting-state data from 48 untreated children having BECTS and 24 healthy children. The fourth edition of the Wechsler Intelligence Scale for Children (WISC-IV) was utilized to divide the children with BECTS into two groups: the cognitive impairment (CI) group with a full-scale intelligence quotient (FSIQ) of < 90 and the cognitive non-impairment (CNI) group with an FSIQ of > 90. We selected 26 bilateral cognitive-related regions of interest based on the triple network model. The neurocognitive core network spectral power was estimated using a minimum norm estimate (MNE).

Results

In the CNI group, the spectral power inside the bilateral anterior cingulate cortex (ACC) and the bilateral caudal middle frontal cortex (CMF) enhanced within the delta band and reduced within the alpha band. Both the CI and the CNI group demonstrated enhanced spectral power inside the bilateral posterior cingulate cortex (PCC), bilateral precuneus (PCu) region, bilateral superior and middle temporal cortex, bilateral inferior parietal lobe (IPL), and bilateral supramarginal cortex (SM) region in the delta band. Moreover, there was decreased spectral power in the alpha band. In addition, there were consistent changes in the high-frequency spectrum (> 90 Hz). The spectral power density within the insula cortex (IC), superior temporal cortex (ST), middle temporal cortex (MT), and parahippocampal cortex (PaH) also decreased. Therefore, studying high-frequency activity could lead to a new understanding of the pathogenesis of BECTS.

Conclusion

The alternations of spectral power among neurocognitive core networks could account for CI among early untreated children having BECTS. The dynamic properties of spectral power in different frequency bands could behave as biomarkers for diagnosing new BECTS.

Temporal and spatial dynamic propagation of electroencephalogram by combining power spectral and synchronization in childhood absence epilepsy

Objective

During the transition from normal to seizure and then to termination, electroencephalography (EEG) signals have complex changes in time-frequency-spatial characteristics. The quantitative analysis of EEG characteristics and the exploration of their dynamic propagation in this paper would help to provide new biomarkers for distinguishing between pre-ictal and inter-ictal states and to better understand the seizure mechanisms.

Methods

Thirty-three children with absence epilepsy were investigated with EEG signals. Power spectral and synchronization were combined to provide the time-frequency-spatial characteristics of EEG and analyze the spatial distribution and propagation of EEG in the brain with topographic maps. To understand the mechanism of spatial-temporal evolution, we compared inter-ictal, pre-ictal, and ictal states in EEG power spectral and synchronization network and its rhythms in each frequency band.

Results

Power, frequency, and spatial synchronization are all enhanced during the absence seizures to jointly dominate the epilepsy process. We confirmed that a rapid diffusion at the onset accompanied by the frontal region predominance exists. The EEG power rapidly bursts in 2–4 Hz through the whole brain within a few seconds after the onset. This spatiotemporal evolution is associated with spatial diffusion and brain regions interaction, with a similar pattern, increasing first and then decreasing, in both the diffusion of the EEG power and the connectivity of the brain network during the childhood absence epilepsy (CAE) seizures. Compared with the inter-ictal group, we observed increases in power of delta and theta rhythms in the pre-ictal group (P < 0.05). Meanwhile, the synchronization of delta rhythm decreased while that of alpha rhythm enhanced.

Conclusion

The initiation and propagation of CAE seizures are related to the abnormal discharge diffusion and the synchronization network. During the seizures, brain activity is completely changed with the main component delta rhythm. Furthermore, this article demonstrated for the first time that alpha inhibition, which is consistent with the brain’s feedback regulation mechanism, is caused by the enhancement of the network connection. Temporal and spatial evolution of EEG is of great significance for the transmission mechanism, clinical diagnosis and automatic detection of absence epilepsy seizures.

Altered functional connectivity in newly diagnosed benign epilepsy with unilateral or bilateral centrotemporal spikes: A multi-frequency MEG study

OBJECTIVE

Rolandic epilepsy (RE) is one of the most common forms of epilepsy syndromes in children. The condition is usually accompanied with either unilateral or bilateral centrotemporal epileptic discharge. Despite the term "benign", many studies have reported that children with benign epilepsy with centrotemporal spikes (BECTS) display a range of pervasive cognitive difficulties. In addition, existing research suggests that unilateral and bilateral centrotemporal spikes may affect cognition through different mechanisms. Consequently, the present study aimed to investigate cognitive impairment and the resting-state network topology of children with benign epilepsy with unilateral centrotemporal spikes (U-BECTS) and with bilateral centrotemporal spikes (B-BECTS).

METHODS

This study recruited 14 children with U-BECTS and 14 with B-BECTS. Thereafter, cognition was assessed in 28 children with BECTS and 14 healthy controls, using the fourth edition of the Wechsler Intelligence Scale (WISC-IV). Additionally, the functional network of the brain was constructed through magnetoencephalography (MEG) to record the resting-state brain magnetic signals of the brain and by computing virtual sensor waveforms at the source level. Moreover, graph theory (GT) analysis was used to assess the properties of the brain network.

RESULTS

Children in the B-BECTS group had an earlier onset of epilepsy compared to those in the U-BECTS category. In addition, both the B-BECTS and U-BECTS groups had lower Full Scale Intelligence Quotient (FSIQ), Verbal Comprehension Index (VCI), and Working Memory Index (WMI) scores, compared to the healthy controls although only children in the B-BECTS category had lower Perceptual Reasoning Index (PRI) scores. The results also showed that both BECTS groups had increased frontal cortex connectivity in specific frequency bands. Notably, children with B-BECTS showed a more disorderly and randomized network in the 1-4-Hz and 80-250-Hz frequency bands. Moreover, GT analysis showed that children with B-BECTS had lower clustering coefficient and characteristic path length in the 80-250-Hz frequency bands and higher connection strength in the 4-8-Hz frequency bands. On the other hand, the U-BECTS group had a higher clustering coefficient in the 8-12-Hz frequency bands, compared to the healthy controls. Correlation analysis revealed that there were negative correlations between network parameters, clinical characteristics, and neuropsychological data in the U-BECTS category.

CONCLUSION

The findings revealed that children with BECTS display a diffuse early cognitive deficit. In addition, resting-state suboptimal network topology may be the mechanism of cognitive impairment in children with BECTS. The study also showed that and children with B-BECTS may be at a higher risk of cognitive impairment.

Functional reorganization of brain regions into a network in childhood absence epilepsy: A magnetoencephalography study

OBJECTIVE

Epilepsy is considered as a network disorder. However, it is unknown how normal brain activity develops into the highly synchronized discharging activity seen in disordered networks. This study aimed to explore the epilepsy brain network and the significant re-combined brain areas in childhood absence epilepsy (CAE).

METHODS

Twenty-two children with CAE were recruited to study the neural source activity during ictal-onset and interictal periods at frequency bands of 1-30 Hz and 30-80 Hz with magnetoencephalography (MEG) scanning. Accumulated source imaging (ASI) was used to analyze the locations of neural source activity and peak source strength.

RESULTS

Most of the participants had more active source activity locations in the ictal-onset period rather than in the interictal period, both at 1-30 Hz and 30-80 Hz. The frontal lobe (FL), the temporo-parietal junction (T-P), and the parietal lobe (PL) became the main active areas of source activity during the ictal period, while the precuneus (PC), cuneus, and thalamus were relatively inactive.

CONCLUSIONS

Some brain areas become more excited and have increased source activity during seizures. These significant brain regions might be re-combined to form an epilepsy network that regulates the process of absence seizures.

SIGNIFICANCE

The study confirmed that important brain regions are reorganized in an epilepsy network, which provides a basis for exploring the network mechanism of CAE development. Imaging findings may provide a reference for clinical characteristics.

Pretreatment Source Location and Functional Connectivity Network Correlated With Therapy Response in Childhood Absence Epilepsy: A Magnetoencephalography Study

Objective: This study aims to investigate the differences between antiepileptic drug (AED) responders and nonresponders among patients with childhood absence epilepsy (CAE) using magnetoencephalography (MEG) and to additionally evaluate whether the neuromagnetic signals of the brain neurons were correlated with the response to therapy.

Methods: Twenty-four drug-naïve patients were subjected to MEG under six frequency bandwidths during ictal periods. The source location and functional connectivity were analyzed using accumulated source imaging and correlation analysis, respectively. All patients were treated with appropriate AED, at least 1 year after their MEG recordings, their outcome was assessed, and they were consequently divided into responders and nonresponders.

Results: The source location of the nonresponders was mainly in the frontal cortex at a frequency range of 8–12 and 30–80 Hz, especially 8–12 Hz, while the source location of the nonresponders was mostly in the medial frontal cortex, which was chosen as the region of interest. The nonresponders showed strong positive local frontal connections and deficient anterior and posterior connections at 80–250 Hz.

Conclusion: The frontal cortex and especially the medial frontal cortex at α band might be relevant to AED-nonresponsive CAE patients. The local frontal positive epileptic network at 80–250 Hz in our study might further reveal underlying cerebral abnormalities even before treatment in CAE patients, which could cause them to be nonresponsive to AED. One single mechanism cannot explain AED resistance; the nonresponders may represent a subgroup of CAE who is refractory to several antiepileptic drugs.