Systematically altered connectome gradient in benign childhood epilepsy with centrotemporal spikes: Potential effect on cognitive function

OBJECTIVE

Benign childhood epilepsy with centrotemporal spikes (BECTS) affects brain network hierarchy and cognitive function; however, itremainsunclearhowhierarchical changeaffectscognition in patients with BECTS. A major aim of this study was to examine changes in the macro-network function hierarchy in BECTS and its potential contribution to cognitive function.

METHODS

Overall, the study included 50 children with BECTS and 69 healthy controls. Connectome gradient analysis was used to determine the brain network hierarchy of each group. By comparing gradient scores at each voxel level and network between groups, we assessed changes in whole-brain voxel-level and network hierarchy. Functional connectivity was used to detect the functional reorganization of epilepsy caused by these abnormal brain regions based on these aberrant gradients. Lastly, we explored the relationships between the change gradient and functional connectivity values and clinical variables and further predicted the cognitive function associated with BECTS gradient changes.

RESULTS

In children with BECTS, the gradient was extended at different network and voxel levels. The gradient scores frontoparietal network was increased in the principal gradient of patients with BECTS. The left precentral gyrus (PCG) and right angular gyrus gradient scores were significantly increased in the principal gradient of children with BECTS. Moreover, in regions of the brain with abnormal principal gradients, functional connectivity was disrupted. The left PCG gradient score of children with BECTS was correlated with the verbal intelligence quotient (VIQ), and the disruption of functional connectivity in brain regions with abnormal principal gradients was closely related to cognitive function. VIQ was significantly predicted by the principal gradient map of patients.

SIGNIFICANCE

The results indicate connectome gradient disruption in children with BECTS and its relationship to cognitive function, thereby increasing our understanding of the functional connectome hierarchy and providing potential biomarkers for cognitive function of children with BECTS.

Functional brain connectivity in children with focal epilepsy: A systematic review of functional MRI studies

Epilepsy is increasingly recognised as a brain network disorder and many studies have investigated functional connectivity (FC) in children with epilepsy using functional MRI (fMRI). This systematic review of fMRI studies, published up to November 2023, investigated profiles of FC changes and their clinical relevance in children with focal epilepsy compared to healthy controls. A literature search in PubMed and Web of Science yielded 62 articles. We categorised the results into three groups: 1) differences in correlation-based FC between patients and controls; 2) differences in other FC measures between patients and controls; and 3) associations between FC and disease variables (for example, age of onset), cognitive and seizure outcomes. Studies revealed either increased or decreased FC across multiple brain regions in children with focal epilepsy. However, findings lacked consistency: conflicting FC alterations (decreased and increased FC) co-existed within or between brain regions across all focal epilepsy groups. The studies demonstrated overall that 1) interhemispheric connections often displayed abnormal connectivity and 2) connectivity within and between canonical functional networks was decreased, particularly for the default mode network. Focal epilepsy disrupted FC in children both locally (e.g., seizure-onset zones, or within-brain subnetworks) and globally (e.g., whole-brain network architecture). The wide variety of FC study methodologies limits clinical application of the results. Future research should employ longitudinal designs to understand the evolution of brain networks during the disease course and explore the potential of FC biomarkers for predicting cognitive and postsurgical seizure outcomes.

Connectivity Disturbances in Self-Limited Epilepsy with Centrotemporal Spikes: A Partial Directed Coherence Analysis of Electroencephalogram

Although the remission of self-limited epilepsy with centrotemporal spikes (SeLECTS) usually occurs by adolescence, deficits in cognition and behavior are not uncommon. Several functional magnetic resonance imaging (fMRI) studies have revealed connectivity disturbances in patients with SeLECTS associated with cognitive impairment. However, the disadvantages of fMRI are expensive, time-consuming, and motion sensitive. In the current study, we used a partial directed coherence (PDC) method to analyze electroencephalogram (EEG) for exploring brain connectivity in patients with SeLECTS. This study enrolled 38 participants (19 patients with SeLECTS and 19 healthy controls) for PDC analysis. Our results demonstrated that the controls had significantly higher PDC inflow connectivity in the F7, T3, FP1, and F8 channels than patients with SeLECTS. By contrast, the patients with SeLECTS demonstrated significantly higher PDC inflow connectivity than did the controls in the T5, Pz, and P4 channels. We also compared the PDC connectivity in different Brodmann areas between the patients with SeLECTS and the controls. The results revealed that the inflow connectivity in the BA9_46_L area was significantly higher in the controls than in the patients with SeLECTS, whereas the inflow connectivity in the MIF_L area 4 was significantly higher in the patients with SeLECTS than in the controls. Our proposed approach of combining EEG with PDC provides a convenient and useful tool for investigating functional connectivity in patients with SeLECTS. This approach is time-saving and inexpensive compared with fMRI, but it achieves similar results to fMRI.

Interictal magnetic signals in new-onset Rolandic epilepsy may help with timing of treatment selection

OBJECTIVE

With research progress on Rolandic epilepsy (RE), its "benign" nature has been phased out. Clinicians are exhibiting an increasing tendency toward a more assertive treatment approach for RE. Nonetheless, in clinical practice, delayed treatment remains common because of the "self-limiting" nature of RE. Therefore, this study aimed to identify an imaging marker to aid treatment decisions and select a more appropriate time for initiating therapy for RE.

METHODS

We followed up with children newly diagnosed with RE, classified them into medicated and non-medicated groups according to the follow-up results, and compared them with matched healthy controls. Before beginning follow-up visits, interictal magnetic data were collected using magnetoencephalography in treatment-naïve recently diagnosed patients. The spectral power of the whole brain during initial diagnosis was determined using minimum normative estimation combined with the Welch technique.

RESULTS

A difference was observed in the magnetic source intensity within the left caudal anterior cingulate and precentral and postcentral gyri in the delta band between the medicated and non-medicated groups. The results revealed good discriminatory ability within the receiver operator characteristic curve. In the medicated group, there was a specific change in the frontotemporal magnetic source intensity, which shifted from high to low frequencies, compared with the healthy control group.

SIGNIFICANCE

The intensity of the precentral gyrus magnetic source within the delta band showed good specificity. Considering the rigor of initial treatment, the intensity of the precentral gyrus magnetic source can provide some help as an imaging marker for initial RE treatment, particularly for the timing of treatment initiation.

Atypical functional connectivity hierarchy in Rolandic epilepsy

Functional connectivity hierarchy is an important principle in the process of brain functional organization and an important feature reflecting brain development. However, atypical brain network hierarchy organization in Rolandic epilepsy have not been systematically investigated. We examined connectivity alteration with age and its relation to epileptic incidence, cognition, or underlying genetic factors in 162 cases of Rolandic epilepsy and 117 typically developing children, by measuring fMRI multi-axis functional connectivity gradients. Rolandic epilepsy is characterized by contracting and slowing expansion of the functional connectivity gradients, highlighting the atypical age-related change of the connectivity hierarchy in segregation properties. The gradient alterations are relevant to seizure incidence, cognition, and connectivity deficit, and development-associated genetic basis. Collectively, our approach provides converging evidence for atypical connectivity hierarchy as a system-level substrate of Rolandic epilepsy, suggesting this is a disorder of information processing across multiple functional domains, and established a framework for large-scale brain hierarchical research.

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.

Connectivity increases during spikes and spike-free periods in self-limited epilepsy with centrotemporal spikes

OBJECTIVE

To understand the impact of interictal spikes on brain connectivity in patients with Self-Limited Epilepsy with Centrotemporal Spikes (SeLECTS).

METHODS

Electroencephalograms from 56 consecutive SeLECTS patients were segmented into periods with and without spikes. Connectivity between electrodes was calculated using the weighted phase lag index. To determine if there are chronic alterations in connectivity in SeLECTS, we compared spike-free connectivity to connectivity in 65 matched controls. To understand the acute impact of spikes, we compared connectivity immediately before, during, and after spikes versus baseline, spike-free connectivity. We explored whether behavioral state, spike laterality, or antiseizure medications affected connectivity.

RESULTS

Children with SeLECTS had markedly higher connectivity than controls during sleep but not wakefulness, with greatest difference in the right hemisphere. During spikes, connectivity increased globally; before and after spikes, left frontal and bicentral connectivity increased. Right hemisphere connectivity increased more during right-sided than left-sided spikes; left hemisphere connectivity was equally affected by right and left spikes.

CONCLUSIONS

SeLECTS patient have persistent increased connectivity during sleep; connectivity is further elevated during the spike and perispike periods.

SIGNIFICANCE

Testing whether increased connectivity impacts cognition or seizure susceptibility in SeLECTS and more severe epilepsies could help determine if spikes should be treated.

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.

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.

Computational Evidence for a Competitive Thalamocortical Model of Spikes and Spindle Activity in Rolandic Epilepsy

Rolandic epilepsy (RE) is the most common idiopathic focal childhood epilepsy syndrome, characterized by sleep-activated epileptiform spikes and seizures and cognitive deficits in school age children. Recent evidence suggests that this disease may be caused by disruptions to the Rolandic thalamocortical circuit, resulting in both an abundance of epileptiform spikes and a paucity of sleep spindles in the Rolandic cortex during non-rapid eye movement sleep (NREM); electrographic features linked to seizures and cognitive symptoms, respectively. The neuronal mechanisms that support the competitive shared thalamocortical circuitry between pathological epileptiform spikes and physiological sleep spindles are not well-understood. In this study we introduce a computational thalamocortical model for the sleep-activated epileptiform spikes observed in RE. The cellular and neuronal circuits of this model incorporate recent experimental observations in RE, and replicate the electrophysiological features of RE. Using this model, we demonstrate that: (1) epileptiform spikes can be triggered and promoted by either a reduced NMDA current or h-type current; and (2) changes in inhibitory transmission in the thalamic reticular nucleus mediates an antagonistic dynamic between epileptiform spikes and spindles. This work provides the first computational model that both recapitulates electrophysiological features and provides a mechanistic explanation for the thalamocortical switch between the pathological and physiological electrophysiological rhythms observed during NREM sleep in this common epileptic encephalopathy.

Voxel-wise functional connectivity of the default mode network in epilepsies: a systematic review and meta-analysis

Background:

Default Mode Network (DMN) is recognized to be involved in the generation and propagation of epileptic activities in various epilepsies. Converging evidence has suggested disturbed Functional Connectivity (FC) in epilepsies, which was inferred to be related to underlying pathological mechanisms. However, abnormal changes of FC in DMN revealed by different studies are controversial, which obscures the role of DMN in distinct epilepsies.

Objective:

The present work aims to investigate the voxel-wise FC in DMN across epilepsies.

Methods:

A systematic review was conducted on 22 published articles before October 2020, indexed in PubMed and Web of Science. A meta-analysis with a random-effect model was performed using the effect-size signed differential mapping approach. Subgroup analyses were performed in three groups: Idiopathic Generalized Epilepsy (IGE), mixed Temporal Lobe Epilepsy (TLE), and mixed Focal Epilepsy (FE) with different foci.

Results:

The meta-analysis suggested commonly decreased FC in mesial prefrontal cortices across different epilepsies. Additionally decreased FC in posterior DMN was observed in IGE. The TLE showed decreased FC in temporal lobe regions and increased FC in the dorsal posterior cingulate cortex. Interestingly, an opposite finding in the ventral and dorsal middle frontal gyrus was observed in TLE. The FE demonstrated increased FC in the cuneus.

Evaluation of patients with epileptiform activities in the posterior temporal-parietal-occipital regions

OBJECTIVE

The aim of this study was to determine the type, etiology and the rates of epilepsy and to identify accompanying cognitive and behavioral problems in patients with epileptiform abnormalities in the posterior cerebral localization.

METHODS

In this study, 3500 patients with at least one EEG record at the EEG Laboratory of Clinical Child Neurology Department of Cerrahpaşa Medical Faculty of Istanbul University were evaluated in 2014-2015. Three hundred forty-six patients were included in the study.

RESULTS

Of the 346 patients included in the study, 42.4% were female and 57.5% were male. The age range of the cases was 1-21 (mean: 8.7) years. Epileptiform activities were observed in post TPO region isolatedly in 58,95% (n = 204), post-TPO epileptiform focus with focal epileptiform focus in different localizations in 31.21% (n = 108), generalized epileptiform activity with more than one epileptiform focus in 9.8% (n= 34). In the period of EEG examinations 250 (72.25%) patients had a history of epileptic seizures and / or epilepsy, while 96 (27.74%) had non-epileptic clinical conditions such as behavioral disorder and autism.

CONCLUSION

In the EEG recordings we examined, sharp and spike wave activities were frequently observed in the post TPO region isolatedly. We believe that this study, which investigated the relationship between focal epilptiform activity in post TPO region and different clinical conditions, will serve as an example for other studies.

Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication

It is well established that temporal lobe epilepsy-the most common and well-studied form of epilepsy-can impair communication by disrupting social-emotional and language functions. In pediatric epilepsy, where seizures co-occur with the development of critical brain networks, age of onset matters: The earlier in life seizures begin, the worse the disruption in network establishment, resulting in academic hardship and social isolation. Yet, little is known about the processes by which epileptic activity disrupts developing human brain networks. Here we take a synthetic perspective-reviewing a range of research spanning studies on molecular and oscillatory processes to those on the development of large-scale functional networks-in support of a novel model of how such networks can be disrupted by epilepsy. We seek to bridge the gap between research on molecular processes, on the development of human brain circuitry, and on clinical outcomes to propose a model of how epileptic activity disrupts brain development.

Altered Static and Dynamic Spontaneous Neural Activity in Drug-Naïve and Drug-Receiving Benign Childhood Epilepsy With Centrotemporal Spikes

The present study aims to investigate intrinsic abnormalities of brain and the effect of antiepileptic treatment on brain activity in Benign childhood epilepsy with centrotemporal spikes (BECTS). Twenty-six drug-naïve patients (DNP) and 22 drug-receiving patients (DRP) with BECTS were collected in this study. Static amplitude of low frequency fluctuation (sALFF) and dynamic ALFF (dALFF) were applied to resting-state fMRI data. Functional connectivity (FC) analysis was further performed for affected regions identified by static and dynamic analysis. One-way analysis of variance and post hoc statistical analyses were performed for between-group differences. Abnormal sALFF and dALFF values were correlated with clinical features of patients. Compared with healthy controls (HC), DNP group demonstrated alterations of sALFF and/or dALFF in medial prefrontal cortex (MPFC), supplementary motor areas (SMA), cerebellum, hippocampus, pallidum and cingulate cortex, in which the values were close to normal in DRP. Notably, sALFF and dALFF showed specific sensitivity in detecting abnormalities in basal ganglia and cerebellum. Additionally, DRP showed additional changes in precuneus, inferior temporal gyrus, superior frontal gyrus and occipital visual cortex. Compared with HC, the DNP showed increased FC in default network and motion-related networks, and the DRP showed decreased FC in default network. The MPFC, hippocampus, SMA, basal ganglia and cerebellum are indicated to be intrinsically affected regions and effective therapeutic targets. And the FC profiles of default and motion-related networks might be potential core indicators for clinical treatment. This study revealed potential neuromodulatory targets and helped understand pathomechanism of BECTS. Static and dynamic analyses should be combined to investigate neuropsychiatric disorders.

Anomalous intrinsic connectivity within and between visual and auditory networks in major depressive disorder

OBJECTIVE

Major depressive disorder (MDD) is a ubiquitous mental illness with heterogeneous symptoms, however, the pathophysiology mechanisms are still not fully understood. Clinical and preclinical studies suggested that depression could cause disturbances in sensory perception systems, disruptions in auditory and visual functions may serve as an essential clinical features underlying MDD.

METHODS

The current study investigated the abnormal intrinsic connectivity within and between visual and auditory networks in 95 MDD patients and 97 age-, gender-, education level-matched healthy controls (HCs) by using resting-state functional magnetic resonance imaging (fMRI). One auditory network (AN) and three visual components including visual component 1 (VC1), VC2, and VC3 were identified by using independent component analysis method based on the fMRI networks during the resting state with the largest spatial correlations, combining with brain regions and specific network templates.

RESULTS

We found that MDD could be characterized by the following disrupted network model relative to HCs: (i) reduced within-network connectivity in the AN, VC2, and VC3; (ii) reduced between-network connectivity between the AN and the VC3. Furthermore, aberrant functional connectivity (FC) within the visual network was linked to the clinical symptoms.

CONCLUSIONS

Overall, our results demonstrated that abnormalities of FC in perception systems including intrinsic visual and auditory networks may explain neurobiological mechanisms underlying MDD and could serve as a potential effective biomarker.

Electrical status epilepticus in sleep affects intrinsically connected networks in patients with benign childhood epilepsy with centrotemporal spikes

BACKGROUND

Although outcomes of benign childhood epilepsy with centrotemporal spikes (BECTS) are frequently excellent, some atypical forms of BECTS, especially electrical status epilepticus in sleep (ESES), are characterized by worse outcomes and negative impacts on cognitive development.

METHODS

To explore specific ESES-related brain networks in patients with BECTS, we used resting-state functional magnetic resonance imaging (fMRI) to scan patients with BECTS with ESES (n = 9), patients with BECTS without ESES (n = 17), and healthy controls (n = 36). Unbiased seed-based whole-brain functional connectivity (FC) was adopted to explore the connectivity mode of three resting-state cerebral networks: the default mode network (DMN), salience network (SN), and central executive network (CEN).

RESULTS

Compared with the other two groups, patients with BECTS with ESES showed FC in the SN or in the CEN decreased, but not in the DMN. Moreover, we found the FC in the CEN in patients with BECTS without ESES decreased when compared with controls. Our currently intrinsically defined anticorrelated networks strength was disrupted in BECTS and connote greater deactivation than the results from FC for a seed region in children with BECTS.

CONCLUSION

These results indicated that children with BECTS with ESES showed brain activity altered in the CEN and the SN. The difference of impairment in the SN and CEN may lead to improve the understanding of the underlying neuropathophysiology, and to assess the activity of patients with BECTS with ESES, which is crucial for measuring disease activity, improving patient care, and assessing the effect of antiepilepsy therapy.

Automatic Seizure Detection using Fully Convolutional Nested LSTM

The automatic seizure detection system can effectively help doctors to monitor and diagnose epilepsy thus reducing their workload. Many outstanding studies have given good results in the two-class seizure detection problems, but most of them are based on hand-wrought feature extraction. This study proposes an end-to-end automatic seizure detection system based on deep learning, which does not require heavy preprocessing on the EEG data or feature engineering. The fully convolutional network with three convolution blocks is first used to learn the expressive seizure characteristics from EEG data. Then these robust EEG features pertinent to seizures are presented as an input to the Nested Long Short-Term Memory (NLSTM) model to explore the inherent temporal dependencies in EEG signals. Lastly, the high-level features obtained from the NLSTM model are fed into the softmax layer to output predicted labels. The proposed method yields an accuracy range of 98.44–100% in 10 different experiments based on the Bonn University database. A larger EEG database is then used to evaluate the performance of the proposed method in real-life situations. The average sensitivity of 97.47%, specificity of 96.17%, and false detection rate of 0.487 per hour are yielded. For CHB–MIT Scalp EEG database, the proposed model also achieves a segment-level sensitivity of 94.07% with a false detection rate of 0.66 per hour. The excellent results obtained on three different EEG databases demonstrate that the proposed method has good robustness and generalization power under ideal and real-life conditions.

Abnormal dynamics of functional connectivity density in children with benign epilepsy with centrotemporal spikes

Converging evidence has shown the link between benign epilepsy with centrotemporal spikes (BECTS) and abnormal functional connectivity among distant brain regions. However, prior research in BECTS has not examined the dynamic changes in functional connectivity as networks form. We combined functional connectivity density (FCD) mapping and sliding windows correlation analyses, to fully capture the functional dynamics in patients with respect to the presence of interictal epileptic discharges (IEDs). Resting-state fMRI was performed in 43 BECTS patients and 28 healthy controls (HC). Patients were further classified into two subgroups, namely, IED (n = 20) and non-IED (n = 23) depending on the simultaneous EEG-fMRI recordings. The global dynamic FCD (dFCD) was measured using sliding window correlation. Then we quantified dFCD variability using their standard deviation. Compared with HC, patients with and without IEDs both showed invariable dFCD (decreased) among the orbital fontal cortex, anterior cingulate cortex and striatum, as well as variable dFCD (increased) in the posterior default mode network (P < 0.05, AlphaSim corrected). Correlation analysis indicated that the variable dFCD in precuneus was related to seizure onset age (P < 0.05, uncorrected). BECTS with IEDs showed variable dFCD in regions related to the typical seizure semiology. The abnormal patterns of fluctuating FCD in BECTS suggest that both active and chronic epileptic state may contribute to altered dynamics of functional connectivity associated with cognitive disturbances and developmental alterations. These findings highlight the importance of considering fluctuating dynamic neural communication among brain systems to deepen our understanding of epilepsy diseases.

Impact of epilepsy on language and discourse: Two self-limited focal epileptic syndromes of childhood

Self-limited focal epilepsy with centro-temporal spikes, also known as Rolandic epilepsy (RE), is a well-established focal epilepsy of childhood, characterized with language impairment. To investigate the relationship between language deficits and clinical parameters of self-limited focal epilepsies of childhood (SFEC), 21 patients with RE, 10 patients with childhood occipital epilepsy of Gastaut type (COE-G) (another SFEC that is not typically associated with language impairment), and 31 healthy controls were recruited. A broad panel of language tests also including narration sample was administered, and clinical features were documented. The language was significantly impaired in both RE and COE-G. Patients with COE-G showed worse scores than patients with RE in subtests measuring semantic functions. Clinical parameters were not associated with impaired language domains. Language impairment is experienced in different types of SFEC, emphasizing the broad representation of the language network. In SFEC, recent activity of epilepsy does not affect the severity of language dysfunction.

Reorganization of Large-Scale Functional Networks During Low-Frequency Electrical Stimulation of the Cortical Surface

We investigated the functional network reorganization caused by low-frequency electrical stimulation (LFES) of human brain cortical surface. Intracranial EEG data from subdural grid positions were analyzed in 16 pre-surgery epileptic patients. LFES was performed by injecting current pulses (10[Formula: see text]mA, 0.2[Formula: see text]ms pulse width, 0.5[Formula: see text]Hz, 25 trials) into all adjacent electrode contacts. Dynamic functional connectivity analysis was carried out on two frequency bands (low: 1–4[Formula: see text]Hz; high: 10–40[Formula: see text]Hz) to investigate the early, high frequency and late, low frequency responses elicited by the stimulation. The centralization increased in early compared to late responses, suggesting a more prominent role of direct neural links between primarily activated areas and distant brain regions. Injecting the current into the seizure onset zone (SOZ) evoked a more integrated functional topology during the early (N1) period of the response, whereas during the late (N2) period — regardless of the stimulation site — the connectedness of the SOZ was elevated compared to the non-SOZ tissue. The abnormal behavior of the epileptic sub-network during both part of the responses supports the idea of the pathogenic role of impaired inhibition and excitation mechanisms in epilepsy.

The Role of EEG-fMRI in Studying Cognitive Network Alterations in Epilepsy

Brain functions do not arise from isolated brain regions, but from interactions in widespread networks necessary for both normal and pathological conditions. These Intrinsic Connectivity Networks (ICNs) support cognitive processes such as language, memory, or executive functions, but can be disrupted by epileptic activity. Simultaneous EEG-fMRI can help explore the hemodynamic changes associated with focal or generalized epileptic discharges, thus providing information about both transient and non-transient impairment of cognitive networks related to spatio-temporal overlap with epileptic activity. In the following review, we discuss the importance of interictal discharges and their impact on cognition in different epilepsy syndromes. We explore the cognitive impact of interictal activity in both animal models and human connectivity networks in order to confirm that this effect could have a possible clinical impact for prescribing medication and characterizing post-surgical outcome. Future work is needed to further investigate electrophysiological changes, such as amplitude/latency of single evoked responses or spontaneous epileptic activity in either scalp or intracranial EEG and determine its relative change in hemodynamic response with subsequent network modifications.

The epileptic network and cognition: What functional connectivity is teaching us about the childhood epilepsies

Our objective was to summarize and evaluate the rapidly expanding body of literature studying functional connectivity in childhood epilepsy. In the self-limited childhood epilepsies, awareness of cognitive comorbidities has been steadily increasing, and recent advances in our understanding of the network effects of these disorders promise insights into the underlying neurobiology. We reviewed publications addressing functional connectivity in children with epilepsy with an emphasis on studies of children with self-limited childhood epilepsies. The majority of studies have been published in the past 10 years and predominantly examine childhood epilepsy with centrotemporal spikes and childhood absence epilepsy. Cognitive network alterations are commonly observed across the childhood epilepsies. Some of these effects appear to be nonspecific to epilepsy syndrome or even to category of neurological disorder. Other patterns, such as changes in the connectivity of cortical language areas in childhood epilepsy with centrotemporal spikes, provide clues to the underlying cognitive deficits seen in affected children. The literature to date is dominated by general observations of connectivity patterns without a priori hypotheses. These data-driven studies build an important foundation for hypothesis generation and are already providing useful insights into the neuropathology of the childhood epilepsies. Future work should emphasize hypothesis-driven approaches and rigorous clinical correlations to better understand how the knowledge of network alterations can be applied to guidance and treatment for the children in our clinics.

Dysfunctional white-matter networks in medicated and unmedicated benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECT) is the most common childhood idiopathic focal epilepsy syndrome, which characterized with white-matter abnormalities in the rolandic cortex. Although diffusion tensor imaging research could characterize white-matter structural architecture, it cannot detect neural activity or white-matter functions. Recent studies demonstrated the functional organization of white-matter by using functional magnetic resonance imaging (fMRI), suggesting that it is feasible to investigate white-matter dysfunctions in BECT. Resting-state fMRI data were collected from 24 new-onset drug-naive (unmedicated [NMED]), 21 medicated (MED) BECT patients, and 27 healthy controls (HC). Several white-matter functional networks were obtained using a clustering analysis on voxel-by-voxel correlation profiles. Subsequently, conventional functional connectivity (FC) was calculated in four frequency sub-bands (Slow-5:0.01-0.027, Slow-4:0.027-0.073, Slow-3:0.073-0.198, and Slow-2:0.198-0.25 Hz). We also employed a functional covariance connectivity (FCC) to estimate the covariant relationship between two white-matter networks based on their correlations with multiple gray-matter regions. Compared with HC, the NMED showed increased FC and/or FCC in rolandic network (RN) and precentral/postcentral network, and decreased FC and/or FCC in dorsal frontal network, while these alterations were not observed in the MED group. Moreover, the changes exhibited frequency-specific properties. Specifically, only two alterations were shared in at least two frequency bands. Most of these alterations were observed in the frequency bands of Slow-3 and Slow-4. This study provided further support on the existence of white-matter functional networks which exhibited frequency-specific properties, and extended abnormalities of rolandic area from the perspective of white-matter dysfunction in BECT.

Altered attention networks and DMN in refractory epilepsy: A resting-state functional and causal connectivity study

PURPOSE

Epilepsy is considered a disorder of neural networks. Patients diagnosed with refractory epilepsy frequently experience attention impairments. Seizure activity in epilepsy may disturb brain networks and damage the brain function of attention. The aims of this study were to assess functional and causal connectivities of the attention networks and default mode network using resting-state functional magnetic resonance imaging (fMRI).

METHOD

Resting-state fMRI data were gathered from 19 patients with refractory epilepsy (mixed localization and aetiologies) and 21 healthy people. The fMRI data were analyzed by group independent component analysis (ICA) fMRI toolbox to extract dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). The components of the selected networks were compared between patients and healthy controls to explore the change in functional connectivity (FC). Granger causality analysis was performed by taking the aforementioned significant brain areas as regions of interest (ROIs) to calculate autoregression coefficients of each pair of ROIs. Comparisons were done to find the significantly different causal connectivity when FC was changed between patients and healthy controls.

RESULTS

In DAN, the FC values of the bilateral frontal eye field (FEF) and left intraparietal sulcus (IPS) were decreased. In VAN, the FC values of the double-side ventral prefrontal cortex (vPFC) and the temporoparietal junction (TPJ) were reduced. As for DMN, the FC values of the bilateral medial prefrontal cortices (mPFC) were decreased whereas those for the bilateral precuneus (PCUN) were increased. Granger causal connectivity values were correlated: causal influence was decreased significantly from the left IPS (in DAN) to the double side of the vPFC but remained the same for the right FEF (in DAN) to the right TPJ. The value was decreased from the left PCUN (in DMN) to the right TPJ and FEF, and the causal flow from the right PCUN to the right TPJ and bilateral vPFC was also significantly inhibited (p < 0.05).

CONCLUSION

Frequent seizures in patients with refractory epilepsy may damage the cortex and disturb DAN, VAN, and DMN, leading to functional and causal connectivity alteration. In addition, epileptic activity may disrupt network interactions and further influence information communication.

Sleep Related Epilepsy and Pharmacotherapy: An Insight

In the last several decades, sleep-related epilepsy has drawn considerable attention among epileptologists and neuroscientists in the interest of new paradigms of the disease etiology, pathogenesis and management. Sleep-related epilepsy is nocturnal seizures that manifest solely during the sleep state. Sleep comprises two distinct stages i.e., non-rapid eye movement (NREM) and rapid eye movement (REM) that alternate every 90 min with NREM preceding REM. Current findings indicate that the sleep-related epilepsy manifests predominantly during the synchronized stages of sleep; NREM over REM stage. Sleep related hypermotor epilepsy (SHE), benign partial epilepsy with centrotemporal spikes or benign rolandic epilepsy (BECTS), and Panayiotopoulos Syndrome (PS) are three of the most frequently implicated epilepsies occurring during the sleep state. Although some familial types are described, others are seemingly sporadic occurrences. In the present review, we aim to discuss the predominance of sleep-related epilepsy during NREM, established familial links to the pathogenesis of SHE, BECTS and PS, and highlight the present available pharmacotherapy options.

Frequency-specific alterations in the amplitude and synchronization of resting-state spontaneous low-frequency oscillations in benign childhood epilepsy with centrotemporal spikes

OBJECTIVES

Spontaneous low-frequency oscillations in different frequency bands have diverse physiological meanings. The amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) in different frequency bands in Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS) are unknown and worth exploring.

METHOD

Resting-state functional magnetic resonance imaging data were collected in 51 drug-naïve BECTS patients and 76 healthy controls. The ALFF was calculated for the typical (0.01 - 0.08 Hz), slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), and slow-3 (0.073-0.198 Hz) frequency bands. The bilateral precuneus/posterior cingulate cortex (PCU/PCC) showed a common alteration of ALFF in different frequency bands, and was selected as the seed for calculating FC per voxel.

RESULTS

In the typical band, BECTS patients showed increased ALFF in the left rolandic operculum and the right pre/postcentral gyrus, and decreased ALFF in the bilateral PCU/PCC, some of which were shared by the slow-5, slow-4, and slow-3 bands. Decreased ALFF in the left angular gyrus was also found in the slow-3 band. Only the bilateral PCU/PCC showed a frequency-dependent correlation with the total seizure frequency and full-scale intelligence quotient. Regions having degenerated FC with the bilateral PCU/PCC in BECTS patients were mainly in the left prefrontal cortex and bilateral anterior cingulate cortex for the typical and slow-5 bands, and in the bilateral temporal limbic system and striatum for the slow-4 and slow-3 bands.

CONCLUSION

Alteration of the ALFF and FC differed with distinct frequency bands. Therefore, employing different frequency bands would provide more meaningful findings for BECTS patients.

Aberrant Thalamocortical Connectivity in Juvenile Myoclonic Epilepsy

The purpose of this study was to investigate the functional connectivity (FC) of thalamic subdivisions in patients with juvenile myoclonic epilepsy (JME). Resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data were acquired from 22 JME and 25 healthy controls. We first divided the thalamus into eight subdivisions by performing independent component analysis on tracking fibers and clustering thalamus-related FC maps. We then analyzed abnormal FC in each subdivision in JME compared with healthy controls, and we investigated their associations with clinical features. Eight thalamic sub-regions identified in the current study showed unbalanced thalamic FC in JME: decreased FC with the superior frontal gyrus and enhanced FC with the supplementary motor area in the posterior thalamus increased thalamic FC with the salience network (SN) and reduced FC with the default mode network (DMN). Abnormalities in thalamo-prefrontocortical networks might be related to the propagation of generalized spikes with frontocentral predominance in JME, and the network connectivity differences with the SN and DMN might be implicated in emotional and cognitive defects in JME. JME was also associated with enhanced FC among thalamic sub-regions and with the basal ganglia and cerebellum, suggesting the regulatory role of subcortical nuclei and the cerebellum on the thalamo-cortical circuit. Additionally, increased FC with the pallidum was positive related with the duration of disease. The present study provides emerging evidence of FC to understand that specific thalamic subdivisions contribute to the abnormalities of thalamic-cortical networks in JME. Moreover, the posterior thalamus could play a crucial role in generalized epileptic activity in JME.

Differential patterns of dynamic functional connectivity variability of striato-cortical circuitry in children with benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECTS) is characterized by abnormal (static) functional interactions among cortical and subcortical regions, regardless of the active or chronic epileptic state. However, human brain connectivity is dynamic and associated with ongoing rhythmic activity. The dynamic functional connectivity (dFC) of the distinct striato-cortical circuitry associated with or without interictal epileptiform discharges (IEDs) are poorly understood in BECTS. Herein, we captured the pattern of dFC using sliding window correlation of putamen subregions in the BECTS (without IEDs, n = 23; with IEDs, n = 20) and sex- and age-matched healthy controls (HCs, n = 28) during rest. Furthermore, we quantified dFC variability using their standard deviation. Compared with HCs and patients without IEDs, patients with IEDs exhibited excessive variability in the dorsal striatal-sensorimotor circuitry related to typical seizure semiology. By contrast, excessive stability (decreased dFC variability) was found in the ventral striatal-cognitive circuitry (p < .05, GRF corrected). In addition, correlation analysis revealed that the excessive variability in the dorsal striatal-sensorimotor circuitry was related to highly frequent IEDs (p < .05, uncorrected). Our finding of excessive variability in the dorsal striatal-sensorimotor circuitry could be an indication of increased sensitivity to regional fluctuations in the epileptogenic zone, while excessive stability in the ventral striatal-cognitive circuitry could represent compensatory mechanisms that prevent or postpone cognitive impairments in BECTS. Overall, the differentiated dynamics of the striato-cortical circuitry extend our understanding of interactions among epileptic activity, striato-cortical functional architecture, and neurocognitive processes in BECTS.

Altered language network in benign childhood epilepsy patients with spikes from non-dominant side: A resting-state fMRI study

Benign childhood epilepsy with centrotemporal spikes (BECTS) is one of the most common childhood epilepsy syndromes, and language deficits associated with BECTS have become a hot topic. This study investigated alterations of the language network in BECTS children with spikes from the non-dominant side in comparison with healthy controls. Twenty-three children with BECTS and 20 age-matched healthy controls were enrolled. Region of interest -based whole brain functional connectivity analysis was used to identify the potential differences in the functional connectivity of the Broca's area between the two groups. Increased positive functional connectivity within the Broca's region was detected mainly at the left superior frontal gyrus (Brodmann area 8), bilateral insula, and anterior and posterior cingulate in the BECTS group. No regions showed significantly decreased connection in the BECTS patients compared to the controls. This study suggested alterations in the language network that was related with the Broca's area in children with BECTS from the non-dominant side. Further studies with longitudinal assessments from the perceptive of functional neuroimaging are needed to illustrate the dynamic course of language development and corresponding neuroimaging evidence.

Functional Network Connectivity Patterns between Idiopathic Generalized Epilepsy with Myoclonic and Absence Seizures

The extensive cerebral cortex and subcortical structures are considered as the major regions related to the generalized epileptiform discharges in idiopathic generalized epilepsy. However, various clinical syndromes and electroencephalogram (EEG) signs exist across generalized seizures, such as the loss of consciousness during absence seizures (AS) and the jerk of limbs during myoclonic seizures (MS). It is presumed that various functional systems affected by discharges lead to the difference in syndromes of these seizures. Twenty epileptic patients with MS, 21 patients with AS, and 21 healthy controls were recruited in this study. The functional network connectivity was analyzed based on the resting-state functional magnetic resonance imaging scans. The statistical analysis was performed in three groups to assess the difference in the functional brain networks in two types of generalized seizures. Twelve resting-state networks were identified in three groups. Both patient groups showed common abnormalities, including decreased functional connectivity in salience network (SN), cerebellum network, and primary perceptional networks and decreased connection between SN and visual network, compared with healthy controls. Interestingly, the frontal part of high-level cognitive resting-state networks showed increased functional connectivity (FC) in patients with MS, but decreased FC in patients with AS. Moreover, patients with MS showed decreased negative connections between high-level cognitive networks and primary system. The common alteration in both patient groups, including SN, might reflect a similar mechanism associated with the loss of consciousness during generalized seizures. This study provided the evidence of brain network in generalized epilepsy to understand the difference between MS and AS.