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Li M, Zhou X, Wang Y, Lu J, Zhu Y, Jiang P, Hu K, Wang X. Whole-course power evolution in childhood absence epilepsy: A multi-frequency magnetoencephalography study. Seizure 2025; 124:9-17. [PMID: 39603048 DOI: 10.1016/j.seizure.2024.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 10/18/2024] [Accepted: 11/12/2024] [Indexed: 11/29/2024] Open
Abstract
OBJECTIVE This study explores the whole-course neuromagnetic activity changes in childhood absence epilepsy (CAE) using multifrequency magnetoencephalogram (MEG) analysis. We aim to uncover the underlying neurophysiological mechanisms and identify functional signal targets with potential clinical applications. METHODS We recruited 37 drug-naive children with CAE and collected magnetoencephalography (MEG) data from 62 seizures and interictal periods using a CTF-275 channel MEG system. The seizure course was segmented with temporal unification and subjected to dynamic frequency band analysis. Minimum norm estimation combined with Welch's method was employed for spectral power calculation, followed by correlation analysis between power and seizure duration. RESULTS Whole-brain magnetic source power changes in 2-60 Hz largely paralleled the progression of spike and wave discharges (SWDs), while power in 60-90 Hz was suppressed during seizures. Alpha band (8-12 Hz) activity showed a prompt loss of occipital dominance at seizure onset, with concurrent elevation in frontal alpha activity. This frontal alpha dominance persisted throughout the ictal period and reverted to occipital dominance at termination. Beta and gamma1 band (15-59 Hz) activity characteristically declined before SWDs cessation. The power of SWDs during ictal period was negatively correlated with seizure duration. CONCLUSION Spectral power analysis of neuromagnetic signals throughout CAE process identifies specific frequency-dependent characteristic changes, among which, the distribution of alpha band (8-12 Hz) activity is closely related to absence manifestations, beta band (15-29 Hz) power decline induces seizure termination. Additionally, ictal SWDs power can serve as a neuroimaging indicator of epilepsy severity.
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Affiliation(s)
- Minghao Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China
| | - Xinyi Zhou
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China
| | - Yingfan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China
| | - Jing Lu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China
| | - Yinjie Zhu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China
| | - Peilin Jiang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China
| | - Ke Hu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210024, China.
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Sun F, Wang S, Wang Y, Sun J, Li Y, Li Y, Xu Y, Wang X. Differences in generation and maintenance between ictal and interictal generalized spike-and-wave discharges in childhood absence epilepsy: A magnetoencephalography study. Epilepsy Behav 2023; 148:109440. [PMID: 37748416 DOI: 10.1016/j.yebeh.2023.109440] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 09/05/2023] [Accepted: 09/05/2023] [Indexed: 09/27/2023]
Abstract
PURPOSE Childhood absence epilepsy (CAE) is characterized by impaired consciousness and distinct electroencephalogram (EEG) patterns. However, interictal epileptiform discharges (IEDs) do not lead to noticeable symptoms. This study examines the disparity between ictal and interictal generalized spike-and-wave discharges (GSWDs) to determine the mechanisms behind CAE and consciousness. METHODS We enrolled 24 patients with ictal and interictal GSWDs in the study. The magnetoencephalography (MEG) data were recorded before and during GSWDs at a sampling rate of 6000 Hz and analyzed across six frequency bands. The absolute and relative spectral power were estimated with the Minimum Norm Estimate (MNE) combined with the Welch technique. All the statistical analyses were performed using paired-sample tests. RESULTS During GSWDs, the right lateral occipital cortex indicated a significant difference in the theta band (5-7 Hz) with stronger power (P = 0.027). The interictal group possessed stronger spectral power in the delta band (P < 0.01) and weaker power in the alpha band (P < 0.01) as early as 10 s before GSWDs in absolute and relative spectral power. Additionally, the ictal group revealed enhanced spectral power inside the occipital cortex in the alpha band and stronger spectral power in the right frontal regions within beta (15-29 Hz), gamma 1 (30-59 Hz), and gamma 2 (60-90 Hz) bands. CONCLUSIONS GSWDs seem to change gradually, with local neural activity changing even 10 s before discharge. During GSWDs, visual afferent stimulus insensitivity could be related to the impaired response state in CAE. The inhibitory signal in the low-frequency band can shorten GSWD duration, thereby achieving seizure control through inhibitory effect strengthening.
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Affiliation(s)
- Fangling Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Siyi Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yingfan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yihan Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yanzhang Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yue Xu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
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Xu Y, Wang Y, Xu F, Li Y, Sun J, Niu K, Wang P, Li Y, Zhang K, Wu D, Chen Q, Wang X. Impact of interictal epileptiform discharges on brain network in self-limited epilepsy with centrotemporal spikes: A magnetoencephalography study. Brain Behav 2023; 13:e3038. [PMID: 37137814 PMCID: PMC10275544 DOI: 10.1002/brb3.3038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 04/07/2023] [Accepted: 04/19/2023] [Indexed: 05/05/2023] Open
Abstract
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.
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Affiliation(s)
- Yue Xu
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Yingfan Wang
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Fengyuan Xu
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Yihan Li
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Jintao Sun
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Kai Niu
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Pengfei Wang
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Yanzhang Li
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Ke Zhang
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Di Wu
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Qiqi Chen
- MEG CenterNanjing Brain HospitalNanjingJiangsuP. R. China
| | - Xiaoshan Wang
- Department of NeurologyThe Affiliated Brain HospitalNanjing Medical UniversityNanjingJiangsuP. R. China
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Li Y, Li Y, Sun J, Niu K, Wang P, Xu Y, Wang Y, Chen Q, Zhang K, Wang X. Relationship between brain activity, cognitive function, and sleep spiking activation in new-onset self-limited epilepsy with centrotemporal spikes. Front Neurol 2022; 13:956838. [PMID: 36438972 PMCID: PMC9682286 DOI: 10.3389/fneur.2022.956838] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 10/07/2022] [Indexed: 09/12/2024] Open
Abstract
OBJECTIVE This study aimed to investigate the relationship between cognitive function sleep spiking activation and brain activity in self-limited epilepsy with centrotemporal spikes (SeLECTS). METHODS We used spike-wave index (SWI), which means the percentage of the spike and slow wave duration to the total non-REM (NREM) sleep time, as the grouping standard. A total of 14 children with SeLECTS (SWI ≥ 50%), 21 children with SeLECTS (SWI < 50%), and 20 healthy control children were recruited for this study. Cognitive function was evaluated using the Wechsler Intelligence Scale for Children, Fourth Edition (Chinese version) (WISC-IV). Magnetic source activity was assessed using magnetoencephalography calculated for each frequency band using the accumulated source imaging (ASI) technique. RESULTS Children with SeLECTS (SWI ≥ 50%) had the lowest cognitive function scores, followed by those with SeLECTS (SWI < 50%) and then healthy controls. There were significant differences in the localization of magnetic source activity between the three groups: in the alpha (8-12 Hz) frequency band, children with SeLECTS (SWI ≥ 50%) showed deactivation of the medial frontal cortex (MFC) region; in the beta (12-30 Hz) frequency band, children with SeLECTS (SWI ≥ 50%) showed deactivation of the posterior cingulate cortex (PCC) segment; and in the gamma (30-80 Hz) frequency band, children in the healthy group showed activation of the PCC region. CONCLUSION This study revealed significant decreases in cognitive function in children with SeLECTS (SWI ≥ 50%) compared to children with SeLECTS (SWI < 50%) and healthy children, as well as significant differences in magnetic source activity between the three groups. The findings suggest that deactivation of magnetic source activity in the PCC and MFC regions is the main cause of cognitive function decline in SeLECTS patients with some frequency dependence.
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Affiliation(s)
- Yanzhang Li
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yihan Li
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jintao Sun
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Kai Niu
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Pengfei Wang
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yue Xu
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yingfan Wang
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Qiqi Chen
- MEG Center, Nanjing Brain Hospital, Nanjing, China
| | - Ke Zhang
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Xiaoshan Wang
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
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Aung T, Tenney JR, Bagić AI. Contributions of Magnetoencephalography to Understanding Mechanisms of Generalized Epilepsies: Blurring the Boundary Between Focal and Generalized Epilepsies? Front Neurol 2022; 13:831546. [PMID: 35572923 PMCID: PMC9092024 DOI: 10.3389/fneur.2022.831546] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/08/2022] [Indexed: 12/31/2022] Open
Abstract
According to the latest operational 2017 ILAE classification of epileptic seizures, the generalized epileptic seizure is still conceptualized as "originating at some point within and rapidly engaging, bilaterally distributed networks." In contrast, the focal epileptic seizure is defined as "originating within networks limited to one hemisphere." Hence, one of the main concepts of "generalized" and "focal" epilepsy comes from EEG descriptions before the era of source localization, and a presumed simultaneous bilateral onset and bi-synchrony of epileptiform discharges remains a hallmark for generalized seizures. Current literature on the pathophysiology of generalized epilepsy supports the concept of a cortical epileptogenic focus triggering rapidly generalized epileptic discharges involving intact corticothalamic and corticocortical networks, known as the cortical focus theory. Likewise, focal epilepsy with rich connectivity can give rise to generalized spike and wave discharges resulting from widespread bilateral synchronization. Therefore, making this key distinction between generalized and focal epilepsy may be challenging in some cases, and for the first time, a combined generalized and focal epilepsy is categorized in the 2017 ILAE classification. Nevertheless, treatment options, such as the choice of antiseizure medications or surgical treatment, are the reason behind the importance of accurate epilepsy classification. Over the past several decades, plentiful scientific research on the pathophysiology of generalized epilepsy has been conducted using non-invasive neuroimaging and postprocessing of the electromagnetic neural signal by measuring the spatiotemporal and interhemispheric latency of bi-synchronous or generalized epileptiform discharges as well as network analysis to identify diagnostic and prognostic biomarkers for accurate diagnosis of the two major types of epilepsy. Among all the advanced techniques, magnetoencephalography (MEG) and multiple other methods provide excellent temporal and spatial resolution, inherently suited to analyzing and visualizing the propagation of generalized EEG activities. This article aims to provide a comprehensive literature review of recent innovations in MEG methodology using source localization and network analysis techniques that contributed to the literature of idiopathic generalized epilepsy in terms of pathophysiology and clinical prognosis, thus further blurring the boundary between focal and generalized epilepsy.
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Affiliation(s)
- Thandar Aung
- Department of Neurology, University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States
| | - Jeffrey R. Tenney
- Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Anto I. Bagić
- Department of Neurology, University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States
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Jiang W, Sun J, Xiang J, Sun Y, Tang L, Zhang K, Chen Q, Wang X. Altered Neuromagnetic Activity in Persistent Postural-Perceptual Dizziness: A Multifrequency Magnetoencephalography Study. Front Hum Neurosci 2022; 16:759103. [PMID: 35350444 PMCID: PMC8957837 DOI: 10.3389/fnhum.2022.759103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 01/10/2022] [Indexed: 12/12/2022] Open
Abstract
Objective The aim of our study was to investigate abnormal changes in brain activity in patients with persistent postural-perceptual dizziness (PPPD) using magnetoencephalography (MEG). Methods Magnetoencephalography recordings from 18 PPPD patients and 18 healthy controls were analyzed to determine the source of brain activity in seven frequency ranges using accumulated source imaging (ASI). Results Our study showed that significant changes in the patterns of localization in the temporal-parietal junction (TPJ) were observed at 1–4, 4–8, and 12–30 Hz in PPPD patients compared with healthy controls, and changes in the frontal cortex were found at 1–4, 80–250, and 250–500 Hz in PPPD patients compared with controls. The neuromagnetic activity in TPJ was observed increased significantly in 1–4 and 4–8 Hz, while the neuromagnetic activity in frontal cortex was found increased significantly in 1–4 Hz. In addition, the localized source strength in TPJ in 1–4 Hz was positively correlated with DHI score (r = 0.7085, p < 0.05), while the localized source strength in frontal cortex in 1–4 Hz was positively correlated with HAMA score (r = 0.5542, p < 0.05). Conclusion Our results demonstrated that alterations in the TPJ and frontal cortex may play a critical role in the pathophysiological mechanism of PPPD. The neuromagnetic activity in TPJ may be related to dizziness symptom of PPPD patients, while the neuromagnetic activity in frontal lobe may be related to emotional symptoms of PPPD patients. In addition, frequency-dependent changes in neuromagnetic activity, especially neuromagnetic activity in low frequency bands, were involved in the pathophysiology of PPPD.
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Affiliation(s)
- Weiwei Jiang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jing Xiang
- Division of Neurology, MEG Center, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Yulei Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Lu Tang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Ke Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Qiqi Chen
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
- *Correspondence: Xiaoshan Wang,
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Sun J, Li Y, Zhang K, Sun Y, Wang Y, Miao A, Xiang J, Wang X. Frequency-Dependent Dynamics of Functional Connectivity Networks During Seizure Termination in Childhood Absence Epilepsy: A Magnetoencephalography Study. Front Neurol 2021; 12:744749. [PMID: 34759883 PMCID: PMC8573389 DOI: 10.3389/fneur.2021.744749] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 09/21/2021] [Indexed: 12/04/2022] Open
Abstract
Objective: Our aim was to investigate the dynamics of functional connectivity (FC) networks during seizure termination in patients with childhood absence epilepsy (CAE) using magnetoencephalography (MEG) and graph theory (GT) analysis. Methods: MEG data were recorded from 22 drug-naïve patients diagnosed with CAE. FC analysis was performed to evaluate the FC networks in seven frequency bands of the MEG data. GT analysis was used to assess the topological properties of FC networks in different frequency bands. Results: The patterns of FC networks involving the frontal cortex were altered significantly during seizure termination compared with those during the ictal period. Changes in the topological parameters of FC networks were observed in specific frequency bands during seizure termination compared with those in the ictal period. In addition, the connectivity strength at 250–500 Hz during the ictal period was negatively correlated with seizure frequency. Conclusions: FC networks associated with the frontal cortex were involved in the termination of absence seizures. The topological properties of FC networks in different frequency bands could be used as new biomarkers to characterize the dynamics of FC networks related to seizure termination.
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Affiliation(s)
- Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Yihan Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Ke Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Yulei Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Yingfan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Ailiang Miao
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jing Xiang
- Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
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Wang P, Li Y, Sun Y, Sun J, Niu K, Zhang K, Xiang J, Chen Q, Hu Z, Wang X. Altered functional connectivity in newly diagnosed benign epilepsy with unilateral or bilateral centrotemporal spikes: A multi-frequency MEG study. Epilepsy Behav 2021; 124:108276. [PMID: 34547687 DOI: 10.1016/j.yebeh.2021.108276] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 08/15/2021] [Accepted: 08/15/2021] [Indexed: 11/22/2022]
Abstract
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.
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Affiliation(s)
- Pengfei Wang
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yihan Li
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yulei Sun
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Jingtao Sun
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Kai Niu
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Ke Zhang
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Jing Xiang
- MEG Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45220, United States
| | - Qiqi Chen
- MEG Center, Nanjing Brain Hospital, Nanjing, Jiangsu 210029, China
| | - Zheng Hu
- Department of Neurology, Nanjing Children's Hospital, Nanjing, Jiangsu 210029, China
| | - Xiaoshan Wang
- Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China.
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Sun Y, Li Y, Sun J, Zhang K, Tang L, Wu C, Gao Y, Liu H, Huang S, Hu Z, Xiang J, Wang X. Functional reorganization of brain regions into a network in childhood absence epilepsy: A magnetoencephalography study. Epilepsy Behav 2021; 122:108117. [PMID: 34246893 DOI: 10.1016/j.yebeh.2021.108117] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 05/24/2021] [Accepted: 05/25/2021] [Indexed: 11/26/2022]
Abstract
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.
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Affiliation(s)
- Yulei Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yihan Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Ke Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Lu Tang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Caiyun Wu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yuan Gao
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Hongxing Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Shuyang Huang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Zheng Hu
- Department of Neurology, Nanjing Children's Hospital, Nanjing, Jiangsu 210029, China
| | - Jing Xiang
- Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu 210029, China.
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Zhang K, Sun J, Sun Y, Niu K, Wang P, Wu C, Chen Q, Wang X. Pretreatment Source Location and Functional Connectivity Network Correlated With Therapy Response in Childhood Absence Epilepsy: A Magnetoencephalography Study. Front Neurol 2021; 12:692126. [PMID: 34413824 PMCID: PMC8368437 DOI: 10.3389/fneur.2021.692126] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 06/07/2021] [Indexed: 11/30/2022] Open
Abstract
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.
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Affiliation(s)
- Ke Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Yulei Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Kai Niu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Pengfei Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Caiyun Wu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Qiqi Chen
- MEG Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
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11
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Oliva JT, Rosa JLG. Binary and multiclass classifiers based on multitaper spectral features for epilepsy detection. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102469] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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