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Hu J, Chen G, Zeng Z, Ran H, Zhang R, Yu Q, Xie Y, He Y, Wang F, Li X, Huang K, Liu H, Zhang T. Systematically altered connectome gradient in benign childhood epilepsy with centrotemporal spikes: Potential effect on cognitive function. Neuroimage Clin 2024; 43:103628. [PMID: 38850833 PMCID: PMC11201345 DOI: 10.1016/j.nicl.2024.103628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 05/06/2024] [Accepted: 06/01/2024] [Indexed: 06/10/2024]
Abstract
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.
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Affiliation(s)
- Jie Hu
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China; Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Guiqin Chen
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China; Department of Radiology, The Second Affiliated Hospital of Guizhou University of TCM, Guiyang 550001, China
| | - Zhen Zeng
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Haifeng Ran
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Ruoxi Zhang
- Department of Radiology, The Second Affiliated Hospital of Guizhou University of TCM, Guiyang 550001, China
| | - Qiane Yu
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Yuxin Xie
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Yulun He
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Fuqin Wang
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Xuhong Li
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Kexing Huang
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Heng Liu
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China.
| | - Tijiang Zhang
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China.
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Feng X, Piper RJ, Prentice F, Clayden JD, Baldeweg T. Functional brain connectivity in children with focal epilepsy: A systematic review of functional MRI studies. Seizure 2024; 117:164-173. [PMID: 38432080 DOI: 10.1016/j.seizure.2024.02.021] [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: 12/18/2023] [Revised: 02/26/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024] Open
Abstract
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.
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Affiliation(s)
- Xiyu Feng
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom
| | - Rory J Piper
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom; Department of Neurosurgery, Great Ormond Street Hospital, London, United Kingdom
| | - Freya Prentice
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom
| | - Jonathan D Clayden
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom
| | - Torsten Baldeweg
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom.
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Chiang CT, Yang RC, Kao YC, Wu RC, Ouyang CS, Lin LC. Connectivity Disturbances in Self-Limited Epilepsy with Centrotemporal Spikes: A Partial Directed Coherence Analysis of Electroencephalogram. Clin EEG Neurosci 2024; 55:257-264. [PMID: 37229662 DOI: 10.1177/15500594231177979] [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] [Indexed: 05/27/2023]
Abstract
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.
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Affiliation(s)
- Ching-Tai Chiang
- Department of Computer and Communication, National Pingtung University, Pingtung, Taiwan (R.O.C.)
| | - Rei-Cheng Yang
- Departments of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan (R.O.C.)
| | - Yu-Chia Kao
- Departments of Pediatrics, E-Da Hospital, Kaohsiung, Taiwan (R.O.C.), Taiwan (R.O.C.)
| | - Rong-Ching Wu
- Department of Electrical Engineering, I-Shou University, Kaohsiung, Taiwan (R.O.C.)
| | - Chen-Sen Ouyang
- Department of Information Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan (R.O.C.)
| | - Lung-Chang Lin
- Departments of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan (R.O.C.)
- Department of Pediatrics, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan (R.O.C)
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Xu F, Li Y, Wang Y, Wang S, Sun F, Wang X. Interictal magnetic signals in new-onset Rolandic epilepsy may help with timing of treatment selection. Epilepsia Open 2024; 9:368-379. [PMID: 38145506 PMCID: PMC10839299 DOI: 10.1002/epi4.12884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 11/03/2023] [Accepted: 12/15/2023] [Indexed: 12/27/2023] Open
Abstract
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.
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Affiliation(s)
- Fengyuan Xu
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Yihan Li
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Yingfan Wang
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Siyi Wang
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Fangling Sun
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Xiaoshan Wang
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
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Zhang Q, Li J, He Y, Yang F, Xu Q, Larivière S, Bernhardt BC, Liao W, Lu G, Zhang Z. Atypical functional connectivity hierarchy in Rolandic epilepsy. Commun Biol 2023; 6:704. [PMID: 37429897 DOI: 10.1038/s42003-023-05075-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 06/26/2023] [Indexed: 07/12/2023] Open
Abstract
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.
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Affiliation(s)
- Qirui Zhang
- Department of Diagnostic Radiology, Jinling Hospital, the First School of Clinical Medicine, Southern Medical University, Nanjing, 210002, China
- Department of Diagnostic Radiology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Yan He
- Department of Neurology, Children's Hospital of Nanjing Medical University, Nanjing, 210002, China
| | - Fang Yang
- Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Qiang Xu
- Department of Diagnostic Radiology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210002, China
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, H3A 2B4, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, H3A 2B4, Canada
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Guangming Lu
- Department of Diagnostic Radiology, Jinling Hospital, the First School of Clinical Medicine, Southern Medical University, Nanjing, 210002, China.
- Department of Diagnostic Radiology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China.
| | - Zhiqiang Zhang
- Department of Diagnostic Radiology, Jinling Hospital, the First School of Clinical Medicine, Southern Medical University, Nanjing, 210002, China.
- Department of Diagnostic Radiology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, 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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Wang S, Wang Y, Li Y, Sun J, Wang P, Niu K, Xu Y, Li Y, Sun F, Chen Q, Wang X. Alternations of neuromagnetic activity across neurocognitive core networks among benign childhood epilepsy with centrotemporal spikes: A multi-frequency MEG study. Front Neurosci 2023; 17:1101127. [PMID: 36908802 PMCID: PMC9992197 DOI: 10.3389/fnins.2023.1101127] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 02/07/2023] [Indexed: 02/24/2023] Open
Abstract
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.
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Affiliation(s)
- 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
| | - Yihan Li
- 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
| | - Pengfei Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Kai Niu
- 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
| | - Yanzhang Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Fangling Sun
- Department of Neurology, The Affiliated Brain Hospital of 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, China
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Goad BS, Lee-Messer C, He Z, Porter BE, Baumer FM. Connectivity increases during spikes and spike-free periods in self-limited epilepsy with centrotemporal spikes. Clin Neurophysiol 2022; 144:123-134. [PMID: 36307364 PMCID: PMC10883644 DOI: 10.1016/j.clinph.2022.09.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/01/2022] [Accepted: 09/13/2022] [Indexed: 12/26/2022]
Abstract
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.
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Affiliation(s)
- Beatrice S Goad
- Department of Neurology, Stanford University School of Medicine, Palo Alto, CA, USA.
| | | | - Zihuai He
- Department of Neurology, Stanford University School of Medicine, Palo Alto, CA, USA.
| | - Brenda E Porter
- Department of Neurology, Stanford University School of Medicine, Palo Alto, CA, USA.
| | - Fiona M Baumer
- Department of Neurology, Stanford University School of Medicine, Palo Alto, CA, USA.
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Xu K, Wang F, Geng B, Peng Y, Zhang S, Li P, Chen D, Zeng X, Liu H, Liu P. Abnormal percent amplitude of fluctuation and functional connectivity within and between networks in benign epilepsy with centrotemporal spikes. Epilepsy Res 2022; 185:106989. [DOI: 10.1016/j.eplepsyres.2022.106989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 06/21/2022] [Accepted: 07/18/2022] [Indexed: 11/25/2022]
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Yang Y, Wang F, Andrade-Machado R, De Vito A, Wang J, Zhang T, Liu H. Disrupted functional connectivity patterns of the left inferior frontal gyrus subregions in benign childhood epilepsy with centrotemporal spikes. Transl Pediatr 2022; 11:1552-1561. [PMID: 36247884 PMCID: PMC9561512 DOI: 10.21037/tp-22-270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/26/2022] [Indexed: 11/25/2022] Open
Abstract
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.
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Affiliation(s)
- Yang Yang
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi, China.,Department of Radiology, Suining Central Hospital, Suining, China
| | - Fuqin Wang
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi, China
| | - René Andrade-Machado
- Epilepsy Fellow at Children Hospital of Michigan, Detroit Medical Center, Detroit, MI, USA
| | - Andrea De Vito
- Department of Neuroradiology, H. S. Gerardo Monza, Monza, Italy
| | - Jiaojian Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Tijiang Zhang
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi, China
| | - Heng Liu
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi, China
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11
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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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12
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Li Q, Westover MB, Zhang R, Chu CJ. Computational Evidence for a Competitive Thalamocortical Model of Spikes and Spindle Activity in Rolandic Epilepsy. Front Comput Neurosci 2021; 15:680549. [PMID: 34220477 PMCID: PMC8249809 DOI: 10.3389/fncom.2021.680549] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 05/12/2021] [Indexed: 11/24/2022] Open
Abstract
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.
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Affiliation(s)
- Qiang Li
- Medical Big Data Research Center, Northwest University, Xi'an, China
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - M. Brandon Westover
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Rui Zhang
- Medical Big Data Research Center, Northwest University, Xi'an, China
| | - Catherine J. Chu
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
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13
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Jiang S, Li H, Liu L, Yao D, Luo C. Voxel-wise functional connectivity of the default mode network in epilepsies: a systematic review and meta-analysis. Curr Neuropharmacol 2021; 20:254-266. [PMID: 33823767 PMCID: PMC9199542 DOI: 10.2174/1570159x19666210325130624] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 02/24/2021] [Accepted: 03/18/2021] [Indexed: 11/22/2022] Open
Abstract
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.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Linli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
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14
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Evaluation of patients with epileptiform activities in the posterior temporal-parietal-occipital regions. Neurol Sci 2021; 42:4607-4613. [PMID: 33661483 DOI: 10.1007/s10072-021-05154-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 02/23/2021] [Indexed: 10/22/2022]
Abstract
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.
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15
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Chen H, Lu F, He B. Topographic property of backpropagation artificial neural network: From human functional connectivity network to artificial neural network. Neurocomputing 2020. [DOI: 10.1016/j.neucom.2020.07.103] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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16
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Reh R, Williams LJ, Todd RM, Ward LM. Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication. Behav Brain Res 2020; 399:113016. [PMID: 33212087 DOI: 10.1016/j.bbr.2020.113016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 12/27/2022]
Abstract
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.
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Affiliation(s)
- Rebecca Reh
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada
| | - Lynne J Williams
- BC Children's Hospital MRI Research Facility, 4480 Oak Street, Vancouver, BC V6H 0B3, Canada
| | - Rebecca M Todd
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada; University of British Columbia, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada.
| | - Lawrence M Ward
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada; University of British Columbia, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
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17
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Jiang S, Luo C, Huang Y, Li Z, Chen Y, Li X, Pei H, Wang P, Wang X, Yao D. Altered Static and Dynamic Spontaneous Neural Activity in Drug-Naïve and Drug-Receiving Benign Childhood Epilepsy With Centrotemporal Spikes. Front Hum Neurosci 2020; 14:361. [PMID: 33005141 PMCID: PMC7485420 DOI: 10.3389/fnhum.2020.00361] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 08/07/2020] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, China
| | - Yang Huang
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhiliang Li
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiangkui Li
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Pingfu Wang
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoming Wang
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, China
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18
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Anomalous intrinsic connectivity within and between visual and auditory networks in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2020; 100:109889. [PMID: 32067960 DOI: 10.1016/j.pnpbp.2020.109889] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 01/30/2020] [Accepted: 02/14/2020] [Indexed: 01/07/2023]
Abstract
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.
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19
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He W, Liu H, Liu Z, Wu Q. Electrical status epilepticus in sleep affects intrinsically connected networks in patients with benign childhood epilepsy with centrotemporal spikes. Epilepsy Behav 2020; 106:107032. [PMID: 32220803 DOI: 10.1016/j.yebeh.2020.107032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 02/14/2020] [Accepted: 03/04/2020] [Indexed: 12/19/2022]
Abstract
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.
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Affiliation(s)
- Wen He
- Radiology Department of Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Renmin Middle Road 253rd, Guangzhou 510220, China
| | - Hongsheng Liu
- Radiology Department of Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Renmin Middle Road 253rd, Guangzhou 510220, China.
| | - Zhenqing Liu
- Radiology Department of Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Renmin Middle Road 253rd, Guangzhou 510220, China
| | - Qianqian Wu
- Radiology Department of Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Renmin Middle Road 253rd, Guangzhou 510220, China
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20
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Li Y, Yu Z, Chen Y, Yang C, Li Y, Allen Li X, Li B. Automatic Seizure Detection using Fully Convolutional Nested LSTM. Int J Neural Syst 2020; 30:2050019. [DOI: 10.1142/s0129065720500197] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
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.
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Affiliation(s)
- Yang Li
- Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, P. R. China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, P. R. China
| | - Zuyi Yu
- School of Information Science and Engineering, Shandong University, Jinan, Shandong 250100, P. R. China
| | - Yang Chen
- Laboratory of Image Science and Technology, Southeast University, Nanjing, Jiangsu 210096, P. R. China
| | - Chunfeng Yang
- Laboratory of Image Science and Technology, Southeast University, Nanjing, Jiangsu 210096, P. R. China
| | - Yue Li
- School of Clinical Medicine, Dali University, Dali, Yunnan 671000, P. R. China
| | - X. Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Baosheng Li
- Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, P. R. China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, P. R. China
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21
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Abnormal dynamics of functional connectivity density in children with benign epilepsy with centrotemporal spikes. Brain Imaging Behav 2020; 13:985-994. [PMID: 29956102 DOI: 10.1007/s11682-018-9914-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
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.
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Savaş M, Tunçer AM, Çokar AÖ, Demirbilek AV, Tüzün E. Impact of epilepsy on language and discourse: Two self-limited focal epileptic syndromes of childhood. Epilepsy Behav 2020; 102:106671. [PMID: 31805505 DOI: 10.1016/j.yebeh.2019.106671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 10/12/2019] [Accepted: 10/12/2019] [Indexed: 11/27/2022]
Abstract
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.
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Affiliation(s)
- Merve Savaş
- Department of Speech and Language Therapy, Faculty of Health Science, Biruni Universty, Istanbul, Turkey.
| | - Aylin Müge Tunçer
- Department of Speech and Language Therapy, Faculty of Health Science, Anadolu Universty, Eskişehir, Turkey
| | - Ayşe Özlem Çokar
- Department of Neurology, Haseki Research and Training Hospital, Health Sciences University, Istanbul, Turkey
| | - Ahmet Veysi Demirbilek
- Department of Neurology, Cerrahpaşa Faculty of Medicine, İstanbul Universty, Istanbul, Turkey
| | - Erdem Tüzün
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, İstanbul Universty, Istanbul, Turkey
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Han S, Wang Y, Liao W, Duan X, Guo J, Yu Y, Ye L, Li J, Chen X, Chen H. The distinguishing intrinsic brain circuitry in treatment-naïve first-episode schizophrenia: Ensemble learning classification. Neurocomputing 2019. [DOI: 10.1016/j.neucom.2019.07.061] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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File B, Nánási T, Tóth E, Bokodi V, Tóth B, Hajnal B, Kardos Z, Entz L, Erőss L, Ulbert I, Fabó D. Reorganization of Large-Scale Functional Networks During Low-Frequency Electrical Stimulation of the Cortical Surface. Int J Neural Syst 2019; 30:1950022. [DOI: 10.1142/s0129065719500229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
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.
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Affiliation(s)
- Bálint File
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Computational Neuroscience Group, Wigner Research Centre for Physics, HAS, Budapest, H-1121, Hungary
| | - Tibor Nánási
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
- János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, H-1085, Hungary
| | - Emília Tóth
- Department of Neurology, University of Alabama at Birmingham, AL 35233, USA
| | - Virág Bokodi
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, H-1145, Hungary
| | - Brigitta Tóth
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
| | - Boglárka Hajnal
- Juhász Pál Epilepsy Centrum, National Institute of Clinical Neuroscience, Budapest, H-1145, Hungary
| | - Zsófia Kardos
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
| | - László Entz
- Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, H-1145, Hungary
| | - Loránd Erőss
- Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, H-1145, Hungary
| | - István Ulbert
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
| | - Dániel Fabó
- Juhász Pál Epilepsy Centrum, National Institute of Clinical Neuroscience, Budapest, H-1145, Hungary
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Shamshiri EA, Sheybani L, Vulliemoz S. The Role of EEG-fMRI in Studying Cognitive Network Alterations in Epilepsy. Front Neurol 2019; 10:1033. [PMID: 31608007 PMCID: PMC6771300 DOI: 10.3389/fneur.2019.01033] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 09/11/2019] [Indexed: 02/01/2023] Open
Abstract
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.
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Affiliation(s)
- Elhum A Shamshiri
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Laurent Sheybani
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland.,Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
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Bear JJ, Chapman KE, Tregellas JR. The epileptic network and cognition: What functional connectivity is teaching us about the childhood epilepsies. Epilepsia 2019; 60:1491-1507. [PMID: 31247129 PMCID: PMC7175745 DOI: 10.1111/epi.16098] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 05/09/2019] [Accepted: 06/05/2019] [Indexed: 12/13/2022]
Abstract
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.
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Affiliation(s)
- Joshua J Bear
- Department of Pediatrics, Section of Neurology, Children’s Hospital Colorado
- Department of Pediatrics, University of Colorado Anschutz Medical Campus
| | - Kevin E Chapman
- Department of Pediatrics, Section of Neurology, Children’s Hospital Colorado
- Department of Pediatrics, University of Colorado Anschutz Medical Campus
| | - Jason R Tregellas
- Department of Psychiatry, University of Colorado Anschutz Medical Campus
- Research Service, Rocky Mountain Regional VA Medical Center
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Jiang Y, Song L, Li X, Zhang Y, Chen Y, Jiang S, Hou C, Yao D, Wang X, Luo C. Dysfunctional white-matter networks in medicated and unmedicated benign epilepsy with centrotemporal spikes. Hum Brain Mapp 2019; 40:3113-3124. [PMID: 30937973 PMCID: PMC6865396 DOI: 10.1002/hbm.24584] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 03/11/2019] [Accepted: 03/18/2019] [Indexed: 12/18/2022] Open
Abstract
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.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Li Song
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Xuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Yaodan Zhang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
- Chengdu University of Traditional Chinese MedicineChengdu, SichuanChina
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Changyue Hou
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xiaoming Wang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
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Network characteristics in benign epilepsy with centro-temporal spikes patients indicating defective connectivity during spindle sleep: A partial directed coherence study of EEG signals. Clin Neurophysiol 2018; 129:2372-2379. [DOI: 10.1016/j.clinph.2018.09.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 08/31/2018] [Accepted: 09/07/2018] [Indexed: 11/19/2022]
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Jiang LW, Qian RB, Fu XM, Zhang D, Peng N, Niu CS, Wang YH. Altered attention networks and DMN in refractory epilepsy: A resting-state functional and causal connectivity study. Epilepsy Behav 2018; 88:81-86. [PMID: 30243110 DOI: 10.1016/j.yebeh.2018.06.045] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 06/21/2018] [Accepted: 06/21/2018] [Indexed: 12/19/2022]
Abstract
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.
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Affiliation(s)
- Lu-Wei Jiang
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; School of Neurosurgery, Anhui Medical University, 81 Meishan Road, Hefei, Anhui Province 230032, China
| | - Ruo-Bing Qian
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China.
| | - Xian-Ming Fu
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Dong Zhang
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Nan Peng
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Chao-Shi Niu
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Ye-Han Wang
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China
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Kumar J, Solaiman A, Mahakkanukrauh P, Mohamed R, Das S. Sleep Related Epilepsy and Pharmacotherapy: An Insight. Front Pharmacol 2018; 9:1088. [PMID: 30319421 PMCID: PMC6171479 DOI: 10.3389/fphar.2018.01088] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 09/07/2018] [Indexed: 01/26/2023] Open
Abstract
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.
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Affiliation(s)
- Jaya Kumar
- Department of Physiology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
| | - Amro Solaiman
- Department of Anatomy, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
| | - Pasuk Mahakkanukrauh
- Department of Anatomy, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
- Excellence Centre in Forensic Osteology Research Center, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Rashidi Mohamed
- Department of Familty Medicine, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
| | - Srijit Das
- Department of Anatomy, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
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Altered Dynamic Functional Network Connectivity in Frontal Lobe Epilepsy. Brain Topogr 2018; 32:394-404. [DOI: 10.1007/s10548-018-0678-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2018] [Accepted: 09/10/2018] [Indexed: 01/10/2023]
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Tan G, Xiao F, Chen S, Wang H, Chen D, Zhu L, Xu D, Zhou D, Liu L. Frequency-specific alterations in the amplitude and synchronization of resting-state spontaneous low-frequency oscillations in benign childhood epilepsy with centrotemporal spikes. Epilepsy Res 2018; 145:178-184. [PMID: 30048931 DOI: 10.1016/j.eplepsyres.2018.07.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 07/15/2018] [Accepted: 07/18/2018] [Indexed: 02/05/2023]
Abstract
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.
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Affiliation(s)
- Ge Tan
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China
| | - Fenglai Xiao
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China
| | - Sihan Chen
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China
| | - Haijiao Wang
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China
| | - Deng Chen
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China
| | - Lina Zhu
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China
| | - Da Xu
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China.
| | - Ling Liu
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Guo Xue Xiang, Chengdu, 610041, Sichuan Province, China.
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Jiang S, Luo C, Gong J, Peng R, Ma S, Tan S, Ye G, Dong L, Yao D. Aberrant Thalamocortical Connectivity in Juvenile Myoclonic Epilepsy. Int J Neural Syst 2017; 28:1750034. [PMID: 28830309 DOI: 10.1142/s0129065717500344] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
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.
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Affiliation(s)
- S. Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - C. Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - J. Gong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - R. Peng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - S. Ma
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
- Neurology Department, Sichuan Provincial People’s Hospital, The affiliated Hospital of University of Electronic Science and Technology of China, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - S. Tan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
- Neurology Department, Sichuan Provincial People’s Hospital, The affiliated Hospital of University of Electronic Science and Technology of China, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - G. Ye
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - L. Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - D. Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
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Li R, Liao W, Yu Y, Chen H, Guo X, Tang YL, Chen H. Differential patterns of dynamic functional connectivity variability of striato-cortical circuitry in children with benign epilepsy with centrotemporal spikes. Hum Brain Mapp 2017; 39:1207-1217. [PMID: 29206330 DOI: 10.1002/hbm.23910] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 11/21/2017] [Accepted: 11/29/2017] [Indexed: 12/17/2022] Open
Abstract
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.
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Affiliation(s)
- Rong Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Yangyang Yu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Heng Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Xiaonan Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Ye-Lei Tang
- Departments of Neurology, The Second Affiliated Hospital of Medial College, Zhejiang University, Hangzhou, 310009, People's Republic of China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
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Fang J, Chen S, Luo C, Gong Q, An D, Zhou D. Altered language network in benign childhood epilepsy patients with spikes from non-dominant side: A resting-state fMRI study. Epilepsy Res 2017; 136:109-114. [PMID: 28822871 DOI: 10.1016/j.eplepsyres.2017.07.020] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Revised: 06/22/2017] [Accepted: 07/28/2017] [Indexed: 02/05/2023]
Abstract
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.
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Affiliation(s)
- Jiajia Fang
- Department of Neurology, The Fourth Affiliated Hospital, Zhejiang University, Yiwu, Zhejiang, China
| | - Sihan Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Cheng Luo
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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36
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Li Q, Chen Y, Wei Y, Chen S, Ma L, He Z, Chen Z. Functional Network Connectivity Patterns between Idiopathic Generalized Epilepsy with Myoclonic and Absence Seizures. Front Comput Neurosci 2017; 11:38. [PMID: 28588471 PMCID: PMC5440462 DOI: 10.3389/fncom.2017.00038] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Accepted: 05/04/2017] [Indexed: 11/17/2022] Open
Abstract
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.
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Affiliation(s)
- Qifu Li
- Department of Neurology, First Affiliated Hospital of Hainan Medical UniversityHaikou, China.,Department of Neurology, First Hospital of China Medical UniversityShenyang, China
| | - Yongmin Chen
- Department of Neurology, First Affiliated Hospital of Hainan Medical UniversityHaikou, China
| | - Yong Wei
- Department of Radiology, Maternal and Child Health Care Hospital of Hainan ProvinceHaikou, China
| | - Shengmei Chen
- Department of Neurology, First Affiliated Hospital of Hainan Medical UniversityHaikou, China
| | - Lin Ma
- Department of Neurology, First Affiliated Hospital of Hainan Medical UniversityHaikou, China
| | - Zhiyi He
- Department of Neurology, First Hospital of China Medical UniversityShenyang, China
| | - Zhibin Chen
- Department of Neurology, First Affiliated Hospital of Hainan Medical UniversityHaikou, China
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