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Yin Y, Qiu X, Nie L, Wang F, Luo X, Zhao C, Yu H, Luo D, Wang J, Liu H. Individual-based morphological brain network changes in children with Rolandic epilepsy. Clin Neurophysiol 2024; 165:90-96. [PMID: 38991378 DOI: 10.1016/j.clinph.2024.06.013] [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: 12/30/2023] [Revised: 04/09/2024] [Accepted: 06/15/2024] [Indexed: 07/13/2024]
Abstract
OBJECTIVE To investigate the local cortical morphology and individual-based morphological brain networks (MBNs) changes in children with Rolandic epilepsy (RE). METHODS Based on the structural MRI data of 56 children with RE and 56 healthy controls (HC), we constructed four types of individual-based MBNs using morphological indices (cortical thickness [CT], fractal dimension [FD], gyrification index [GI], and sulcal depth [SD]). The global and nodal properties of the brain networks were analyzed using graph theory. The between-group difference in local morphology and network topology was estimated, and partial correlation analysis was further analyzed. RESULTS Compared with the HC, children with RE showed regional GI increases in the right posterior cingulate gyrus and SD increases in the right anterior cingulate gyrus and medial prefrontal cortex. Regarding the network level, RE exhibited increased characteristic path length in CT-based and FD-based networks, while decreased FD-based network node efficiency in the right inferior frontal gyrus. No significant correlation between altered morphological features and clinical variables was found in RE. CONCLUSIONS These findings indicated that children with RE have disrupted morphological brain network organization beyond local morphology changes. SIGNIFICANCE The present study could provide more theoretical basis for exploring the neuropathological mechanisms in RE.
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Affiliation(s)
- Yu Yin
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Engineering Research Center of Intelligent Medical Imaging in Guizhou Higher Education Institutions, Zunyi 563003, China; Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Xiaofan Qiu
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Lisha Nie
- GE Healthcare, MR Research China, Beijing, China
| | - Fuqin Wang
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Engineering Research Center of Intelligent Medical Imaging in Guizhou Higher Education Institutions, Zunyi 563003, China
| | - Xinyu Luo
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Engineering Research Center of Intelligent Medical Imaging in Guizhou Higher Education Institutions, Zunyi 563003, China
| | - Chunfeng Zhao
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Engineering Research Center of Intelligent Medical Imaging in Guizhou Higher Education Institutions, Zunyi 563003, China
| | - Haoyue Yu
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Engineering Research Center of Intelligent Medical Imaging in Guizhou Higher Education Institutions, Zunyi 563003, China
| | - Dan Luo
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Engineering Research Center of Intelligent Medical Imaging in Guizhou Higher Education Institutions, Zunyi 563003, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Heng Liu
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Engineering Research Center of Intelligent Medical Imaging in Guizhou Higher Education Institutions, Zunyi 563003, China.
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Li C, Wang J, Zhou Y, Li T, Wu B, Yuan X, Li L, Qin R, Liu H, Chen L, Wang X. Sex-related patterns of functional brain networks in children and adolescents with autism spectrum disorder. Autism Res 2024; 17:1344-1355. [PMID: 39051596 DOI: 10.1002/aur.3180] [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: 03/04/2024] [Accepted: 06/13/2024] [Indexed: 07/27/2024]
Abstract
Although numerous studies have emphasized the male predominance in autism spectrum disorder (ASD), how sex differences are related to the topological organization of functional networks remains unclear. This study utilized imaging data from 86 ASD (43 females, aged 7-18 years) and 86 typically developing controls (TCs) (43 females, aged 7-18 years) obtained from Autism Brain Imaging Data Exchange databases, constructed individual whole-brain functional networks, used a graph theory analysis to compute topological metrics, and assessed sex-related differences in topological metrics using a 2 × 2 factorial design. At the global level, females with ASD exhibited significantly higher cluster coefficient and local efficiency than female TCs, while no significant difference was observed between males with ASD and male TCs. Meanwhile, the neurotypical sex differences in cluster coefficient and local efficiency observed in TCs were not present in ASD. At the nodal level, ASD exhibited abnormal nodal centrality in the left middle temporal gyrus.
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Affiliation(s)
- Cuicui Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jingxuan Wang
- Department of Painology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yunna Zhou
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Tong Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Baolin Wu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xianshun Yuan
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Lin Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Rui Qin
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Hongzhu Liu
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Linglong Chen
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, China
| | - Ximing Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
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He Q, Yang Z, Xue B, Song X, Zhang C, Yin C, Li Z, Deng Z, Sun S, Qiao H, Xie J, Hou Z. Epilepsy alters brain networks in patients with insular glioma. CNS Neurosci Ther 2024; 30:e14805. [PMID: 38887197 PMCID: PMC11183176 DOI: 10.1111/cns.14805] [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: 01/31/2024] [Revised: 05/13/2024] [Accepted: 05/30/2024] [Indexed: 06/20/2024] Open
Abstract
AIMS We intend to elucidate the alterations of cerebral networks in patients with insular glioma-related epilepsy (GRE) based on resting-state functional magnetic resonance images. METHODS We collected 62 insular glioma patients, who were subsequently categorized into glioma-related epilepsy (GRE) and glioma with no epilepsy (GnE) groups, and recruited 16 healthy individuals matched to the patient's age and gender to form the healthy control (HC) group. Graph theoretical analysis was applied to reveal differences in sensorimotor, default mode, visual, and executive networks among different subgroups. RESULTS No significant alterations in functional connectivity were found in either hemisphere insular glioma. Using graph theoretical analysis, differences were found in visual, sensorimotor, and default mode networks (p < 0.05). When the glioma located in the left hemisphere, the degree centrality was reduced in the GE group compared to the GnE group. When the glioma located in the right insula, the degree centrality, nodal efficiency, nodal local efficiency, and nodal clustering coefficient of the GE group were lower than those of the GnE group. CONCLUSION The impact of insular glioma itself and GRE on the brain network is widespread. The networks altered by insular GRE differ depending on the hemisphere location. GRE reduces the nodal properties of brain networks than that in insular glioma.
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Affiliation(s)
- Qifeng He
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zuocheng Yang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - BoWen Xue
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xinyu Song
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Chuanhao Zhang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - ChuanDong Yin
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zhenye Li
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zhenghai Deng
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Shengjun Sun
- Department of Neuroradiology, Beijing Neurosurgical Institute, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- Department of Radiology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Hui Qiao
- Department of Neurophysiology, Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
| | - Jian Xie
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zonggang Hou
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
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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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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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Epilepsy-related white matter network changes in patients with frontal lobe glioma. J Neuroradiol 2023; 50:258-265. [PMID: 35346748 DOI: 10.1016/j.neurad.2022.03.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/22/2022] [Accepted: 03/21/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE Epilepsy is a common symptom in patients with frontal lobe glioma. Tumor-related epilepsy was recently considered a type of network disease. Glioma can severely influence the integrity of the white matter network. The association between white matter network changes and presurgical epilepsy remains unclear in glioma patients. This study aims to identify alterations to the subcortical brain networks caused by glioma and glioma-related epilepsy. METHODS Sixty-one patients with frontal lobe gliomas were enrolled and stratified into the epileptic and non-epileptic groups. Additionally, 14 healthy participants were enrolled after matching for age, sex, and education level. All participants underwent diffusion tensor imaging. Graph theoretical analysis was applied to reveal topological changes in their white matter networks. Regions affected by tumors were excluded from the analysis. RESULTS Global efficiency was significantly decreased (p = 0.008), while the shortest path length increased (p = 0.02) in the left and right non-epileptic groups compared to the controls. A total of five edges exhibited decreased fiber count in the non-epileptic group (p < 0.05, false discovery rate-corrected). The topological properties and connectional edges showed no significant differences when comparing the epileptic groups and the controls. Additionally, the degree centrality of several nodes connected to the alternated edges was also diminished. CONCLUSIONS Compared to the controls, the epilepsy groups showed raletively intact WM networks, while the non-epileptsy groups had damaged network with lower efficiency and longer path length. These findings indicated that the occurrence of glioma related epilepsy have association with white matter network intergrity.
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Li Z, Hou X, Lu Y, Zhao H, Wang M, Xu B, Shi Q, Gui Q, Wu G, Shen M, Zhu W, Xu Q, Dong X, Cheng Q, Zhang J, Feng H. Study of brain network alternations in non-lesional epilepsy patients by BOLD-fMRI. Front Neurosci 2023; 16:1031163. [PMID: 36741055 PMCID: PMC9889547 DOI: 10.3389/fnins.2022.1031163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 12/30/2022] [Indexed: 01/20/2023] Open
Abstract
Objective To investigate the changes of brain network in epilepsy patients without intracranial lesions under resting conditions. Methods Twenty-six non-lesional epileptic patients and 42 normal controls were enrolled for BOLD-fMRI examination. The differences in brain network topological characteristics and functional network connectivity between the epilepsy group and the healthy controls were compared using graph theory analysis and independent component analysis. Results The area under the curve for local efficiency was significantly lower in the epilepsy patients compared with healthy controls, while there were no differences in global indicators. Patients with epilepsy had higher functional connectivity in 4 connected components than healthy controls (orbital superior frontal gyrus and medial superior frontal gyrus, medial superior frontal gyrus and angular gyrus, superior parietal gyrus and paracentral lobule, lingual gyrus, and thalamus). In addition, functional connectivity was enhanced in the default mode network, frontoparietal network, dorsal attention network, sensorimotor network, and auditory network in the epilepsy group. Conclusion The topological characteristics and functional connectivity of brain networks are changed in in non-lesional epilepsy patients. Abnormal functional connectivity may suggest reduced brain efficiency in epilepsy patients and also may be a compensatory response to brain function early at earlier stages of the disease.
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Affiliation(s)
- Zhisen Li
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaoxia Hou
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Yanli Lu
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Huimin Zhao
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Meixia Wang
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Bo Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qianru Shi
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qian Gui
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Guanhui Wu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Mingqiang Shen
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Wei Zhu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qinrong Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaofeng Dong
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qingzhang Cheng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Jibin Zhang
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Hongxuan Feng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China,*Correspondence: Hongxuan Feng,
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Abnormalities of hemispheric specialization in drug-naïve and drug-receiving self-limited epilepsy with centrotemporal spikes. Epilepsy Behav 2022; 136:108940. [PMID: 36228484 DOI: 10.1016/j.yebeh.2022.108940] [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: 06/10/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 12/14/2022]
Abstract
PURPOSE Self-limited epilepsy with centrotemporal spikes (SLECTS) is a pediatric benign epilepsy but often accompanied by subsequent (in adulthood) functional changes such as language, which are thought to have distinct areas of hemispheric lateralization and functional differentiation. This study aimed to explore hemispheric specialization measured by resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity in drug-naïve and drug-receiving SLECTS. METHODS Hemispheric specialization was quantified in three groups of children, including 21 drug-naïve patients (DNP) with SLECTS, 34 drug-receiving patients (DRP) with SLECTS and 36 demographically matched typical development (TD). RESULTS Compared with the TD group, both the DNP and DRP groups exhibited significantly higher specialization in the left superior temporal gyrus, right parahippocampus, left putamen, and right caudate. The DNP group exhibited significantly higher hemispheric specialization in the right precentral gyrus and right inferior temporal gyrus, while the DRP group demonstrated significantly higher hemispheric specialization in the left postcentral gyrus and right hippocampus than the TD group. Furthermore, bilateral cerebellum_6 showed opposing hemispheric specialization trends in the two patient groups. Further meta-analytical mapping demonstrated that hemispheric specialization-related differential brain regions are primarily involved in language processing. CONCLUSION Our findings showed that children with SLECTS had altered hemispheric specialization, mainly in language processing regions, suggesting both abnormal intrahemispheric segregation and interhemispheric integration in these children.
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Fang S, Weng S, Li L, Guo Y, Fan X, Zhang Z, Jiang T, Wang Y. Association of homotopic areas in the right hemisphere with language deficits in the short term after tumor resection. J Neurosurg 2022; 138:1206-1215. [PMID: 36308477 DOI: 10.3171/2022.9.jns221475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/08/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE
It is important to identify language deficit and recovery in the week following a tumor resection procedure. The homotopic Broca’s area and the superior longitudinal fasciculus in the right hemisphere participate in language functional compensation. However, the nodes in these structures, as well as their contributions to language rehabilitation, remain unknown. In this study, the authors investigated the association of homotopic areas in the right hemisphere with language deficit.
METHODS
The authors retrospectively reviewed the records of 50 right-handed patients with left hemispheric lower-grade glioma that had been surgically treated between June 2020 and May 2022. The patients were divided into normal and aphasia groups based on their postoperative aphasia quotient (AQ) from the Western Aphasia Battery. Preoperative (within 24 hours before surgery) and postoperative (7 days after tumor resection) diffusion tensor images were used to reveal alterations of structural networks by using graphic theory analysis. The shortest distance between the glioma and the nodes belonging to the language network (SDTN) was quantitatively assessed. Pearson’s correlation and causal mediation analyses were used to identify correlations and mediator factors among SDTN, topological properties, and AQs.
RESULTS
Postoperative nodal local efficiency of the node dorsal Brodmann area (BA) 44 (A44d; p = 0.0330), nodal clustering coefficient of the nodes A44d (p = 0.0402) and dorsal lateral BA6 (A6dl; p = 0.0097), and nodal degree centrality (p = 0.0058) of the node medial BA7 (A7m) were higher in the normal group than in the aphasia group. SDTN was positively correlated with postoperative AQ (r = 0.457, p = 0.0009) and ΔAQ (r = 0.588, p < 0.0001). The nodal local efficiency of node A44d and the nodal efficiency, nodal betweenness centrality, and degree centrality of node A7m were mediators of SDTN and postoperative AQs.
CONCLUSIONS
The decreased ability of nodes A44d, A6dl, and A7m to convey information in the right hemisphere was associated with short-term language deficits after tumor resection. A smaller SDTN induced a worsened postoperative language deficit through a significant decrease in the ability to convey information from these three nodes.
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Affiliation(s)
- Shengyu Fang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing
- Beijing Neurosurgical Institute, Capital Medical University, Beijing; and
| | - Shimeng Weng
- Beijing Neurosurgical Institute, Capital Medical University, Beijing; and
| | - Lianwang Li
- Beijing Neurosurgical Institute, Capital Medical University, Beijing; and
| | - Yuhao Guo
- Beijing Neurosurgical Institute, Capital Medical University, Beijing; and
| | - Xing Fan
- Beijing Neurosurgical Institute, Capital Medical University, Beijing; and
| | - Zhong Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing
| | - Tao Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing
- Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain Tumors, Chinese Academy of Medical Sciences, Beijing, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing
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11
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Zhang S, Tang J, Huang J, Suo G, Zhou Z, You B, Dai Y, Liu Y. Whole-Brain Dynamic Resting-State Functional Network Analysis in Benign Epilepsy with Centrotemporal Spikes. IEEE J Biomed Health Inform 2022; 26:3813-3821. [PMID: 35380976 DOI: 10.1109/jbhi.2022.3164907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Benign epilepsy with centrotemporal spikes (BECTS), the most common type of epilepsy among children, is considered a network disorder. Both fMRI and EEG source imaging (ESI) studies have indicated that BECTS is associated with static resting-state functional network (SFN) alterations (e.g., decreased global efficiency) in source space. However, we find that the abovementioned alterations are not significant when the SFN calculations are performed in the scalp space using only clinical routine low-density (e.g., 19 channels) EEG recordings (shown in our results). In the context of EEG microstates, it is clear that networks in the scalp space with resting-state EEG recordings dynamically reconfigure in a well-organized way based on different functional states. We are therefore inspired to propose a whole-brain dynamic resting-state functional network (DFN) computation method based on resting-state low-density EEG recordings with four classical microstates in scalp space. Notably, on the one hand, this approach is suitable for clinical conditions, and, on the other hand, the dynamic alternations calculated with a DFN may promote our understanding of how the networks change in BECTS. We analysed the changes in a DFN in six frequency bands (, low, high, and) in patients with BECTS compared to those for healthy controls. Superior to traditional SFNs, the proposed DFN can reveal significant differences between individuals with BECTS and healthy controls (e.g., lower global efficiency), thus matching traditional fMRI and ESI methods in the source space. Our method directly performs DFN computations from low-density EEG recordings and avoids complex ESI computations, making it promising for clinical applications, especially in the outpatient diagnosis stage.
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12
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Coluzzi D, Pirastru A, Pelizzari L, Cabinio M, Laganà MM, Baselli G, Baglio F. Development and Testing of SPIDER-NET: An Interactive Tool for Brain Connectogram Visualization, Sub-Network Exploration and Graph Metrics Quantification. Front Neurosci 2022; 16:818385. [PMID: 35368253 PMCID: PMC8968144 DOI: 10.3389/fnins.2022.818385] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/17/2022] [Indexed: 11/13/2022] Open
Abstract
Brain connectomics consists in the modeling of human brain as networks, mathematically represented as numerical connectivity matrices. However, this representation may result in difficult interpretation of the data. To overcome this limitation, graphical representation by connectograms is currently used via open-source tools, which, however, lack user-friendly interfaces and options to explore specific sub-networks. In this context, we developed SPIDER-NET (Software Package Ideal for Deriving Enhanced Representations of brain NETworks), an easy-to-use, flexible, and interactive tool for connectograms generation and sub-network exploration. This study aims to present SPIDER-NET and to test its potential impact on pilot cases. As a working example, structural connectivity (SC) was investigated with SPIDER-NET in a group of 17 healthy controls (HCs) and in two subjects with stroke injury (Case 1 and Case 2, both with a focal lesion affecting part of the right frontal lobe, insular cortex and subcortical structures). 165 parcels were determined from individual structural magnetic resonance imaging data by using the Destrieux atlas, and defined as nodes. SC matrices were derived with Diffusion Tensor Imaging tractography. SC matrices of HCs were averaged to obtain a single group matrix. SC matrices were then used as input for SPIDER-NET. First, SPIDER-NET was used to derive the connectogram of the right hemisphere of Case 1 and Case 2. Then, a sub-network of interest (i.e., including gray matter regions affected by the stroke lesions) was interactively selected and the associated connectograms were derived for Case 1, Case 2 and HCs. Finally, graph-based metrics were derived for whole-brain SC matrices of Case 1, Case 2 and HCs. The software resulted effective in representing the expected (dis) connectivity pattern in the hemisphere affected by the stroke lesion in Cases 1 and 2. Furthermore, SPIDER-NET allowed to test an a priori hypothesis by interactively extracting a sub-network of interest: Case 1 showed a sub-network connectivity pattern different from Case 2, reflecting the different clinical severity. Global and local graph-based metrics derived with SPIDER-NET were different between cases with stroke injury and HCs. The tool proved to be accessible, intuitive, and interactive in brain connectivity investigation and provided both qualitative and quantitative evidence.
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Affiliation(s)
- Davide Coluzzi
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy
- *Correspondence: Davide Coluzzi,
| | - Alice Pirastru
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy
- Alice Pirastru,
| | | | - Monia Cabinio
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy
| | | | - Giuseppe Baselli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy
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13
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Functional network connectivity imprint in febrile seizures. Sci Rep 2022; 12:3267. [PMID: 35228583 PMCID: PMC8885759 DOI: 10.1038/s41598-022-07173-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 01/10/2022] [Indexed: 11/11/2022] Open
Abstract
Complex febrile seizures (CFS), a subset of paediatric febrile seizures (FS), have been studied for their prognosis, epileptogenic potential and neurocognitive outcome. We evaluated their functional connectivity differences with simple febrile seizures (SFS) in children with recent-onset FS. Resting-state fMRI (rs-fMRI) datasets of 24 children with recently diagnosed FS (SFS-n = 11; CFS-n = 13) were analysed. Functional connectivity (FC) was estimated using time series correlation of seed region–to-whole-brain-voxels and network topology was assessed using graph theory measures. Regional connectivity differences were correlated with clinical characteristics (FDR corrected p < 0.05). CFS patients demonstrated increased FC of the bilateral middle temporal pole (MTP), and bilateral thalami when compared to SFS. Network topology study revealed increased clustering coefficient and decreased participation coefficient in basal ganglia and thalamus suggesting an inefficient-unbalanced network topology in patients with CFS. The number of seizure recurrences negatively correlated with the integration of Left Thalamus (r = − 0.58) and FC of Left MTP to 'Right Supplementary Motor and left Precentral' gyrus (r = − 0.53). The FC of Right MTP to Left Amygdala, Putamen, Parahippocampal, and Orbital Frontal Cortex (r = 0.61) and FC of Left Thalamus to left Putamen, Pallidum, Caudate, Thalamus Hippocampus and Insula (r 0.55) showed a positive correlation to the duration of the longest seizure. The findings of the current study report altered connectivity in children with CFS proportional to the seizure recurrence and duration. Regardless of the causal/consequential nature, such observations demonstrate the imprint of these disease-defining variables of febrile seizures on the developing brain.
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14
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Li Y, Zhang T, Feng J, Qian S, Wu S, Zhou R, Wang J, Sa G, Wang X, Li L, Chen F, Yang H, Zhang H, Tian M. Processing speed dysfunction is associated with functional corticostriatal circuit alterations in childhood epilepsy with centrotemporal spikes: a PET and fMRI study. Eur J Nucl Med Mol Imaging 2022; 49:3186-3196. [PMID: 35199226 PMCID: PMC9250469 DOI: 10.1007/s00259-022-05740-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 02/17/2022] [Indexed: 11/19/2022]
Abstract
Purpose Epilepsy with centrotemporal spikes (ECTS) is the most common epilepsy syndrome in children and usually presents with cognitive dysfunctions. However, little is known about the processing speed dysfunction and the associated neuroimaging mechanism in ECTS. This study aims to investigate the brain functional abnormality of processing speed dysfunction in ECTS patients by using the 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI). Methods This prospective study recruited twenty-eight ECTS patients who underwent the 18F-FDG PET, rs-fMRI, and neuropsychological examinations. Twenty children with extracranial tumors were included as PET controls, and 20 healthy children were recruited as MRI controls. The PET image analysis investigated glucose metabolism by determining standardized uptake value ratio (SUVR). The MRI image analysis explored abnormal functional connectivity (FC) within the cortical–striatal circuit through network-based statistical (NBS) analysis. Correlation analysis was performed to explore the relationship between SUVR, FC, and processing speed index (PSI). Results Compared with healthy controls, ECTS patients showed normal intelligence quotient but significantly decreased PSI (P = 0.04). PET analysis showed significantly decreased SUVRs within bilateral caudate, putamen, pallidum, left NAc, right rostral middle frontal gyrus, and frontal pole of ECTS patients (P < 0.05). Rs-fMRI analysis showed absolute values of 20 FCs were significantly decreased in ECTS patients compared with MRI controls, which connected 16 distinct ROIs. The average SUVR of right caudate and the average of 20 FCs were positively correlated with PSI in ECTS patients (P = 0.034 and P = 0.005, respectively). Conclusion This study indicated that ECTS patients presented significantly reduced PSI, which is closely associated with decreased SUVR and FC of cortical–striatal circuit. Caudate played an important role in processing speed dysfunction. Clinical trial registration NCT04954729; registered on July 8, 2021, public site, https://clinicaltrials.gov/ct2/show/NCT04954729 Supplementary Information The online version contains supplementary material available at 10.1007/s00259-022-05740-w.
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Affiliation(s)
- Yuting Li
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Teng Zhang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Jianhua Feng
- Department of Pediatrics, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shufang Qian
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Shuang Wu
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Rui Zhou
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Jing Wang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Guo Sa
- Department of Radiology, The First Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiawan Wang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Lina Li
- College of Medical Imaging, Shanxi Medical University, Taiyuan, China
| | - Feng Chen
- Department of Radiology, The First Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hong Yang
- Department of Radiology, The First Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hong Zhang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China. .,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China. .,The College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
| | - Mei Tian
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China.
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15
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Topological Characteristics Associated with Intraoperative Stimulation Related Epilepsy of Glioma Patients: A DTI Network Study. Brain Sci 2021; 12:brainsci12010060. [PMID: 35053803 PMCID: PMC8774024 DOI: 10.3390/brainsci12010060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 12/26/2021] [Accepted: 12/29/2021] [Indexed: 11/17/2022] Open
Abstract
Background: Awake craniotomy with intraoperative stimulation has been utilized in glioma surgical resection to preserve the quality of life. Epilepsy may occur in 5–20% of cases, leading to severe consequences. This study aimed to discuss the mechanism of intraoperative stimulation-related epilepsy (ISE) using DTI-based graph theoretical analysis. Methods: Twenty patients with motor-area glioma were enrolled and divided into two groups (Ep and nEp) according to the presence of ISE. Additionally, a group of 10 healthy participants matched by age, sex, and years of education was also included. All participants underwent T1, T2, and DTI examinations. Graph theoretical analysis was applied to reveal the topological characteristics of white matter networks. Results: Three connections were found to be significantly lower in at least one weighting in the Ep group. These connections were between A1/2/3truL and A4ulL, A1/2/3truR and A4tR, and A6mL and A6mR. Global efficiency was significantly decreased, while the shortest path length increased in the Ep group in at least one weighting. Ten nodes exhibited significant differences in nodal efficiency and degree centrality analyses. The nodes A6mL and A6mR showed a marked decrease in total four weightings in the Ep group. Conclusions: The hub nodes A6mL and A6mR are disconnected in patients with ISE, causing subsequent lower efficiency of global and regional networks. These findings provide a basis for presurgical assessment of ISE, for which caution should be taken when it involves hub nodes during intraoperative electrical stimulation.
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16
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Slinger G, Otte WM, Braun KPJ, van Diessen E. An updated systematic review and meta-analysis of brain network organization in focal epilepsy: Looking back and forth. Neurosci Biobehav Rev 2021; 132:211-223. [PMID: 34813826 DOI: 10.1016/j.neubiorev.2021.11.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 06/23/2021] [Accepted: 11/17/2021] [Indexed: 01/10/2023]
Abstract
Abnormalities of the brain network organization in focal epilepsy have been extensively quantified. However, the extent and directionality of abnormalities are highly variable and subtype insensitive. We conducted meta-analyses to obtain a more accurate and epilepsy type-specific quantification of the interictal global brain network organization in focal epilepsy. By using random-effects models, we estimated differences in average clustering coefficient, average path length, and modularity between patients with focal epilepsy and controls, based on 45 studies with a total sample size of 1,468 patients and 1,021 controls. Structural networks had a significant lower level of integration in patients with epilepsy as compared to controls, with a standardized mean difference of -0.334 (95 % confidence interval -0.631 to -0.038; p-value 0.027). Functional networks did not differ between patients and controls, except for the beta band clustering coefficient. Our meta-analyses show that differences in the brain network organization are not as well defined as individual studies often propose. We discuss potential pitfalls and suggestions to enhance the yield and clinical value of network studies.
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Affiliation(s)
- Geertruida Slinger
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands.
| | - Willem M Otte
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands; Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Kees P J Braun
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Eric van Diessen
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
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17
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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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18
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Xu Y, Xu Q, Zhang Q, Stufflebeam SM, Yang F, He Y, Hu Z, Weng Y, Xiao J, Lu G, Zhang Z. Influence of epileptogenic region on brain structural changes in Rolandic epilepsy. Brain Imaging Behav 2021; 16:424-434. [PMID: 34420145 DOI: 10.1007/s11682-021-00517-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2021] [Indexed: 10/20/2022]
Abstract
To investigate the influence of epileptogenic cortex (Rolandic areas) with executive functions in Rolandic epilepsy using structural covariance analysis of structural magnetic resonance imaging (MRI). Structural MRI data of drug-naive patients with Rolandic epilepsy (n = 70) and typically developing children as healthy controls (n = 83) were analyzed using voxel-based morphometry. Gray matter volumes in the patients were compared with those of healthy controls, and were further correlated with epilepsy duration and cognitive score of executive function, respectively. By applying Granger causal analysis to the sequenced morphometric data according to disease progression information, causal network of structural covariance was constructed to assess the causal influence of structural changes from Rolandic cortices to the regions engaging executive function in the patients. Compared with healthy controls, epilepsy patients showed increased gray matter volume in the Rolandic regions, and also the regions engaging in executive function. Covariance network analyses showed that along with disease progression, the Rolandic regions imposed positive causal influence on the regions engaging in executive function. In the patients with Rolandic epilepsy, epileptogenic regions have causal influence on the structural changes in the regions of executive function, implicating damaging effects of Rolandic epilepsy on human brain.
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Affiliation(s)
- Yin Xu
- Department of Medical Imaging, Jinling Hospital, Nanjing Clinical School, Southern Medical University, Nanjing, 210002, China.,Institute of Neurology, Anhui University of Traditional Chinese Medicine, Hefei, China
| | - Qiang Xu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Qirui Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing Clinical School, Southern Medical University, Nanjing, 210002, China.,Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 Thirteenth Street, Suite 2301, Charlestown, MA, 02129, USA
| | - Fang Yang
- Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Yan He
- Department of Neurology, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Zheng Hu
- Department of Neurology, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Junhao Xiao
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Nanjing Clinical School, Southern Medical University, Nanjing, 210002, China. .,Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China. .,State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210093, China.
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing Clinical School, Southern Medical University, Nanjing, 210002, China. .,Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China. .,State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210093, China. .,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 Thirteenth Street, Suite 2301, Charlestown, MA, 02129, USA.
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19
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Brain metabolic characteristics distinguishing typical and atypical benign epilepsy with centro-temporal spikes. Eur Radiol 2021; 31:9335-9345. [PMID: 34050803 DOI: 10.1007/s00330-021-08051-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 03/24/2021] [Accepted: 05/05/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVES Atypical benign epilepsy with centro-temporal spikes (BECTS) have less favorable outcomes than typical BECTS, and thus should be accurately identified for adequate treatment. We aimed to investigate the glucose metabolic differences between typical and atypical BECTS using 18F-fluorodeoxyglucose positron emission tomography ([18F]FDG PET) imaging, and explore whether these differences can help distinguish. METHODS Forty-six patients with typical BECTS, 31 patients with atypical BECTS and 23 controls who underwent [18F]FDG PET examination were retrospectively involved. Absolute asymmetry index (|AI|) was applied to evaluate the severity of metabolic abnormality. Glucose metabolic differences were investigated among typical BECTS, atypical BECTS, and controls by using statistical parametric mapping (SPM). Logistic regression analyses were performed based on clinical, PET, and hybrid features. RESULTS The |AI| was found significantly higher in atypical BECTS than in typical BECTS (p = 0.040). Atypical BECTS showed more hypo-metabolism regions than typical BECTS, mainly located in the fronto-temporo-parietal cortex. The PET model had significantly higher area under the curve (AUC) than the clinical model (0.91 vs. 0.70, p = 0.006). The hybrid model had the highest sensitivity (0.90), specificity (0.85), and accuracy (0.87) of all three models. CONCLUSIONS Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, depending on which the two groups can be well distinguished. The combination of metabolic characteristics and clinical variables has the potential to be used clinically to distinguish between typical and atypical BECTS. KEY POINTS • Distinguishing between typical and atypical BECTS is very important for the formulation of treatment regimens in clinical practice. • Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, mainly located in the fronto-temporo-parietal cortex. • The logistic regression model based on PET outperformed that based on clinical characteristics in classification of typical and atypical BECTS, and the hybrid model achieved the best classification performance.
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Fang S, Zhou C, Wang L, Fan X, Wang Y, Zhang Z, Jiang T. Characteristic Alterations of Network in Patients With Intraoperative Stimulation-Induced Seizures During Awake Craniotomy. Front Neurol 2021; 12:602716. [PMID: 33815243 PMCID: PMC8012772 DOI: 10.3389/fneur.2021.602716] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 02/12/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The use of electrocorticography (ECoG) to avoid intraoperative stimulation-induced seizure (ISS) during awake craniotomy is controversial. Although a standard direct cortical stimulating (DCS) protocol is used to identify the eloquent cortices and subcortical structures, ISS still occurs. Epilepsy is related to alterations in brain networks. In this study, we investigated specific alterations in brain networks in patients with ISS. Methods: Twenty-seven patients with glioma were enrolled and categorized into the ISS and non-ISS groups based on their history of ISS occurrence. A standard DCS protocol was used during awake craniotomy without ECoG supervision. Graph theoretical measurement was used to analyze resting-state functional magnetic resonance imaging data to quantitatively reveal alterations in the functional networks. Results: In the sensorimotor networks, the glioma significantly decreased the functional connectivity (FC) of four edges in the ISS group, which were conversely increased in the non-ISS group after multiple corrections (p < 0.001, threshold of p-value = 0.002). Regarding the topological properties, the sensorimotor network of all participants was classified as a small-world network. Glioma significantly increased global efficiency, nodal efficiency, and the sigma value, as well as decreased the shortest path length in the ISS group compared with the non-ISS group (p < 0.05). Conclusions: The specific alterations indicating patient susceptibility to ISS during DCS increased global and nodal efficiencies and decreased the shortest path length and FC induced by gliomas. If the patient has these specific alterations, ECoG is recommended to monitor after-discharge current during DCS to avoid ISS.
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Affiliation(s)
- Shengyu Fang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chunyao Zhou
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lei Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhong Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain Tumors Chinese (2019RU11), Chinese Academy of Medical Sciences, Beijing, China
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21
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Fang S, Wang Y, Jiang T. Epilepsy enhance global efficiency of language networks in right temporal lobe gliomas. CNS Neurosci Ther 2021; 27:363-371. [PMID: 33464718 PMCID: PMC7871790 DOI: 10.1111/cns.13595] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 12/16/2020] [Accepted: 12/17/2020] [Indexed: 12/11/2022] Open
Abstract
AIMS We analyzed the resting state functional magnetic resonance images to investigate the alterations of neural networks in patients with glioma-related epilepsy (GRE). METHODS Fifty-six patients with right temporal lower-grade glioma were divided into GRE (n = 28) and non-GRE groups. Twenty-eight healthy subjects were recruited after matching age, sex, and education level. Sensorimotor, visual, language, and left executive control networks were applied to generate functional connectivity matrices, and their topological properties were investigated. RESULTS No significant alterations in functional connectivity were found. The least significant discovery test revealed differences only in the language network. The shortest path length, clustering coefficient, local efficiency, and vulnerability were greater in the non-GRE group than in the other groups. The nodal efficiencies of two nodes (mirror areas to Broca and Wernicke) were weaker in the non-GRE group than in the other groups. The node of degree centrality (Broca), nodal local efficiency (Wernicke), and nodal clustering coefficient (temporal polar) were greater in the non-GRE group than in the healthy group. CONCLUSION Different tumor locations alter different neural networks. Temporal lobe gliomas in the right hemisphere altered the language network. Glioma itself and GRE altered the network in opposing ways in patients with right temporal glioma.
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Affiliation(s)
- Shengyu Fang
- Beijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
- Department of NeurosurgeryBeijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yinyan Wang
- Beijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
- Department of NeurosurgeryBeijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Tao Jiang
- Beijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
- Department of NeurosurgeryBeijing Tiantan HospitalCapital Medical UniversityBeijingChina
- Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain Tumors Chinese Academy of Medical SciencesBeijingChina
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Songjiang L, Tijiang Z, Heng L, Wenjing Z, Bo T, Ganjun S, Maoqiang T, Su L. Impact of Brain Functional Network Properties on Intelligence in Children and Adolescents with Focal Epilepsy: A Resting-state MRI Study. Acad Radiol 2021; 28:225-232. [PMID: 32037257 DOI: 10.1016/j.acra.2020.01.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 01/02/2020] [Accepted: 01/05/2020] [Indexed: 02/08/2023]
Abstract
RATIONALE AND OBJECTIVE Epilepsy is a common pediatric disease that often leads to cognitive and intellectual impairments. Here, we explore the reorganized functional networks in children and adolescents with focal epilepsy (CAFE) and analyze the relationship between network reorganization and intellectual deficits to reveal the underlying link between them. MATERIALS AND METHODS Fifty-four CAFE (6-16 years old; right-handed) and 42 well-matched healthy controls were recruited. Subjects underwent resting-state functional magnetic resonance imaging, and functional networks were analyzed by graph analysis. Intelligence testing (Wechsler Intelligence Scale for Children-Chinese revision) included measures for verbal IQ (VIQ), performance IQ, and full-scale IQ. RESULTS (1) In the CAFE compared with the healthy controls, (a) the local efficiency, clustering coefficient and standardized clustering coefficient were significantly decreased (p < 0.05); (b) the degree centrality and nodal efficiency of the left precentral gyrus (LPG) were significantly increased (p < 0.05, Bonferroni correction), and the nodal shortest path length was significantly decreased (p < 0.05, Bonferroni correction); and (c) functional connectivity of the LPG with the bilateral inferior frontal ventral gyrus, right lateral superior occipital gyrus, left middle occipital gyrus, bilateral superior parietal lobule, right anterior prefrontal cortex, and bilateral cerebellum was enhanced (p < 0.05,GRF correction), while functional connectivity with the bilateral superior temporal gyrus was decreased (p < 0.05, GRF correction). (2) The nodal shortest path length of the LPG in CAFE was associated with full-scale IQ, performance IQ, and VIQ, and local efficiency was associated with VIQ. CONCLUSION Our results showed that the middle LPG in CAFE undergoes network reorganization that positively influences intelligence. Differences in local efficiency of functional networks in children and early adolescents have a significant effect on intelligence.
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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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24
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Carboni M, De Stefano P, Vorderwülbecke BJ, Tourbier S, Mullier E, Rubega M, Momjian S, Schaller K, Hagmann P, Seeck M, Michel CM, van Mierlo P, Vulliemoz S. Abnormal directed connectivity of resting state networks in focal epilepsy. NEUROIMAGE-CLINICAL 2020; 27:102336. [PMID: 32679553 PMCID: PMC7363703 DOI: 10.1016/j.nicl.2020.102336] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 06/30/2020] [Accepted: 07/01/2020] [Indexed: 11/03/2022]
Abstract
OBJECTIVE Epilepsy diagnosis can be difficult in the absence of interictal epileptic discharges (IED) on scalp EEG. We used high-density EEG to measure connectivity in large-scale functional networks of patients with focal epilepsy (Temporal and Extratemporal Lobe Epilepsy, TLE and ETLE) and tested for network alterations during resting wakefulness without IEDs, compared to healthy controls. We measured global efficiency as a marker of integration within networks. METHODS We analysed 49 adult patients with focal epilepsy and 16 healthy subjects who underwent high-density-EEG and structural MRI. We estimated cortical activity using electric source analysis in 82 atlas-based cortical regions based on the individual MRI. We applied directed connectivity analysis (Partial Directed Coherence) on these sources and performed graph analysis: we computed the Global Efficiency on the whole brain and on each resting state network. We tested these features in different group of patients. RESULTS Compared to controls, efficiency was increased in both TLE and ETLE (p < 0.05). The somato-motor-network, the ventral-attention-network and the default-mode-network had a significantly increased efficiency (p < 0.05) in both TLE and ETLE as well as TLE with hippocampal sclerosis. SIGNIFICANCE During interictal scalp EEG epochs without IED, patients with focal epilepsy show brain functional connectivity alterations in the whole brain and in specific resting-state-networks. This higher integration reflects a chronic effect of pathological activity within these structures and complement previous work on altered information outflow. These findings could increase the diagnostic sensitivity of scalp EEG to identify epileptic activity in the absence of IED.
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Affiliation(s)
- Margherita Carboni
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland.
| | - Pia De Stefano
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Epilepsy-Center Berlin-Brandenburg, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sebastien Tourbier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Emeline Mullier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Maria Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland; Department of Neurosciences, University of Padova, Padova, Italy
| | - Shahan Momjian
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Karl Schaller
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
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25
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Fang S, Zhou C, Fan X, Jiang T, Wang Y. Epilepsy-Related Brain Network Alterations in Patients With Temporal Lobe Glioma in the Left Hemisphere. Front Neurol 2020; 11:684. [PMID: 32765403 PMCID: PMC7380082 DOI: 10.3389/fneur.2020.00684] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
Background: Seizures are a common symptom in patients with temporal lobe gliomas and may result in brain network alterations. However, brain network changes caused by glioma-related epilepsy (GRE) remain poorly understood. Objective: In this study, we applied graph theory analysis to delineate topological networks with resting-state functional magnetic resonance images (rs-fMRI) and investigated characteristics of functional networks in patients with GRE. Methods: Thirty patients with low-grade gliomas in the left temporal lobe were enrolled and classified into GRE (n = 15) and non-GRE groups. Twenty healthy participants matched for age, sex, and education level were enrolled. All participants had rs-fMRI data. Sensorimotor, visual, default mode, auditory, and right executive control networks were used to construct connection matrices. Topological properties of those sub-networks were investigated. Results: Compared to that in the GRE group, four edges with higher functional connectivity were noted in the non-GRE group. Moreover, 21 edges with higher functional connectivity were identified in the non-GRE group compared to the healthy group. All significant alterations in functional edges belong to the visual network. Increased global efficiency and decreased shortest path lengths were noted in the non-GRE group compared to the GRE and healthy groups. Compared with that in the healthy group, nodal efficiency of three nodes was higher in the GRE and non-GRE groups and the degree centrality of six nodes was altered in the non-GRE group. Conclusion: Temporal lobe gliomas in the left hemisphere and GRE altered visual networks in an opposing manner. These findings provide a novel insight into brain network alterations induced by GRE.
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Affiliation(s)
- Shengyu Fang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunyao Zhou
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Fan
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
| | - Tao Jiang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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26
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Li J, Biswal BB, Meng Y, Yang S, Duan X, Cui Q, Chen H, Liao W. A neuromarker of individual general fluid intelligence from the white-matter functional connectome. Transl Psychiatry 2020; 10:147. [PMID: 32404889 PMCID: PMC7220913 DOI: 10.1038/s41398-020-0829-3] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 04/20/2020] [Accepted: 04/28/2020] [Indexed: 12/13/2022] Open
Abstract
Neuroimaging studies have uncovered the neural roots of individual differences in human general fluid intelligence (Gf). Gf is characterized by the function of specific neural circuits in brain gray-matter; however, the association between Gf and neural function in brain white-matter (WM) remains unclear. Given reliable detection of blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals in WM, we used a functional, rather than an anatomical, neuromarker in WM to identify individual Gf. We collected longitudinal BOLD-fMRI data (in total three times, ~11 months between time 1 and time 2, and ~29 months between time 1 and time 3) in normal volunteers at rest, and identified WM functional connectomes that predicted the individual Gf at time 1 (n = 326). From internal validation analyses, we demonstrated that the constructed predictive model at time 1 predicted an individual's Gf from WM functional connectomes at time 2 (time 1 ∩ time 2: n = 105) and further at time 3 (time 1 ∩ time 3: n = 83). From external validation analyses, we demonstrated that the predictive model from time 1 was generalized to unseen individuals from another center (n = 53). From anatomical aspects, WM functional connectivity showing high predictive power predominantly included the superior longitudinal fasciculus system, deep frontal WM, and ventral frontoparietal tracts. These results thus demonstrated that WM functional connectomes offer a novel applicable neuromarker of Gf and supplement the gray-matter connectomes to explore brain-behavior relationships.
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Affiliation(s)
- 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, PR 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, PR China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR 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, PR China
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, 07102, USA
| | - Yao Meng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR 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, PR China
| | - Siqi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR 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, PR China
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR 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, PR China
| | - Qian Cui
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR 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, PR China
- School of Public Administration, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR 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, PR China.
| | - 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, PR 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, PR China.
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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: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 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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28
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Electroencephalographic abnormalities are correlated with cognitive deficits in children with benign childhood epilepsy with centrotemporal spikes: A clinical study of 61 cases. Epilepsy Behav 2020; 106:107012. [PMID: 32179505 DOI: 10.1016/j.yebeh.2020.107012] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2019] [Revised: 02/24/2020] [Accepted: 02/28/2020] [Indexed: 02/08/2023]
Abstract
OBJECTIVE The objective of this study was to explore the effect of spikes on cognition in patients with benign childhood epilepsy with centrotemporal spikes (BECTS) and to identify electroencephalography (EEG) markers enabling early detection of cognitive impairment. METHODS Sixty-one children with BECTS diagnoses and 60 age- and education-matched healthy controls were enrolled. Four-hour EEG recordings were analyzed for each patient to check for interictal spikes, high-frequency oscillations (HFOs), nondipole spikes, and other atypical EEG features and to examine the spike-wave index of nonrapid eye movement (NREM) sleep. All 121 children underwent a series of neuropsychological tests to assess cognitive function. RESULTS Patients with a high NREM sleep discharge index (≥55%) in the first sleep cycle exhibited significantly lower scores for arithmetic calculation, executive function, and attention and memory tests than patients with a low discharge index (<55%). Eight patients with HFOs exhibited even poorer performance than HFO-negative patients for arithmetic calculation, executive function, vocabulary comprehension, visual perception, vocal perception, spatial memory ability, and response ability. Children with bilateral discharge exhibited poorer ability in three-dimensional spatial imaging test, poorer memory, and slower response than did those with unilateral discharge (P < .05). Nondipole spikes, multiple asynchronous discharges, and generalized spike-wave discharges respectively had an impact on calculation ability, memory, and reaction ability respectively (P < .05). CONCLUSIONS Spike frequencies in stage 3 and 4 sleep varied from those observed in stage 1 and 2 sleep; the highest spike frequency was in stage 2 sleep. High NREM sleep discharge index (i.e., ≥55%) and HFOs were linked to the highest risk for cognitive deficit, while bilateral discharges, nondipole spikes, multiple asynchronous discharges, and generalized spike-wave discharges were less indicative of cognitive impairment.
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Ma K, Yu J, Shao W, Xu X, Zhang Z, Zhang D. Functional Overlaps Exist in Neurological and Psychiatric Disorders: A Proof from Brain Network Analysis. Neuroscience 2020; 425:39-48. [PMID: 31794696 DOI: 10.1016/j.neuroscience.2019.11.018] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 11/10/2019] [Accepted: 11/11/2019] [Indexed: 11/26/2022]
Abstract
Psychopath and neuropath often exhibit similar symptoms in clinical functional performances. However, few studies ever demonstrate the existence of overlapped brain functional mechanism between neurological and psychiatric disorders. Accordingly, in this paper, we have made an attempt to verify the existence of functional overlaps among neurological and psychiatric disorders through brain network analysis. Specifically, our findings suggest that functional overlaps exist in mild cognitive impairment (MCI), Alzheimer's disease (AD) and major depressive disorder (MDD), as well as in epilepsy, attention deficit hyperactivity disorder (ADHD) and schizophrenia. In these overlapped functions, we also find that the brain regions of neuropsychopathic disorders exhibit different cooperative patterns at different levels of brain activities. For example, strong-strong cooperative patterns were observed at high levels of brain activities in epilepsy, ADHD and schizophrenia.
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Affiliation(s)
- Kai Ma
- Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing, Jiangsu Province 210016, China
| | - Jintai Yu
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200433, China
| | - Wei Shao
- Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing, Jiangsu Province 210016, China
| | - Xijia Xu
- Department of Psychiatry, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu Province 210029, China
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu Province 210002, China
| | - Daoqiang Zhang
- Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing, Jiangsu Province 210016, China.
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Luo S, Zhu Y, Fan L, Gao D, Han S. Resting-state brain network properties mediate the association between the oxytocin receptor gene and interdependence. Soc Neurosci 2020; 15:296-310. [PMID: 31928145 DOI: 10.1080/17470919.2020.1714718] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
While an increasing number of behavioral findings have provided gene-culture coevolution accounts of human development, whether and how the brain mediates gene-culture associations remain unresolved. Based on the Culture-Behavior-Brain-Loop Model and the recent finding of associations between the oxytocin receptor gene (OXTR, rs53576) and a cultural trait (i.e., interdependence) across populations, we tested the hypothesis that resting-state brain network properties mediate the relationship between OXTR rs53576 and interdependence. G and A allele carriers of OXTR rs53576 were scanned during a resting state using functional magnetic resonance imaging (fMRI) and completed questionnaires to estimate their interdependence cultural values. We identified significant genotype effects on the local network metrics of the right hippocampus and its functional connectivity with the medial prefrontal cortex, dorsal anterior cingulate cortex, amygdala, basal ganglia and thalamus. The local network metrics of the right hippocampus and its functional connectivity with the basal ganglia and thalamus were correlated with interdependence. Moreover, both the degree of the right hippocampus and its functional connectivity with the basal ganglia and thalamus mediated the relationship between OXTR and interdependence. Our results provide brain imaging evidence for a key function of the brain in mediating the relationship between genes and culture.
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Affiliation(s)
- Siyang Luo
- Department of Psychology, Guangdong Provincial Key Laboratory of Social Cognitive Neuroscience and Mental Health, Guangdong Provincial Key Laboratory of Brain Function and Disease, Sun Yat-Sen University , Guangzhou China
| | - Yiyi Zhu
- Department of Psychology, Guangdong Provincial Key Laboratory of Social Cognitive Neuroscience and Mental Health, Guangdong Provincial Key Laboratory of Brain Function and Disease, Sun Yat-Sen University , Guangzhou China.,School of Behavioral and Brain Sciences, The University of Texas at Dallas , Richardson, TX, USA
| | - Leyi Fan
- Department of Psychology, Guangdong Provincial Key Laboratory of Social Cognitive Neuroscience and Mental Health, Guangdong Provincial Key Laboratory of Brain Function and Disease, Sun Yat-Sen University , Guangzhou China
| | - Dingguo Gao
- Department of Psychology, Guangdong Provincial Key Laboratory of Social Cognitive Neuroscience and Mental Health, Guangdong Provincial Key Laboratory of Brain Function and Disease, Sun Yat-Sen University , Guangzhou China
| | - Shihui Han
- School of Psychological and Cognitive Sciences, PKU-IDG/McGovern Institute for Brain Research, Beijing Key Laboratory of Behavior and Mental Health, Peking University , Beijing, China
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Dai XJ, Xu Q, Hu J, Zhang Q, Xu Y, Zhang Z, Lu G. BECTS Substate Classification by Granger Causality Density Based Support Vector Machine Model. Front Neurol 2019; 10:1201. [PMID: 31798523 PMCID: PMC6868120 DOI: 10.3389/fneur.2019.01201] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 10/28/2019] [Indexed: 12/30/2022] Open
Abstract
Objectives: To investigate the performance of substate classification of children with benign epilepsy with centrotemporal spikes (BECTS) by granger causality density (GCD) based support vector machine (SVM) model. Methods: Forty-two children with BECTS (21 females, 21 males; mean age, 8.6 ± 1.96 years) were classified into interictal epileptic discharges (IEDs; 11 females, 10 males) and non-IEDs (10 females, 11 males) substates depending on presence of central-temporal spikes or not. GCD was calculated on four metrics, including inflow, outflow, total-flow (inflow + outflow) and int-flow (inflow – outflow) connectivity. SVM classifier was applied to discriminate the two substates. Results: The Rolandic area, caudate, dorsal attention network, visual cortex, language networks, and cerebellum had discriminative effect on distinguishing the two substates. Relative to each of the four GCD metrics, using combined metrics could reach up the classification performance (best value; AUC, 0.928; accuracy rate, 90.83%; sensitivity, 90%; specificity, 95%), especially for the combinations with more than three GCD metrics. Specially, combined the inflow, outflow and int-flow metric received the best classification performance with the highest AUC value, classification accuracy and specificity. Furthermore, the GCD-SVM model received good and stable classification performance across 14 dimension reduced data sets. Conclusions: The GCD-SVM model could be used for BECTS substate classification, which might have the potential to provide a promising model for IEDs detection. This may help assist clinicians for administer drugs and prognosis evaluation.
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Affiliation(s)
- Xi-Jian Dai
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.,Shenzhen Mental Health Centre, Shenzhen Kangning Hospital, Shenzhen, China.,Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Qiang Xu
- Shenzhen Mental Health Centre, Shenzhen Kangning Hospital, Shenzhen, China
| | - Jianping Hu
- Shenzhen Mental Health Centre, Shenzhen Kangning Hospital, Shenzhen, China
| | - QiRui Zhang
- Shenzhen Mental Health Centre, Shenzhen Kangning Hospital, Shenzhen, China
| | - Yin Xu
- Shenzhen Mental Health Centre, Shenzhen Kangning Hospital, Shenzhen, China
| | - Zhiqiang Zhang
- Shenzhen Mental Health Centre, Shenzhen Kangning Hospital, Shenzhen, China
| | - Guangming Lu
- Shenzhen Mental Health Centre, Shenzhen Kangning Hospital, Shenzhen, China
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32
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Li J, Biswal BB, Wang P, Duan X, Cui Q, Chen H, Liao W. Exploring the functional connectome in white matter. Hum Brain Mapp 2019; 40:4331-4344. [PMID: 31276262 PMCID: PMC6865787 DOI: 10.1002/hbm.24705] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 06/18/2019] [Accepted: 06/22/2019] [Indexed: 02/03/2023] Open
Abstract
A major challenge in neuroscience is understanding how brain function emerges from the connectome. Most current methods have focused on quantifying functional connectomes in gray-matter (GM) signals obtained from functional magnetic resonance imaging (fMRI), while signals from white-matter (WM) have generally been excluded as noise. In this study, we derived a functional connectome from WM resting-state blood-oxygen-level-dependent (BOLD)-fMRI signals from a large cohort (n = 488). The WM functional connectome exhibited weak small-world topology and nonrandom modularity. We also found a long-term (i.e., over 10 months) topological reliability, with topological reproducibility within different brain parcellation strategies, spatial distance effect, global and cerebrospinal fluid signals regression or not. Furthermore, the small-worldness was positively correlated with individuals' intelligence values (r = .17, pcorrected = .0009). The current findings offer initial evidence using WM connectome and present additional measures by which to uncover WM functional information in both healthy individuals and in cases of clinical disease.
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Affiliation(s)
- Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- School of Life Science and Technology, Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Bharat B. Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- School of Life Science and Technology, Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
- Department of Biomedical EngineeringNew Jersey Institute of TechnologyNewarkNew Jersey
| | - Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- School of Life Science and Technology, Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- School of Life Science and Technology, Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Qian Cui
- School of Public AdministrationUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- School of Life Science and Technology, Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- School of Life Science and Technology, Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
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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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35
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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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36
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Ji G, Chen X, Bai T, Wang L, Wei Q, Gao Y, Tao L, He K, Li D, Dong Y, Hu P, Yu F, Zhu C, Tian Y, Yu Y, Wang K. Classification of schizophrenia by intersubject correlation in functional connectome. Hum Brain Mapp 2019; 40:2347-2357. [PMID: 30663853 PMCID: PMC6865403 DOI: 10.1002/hbm.24527] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Revised: 12/07/2018] [Accepted: 01/08/2019] [Indexed: 01/16/2023] Open
Abstract
Functional connectomes have been suggested as fingerprinting for individual identification. Accordingly, we hypothesized that subjects in the same phenotypic group have similar functional connectome features, which could help to discriminate schizophrenia (SCH) patients from healthy controls (HCs) and from depression patients. To this end, we included resting-state functional magnetic resonance imaging data of SCH, depression patients, and HCs from three centers. We first investigated the characteristics of connectome similarity between individuals, and found higher similarity between subjects belonging to the same group (i.e., SCH-SCH) than different groups (i.e., HC-SCH). These findings suggest that the average connectome within group (termed as group-specific functional connectome [GFC]) may help in individual classification. Consistently, significant accuracy (75-77%) and area under curve (81-86%) were found in discriminating SCH from HC or depression patients by GFC-based leave-one-out cross-validation. Cross-center classification further suggests a good generalizability of the GFC classification. We additionally included normal aging data (255 young and 242 old subjects with different scanning sequences) to show factors could be improved for better classification performance, and the findings emphasized the importance of increasing sample size but not temporal resolution during scanning. In conclusion, our findings suggest that the average functional connectome across subjects contained group-specific biological features and may be helpful in clinical diagnosis for schizophrenia.
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Affiliation(s)
- Gong‐Jun Ji
- Department of Medical PsychologyChaohu Clinical Medical College, Anhui Medical UniversityHefeiChina
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Xingui Chen
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Tongjian Bai
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Lu Wang
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Qiang Wei
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Yaxiang Gao
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Longxiang Tao
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Kongliang He
- Anhui Mental Health CenterHefeiChina
- The Fourth People's Hospital of HefeiHefeiChina
| | - Dandan Li
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Yi Dong
- Anhui Mental Health CenterHefeiChina
- The Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Panpan Hu
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Fengqiong Yu
- Department of Medical PsychologyChaohu Clinical Medical College, Anhui Medical UniversityHefeiChina
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Chunyan Zhu
- Department of Medical PsychologyChaohu Clinical Medical College, Anhui Medical UniversityHefeiChina
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Yanghua Tian
- Laboratory of Cognitive NeuropsychologyCollaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Yongqiang Yu
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Kai Wang
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
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Ji G, Ren C, Li Y, Sun J, Liu T, Gao Y, Xue D, Shen L, Cheng W, Zhu C, Tian Y, Hu P, Chen X, Wang K. Regional and network properties of white matter function in Parkinson's disease. Hum Brain Mapp 2019; 40:1253-1263. [PMID: 30414340 PMCID: PMC6865582 DOI: 10.1002/hbm.24444] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 10/05/2018] [Accepted: 10/16/2018] [Indexed: 02/01/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder with dysfunction in cortices as well as white matter (WM) tracts. While the changes to WM structure have been extensively investigated in PD, the nature of the functional changes to WM remains unknown. In this study, the regional activity and functional connectivity of WM were compared between PD patients (n = 57) and matched healthy controls (n = 52), based on multimodel magnetic resonance imaging data sets. By tract-based spatial statistical analyses of regional activity, patients showed decreased structural-functional coupling in the left corticospinal tract compared to controls. This tract also displayed abnormally increased functional connectivity within the left post-central gyrus and left putamen in PD patients. At the network level, the WM functional network showed small-worldness in both controls and PD patients, yet it was abnormally increased in the latter group. Based on the features of the WM functional connectome, previously un-evaluated individuals could be classified with fair accuracy (73%) and area under the curve of the receiver operating characteristics (75%). These neuroimaging findings provide direct evidence for WM functional changes in PD, which is crucial to understand the functional role of fiber tracts in the pathology of neural circuits.
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Affiliation(s)
- Gong‐Jun Ji
- Department of Medical Psychology, Chaohu Clinical Medical CollegeAnhui Medical UniversityHefeiChina
| | - Cuiping Ren
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Ying Li
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Tingting Liu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Yaxiang Gao
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Dongzhang Xue
- Department of NeurologyThe 123 Hospital of People's Liberation ArmyBengbuChina
| | - Longshan Shen
- Department of ImagingThe Second Affiliated Hospital of Bengbu Medical CollegeBengbuChina
| | - Wen Cheng
- College of Literature and EducationBengbu CollegeBengbuChina
| | - Chunyan Zhu
- Department of Medical Psychology, Chaohu Clinical Medical CollegeAnhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Xianwen Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental HealthHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
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Chen X, Ji GJ, Zhu C, Bai X, Wang L, He K, Gao Y, Tao L, Yu F, Tian Y, Wang K. Neural Correlates of Auditory Verbal Hallucinations in Schizophrenia and the Therapeutic Response to Theta-Burst Transcranial Magnetic Stimulation. Schizophr Bull 2019; 45:474-483. [PMID: 29733409 PMCID: PMC6403092 DOI: 10.1093/schbul/sby054] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Auditory verbal hallucinations (AVHs) are a core symptom of schizophrenia, and resistant to antipsychotic medication in a substantial proportion of patients. This study aimed to investigate the neural correlates of AVHs in schizophrenia patients and its response to a modified continuous theta-burst stimulation (cTBS) by transcranial magnetic stimulation. In a cross-sectional experiment, resting-state functional magnetic resonance images were collected from 31 AVH schizophrenia patients, 26 non-AVH schizophrenia patients, and 33 sex-/age-matched healthy controls (HCs). Functional connectivity strength (FCS) maps were compared among groups by 1-way analysis of variance (ANOVA). In a longitudinal experiment, 16 and 11 AVH patients received real and sham cTBS treatment for 15 days, respectively. Notably, this was not a randomized control trail. Changes in AVH and FCS were analyzed by 2-way ANOVA and 2-sample t-test, respectively. In the cross-sectional experiment, comparison of FCS maps identified 8 clusters among groups, but only one cluster (in left cerebellum) differed significantly in AVH patients compared to both HCs and non-AVH patients. In the longitudinal experiment, the real cTBS group showed a greater improvement in symptoms and a larger FCS decrease in left cerebellum than the sham group. Pearson's correlation analysis indicated that baseline FCS of the overlapping cerebellum cluster (between the cross-sectional and longitudinal findings) was negatively correlated with symptom improvement in the real treatment group. These findings emphasize the role of the left cerebellum in both the pathophysiology and clinical treatment of AVHs in schizophrenia patients.
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Affiliation(s)
- Xingui Chen
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Anhui Province, China,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Gong-Jun Ji
- Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei, China
| | - Chunyan Zhu
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Anhui Province, China,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China,Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei, China
| | - Xiaomeng Bai
- Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei, China
| | - Lu Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | | | - Yaxiang Gao
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Anhui Province, China
| | - Longxiang Tao
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Fengqiong Yu
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Anhui Province, China,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China,Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei, China
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Anhui Province, China,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China,Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei, China
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Anhui Province, China,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China,Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei, China,To whom correspondence should be addressed; Laboratory of Cognitive Neuropsychology, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China; tel: +86-551-62923704, fax: +86-551-62922418, e-mail:
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Ding JR, Ding X, Hua B, Xiong X, Wen Y, Ding Z, Wang Q, Thompson P. Altered connectivity patterns among resting state networks in patients with ischemic white matter lesions. Brain Imaging Behav 2018; 12:1239-1250. [PMID: 29134612 PMCID: PMC6290724 DOI: 10.1007/s11682-017-9793-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
White matter lesions (WMLs) have been associated with cognitive and motor decline. Resting state networks (RSNs) are spatially coherent patterns in the human brain and their interactions sustain our daily function. Therefore, investigating the altered intra- and inter-network connectivity among the RSNs may help to understand the association of WMLs with impaired cognitive and motor function. Here, we assessed alterations in functional connectivity patterns based on six well-defined RSNs-the default mode network (DMN), dorsal attention network (DAN), frontal-parietal control network (FPCN), auditory network (AN), sensory motor network (SMN) and visual network (VN)-in 15 patients with ischemic WMLs and 15 controls. In the patients, Spearman's correlation analysis was further performed between these alterations and cognitive test scores, including Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Our results showed wide alterations of inter-network connectivity mainly involving the SMN, DMN, FPCN and DAN, and some alterations correlated with cognitive test scores in the patients. The reduced functional connectivities in the SMN-AN, SMN-VN, FPCN-AN, DAN-VN pairs may account for the cognitive and motor decline in patients with ischemic WMLs, while the increased functional connectivities in the DMN-AN, DMN-FPCN and DAN-FPCN pairs may reflect a functional network reorganization after damage to white matter. It is unexpected that altered intra-network connectivities were found within the AN and VN, which may explain the impairments in verbal fluency and information retrieval associated with WMLs. This study highlights the importance of functional connectivity in understanding how WMLs influence cognitive and behavior dysfunction.
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Affiliation(s)
- Ju-Rong Ding
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, China.
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, University of Southern California, Marina del Rey, CA, USA.
| | - Xin Ding
- Department of Neurology, Chengdu Military General Hospital, Chengdu, China
| | - Bo Hua
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, China
| | - Xingzhong Xiong
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, China
| | - Yuqiao Wen
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, China
| | - Zhongxiang Ding
- Department of Radiology, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Qingsong Wang
- Department of Neurology, Chengdu Military General Hospital, Chengdu, China
| | - Paul Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, University of Southern California, Marina del Rey, CA, USA.
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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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Liao W, Li J, Duan X, Cui Q, Chen H, Chen H. Static and dynamic connectomics differentiate between depressed patients with and without suicidal ideation. Hum Brain Mapp 2018; 39:4105-4118. [PMID: 29962025 DOI: 10.1002/hbm.24235] [Citation(s) in RCA: 98] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 05/18/2018] [Accepted: 05/21/2018] [Indexed: 02/03/2023] Open
Abstract
Neural circuit dysfunction underlies the biological mechanisms of suicidal ideation (SI). However, little is known about how the brain's "dynome" differentiate between depressed patients with and without SI. This study included depressed patients (n = 48) with SI, without SI (NSI), and healthy controls (HC, n = 30). All participants underwent resting-state functional magnetic resonance imaging. We constructed dynamic and static connectomics on 200 nodes using a sliding window and full-length time-series correlations, respectively. Specifically, the temporal variability of dynamic connectomic was quantified using the variance of topological properties across sliding window. The overall topological properties of both static and dynamic connectomics further differentiated between SI and NSI, and also predicted the severity of SI. The SI showed decreased overall topological properties of static connectomic relative to the HC. The SI exhibited increases in overall topological properties with regard to the dynamic connectomic when compared with the HC and the NSI. Importantly, combining the overall topological properties of dynamic and static connectomics yielded mean 75% accuracy (all p < .001) with mean 71% sensitivity and mean 75% specificity in differentiating between SI and NSI. Moreover, these features may predict the severity of SI (mean r = .55, all p < .05). The findings revealed that combining static and dynamic connectomics could differentiate between SI and NSI, offering new insight into the physiopathological mechanisms underlying SI. Furthermore, combining the brain's connectome and dynome may be considered a neuromarker for diagnostic and predictive models in the study of SI.
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Affiliation(s)
- Wei Liao
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Jiao Li
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Xujun Duan
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Qian Cui
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Heng Chen
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Huafu Chen
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,Center for Information in BioMedicine, 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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Chen S, Fang J, An D, Xiao F, Chen D, Chen T, Zhou D, Liu L. The focal alteration and causal connectivity in children with new-onset benign epilepsy with centrotemporal spikes. Sci Rep 2018; 8:5689. [PMID: 29632387 PMCID: PMC5890242 DOI: 10.1038/s41598-018-23336-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 03/09/2018] [Indexed: 02/05/2023] Open
Abstract
The aim of the current study was to find the epileptic focus and examine its causal relationship to other brain regions in children with new-onset benign childhood epilepsy with centrotemporal spikes (BECTS). Resting-state functional magnetic resonance imaging (fMRI) was performed in 66 children with BECTS and 37 matched control children. We compared the amplitude of low frequency fluctuation (ALFF) signals between the two groups to find the potential epileptogenic zone (EZ), then used Granger causality analysis (GCA) to explore the causal effects of EZ on the whole brain. Children with BECTS had significantly increased ALFF in the right Broca’s area, and decreased ALFF in bilateral fusiform gyrus. The patients also showed increased driving effect from the EZ in Broca’s area to the right prefrontal lobe, and decreased effects to the frontal lobe and posterior parts of the language network. The causal effect on left Wernicke’s area negatively correlated with verbal IQ (VIQ) score. Our research on new-onset BECTS patients illustrates a possible compensatory mechanism in the language network at early stages of BECTS, and the negative correlation of GCA and VIQ suggest the disturbance of epileptiform activity on language. These findings shed light on the mechanisms of and language dysfunction in BECTS.
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Affiliation(s)
- Sihan Chen
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, Chengdu, PR China
| | - Jiajia Fang
- Department of Neurology, Fourth Affiliated Hospital, School of Medicine, Zhejiang University, Yiwu, PR China
| | - Dongmei An
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, Chengdu, PR China
| | - Fenglai Xiao
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, Chengdu, PR China
| | - Deng Chen
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, Chengdu, PR China
| | - Tao Chen
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, Chengdu, PR China
| | - Dong Zhou
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, Chengdu, PR China.
| | - Ling Liu
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, Chengdu, PR China.
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Stimulated left DLPFC-nucleus accumbens functional connectivity predicts the anti-depression and anti-anxiety effects of rTMS for depression. Transl Psychiatry 2018; 7:3. [PMID: 29520002 PMCID: PMC5843586 DOI: 10.1038/s41398-017-0005-6] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Not all depression patients effectively respond to repeated transcranial magnetic stimulation (rTMS). We tested whether the intrinsic functional connectivity (FC) strength between the stimulated left dorsolateral prefrontal cortex (DLPFC) and left nucleus accumbens (NAcc) might predict effects of rTMS. Twenty-two medication-naïve depression patients received rTMS on left DLPFC for 2 weeks and underwent baseline functional magnetic resonance imaging (fMRI). We compared the amplitude of the low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in the stimulated target (the cortex region directly stimulated by rTMS) located in the left DLPFC, and the left NAcc, as well as the intrinsic FC of the DLPFC-NAcc between early improvers and non-improvers. We evaluated the association between the baseline brain imaging features (ALFF, ReHo, and FC) and improvements in depression and anxiety symptoms. We found that the pretreatment ALFF and ReHo in the stimulated DLPFC and left NAcc did not significantly differ between the subgroups. The early improvers displayed increased negative FC strength between the stimulated DLPFC and left NAcc with respect to non-improvers. The stimulated DLPFC-NAcc FC strength negatively correlated with improved depressive and anxious symptoms. This study is the first to demonstrate that the resting-state FC of the stimulated DLPFC-NAcc, rather than regional brain activity or local synchronization in the stimulated target, might predict the anti-depression and anti-anxiety effects of rTMS for depression.
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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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Yang M, Li J, Li Z, Yao D, Liao W, Chen H. Whole-brain functional connectome-based multivariate classification of post-stroke aphasia. Neurocomputing 2017. [DOI: 10.1016/j.neucom.2016.10.094] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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Ma S, Jiang S, Peng R, Zhu Q, Sun H, Li J, Jia X, Goldberg I, Yu L, Luo C. Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures. Front Comput Neurosci 2017; 11:90. [PMID: 29033811 PMCID: PMC5627153 DOI: 10.3389/fncom.2017.00090] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2017] [Accepted: 09/20/2017] [Indexed: 01/09/2023] Open
Abstract
The purpose of this study was to evaluate the spatiotemporal Consistency of spontaneous activities in local brain regions in patients with generalized tonic-clonic seizures (GTCS). The resting-state fMRI data were acquired from nineteen patients with GTCS and twenty-two matched healthy subjects. FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) metric was used to analyze the spontaneous activity in whole brain. The FOCA difference between two groups were detected using a two sample t-test analysis. Correlations between the FOCA values and features of seizures were analyzed. The findings of this study showed that patients had significantly increased FOCA in motor-related cortex regions, including bilateral supplementary motor area, paracentral lobule, precentral gyrus and left basal ganglia, as well as a substantial reduction of FOCA in regions of default mode network (DMN) and parietal lobe. In addition, several brain regions in DMN demonstrated more reduction with longer duration of epilepsy and later onset age, and the motor-related regions showed higher FOCA value in accompany with later onset age. These findings implicated the abnormality of motor-related cortical network in GTCS which were associated with the genesis and propagation of epileptiform activity. And the decreased FOCA in DMN might reflect the intrinsic disturbance of brain activity. Moreover, our study supported that the FOCA might be potential tool to investigate local brain spontaneous activity related with the epileptic activity, and to provide important insights into understanding the underlying pathophysiological mechanisms of GTCS.
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Affiliation(s)
- Shuai Ma
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Sisi Jiang
- 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 Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Rui Peng
- 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 Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qiong Zhu
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Hongbin Sun
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Jianfu Li
- 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 Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoyan Jia
- 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 Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ilan Goldberg
- Neurology Department, Wolfson Medical Center, Holon, Israel
| | - Liang Yu
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- 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 Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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Liu W, An D, Tong X, Niu R, Gong Q, Zhou D. Region-specific connectivity in patients with periventricular nodular heterotopia and epilepsy: A study combining diffusion tensor imaging and functional MRI. Epilepsy Res 2017; 136:137-142. [PMID: 28850831 DOI: 10.1016/j.eplepsyres.2017.08.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 08/02/2017] [Accepted: 08/16/2017] [Indexed: 02/05/2023]
Abstract
OBJECTIVES Periventricular nodular heterotopia (PNH) is an important cause of chronic epilepsy. The purpose of this study was to evaluate region-specific connectivity in PNH patients with epilepsy and assess correlation between connectivity strength and clinical factors including duration and prognosis. METHODS Diffusion tensor imaging (DTI) and resting state functional MRI (fMRI) were performed in 28 subjects (mean age 27.4years; range 9-56years). The structural connectivity of fiber bundles passing through the manually-selected segmented nodules and other brain regions were analyzed by tractography. Cortical lobes showing functional correlations to nodules were also determined. RESULTS For all heterotopic gray matter nodules, including at least one in each subject, the most frequent segments to which nodular heterotopia showed structural (132/151) and functional (146/151) connectivity were discrete regions of the ipsilateral overlying cortex. Agreement between diffusion tensor tractography and functional connectivity analyses was conserved in 81% of all nodules (122/151). In patients with longer duration or refractory epilepsy, the connectivity was significantly stronger, particularly to the frontal and temporal lobes (P<0.05). CONCLUSIONS Nodules in PNH were structurally and functionally connected to the cortex. The extent is stronger in patients with longstanding or intractable epilepsy. These findings suggest the region-specific interactions may help better evaluate prognosis and seek medical or surgical interventions of PNH-related epilepsy.
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Affiliation(s)
- Wenyu Liu
- Departments of Neurology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
| | - Dongmei An
- Departments of Neurology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
| | - Xin Tong
- Departments of Neurology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
| | - Running Niu
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
| | - Qiyong Gong
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
| | - Dong Zhou
- Departments of Neurology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
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Chen H, Nomi JS, Uddin LQ, Duan X, Chen H. Intrinsic functional connectivity variance and state-specific under-connectivity in autism. Hum Brain Mapp 2017; 38:5740-5755. [PMID: 28792117 DOI: 10.1002/hbm.23764] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Revised: 07/14/2017] [Accepted: 07/30/2017] [Indexed: 01/15/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition associated with altered brain connectivity. Previous neuroimaging research demonstrates inconsistent results, particularly in studies of functional connectivity in ASD. Typically, these inconsistent findings are results of studies using static measures of resting-state functional connectivity. Recent work has demonstrated that functional brain connections are dynamic, suggesting that static connectivity metrics fail to capture nuanced time-varying properties of functional connections in the brain. Here we used a dynamic functional connectivity approach to examine the differences in the strength and variance of dynamic functional connections between individuals with ASD and healthy controls (HCs). The variance of dynamic functional connections was defined as the respective standard deviations of the dynamic functional connectivity strength across time. We utilized a large multicenter dataset of 507 male subjects (209 with ASD and 298 HC, from 6 to 36 years old) from the Autism Brain Imaging Data Exchange (ABIDE) to identify six distinct whole-brain dynamic functional connectivity states. Analyses demonstrated greater variance of widespread long-range dynamic functional connections in ASD (P < 0.05, NBS method) and weaker dynamic functional connections in ASD (P < 0.05, NBS method) within specific whole-brain connectivity states. Hypervariant dynamic connections were also characterized by weaker connectivity strength in ASD compared with HC. Increased variance of dynamic functional connections was also related to ASD symptom severity (ADOS total score) (P < 0.05), and was most prominent in connections related to the medial superior frontal gyrus and temporal pole. These results demonstrate that greater intraindividual dynamic variance is a potential biomarker of ASD. Hum Brain Mapp 38:5740-5755, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Heng Chen
- Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, Florida
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, Florida
| | - Xujun Duan
- Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Huafu Chen
- Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, 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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