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Ke M, Luo X, Guo Y, Zhang J, Ren X, Liu G. Alterations in spatiotemporal characteristics of dynamic networks in juvenile myoclonic epilepsy. Neurol Sci 2024; 45:4983-4996. [PMID: 38704479 DOI: 10.1007/s10072-024-07506-8] [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: 11/23/2023] [Accepted: 03/27/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Juvenile myoclonic epilepsy (JME) is characterized by altered patterns of brain functional connectivity (FC). However, the nature and extent of alterations in the spatiotemporal characteristics of dynamic FC in JME patients remain elusive. Dynamic networks effectively encapsulate temporal variations in brain imaging data, offering insights into brain network abnormalities and contributing to our understanding of the seizure mechanisms and origins. METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 37 JME patients and 37 healthy counterparts. Forty-seven network nodes were identified by group-independent component analysis (ICA) to construct the dynamic network. Ultimately, patients' and controls' spatiotemporal characteristics, encompassing temporal clustering and variability, were contrasted at the whole-brain, large-scale network, and regional levels. RESULTS Our findings reveal a marked reduction in temporal clustering and an elevation in temporal variability in JME patients at the whole-brain echelon. Perturbations were notably pronounced in the default mode network (DMN) and visual network (VN) at the large-scale level. Nodes exhibiting anomalous were predominantly situated within the DMN and VN. Additionally, there was a significant correlation between the severity of JME symptoms and the temporal clustering of the VN. CONCLUSIONS Our findings suggest that excessive temporal changes in brain FC may affect the temporal structure of dynamic brain networks, leading to disturbances in brain function in patients with JME. The DMN and VN play an important role in the dynamics of brain networks in patients, and their abnormal spatiotemporal properties may underlie abnormal brain function in patients with JME in the early stages of the disease.
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Affiliation(s)
- Ming Ke
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China.
| | - Xiaofei Luo
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Yi Guo
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Juli Zhang
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Xupeng Ren
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Guangyao Liu
- Department of Nuclear Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, 730030, China.
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Xiao S, Ebner NC, Manzouri A, Li TQ, Cortes DS, Månsson KNT, Fischer H. Age-dependent effects of oxytocin in brain regions enriched with oxytocin receptors. Psychoneuroendocrinology 2024; 160:106666. [PMID: 37951085 PMCID: PMC10841644 DOI: 10.1016/j.psyneuen.2023.106666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 09/03/2023] [Accepted: 10/29/2023] [Indexed: 11/13/2023]
Abstract
Although intranasal oxytocin administration to tap into central functions is the most commonly used non-invasive means for exploring oxytocin's role in human cognition and behavior, the way by which intranasal oxytocin acts on the brain is not yet fully understood. Recent research suggests that brain regions densely populated with oxytocin receptors may play a central role in intranasal oxytocin's action mechanisms in the brain. In particular, intranasal oxytocin may act directly on (subcortical) regions rich in oxytocin receptors via binding to these receptors while only indirectly affecting other (cortical) regions via their neural connections to oxytocin receptor-enriched regions. Aligned with this notion, the current study adopted a novel approach to test 1) whether the connections between oxytocin receptor-enriched regions (i.e., the thalamus, pallidum, caudate nucleus, putamen, and olfactory bulbs) and other regions in the brain were responsive to intranasal oxytocin administration, and 2) whether oxytocin-induced effects varied as a function of age. Forty-six young (24.96 ± 3.06 years) and 44 older (69.89 ± 2.99 years) participants were randomized, in a double-blind procedure, to self-administer either intranasal oxytocin or placebo before resting-state fMRI. Results supported age-dependency in the effects of intranasal oxytocin administration on connectivity between oxytocin receptor-enriched regions and other regions in the brain. Specifically, compared to placebo, oxytocin decreased both connectivity density and connectivity strength of the thalamus for young participants while it increased connectivity density and connectivity strength of the caudate for older participants. These findings inform the mechanisms underlying the effects of exogenous oxytocin on brain function and highlight the importance of age in these processes.
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Affiliation(s)
- Shanshan Xiao
- Department of Psychology, Stockholm University, Campus Albano hus 4, Albanovägen, SE-114 19 Stockholm, Sweden.
| | - Natalie C Ebner
- Department of Psychology, University of Florida, P.O. Box 112250, Gainesville, FL 32611-2250, USA; Cognitive Aging and Memory Program, Clinical Translational Research Program (CAM-CTRP), University of Florida, 2004 Mowry Road, Gainesville, FL 32611, USA; McKnight Brain Institute, University of Florida, 1149 Newell Drive, Gainesville, FL 32610, USA.
| | - Amirhossein Manzouri
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Norra stationsgatan 69, SE-113 64 Stockholm, Sweden.
| | - Tie-Qiang Li
- Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Alfred Nobels Allé 8, SE-141 52 Huddinge, Sweden; Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, SE-141 86 Stockholm, Sweden.
| | - Diana S Cortes
- Department of Psychology, Stockholm University, Campus Albano hus 4, Albanovägen, SE-114 19 Stockholm, Sweden.
| | - Kristoffer N T Månsson
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Norra stationsgatan 69, SE-113 64 Stockholm, Sweden.
| | - Håkan Fischer
- Department of Psychology, Stockholm University, Campus Albano hus 4, Albanovägen, SE-114 19 Stockholm, Sweden; Stockholm University Brain Imaging Center (SUBIC), SE-106 91 Stockholm, Sweden; Aging Research Center, Karolinska Institutet and Stockholm University, Tomtebodavägen 18 A, SE-171 77 Stockholm, Sweden.
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Persson H, Li TQ, Markovic G. CHANGES IN FUNCTIONAL CONNECTIVITY FOLLOWING INTENSIVE ATTENTION TRAINING IN PATIENTS WITH TRAUMATIC BRAIN INJURY. A PILOT STUDY. JOURNAL OF REHABILITATION MEDICINE. CLINICAL COMMUNICATIONS 2024; 7:12436. [PMID: 38264065 PMCID: PMC10802785 DOI: 10.2340/jrmcc.v7.12436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 12/21/2023] [Indexed: 01/25/2024]
Abstract
Objective To explore functional connectivity after intensive attention training in the chronic phase after traumatic brain injury as clinical evidence indicates that intensive attention training improves attention dysfunction in persons with traumatic brain injury. Design and subjects A case series study. Two young adults, 13- and 18-months post traumatic brain injury, with traumatic brain injury induced attention deficits were assigned to 20 h of intensive attention training and neuroimaging. Methods Functional magnetic resonance imaging during a psychomotor vigilance test was conducted pre- and post-intervention. Results The neuroimaging indicated both increased and decreased connectivity density in frontal, posterior and subcortical brain regions, for some regions with separate change patterns for left and right hemisphere respectively, and an overall reduction in variability in functional connectivity. Conclusion The changed and decreased variability of functional connectivity in various brain regions, captured by fMRI during a psychomotor vigilance test after direct attention training in a small sample of persons with traumatic brain injury, suggests further studies of functional connectivity changes in neural networks.
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Affiliation(s)
- Hanna Persson
- Division of Rehabilitation Medicine, Danderyd University Hospital
| | - Tie-Qiang Li
- Department of Clinical Science, Intervention, and Technology, Karolinska Institutet
- Department of Medical Radiation and Nuclear Medicine, Karolinska University Hospital
| | - Gabriela Markovic
- Division of Rehabilitation Medicine, Danderyd University Hospital
- Department of Clinical Sciences, Karolinska Institutet, Danderyd University Hospital, Stockholm, Sweden
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4
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Chen N, Guo M, Li Y, Hu X, Yao Z, Hu B. Estimation of Discriminative Multimodal Brain Network Connectivity Using Message-Passing-Based Nonlinear Network Fusion. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:2398-2406. [PMID: 34941518 DOI: 10.1109/tcbb.2021.3137498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Effective estimation of brain network connectivity enables better unraveling of the extraordinary complexity interactions of brain regions and helps in auxiliary diagnosis of psychiatric disorders. Considering different modalities can provide comprehensive characterizations of brain connectivity, we propose the message-passing-based nonlinear network fusion (MP-NNF) algorithm to estimate multimodal brain network connectivity. In the proposed method, the initial functional and structural networks were computed from fMRI and DTI separately. Then, we update every unimodal network iteratively, making it more similar to the others in every iteration, and finally converge to one unified network. The estimated brain connectivities integrate complementary information from multiple modalities while preserving their original structure, by adding the strong connectivities present in unimodal brain networks and eliminating the weak connectivities. The effectiveness of the method was evaluated by applying the learned brain connectivity for the classification of major depressive disorder (MDD). Specifically, 82.18% classification accuracy was achieved even with the simple feature selection and classification pipeline, which significantly outperforms the competing methods. Exploration of brain connectivity contributed to MDD identification suggests that the proposed method not only improves the classification performance but also was sensitive to critical disease-related neuroimaging biomarkers.
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Marapin RS, van der Horn HJ, van der Stouwe AMM, Dalenberg JR, de Jong BM, Tijssen MAJ. Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI. Neuroimage Clin 2022; 37:103302. [PMID: 36669351 PMCID: PMC9868884 DOI: 10.1016/j.nicl.2022.103302] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 12/25/2022]
Abstract
BACKGROUND Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive. OBJECTIVES Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures. METHODS A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes. RESULTS Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described. CONCLUSION Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.
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Affiliation(s)
- Ramesh S Marapin
- University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Expertise Center Movement Disorders Groningen, University Medical Center Groningen (UMCG), Groningen, the Netherlands
| | - Harm J van der Horn
- University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands
| | - A M Madelein van der Stouwe
- University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Expertise Center Movement Disorders Groningen, University Medical Center Groningen (UMCG), Groningen, the Netherlands
| | - Jelle R Dalenberg
- University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Expertise Center Movement Disorders Groningen, University Medical Center Groningen (UMCG), Groningen, the Netherlands
| | - Bauke M de Jong
- University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands
| | - Marina A J Tijssen
- University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Expertise Center Movement Disorders Groningen, University Medical Center Groningen (UMCG), Groningen, the Netherlands.
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Kim KM, Hwang H, Sohn B, Park K, Han K, Ahn SS, Lee W, Chu MK, Heo K, Lee SK. Development and Validation of MRI-Based Radiomics Models for Diagnosing Juvenile Myoclonic Epilepsy. Korean J Radiol 2022; 23:1281-1289. [PMID: 36447416 PMCID: PMC9747272 DOI: 10.3348/kjr.2022.0539] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/21/2022] [Accepted: 09/26/2022] [Indexed: 11/11/2022] Open
Abstract
OBJECTIVE Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. MATERIALS AND METHODS A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. RESULTS The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. CONCLUSION Radiomic models using MRI were able to differentiate JME from HCs.
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Affiliation(s)
- Kyung Min Kim
- Department of Neurology, Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Heewon Hwang
- Department of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Beomseok Sohn
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Centre for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.
| | - Kisung Park
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Centre for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.,Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Korea
| | - Kyunghwa Han
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Centre for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Sung Soo Ahn
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Centre for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Wonwoo Lee
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Korea
| | - Min Kyung Chu
- Department of Neurology, Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Kyoung Heo
- Department of Neurology, Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Centre for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
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7
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Qin L, Zhang Y, Ren J, Lei D, Li X, Yang T, Gong Q, Zhou D. Altered brain activity in juvenile myoclonic epilepsy with a monotherapy: a resting-state fMRI study. ACTA EPILEPTOLOGICA 2022. [DOI: 10.1186/s42494-022-00101-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Juvenile myoclonic epilepsy (JME) is the most common syndrome of idiopathic generalized epilepsy. Although resting-state functional magnetic resonance imaging (rs-fMRI) studies have found thalamocortical circuit dysfunction in patients with JME, the pathophysiological mechanism of JME remains unclear. In this study, we used three complementary parameters of rs-fMRI to investigate aberrant brain activity in JME patients in comparison to that of healthy controls.
Methods
Rs-fMRI and clinical data were acquired from 49 patients with JME undergoing monotherapy and 44 age- and sex-matched healthy controls. After fMRI data preprocessing, the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated and compared between the two groups. Correlation analysis was conducted to explore the relationship between local brain abnormalities and clinical features in JME patients.
Results
Compared with the controls, the JME patients exhibited significantly decreased fALFF, ReHo and DC in the cerebellum, inferior parietal lobe, and visual cortex (including the fusiform and the lingual and middle occipital gyri), and increased DC in the right orbitofrontal cortex. In the JME patients, there were no regions with reduced ReHo compared to the controls. No significant correlation was observed between regional abnormalities of fALFF, ReHo or DC, and clinical features.
Conclusions
We demonstrated a wide range of abnormal functional activity in the brains of patients with JME, including the prefrontal cortex, visual cortex, default mode network, and cerebellum. The results suggest dysfunctions of the cerebello-cerebral circuits, which provide a clue on the potential pathogenesis of JME.
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Liu G, Zheng W, Liu H, Guo M, Ma L, Hu W, Ke M, Sun Y, Zhang J, Zhang Z. Aberrant dynamic structure-function relationship of rich-club organization in treatment-naïve newly diagnosed juvenile myoclonic epilepsy. Hum Brain Mapp 2022; 43:3633-3645. [PMID: 35417064 PMCID: PMC9294302 DOI: 10.1002/hbm.25873] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 03/28/2022] [Accepted: 04/03/2022] [Indexed: 11/25/2022] Open
Abstract
Neuroimaging studies have shown that juvenile myoclonic epilepsy (JME) is characterized by impaired brain networks. However, few studies have investigated the potential disruptions in rich‐club organization—a core feature of the brain networks. Moreover, it is unclear how structure–function relationships dynamically change over time in JME. Here, we quantify the anatomical rich‐club organization and dynamic structural and functional connectivity (SC–FC) coupling in 47 treatment‐naïve newly diagnosed patients with JME and 40 matched healthy controls. Dynamic functional network efficiency and its association with SC–FC coupling were also calculated to examine the supporting of structure–function relationship to brain information transfer. The results showed that the anatomical rich‐club organization was disrupted in the patient group, along with decreased connectivity strength among rich‐club hub nodes. Furthermore, reduced SC–FC coupling in rich‐club organization of the patients was found in two functionally independent dynamic states, that is the functional segregation state (State 1) and the strong somatomotor‐cognitive control interaction state (State 5); and the latter was significantly associated with disease severity. In addition, the relationships between SC–FC coupling of hub nodes connections and functional network efficiency in State 1 were found to be absent in patients. The aberrant dynamic SC–FC coupling of rich‐club organization suggests a selective influence of densely interconnected network core in patients with JME at the early phase of the disease, offering new insights and potential biomarkers into the underlying neurodevelopmental basis of behavioral and cognitive impairments observed in JME.
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Affiliation(s)
- Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China.,Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Hong Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China.,Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Man Guo
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Laiyang Ma
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China.,Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Wanjun Hu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China.,Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Ming Ke
- College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Yu Sun
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China.,Zhejiang Lab, Hangzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China.,Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Zhe Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China.,School of Physics, Hangzhou Normal University, Hangzhou, China
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Yang L, Liu Q, Zhou Y, Wang X, Wu T, Chen Z. No Alteration Between Intrinsic Connectivity Networks by a Pilot Study on Localized Exposure to the Fourth-Generation Wireless Communication Signals. Front Public Health 2022; 9:734370. [PMID: 35096727 PMCID: PMC8793026 DOI: 10.3389/fpubh.2021.734370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 12/14/2021] [Indexed: 11/13/2022] Open
Abstract
Neurophysiological effect of human exposure to radiofrequency signals has attracted considerable attention, which was claimed to have an association with a series of clinical symptoms. A few investigations have been conducted on alteration of brain functions, yet no known research focused on intrinsic connectivity networks, an attribute that may relate to some behavioral functions. To investigate the exposure effect on functional connectivity between intrinsic connectivity networks, we conducted experiments with seventeen participants experiencing localized head exposure to real and sham time-division long-term evolution signal for 30 min. The resting-state functional magnetic resonance imaging data were collected before and after exposure, respectively. Group-level independent component analysis was used to decompose networks of interest. Three states were clustered, which can reflect different cognitive conditions. Dynamic connectivity as well as conventional connectivity between networks per state were computed and followed by paired sample t-tests. Results showed that there was no statistical difference in static or dynamic functional network connectivity in both real and sham exposure conditions, and pointed out that the impact of short-term electromagnetic exposure was undetected at the ICNs level. The specific brain parcellations and metrics used in the study may lead to different results on brain modulation.
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Affiliation(s)
- Lei Yang
- China Academy of Information and Communications Technology, Beijing, China
| | - Qingmeng Liu
- China Academy of Information and Communications Technology, Beijing, China
| | - Yu Zhou
- China Academy of Information and Communications Technology, Beijing, China
| | - Xing Wang
- China Academy of Information and Communications Technology, Beijing, China
| | - Tongning Wu
- China Academy of Information and Communications Technology, Beijing, China
| | - Zhiye Chen
- Hainan Hospital of Chinese People's Liberation Army General Hospital, Hainan, China
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A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy. Brain Imaging Behav 2021; 16:1465-1494. [PMID: 34786666 DOI: 10.1007/s11682-021-00595-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/20/2021] [Indexed: 10/19/2022]
Abstract
Functional neuroimaging modalities have enhanced our understanding of juvenile myoclonic epilepsy (JME) underlying neural mechanisms. Due to its non-invasive, sensitive and analytical nature, functional magnetic resonance imaging (fMRI) provides valuable insights into relevant functional brain networks and their segregation and integration properties. We systematically reviewed the contribution of resting-state and task-based fMRI to the current understanding of the pathophysiology and the patterns of seizure propagation in JME Altogether, despite some discrepancies, functional findings suggest that corticothalamo-striato-cerebellar network along with default-mode network and salience network are the most affected networks in patients with JME. However, further studies are required to investigate the association between JME's main deficiencies, e.g., motor and cognitive deficiencies and fMRI findings. Moreover, simultaneous electroencephalography-fMRI (EEG-fMRI) studies indicate that alterations of these networks play a role in seizure modulation but fall short of identifying a causal relationship between altered functional properties and seizure propagation. This review highlights the complex pathophysiology of JME, which necessitates the design of more personalized diagnostic and therapeutic strategies in this group.
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Dataset of whole-brain resting-state fMRI of 227 young and elderly adults acquired at 3T. Data Brief 2021; 38:107333. [PMID: 34504919 PMCID: PMC8417222 DOI: 10.1016/j.dib.2021.107333] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 02/06/2023] Open
Abstract
To investigate the impact of adult age on the brain functional connectivity, whole-brain resting-state functional magnetic resonance imaging (R-fMRI) data were acquired on a 3T clinical MRI scanner in a cohort of 227, right-handed, native Swedish-speaking, healthy adult volunteers (N=227, aged 18-74 years old, male/female=99/128). The dataset is mainly consisted of a younger (18-30 years old n=124, males/females=51/73) and elderly adult (n=76, 60-76 years old, males/females=35/41) subgroups. The dataset was analyzed using a new data-driven analysis (QDA) framework. With QDA two types of threshold-free voxel-wise resting-state functional connectivity (RFC) metrics were derived: the connectivity strength index (CSI) and connectivity density index (CDI), which can be utilized to assess the brain changes in functional connectivity associated with adult age. The dataset can also be useful as a reference to identify abnormal changes in brain functional connectivity resulted from neurodegenerative or neuropsychiatric disorders.
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12
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Jiao Z, Gao P, Ji Y, Shi H. Integration and Segregation of Dynamic Functional Connectivity States for Mild Cognitive Impairment Revealed by Graph Theory Indicators. CONTRAST MEDIA & MOLECULAR IMAGING 2021; 2021:6890024. [PMID: 34366726 PMCID: PMC8313367 DOI: 10.1155/2021/6890024] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/14/2021] [Accepted: 07/01/2021] [Indexed: 02/06/2023]
Abstract
Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Researchers tend to discuss its early state (early MCI, eMCI) due to its high conversion rate of dementia and poor treatment effect in the middle and late stages. Currently, the research on the disease evolution of the brain functional networks of patients with MCI has gradually become a research hotspot. In this study, we compare the differences in dynamic functional connectivity among eMCI, late MCI (lMCI), and normal control (NC) groups, and their graph theory indicators reveal the integration and segregation of functional connectivity states. Firstly, dynamic functional network windows were constructed based on the sliding time window method, and then these window samples were clustered by k-means to extract the functional connectivity states. The differences in the three groups were compared by analyzing the graph theory indicators, such as the participation coefficient, module degree distribution, clustering coefficient, global efficiency, and local efficiency, which distinguish the functional connectivity states. The results reveal that the NC group has the strongest integration and segregation, followed by the eMCI group, and the lMCI group has the weakest integration and segregation. We conclude that with the aggravation of MCI, the integration and segregation of dynamic functional connectivity states tend to decline. The results also reflect that the lMCI group has significantly more brain functional connections in some states, such as IPL.L-MTG.R and DCG.R-SMG.L, than the eMCI group, while the lMCI group has significantly less OLF.L-SPG.L than the NC group.
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Affiliation(s)
- Zhuqing Jiao
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Peng Gao
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China
| | - Yixin Ji
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China
| | - Haifeng Shi
- Department of Radiology, Changzhou Second People's Hospital Affiliated to Nanjing Medical University, Changzhou 213003, China
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Yang Y, Zha X, Zhang X, Ke J, Hu S, Wang X, Su Y, Hu C. Dynamics and Concordance Abnormalities Among Indices of Intrinsic Brain Activity in Individuals With Subjective Cognitive Decline: A Temporal Dynamics Resting-State Functional Magnetic Resonance Imaging Analysis. Front Aging Neurosci 2021; 12:584863. [PMID: 33568986 PMCID: PMC7868384 DOI: 10.3389/fnagi.2020.584863] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 12/03/2020] [Indexed: 11/13/2022] Open
Abstract
Individuals with subjective cognitive decline (SCD) are more likely to develop into Alzheimer disease (AD) in the future. Resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown alterations of intrinsic brain activity (IBA) in SCD individuals. However, rs-fMRI studies to date have mainly focused on static characteristics of IBA, with few studies reporting dynamics- and concordance-related changes in IBA indices in SCD individuals. To investigate these aberrant changes, a temporal dynamic analysis of rs-fMRI data was conducted on 94 SCD individuals (71.07 ± 6.18 years, 60 female), 75 (74.36 ± 8.42 years, 35 female) mild cognitive impairment (MCI) patients, and 82 age-, gender-, and education-matched controls (NCs; 73.88 ± 7.40 years, 49 female) from the Alzheimer's Disease Neuroimaging Initiative database. The dynamics and concordance of the rs-fMRI indices were calculated. The results showed that SCD individuals had a lower amplitude of low-frequency fluctuations dynamics in bilateral hippocampus (HP)/parahippocampal gyrus (PHG)/fusiform gyrus (FG) and bilateral cerebellum, a lower fractional amplitude of low-frequency fluctuation dynamics in bilateral precuneus (PreCu) and paracentral lobule, and a lower regional homogeneity dynamics in bilateral cerebellum, vermis, and left FG compared with the other two groups, whereas those in MCI patients were higher (Gaussian random field-corrected, voxel-level P < 0.001, cluster-level P < 0.05). Furthermore, SCD individuals had higher concordance in bilateral HP/PHG/FG, temporal lobe, and left midcingulate cortex than NCs, but those in MCI were lower than those in NCs. No correlation between concordance values and neuropsychological scale scores was found. SCD individuals showed both dynamics and concordance-related alterations in IBA, which indicates a compensatory mechanism in SCD individuals. Temporal dynamics analysis offers a novel approach to capturing brain alterations in individuals with SCD.
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Affiliation(s)
- Yiwen Yang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Medical Imaging, Soochow University, Suzhou, China
| | - Xinyi Zha
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiaodong Zhang
- Department of Radiology, Tianjin First Central Hospital, Tianjin, China
| | - Jun Ke
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Medical Imaging, Soochow University, Suzhou, China
| | - Su Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Medical Imaging, Soochow University, Suzhou, China
| | - Ximing Wang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Medical Imaging, Soochow University, Suzhou, China
| | - Yunyan Su
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Medical Imaging, Soochow University, Suzhou, China
| | - Chunhong Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Medical Imaging, Soochow University, Suzhou, China
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14
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Do interictal EEG findings reflect cognitive function in juvenile myoclonic epilepsy? Epilepsy Behav 2020; 111:107281. [PMID: 32702653 DOI: 10.1016/j.yebeh.2020.107281] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 06/17/2020] [Accepted: 06/17/2020] [Indexed: 11/20/2022]
Abstract
PURPOSE This study investigated the relationship between frontal lobe cognitive function and frontal focal electroencephalography (EEG) findings in patients with juvenile myoclonic epilepsy (JME). METHODS The study enrolled 60 patients diagnosed with JME and followed at the Epilepsy Outpatient Clinic of the University of Health Sciences, Bakırkoy Psychiatric Hospital, and 30 healthy volunteers. Demographic and clinical features were recorded. Frontal lobe cognitive functions were tested in both groups. Video-EEG recordings of patients with JME were evaluated. The presence and duration of generalized discharges, the presence and lateralization of focal findings, and the presence of generalized discharges during hyperventilation and photic stimulation were recorded during EEG. Cognitive function test results were compared between the two groups, and the relationship between the EEG findings and cognitive function was investigated. RESULTS The study included 35 (58.3%) female and 25 (41.6%) male patients and 17 (56.7%) female and 13 (43.3%) male healthy controls. The mean ages of the group with JME and controls were 28.3 ± 8.6 (16-50) and 31.3 ± 7.9 (17-45) years, respectively. Patients with JME performed more poorly on the frontal lobe cognitive tests than controls (p < 0.05). Patients whose generalized discharges were longer than 1 s performed more poorly on tests evaluating attention and made more perseverative errors (p < 0.05). There was no significant correlation between the presence of focal EEG findings and the scores on frontal lobe cognitive functions tests in the group with JME (p > 0.05). CONCLUSION Frontal lobe cognitive functions are affected in patients with JME. The cognitive effects were more pronounced in patients with prolonged generalized discharges on EEG.
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Zhang Z, Liu G, Zheng W, Shi J, Liu H, Sun Y. Altered dynamic effective connectivity of the default mode network in newly diagnosed drug-naïve juvenile myoclonic epilepsy. Neuroimage Clin 2020; 28:102431. [PMID: 32950903 PMCID: PMC7509229 DOI: 10.1016/j.nicl.2020.102431] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 08/08/2020] [Accepted: 09/08/2020] [Indexed: 01/21/2023]
Abstract
Juvenile myoclonic epilepsy (JME) has been repeatedly revealed to be associated with brain dysconnectivity in the default mode network (DMN). However, the implicit assumption of stationary and nondirectional functional connectivity (FC) in most previous resting-state fMRI studies raises an open question of JME-related aberrations in dynamic causal properties of FC. Here, we introduces an empirical method incorporating sliding-window approach and a multivariate Granger causality analysis to investigate, for the first time, the reorganization of dynamic effective connectivity (DEC) in DMN for patients with JME. DEC was obtained from resting-state fMRI of 34 patients with newly diagnosed and drug-naïve JME and 34 matched controls. Through clustering analysis, we found two distinct states that characterize the DEC patterns (i.e., a less frequent, strongly connected state (State 1) and a more frequent, weakly connected state (State 2)). Patients showed altered ECs within DMN subnetworks in the State 2, whereas abnormal ECs between DMN subnetworks were found in the State 1. Furthermore, we observed that the causal influence flows of the medial prefrontal cortex and angular gyrus were altered in a manner of state specificity, and associated with disease severity of patients. Overall, our findings extend the dysconnectivity hypothesis in JME from static to dynamic causal FC and demonstrate that aberrant DEC may underlie abnormal brain function in JME at early phase of illness.
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Affiliation(s)
- Zhe Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Zhejiang, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Weihao Zheng
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Zhejiang, China
| | - Jie Shi
- School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Hong Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Yu Sun
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Zhejiang, China; Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Zhejiang, China.
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16
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First Epileptic Seizure and Initial Diagnosis of Juvenile Myoclonus Epilepsy (JME) in a Transcranial Direct Current Stimulation (tDCS) Study– Ethical Analysis of a Clinical case. NEUROETHICS-NETH 2020. [DOI: 10.1007/s12152-020-09444-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
AbstractWe discuss an epileptic incident in an undiagnosed 13-year old girl participating in a clinical study investigating the effects of transcranial direct current stimulation (tDCS) in healthy children and adolescents. This incident poses important research ethics questions with regard to study design, especially pertaining to screening and gaining informed consent. Potential benefits and problems of the incident also need to be considered. The ethical analysis of the case presented in this paper has been informed by an in-depth interview conducted after the incident with the child and the accompanying parent. We discuss the ethical implications of the epileptic incident, the need for improving screening procedures for studies with minors and for providing more effective communication. This case also underscores the problem of undetected teenage epilepsy in neuropsychological clinical studies and the necessity of raising more awareness of this issue. Since research in tDCS is an active and expanding field, we conclude with providing some recommendation that could ensure that future research on tDCS, or other therapies and neuro-interventions where there is a risk of triggering an epileptic seizure, take into account the specifics of teenage epilepsy and the need for more thorough provision of information during the process of gaining informed consent.
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17
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Christiaen E, Goossens MG, Descamps B, Larsen LE, Boon P, Raedt R, Vanhove C. Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration. Neurobiol Dis 2020; 139:104808. [PMID: 32087287 DOI: 10.1016/j.nbd.2020.104808] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 01/21/2020] [Accepted: 02/18/2020] [Indexed: 12/14/2022] Open
Abstract
Epilepsy is a neurological disorder characterized by recurrent epileptic seizures. The involvement of abnormal functional brain networks in the development of epilepsy and its comorbidities has been demonstrated by electrophysiological and neuroimaging studies in patients with epilepsy. This longitudinal study investigated changes in dynamic functional connectivity (dFC) and network topology during the development of epilepsy using the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE). Resting state functional magnetic resonance images (rsfMRI) of 20 IPKA animals and 7 healthy control animals were acquired before and 1, 3, 6, 10 and 16 weeks after status epilepticus (SE) under medetomidine anaesthesia using a 7 T MRI system. Starting from 17 weeks post-SE, hippocampal EEG was recorded to determine the mean daily seizure frequency of each animal. Dynamic FC was assessed by calculating the correlation matrices between fMRI time series of predefined regions of interest within a sliding window of 50 s using a step length of 2 s. The matrices were classified into 6 FC states, each characterized by a correlation matrix, using k-means clustering. In addition, several time-variable graph theoretical network metrics were calculated from the time-varying correlation matrices and classified into 6 states of functional network topology, each characterized by a combination of network metrics. Our results showed that FC states with a lower mean functional connectivity, lower segregation and integration occurred more often in IPKA animals compared to control animals. Functional connectivity also became less variable during epileptogenesis. In addition, average daily seizure frequency was positively correlated with percentage dwell time (i.e. how often a state occurs) in states with high mean functional connectivity, high segregation and integration, and with the number of transitions between states, while negatively correlated with percentage dwell time in states with a low mean functional connectivity, low segregation and low integration. This indicates that animals that dwell in states of higher functional connectivity, higher segregation and higher integration, and that switch more often between states, have more seizures.
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Affiliation(s)
- Emma Christiaen
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium.
| | | | - Benedicte Descamps
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Lars E Larsen
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; 4Brain Team, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Paul Boon
- 4Brain Team, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- 4Brain Team, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
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18
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First generalized tonic clonic seizure in the context of pediatric tDCS – A case report. Neurophysiol Clin 2020; 50:69-72. [DOI: 10.1016/j.neucli.2019.11.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 11/18/2019] [Accepted: 11/19/2019] [Indexed: 02/02/2023] Open
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19
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Valsasina P, Hidalgo de la Cruz M, Filippi M, Rocca MA. Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis. Front Neurosci 2019; 13:618. [PMID: 31354402 PMCID: PMC6636554 DOI: 10.3389/fnins.2019.00618] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 05/29/2019] [Indexed: 01/27/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called “sliding windows,” in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.
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Affiliation(s)
- Paola Valsasina
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Milagros Hidalgo de la Cruz
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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