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Zhang C, Zhang K, Hu X, Cai X, Chen Y, Gao F, Wang G. Regional GABA levels modulate abnormal resting-state network functional connectivity and cognitive impairment in multiple sclerosis. Cereb Cortex 2024; 34:bhad535. [PMID: 38271282 DOI: 10.1093/cercor/bhad535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/18/2023] [Accepted: 12/19/2023] [Indexed: 01/27/2024] Open
Abstract
More evidence shows that changes in functional connectivity with regard to brain networks and neurometabolite levels correlated to cognitive impairment in multiple sclerosis. However, the neurological basis underlying the relationship among neurometabolite levels, functional connectivity, and cognitive impairment remains unclear. For this purpose, we used a combination of magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to study gamma-aminobutyric acid and glutamate concentrations in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus, and inter-network functional connectivity in 29 relapsing-remitting multiple sclerosis patients and 34 matched healthy controls. Neuropsychological tests were used to evaluate the cognitive function. We found that relapsing-remitting multiple sclerosis patients demonstrated significantly reduced gamma-aminobutyric acid and glutamate concentrations and aberrant functional connectivity involving cognitive-related networks compared to healthy controls, and both alterations were associated with specific cognition decline. Moreover, mediation analyses indicated that decremented hippocampus gamma-aminobutyric acid levels in relapsing-remitting multiple sclerosis patients mediated the association between inter-network functional connectivity in various components of default mode network and verbal memory deficits. In summary, our findings shed new lights on the essential function of GABAergic system abnormalities in regulating network dysconnectivity and functional connectivity in relapsing-remitting multiple sclerosis patients, suggesting potential novel approach to treatment.
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Affiliation(s)
- Chao Zhang
- Department of Radiology, Shandong Provincial Hospital, Shandong University, Jinan 250021, China
| | - Kaihua Zhang
- School of Psychology, Shandong Normal University, Jinan 250358, China
| | - Xin Hu
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Xianyun Cai
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Yufan Chen
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Fei Gao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital, Shandong University, Jinan 250021, China
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
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George AB, Beniwal RP, Singh S, Bhatia T, Khushu S, Deshpande SN. Association between thyroid functions, cognition, and functional connectivity of the brain in early-course schizophrenia: A preliminary study. Ind Psychiatry J 2023; 32:S76-S82. [PMID: 38370920 PMCID: PMC10871410 DOI: 10.4103/ipj.ipj_198_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/28/2023] [Accepted: 07/16/2023] [Indexed: 02/20/2024] Open
Abstract
Background The functional outcome of the debilitating mental illness schizophrenia (SZ) has an integral role in cognition. The thyroid hormone has a vital role in the developmental stages and functioning of the human brain. Aim This study aimed to evaluate the relationship between thyroid functions, cognition, and functional imaging of the brain in persons with SZ. Materials and Methods Sixty SZ (Diagnostic and Statistical Manual (DSM-5)) persons, aged 18-50 years of both genders, were recruited in this cross-sectional observational study. Positive and Negative Syndrome Scale (PANSS) and Trail Making Tests (TMTs) A and B were administered to all patients. To assess the level of thyroid hormone, a test was conducted. Functional connectivity of the brain was assessed using resting-state functional magnetic resonance imaging (rs-fMRI). Data analysis was performed by descriptive and analytical statistical methods. FSL version 5.9 (FMRIB's) software was used for analyses of fMRI neuroimages. Results There were no significant differences between the two populations on sociodemographic factors. The average value for thyroid-stimulating hormone (TSH) in the hypothyroid group (n = 12) and the euthyroid group (n = 47) was 8.38 mIU/l and 2.44 mIU/l, respectively. The average time in seconds for TMT-A and TMT-B was 87.27 and 218.27 in the hypothyroid group and 97.07 and 293.27 in the euthyroid group, respectively. Similarly, in the sample matched on age, gender, and age at onset of illness, there were no significant differences in demographic and clinical factors and resting-state network (RSN) between the hypothyroid (N = 10) and euthyroid (N = 10) groups. Conclusion No differences were found in the functional brain network between the hypothyroid and euthyroid groups as the study sample did not include clinically hypothyroid persons with SZ.
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Affiliation(s)
- Aishwariya B George
- Department of Psychiatry, Malabar Medical College Hospital and Research Centre, Kozhikode, Kerala, India
| | - Ram P Beniwal
- Department of Psychiatry, Centre of Excellence in Mental Health, Atal Bihari Vajpayee Institute of Medical Sciences and Dr. Ram Manohar Lohia Hospital, New Delhi, India
| | - Sadhana Singh
- Centre for Brain Research, Indian Institute of Science, Bengaluru, Karnataka, India
| | - Triptish Bhatia
- Department of Psychiatry, Centre of Excellence in Mental Health, Atal Bihari Vajpayee Institute of Medical Sciences and Dr. Ram Manohar Lohia Hospital, New Delhi, India
| | - Subhash Khushu
- Division of Radiological Imaging, and Bio-Medical Imaging, The University of Trans-Disciplinary Health Sciences and Technology, Bengaluru, Karnataka, India
| | - Smita N Deshpande
- Department of Psychiatry, St John's Medical College Hospital, Bengaluru, Karnataka, India
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Li Y, Yang Q, Liu Y, Wang R, Zheng Y, Zhang Y, Si Y, Jiang L, Chen B, Peng Y, Wan F, Yu J, Yao D, Li F, He B, Xu P. Resting-state network predicts the decision-making behaviors of the proposer during the ultimatum game. J Neural Eng 2023; 20:056003. [PMID: 37659391 DOI: 10.1088/1741-2552/acf61e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 09/01/2023] [Indexed: 09/04/2023]
Abstract
Objective. The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer's decision-making is a crucial issue. Yet the neural substrate of the proposer's decision behavior, especially from the resting-state network perspective, remains unclear.Approach. In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers' unfair offer rates in the ultimatum game.Main results.The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors.Significance. Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.
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Affiliation(s)
- Yuqin Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Qian Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Yuxin Liu
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Rui Wang
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Yutong Zheng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Yubo Zhang
- School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, People's Republic of China
| | - Yajing Si
- School of Psychology, Xinxiang Medical University, Xinxiang 453003, People's Republic of China
| | - Lin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Baodan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Yueheng Peng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, People's Republic of China
| | - Jing Yu
- Faculty of Psychology, Southwest University, Chongqing 400715, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, People's Republic of China
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, People's Republic of China
| | - Baoming He
- Department of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, People's Republic of China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu 610072, People's Republic of China
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, People's Republic of China
- Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610041, People's Republic of China
- Rehabilitation Center, Qilu Hospital of Shandong University, Jinan 250012, People's Republic of China
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Yu Z, Pang H, Liu Y, Li X, Bu S, Wang J, Zhao M, Ren K. Disrupted network communication predicts mild cognitive impairment in end-stage renal disease: an individualized machine learning study based on resting-state fMRI. Cereb Cortex 2023; 33:10098-10107. [PMID: 37492012 DOI: 10.1093/cercor/bhad269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 07/27/2023] Open
Abstract
End-Stage Renal Disease (ESRD) is known to be associated with a range of brain injuries, including cognitive decline. The purpose of this study is to investigate the functional connectivity (FC) of the resting-state networks (RSNs) through resting state functional magnetic resonance imaging (MRI), in order to gain insight into the neuropathological mechanism of ESRD. A total of 48 ESRD patients and 49 healthy controls underwent resting-state functional MRI and neuropsychological tests, for which Independent Components Analysis and graph-theory (GT) analysis were utilized. With the machine learning results, we examined the connections between RSNs abnormalities and neuropsychological test scores. Combining intra/inter network FC differences and GT results, ESRD was optimally distinguished in the testing dataset, with a balanced accuracy of 0.917 and area under curve (AUC) of 0.942. Shapley additive explanations results revealed that the increased functional network connectivity between DMN and left frontoparietal network (LFPN) was the most critical predictor for ESRD associated mild cognitive impairment diagnosis. Moreover, hypoSN (salience network) was positively correlated with Attention scores, while hyperLFPN was negatively correlated with Execution scores, indicating correlations between functional disruption and cognitive impairment measurements in ESRD patients. This study demonstrated that both the loss of FC within the SN and compensatory FC within the lateral frontoparietal network coexist in ESRD. This provides a network basis for understanding the individual brain circuits and offers additional noninvasive evidence to comprehend the brain networks in ESRD.
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Affiliation(s)
- Ziyang Yu
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
- School of Medicine, Xiamen University, Xiamen, Fujian Province, China
| | - Huize Pang
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - Yu Liu
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - Xiaolu Li
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - Shuting Bu
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - Juzhou Wang
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - Mengwan Zhao
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - Ke Ren
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
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5
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Bartnik A, Fuchs TA, Ashton K, Kuceyeski A, Li X, Mallory M, Oship D, Bergsland N, Ramasamy D, Jakimovski D, Benedict RHB, Weinstock-Guttman B, Zivadinov R, Dwyer MG. Functional alteration due to structural damage is network dependent: insight from multiple sclerosis. Cereb Cortex 2023; 33:6090-6102. [PMID: 36585775 PMCID: PMC10498137 DOI: 10.1093/cercor/bhac486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 11/15/2022] [Accepted: 11/17/2022] [Indexed: 01/01/2023] Open
Abstract
Little is known about how the brain's functional organization changes over time with respect to structural damage. Using multiple sclerosis as a model of structural damage, we assessed how much functional connectivity (FC) changed within and between preselected resting-state networks (RSNs) in 122 subjects (72 with multiple sclerosis and 50 healthy controls). We acquired the structural, diffusion, and functional MRI to compute functional connectomes and structural disconnectivity profiles. Change in FC was calculated by comparing each multiple sclerosis participant's pairwise FC to controls, while structural disruption (SD) was computed from abnormalities in diffusion MRI via the Network Modification tool. We used an ordinary least squares regression to predict the change in FC from SD for 9 common RSNs. We found clear differences in how RSNs functionally respond to structural damage, namely that higher-order networks were more likely to experience changes in FC in response to structural damage (default mode R2 = 0.160-0.207, P < 0.001) than lower-order sensory networks (visual network 1 R2 = 0.001-0.007, P = 0.157-0.387). Our findings suggest that functional adaptability to structural damage depends on how involved the affected network is in higher-order processing.
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Affiliation(s)
- Alexander Bartnik
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Tom A Fuchs
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Kira Ashton
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Amy Kuceyeski
- Department of Radiology, Weill Medical College of Cornell University, New York, NY 10065, United States
| | - Xian Li
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Psychological and Brain Science Department, Johns Hopkins University, Baltimore, MD 21218, United States
| | - Matthew Mallory
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Devon Oship
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Niels Bergsland
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan 20148, Italy
| | - Deepa Ramasamy
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Dejan Jakimovski
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Ralph H B Benedict
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Bianca Weinstock-Guttman
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Robert Zivadinov
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
| | - Michael G Dwyer
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States
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6
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Qiu S, Lyu X, Zheng Q, He H, Jin R, Peng W. Temporal dynamics of electroencephalographic microstates during sustained pain. Cereb Cortex 2023:7145897. [PMID: 37106566 DOI: 10.1093/cercor/bhad143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 04/10/2023] [Accepted: 04/11/2023] [Indexed: 04/29/2023] Open
Abstract
Brain dynamics can be modeled by a sequence of transient, nonoverlapping patterns of quasi-stable electrical potentials named "microstates." While electroencephalographic (EEG) microstates among patients with chronic pain remained inconsistent in the literature, this study characterizes the temporal dynamics of EEG microstates among healthy individuals during experimental sustained pain. We applied capsaicin (pain condition) or control (no-pain condition) cream to 58 healthy participants in different sessions and recorded resting-state EEG 15 min after application. We identified 4 canonical microstates (A-D) that are related to auditory, visual, salience, and attentional networks. Microstate C had less occurrence, as were bidirectional transitions between microstate C and microstates A and B during sustained pain. In contrast, sustained pain was associated with more frequent and longer duration of microsite D, as well as more bidirectional transitions between microstate D and microstates A and B. Microstate D duration positively correlated with intensity of ongoing pain. Sustained pain improved global integration within microstate C functional network, but weakened global integration and efficiency within microstate D functional network. These results suggest that sustained pain leads to an imbalance between processes that load on saliency (microstate C) and processes related to switching and reorientation of attention (microstate D).
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Affiliation(s)
- Shuang Qiu
- Laboratory of Brain Atlas and Brain-Inspired Intelligence, State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Science, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaohan Lyu
- School of Psychology, Shenzhen University, Shenzhen, Guangdong 518060, China
| | - Qianqian Zheng
- School of Psychology, Shenzhen University, Shenzhen, Guangdong 518060, China
| | - Huiguang He
- Laboratory of Brain Atlas and Brain-Inspired Intelligence, State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Science, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Richu Jin
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Weiwei Peng
- School of Psychology, Shenzhen University, Shenzhen, Guangdong 518060, China
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7
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Pandria N, Athanasiou A, Styliadis C, Terzopoulos N, Mitsopoulos K, Paraskevopoulos E, Karagianni M, Pataka A, Kourtidou-Papadeli C, Makedou K, Iliadis S, Lymperaki E, Nimatoudis I, Argyropoulou-Pataka P, Bamidis PD. Does combined training of biofeedback and neurofeedback affect smoking status, behavior, and longitudinal brain plasticity? Front Behav Neurosci 2023; 17:1096122. [PMID: 36778131 PMCID: PMC9911884 DOI: 10.3389/fnbeh.2023.1096122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 01/02/2023] [Indexed: 01/28/2023] Open
Abstract
Introduction: Investigations of biofeedback (BF) and neurofeedback (NF) training for nicotine addiction have been long documented to lead to positive gains in smoking status, behavior and to changes in brain activity. We aimed to: (a) evaluate a multi-visit combined BF/NF intervention as an alternative smoking cessation approach, (b) validate training-induced feedback learning, and (c) document effects on resting-state functional connectivity networks (rsFCN); considering gender and degree of nicotine dependence in a longitudinal design. Methods: We analyzed clinical, behavioral, and electrophysiological data from 17 smokers who completed five BF and 20 NF sessions and three evaluation stages. Possible neuroplastic effects were explored comparing whole-brain rsFCN by phase-lag index (PLI) for different brain rhythms. PLI connections with significant change across time were investigated according to different resting-state networks (RSNs). Results: Improvements in smoking status were observed as exhaled carbon monoxide levels, Total Oxidative Stress, and Fageström scores decreased while Vitamin E levels increased across time. BF/NF promoted gains in anxiety, self-esteem, and several aspects of cognitive performance. BF learning in temperature enhancement was observed within sessions. NF learning in theta/alpha ratio increase was achieved across baselines and within sessions. PLI network connections significantly changed across time mainly between or within visual, default mode and frontoparietal networks in theta and alpha rhythms, while beta band RSNs mostly changed significantly after BF sessions. Discussion: Combined BF/NF training positively affects the clinical and behavioral status of smokers, displays benefit in smoking harm reduction, plays a neuroprotective role, leads to learning effects and to positive reorganization of RSNs across time. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02991781.
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Affiliation(s)
- Niki Pandria
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
| | - Alkinoos Athanasiou
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
| | - Charis Styliadis
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
| | - Nikos Terzopoulos
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
| | - Konstantinos Mitsopoulos
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
| | - Evangelos Paraskevopoulos
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece,Department of Psychology, University of Cyprus, Nicosia, Cyprus
| | - Maria Karagianni
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
| | - Athanasia Pataka
- Pulmonary Department-Oncology Unit, “G. Papanikolaou” General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | - Kali Makedou
- Laboratory of Biochemistry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Stavros Iliadis
- Laboratory of Biochemistry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Evgenia Lymperaki
- Department of Biomedical Sciences, International Hellenic University, Thessaloniki, Greece
| | - Ioannis Nimatoudis
- Third Department of Psychiatry, AHEPA University General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | - Panagiotis D. Bamidis
- Laboratory of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece,*Correspondence: Panagiotis D. Bamidis
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8
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Sjuls GS, Specht K. Variability in Resting-State Functional Magnetic Resonance Imaging: The Effect of Body Mass, Blood Pressure, Hematocrit, and Glycated Hemoglobin on Hemodynamic and Neuronal Parameters. Brain Connect 2022; 12:870-882. [PMID: 35473334 PMCID: PMC9807254 DOI: 10.1089/brain.2021.0125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Introduction: Replicability has become an increasing focus within the scientific communities with the ongoing "replication crisis." One area that appears to struggle with unreliable results is resting-state functional magnetic resonance imaging (rs-fMRI). Therefore, the current study aimed at improving the knowledge of endogenous factors that contribute to inter-individual variability. Methods: Arterial blood pressure (BP), body mass, hematocrit, and glycated hemoglobin were investigated as potential sources of between-subject variability in rs-fMRI, in healthy individuals. Whether changes in resting-state networks (rs-networks) could be attributed to variability in the blood-oxygen-level-dependent (BOLD)-signal, changes in neuronal activity, or both was of special interest. Within-subject parameters were estimated by utilizing dynamic-causal modeling, as it allows to make inferences on the estimated hemodynamic (BOLD-signal dynamics) and neuronal parameters (effective connectivity) separately. Results: The results of the analyses imply that BP and body mass can cause between-subject and between-group variability in the BOLD-signal and that all the included factors can affect the underlying connectivity. Discussion: Given the results of the current and previous studies, rs-fMRI results appear to be susceptible to a range of factors, which is likely to contribute to the low degree of replicability of these studies. Interestingly, the highest degree of variability seems to appear within the much-studied default mode network and its connections to other networks. Impact statement We believe that thanks to the evidence that we have collected by analyzing the well-controlled data of the Human Connectome Project with dynamic-causal modeling (DCM) and by focusing not only on the effective connectivity, which is the typical way of using DCM, but also by analyzing the underlying hemodynamic parameters, we were able to explore the underlying vascular dependencies in a much broader perspective. Our results challenge the premise for studying changes in the default mode network as a clinical marker of disease, and we add to the growing list of factors that contribute to resting-state network variability.
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Affiliation(s)
- Guro Stensby Sjuls
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.,Mohn Medical and Imaging Visualization Centre, Haukeland University Hospital, Bergen, Norway.,Language Acquisition and Language Processing Lab, Department of Language and Literature, Norwegian University of Science and Technology, Trondheim, Norway.,Address correspondence to: Guro Stensby Sjuls, Language Acquisition and Language Processing Lab, Department of Language and Literature, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Karsten Specht
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.,Mohn Medical and Imaging Visualization Centre, Haukeland University Hospital, Bergen, Norway.,Department of Education, UiT/The Arctic University of Norway, Tromsø, Norway
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9
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Li Y, Liu H, Yu H, Yang H, Guo M, Cao C, Pang H, Liu Y, Cao K, Fan G. Alterations of voxel-wise spontaneous activity and corresponding brain functional networks in multiple system atrophy patients with mild cognitive impairment. Hum Brain Mapp 2022; 44:403-417. [PMID: 36073537 PMCID: PMC9842910 DOI: 10.1002/hbm.26058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 07/18/2022] [Accepted: 08/04/2022] [Indexed: 01/25/2023] Open
Abstract
Emerging evidence has indicated that cognitive impairment is an underrecognized feature of multiple system atrophy (MSA). Mild cognitive impairment (MCI) is related to a high risk of dementia. However, the mechanism underlying MCI in MSA remains controversial. In this study, we conducted the amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) analyses to detect the characteristics of local neural activity and corresponding network alterations in MSA patients with MCI (MSA-MCI). We enrolled 80 probable MSA patients classified as cognitively normal (MSA-NC, n = 36) and MSA-MCI (n = 44) and 40 healthy controls. Compared with MSA-NC, MSA-MCI exhibited decreased ALFF in the right dorsal lateral prefrontal cortex (RDLPFC) and increased ALFF in the right cerebellar lobule IX and lobule IV-V. In the secondary FC analyses, decreased FC in the left inferior parietal lobe (IPL) was observed when we set the RDLPFC as the seed region. Decreased FC in the bilateral cuneus, left precuneus, and left IPL and increased FC in the right middle temporal gyrus were shown when we set the right cerebellar lobule IX as the seed region. Furthermore, FC of DLPFC-IPL and cerebello-cerebral circuit, as well as ALFF alterations, were significantly correlated with Montreal Cognitive Assessment scores in MSA patients. We also employed whole-brain voxel-based morphometry analysis, but no gray matter atrophy was detected between the patient subgroups. Our findings indicate that altered spontaneous activity in the DLPFC and the cerebellum and disrupted DLPFC-IPL, cerebello-cerebral networks are possible biomarkers of early cognitive decline in MSA patients.
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Affiliation(s)
- Yingmei Li
- Department of Radiology, The First HospitalChina Medical UniversityShenyangLiaoningChina
| | - Hu Liu
- Department of Radiology, The First HospitalChina Medical UniversityShenyangLiaoningChina
| | - Hongmei Yu
- Department of Neurology, The First HospitalChina Medical UniversityShenyangLiaoningChina
| | - Huaguang Yang
- Department of Radiology, Renmin HospitalWuhan UniversityWuhanHubeiChina
| | - Miaoran Guo
- Department of Radiology, The First HospitalChina Medical UniversityShenyangLiaoningChina
| | - Chenghao Cao
- Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Huize Pang
- Department of Radiology, The First HospitalChina Medical UniversityShenyangLiaoningChina
| | - Yu Liu
- Department of Radiology, The First HospitalChina Medical UniversityShenyangLiaoningChina
| | - Kaiqiang Cao
- Department of Radiology, The First HospitalChina Medical UniversityShenyangLiaoningChina
| | - Guoguang Fan
- Department of Radiology, The First HospitalChina Medical UniversityShenyangLiaoningChina
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10
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Luo Q, Chen J, Li Y, Wu Z, Lin X, Yao J, Yu H, Wu H, Peng H. Aberrant brain connectivity is associated with childhood maltreatment in individuals with major depressive disorder. Brain Imaging Behav 2022; 16:2021-2036. [PMID: 35906517 DOI: 10.1007/s11682-022-00672-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/28/2022] [Indexed: 11/02/2022]
Abstract
Although childhood maltreatment confers a high risk for the development of major depressive disorder, the neurobiological mechanisms underlying this connection remain unknown. The present study sought to identify the specific resting-state networks associated with childhood maltreatment. We recruited major depressive disorder patients with and without a history of childhood maltreatment (n = 31 and n = 30, respectively) and healthy subjects (n = 80). We used independent component analysis to compute inter- and intra- network connectivity. We found that individuals with major depressive disorder and childhood maltreatment could be characterized by the following network disconnectivity model relative to healthy subjects: (i) decreased intra-network connectivity in the left frontoparietal network and increased intra-network connectivity in the right frontoparietal network, (ii) decreased inter-network connectivity in the posterior default mode network-auditory network, posterior default mode network-limbic system, posterior default mode network-anterior default mode network, auditory network-medial visual network, lateral visual network - medial visual network, medial visual network-sensorimotor network, medial visual network - anterior default mode network, occipital pole visual network-dorsal attention network, and posterior default mode network-anterior default mode network, and (iii) increased inter-network connectivity in the sensorimotor network-ventral attention network, and dorsal attention network-ventral attention network. Moreover, we found significant correlations between the severity of childhood maltreatment and the intra-network connectivity of the frontoparietal network. Our study demonstrated that childhood maltreatment is integrally associated with aberrant network architecture in patients with major depressive disorder.
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Affiliation(s)
- Qianyi Luo
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Juran Chen
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Yuhong Li
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Zhiyao Wu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Xinyi Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Jiazheng Yao
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Huiwen Yu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China. .,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China.
| | - Hongjun Peng
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China. .,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China.
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11
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Chen PH, Ku HL, Wang JK, Kang JH, Hsu TY. Electroencephalographic Microstates are Correlated with Global Functioning in Schizophrenia But Not in Bipolar Disorder. Clin EEG Neurosci 2022; 54:215-223. [PMID: 35491557 DOI: 10.1177/15500594221098286] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Objectives. Microstate studies of electroencephalograms (EEGs) on schizophrenia (SCZ) and bipolar disorder (BD) demonstrated categorical differences. The relationship between microstate indices and clinical symptoms in each group, however, remained unclear. Our objective was to examine associations between EEG microstates and the core features of SCZ and BD. Methods. This study examined the resting EEG data of 40 patients with SCZ, 19 patients with BD (12 BD type I and 7 BD type II), and 16 healthy controls. EEG topographic maps were divided into four canonical microstate classes: A, B, C, and D. The Positive and Negative Syndrome Scale (PANSS), Young Mania Rating Scale, Hamilton Depression Rating Scale (HAMD), and Global Assessment of Functioning (GAF) were used to measure clinical symptoms and global functioning. Results. There was a significant inverse correlation between the proportion of time spent in microstate class A and GAF in patients with SCZ but not BD. Furthermore, the occurrence of microstate class A was positively correlated with the Positive Scale scores of the PANSS. Nevertheless, there were no group differences between the microstate classes. Conclusions. The results of this study indicate a negative correlation between microstate class A and global functioning in SCZ but not in BD. The association may be mediated by positive symptoms of SZ. Neural mechanisms underlying this relationship require further investigation.
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Affiliation(s)
- Pao-Huan Chen
- Department of Psychiatry, 63474Taipei Medical University Hospital, Taipei.,Department of Psychiatry, School of Medicine, College of Medicine, 38032Taipei Medical University, Taipei
| | - Hsiao-Lun Ku
- Department of Psychiatry, School of Medicine, College of Medicine, 38032Taipei Medical University, Taipei.,Department of Psychiatry, 38032Taipei Medical University Shuang-Ho Hospital, New Taipei City.,Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City
| | - Jiunn-Kae Wang
- Department of Psychiatry, School of Medicine, College of Medicine, 38032Taipei Medical University, Taipei.,Department of Psychiatry, 38032Taipei Medical University Shuang-Ho Hospital, New Taipei City.,Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City
| | - Jiunn-Horng Kang
- Department of Physical Medicine and Rehabilitation, 63474Taipei Medical University Hospital, Taipei.,Graduate Institute of Nanomedicine and Medical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei.,Research Center of Artificial Intelligence in Medicine, 38032Taipei Medical University, Taipei
| | - Tzu-Yu Hsu
- Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City.,Graduate Institute of Mind, Brain and Consciousness, 38032Taipei Medical University, Taipei
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12
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Ke M, Li H, Liu G. The Local Topological Reconfiguration in the Brain Network After Targeted Hub Dysfunction Attacks in Patients With Juvenile Myoclonic Epilepsy. Front Neurosci 2022; 16:864040. [PMID: 35495041 PMCID: PMC9047017 DOI: 10.3389/fnins.2022.864040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 03/15/2022] [Indexed: 11/16/2022] Open
Abstract
The central brain regions of brain networks have been extensively studied in terms of their roles in various diseases. This study provides a direct measure of the brain's responses to targeted attacks on central regions, revealing the critical role these regions play in patients with juvenile myoclonic epilepsy (JME). The resting-state data of 37 patients with JME and 37 healthy subjects were collected, and brain functional networks were constructed for the two groups of data according to their Pearson correlation coefficients. The left middle cingulate gyrus was defined as the central brain region by the eigenvector centrality algorithm and was attacked by the CLM sequential failure model. The rich-club connection differences between the patients with JME and healthy controls before and after the attacks were compared according to graph theory indices and the number of rich-club connections. We found that the numbers of rich connections in the brain networks of the healthy control group and the group of patients with JME were significantly reduced [p < 0.05, false discovery rate (FDR) correction] before the CLM sequential failure attacks, and no significant differences were observed between the feeder connections and local connections. In the healthy control group, significant rich connection differences were obtained (p < 0.01, FDR correction), and no statistically significant differences were observed regarding the feeder connections and local connections in the brain network before and after CLM failure attacks on the central brain region. No significant differences were obtained between the rich connections, feeder connections, and local connections in patients with JME before and after CLM successive failure attacks on the central brain area. The rich connections, feeder connections, and local connections were not significantly different in the brain networks of the healthy control group and the group of patients with JME after CLM successive failure attacks on the central brain region. We concluded that the damage to the left middle cingulate gyrus is closely linked to various brain disorders, suggesting that this region is of great importance for understanding the pathophysiological basis of myoclonic seizures in patients with JME.
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Affiliation(s)
- Ming Ke
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Huimin Li
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
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13
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Yu K, Lin Q, Ge QM, Yu CY, Li QY, Pan YC, Shao Y. Measuring functional connectivity in patients with strabismus using stationary functional magnetic resonance imaging: a resting-state network study. Acta Radiol 2022; 63:110-121. [PMID: 33423531 DOI: 10.1177/0284185120983978] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND Strabismus (STR) is a common eye disease characterized by abnormal eye movements and stereo vision. Neuroimaging studies have revealed that STR patients have impaired functional connectivity (FC) in the visual cortex and sensorimotor cortex. PURPOSE To investigate alterations in FC and connections within and between subnetworks of the visual network (VN), sensorimotor network (SMN), and default mode network (DMN) in patients with STR. MATERIAL AND METHODS A total of 32 patients with STR (24 men, 8 women) and 32 age- and sex-matched healthy controls (HCs) (24 men, 8 women) were recruited. Participants underwent resting-state functional magnetic resonance imaging scans. The resting-state network (RSN) was examined by independent component analysis, and differences in RSN FC between STR and HC groups were evaluated with the t test. Functional network connectivity (FNC) analysis was performed for the three RSNs. RESULTS Compared to the HC group, the STR group showed increased FC in the VN and SMN (voxel-level P < 0.01; two-tailed Gaussian random field correction; cluster-level P < 0.05). There were no significant alterations in DMN FC between the two groups. FNC analysis of connections in the RSN revealed that one of the three connections in the VN was reduced, but no connectivity changes were observed in the SMN or DMN. FNC analysis of the connection between two RSNs showed that two had increased and one had a decreased connection value. CONCLUSION The VN, SMN, and DMN are reorganized in patients with STR compared to HCs, providing novel insight into the neural substrates of STR.
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Affiliation(s)
- Kang Yu
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang, Jiangxi, PR China
| | - Qi Lin
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang, Jiangxi, PR China
| | - Qian-Min Ge
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang, Jiangxi, PR China
| | - Chen-Yu Yu
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang, Jiangxi, PR China
| | - Qiu-Yu Li
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang, Jiangxi, PR China
| | - Yi-Cong Pan
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang, Jiangxi, PR China
| | - Yi Shao
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang, Jiangxi, PR China
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14
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Wang S, Chen B, Yu Y, Yang H, Cui W, Fan G, Li J. Altered resting-state functional network connectivity in profound sensorineural hearing loss infants within an early sensitive period: A group ICA study. Hum Brain Mapp 2021; 42:4314-4326. [PMID: 34060682 PMCID: PMC8356983 DOI: 10.1002/hbm.25548] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/29/2021] [Accepted: 05/20/2021] [Indexed: 12/21/2022] Open
Abstract
Data from both animal models and deaf children provide evidence for that the maturation of auditory cortex has a sensitive period during the first 2-4 years of life. During this period, the auditory stimulation can affect the development of cortical function to the greatest extent. Thus far, little is known about the brain development trajectory after early auditory deprivation within this period. In this study, independent component analysis (ICA) technique was used to detect the characteristics of brain network development in children with bilateral profound sensorineural hearing loss (SNHL) before 3 years old. Seven resting-state networks (RSN) were identified in 50 SNHL and 36 healthy controls using ICA method, and further their intra-and inter-network functional connectivity (FC) were compared between two groups. Compared with the control group, SNHL group showed decreased FC within default mode network, while enhanced FC within auditory network (AUN) and salience network. No significant changes in FC were found in the visual network (VN) and sensorimotor network (SMN). Furthermore, the inter-network FC between SMN and AUN, frontal network and AUN, SMN and VN, frontal network and VN were significantly increased in SNHL group. The results implicate that the loss and the compensatory reorganization of brain network FC coexist in SNHL infants. It provides a network basis for understanding the brain development trajectory after hearing loss within early sensitive period.
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Affiliation(s)
- Shanshan Wang
- Department of Radiology, The First Hospital, China Medical University, Shenyang, Liaoning, China
| | - Boyu Chen
- Department of Radiology, The First Hospital, China Medical University, Shenyang, Liaoning, China
| | - Yalian Yu
- Department of Otorhinolaryngology, The First Hospital, China Medical University, Shenyang, Liaoning, China
| | - Huaguang Yang
- Department of Radiology, Renmin Hospital, Wuhan University, Wuhan, China
| | - Wenzhuo Cui
- Department of Radiology, The First Hospital, China Medical University, Shenyang, Liaoning, China
| | - Guoguang Fan
- Department of Radiology, The First Hospital, China Medical University, Shenyang, Liaoning, China
| | - Jian Li
- Department of Radiology, The First Hospital, China Medical University, Shenyang, Liaoning, China
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15
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Ghasemi M, Foroutannia A, Babajani‐Feremi A. Characterizing resting-state networks in Parkinson's disease: A multi-aspect functional connectivity study. Brain Behav 2021; 11:e02101. [PMID: 33784022 PMCID: PMC8119826 DOI: 10.1002/brb3.2101] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 01/03/2021] [Accepted: 02/21/2021] [Indexed: 01/04/2023] Open
Abstract
PURPOSE Resting-state functional magnetic resonance imaging (Rs-fMRI) can be used to investigate the alteration of resting-state brain networks (RSNs) in patients with Parkinson's disease (PD) when compared with healthy controls (HCs). The aim of this study was to identify the differences between individual RSNs and reveal the most important discriminatory characteristic of RSNs between the HCs and PDs. METHODS This study used Rs-fMRI data of 23 patients with PD and 18 HCs. Group independent component analysis (ICA) was performed, and 23 components were extracted by spatially overlapping the components with a template RSN. The extracted components were used in the following three methods to compare RSNs of PD patients and HCs: (1) a subject-specific score based on group RSNs and a dual-regression approach (namely RSN scores); (2) voxel-wise comparison of the RSNs in the PD patient and HC groups using a nonparametric permutation test; and (3) a hierarchical clustering analysis of RSNs in the PD patient and HC groups. RESULTS The results of RSN scores showed a significant decrease in connectivity in seven ICs in patients with PD compared with HCs, and this decrease was particularly striking on the lateral and medial posterior occipital cortices. The results of hierarchical clustering of the RSNs revealed that the cluster of the default mode network breaks down into the three other clusters in PD patients. CONCLUSION We found various characteristics of the alteration of the RSNs in PD patients compared with HCs. Our results suggest that different characteristics of RSNs provide insights into the biological mechanism of PD.
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Affiliation(s)
- Mahdieh Ghasemi
- Neural Engineering LaboratoryDepartment of Biomedical EngineeringUniversity of NeyshaburNeyshaburIran
| | - Ali Foroutannia
- Neural Engineering LaboratoryDepartment of Biomedical EngineeringUniversity of NeyshaburNeyshaburIran
| | - Abbas Babajani‐Feremi
- Department of NeurologyDell Medical SchoolThe University of Texas at AustinAustinTXUSA
- Magnetoencephalography LabDell Children's Medical CenterAustinTXUSA
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16
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Abstract
Introduction: With the recent technical advances in brain imaging modalities such as magnetic resonance imaging, positron emission tomography, and functional magnetic resonance imaging (fMRI), researchers' interests have inclined over the years to study brain functions through the analysis of the variations in the statistical dependence among various brain regions. Through its wide use in studying brain connectivity, the low temporal resolution of the fMRI represented by the limited number of samples per second, in addition to its dependence on brain slow hemodynamic changes, makes it of limited capability in studying the fast underlying neural processes during information exchange between brain regions. Materials and Methods: In this article, the high temporal resolution of the electroencephalography (EEG) is utilized to estimate the effective connectivity within the default mode network (DMN). The EEG data are collected from 20 subjects with alcoholism and 25 healthy subjects (controls), and used to obtain the effective connectivity diagram of the DMN using the Partial Directed Coherence algorithm. Results: The resulting effective connectivity diagram within the DMN shows the unidirectional causal effect of each region on the other. The variations in the causal effects within the DMN between controls and alcoholics show clear correlation with the symptoms that are usually associated with alcoholism, such as cognitive and memory impairments, executive control, and attention deficiency. The correlation between the exchanged causal effects within the DMN and symptoms related to alcoholism is discussed and properly analyzed. Conclusion: The establishment of the causal differences between control and alcoholic subjects within the DMN regions provides valuable insight into the mechanism by which alcohol modulates our cognitive and executive functions and creates better possibility for effective treatment of alcohol use disorder.
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Affiliation(s)
- Danish M Khan
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical & Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Malaysia.,Department of Electronic and Telecommunications Engineering, NED University of Engineering & Technology, University Road, Karachi, Pakistan
| | - Nidal Kamel
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical & Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Malaysia
| | - Mustapha Muzaimi
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian Malaysia
| | - Timothy Hill
- Neurotherapy & Psychology, Brain Therapy Centre, Kent Town, Australia
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17
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Xing XX, Hua XY, Zheng MX, Ma ZZ, Huo BB, Wu JJ, Ma SJ, Ma J, Xu JG. Intra and inter: Alterations in functional brain resting-state networks after peripheral nerve injury. Brain Behav 2020; 10:e01747. [PMID: 32657022 PMCID: PMC7507705 DOI: 10.1002/brb3.1747] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Revised: 05/18/2020] [Accepted: 06/04/2020] [Indexed: 12/16/2022] Open
Abstract
INTRODUCTION Numerous treatments suggest that brain plasticity changes after peripheral nerve injury (PNI), and most studies examining functional magnetic resonance imaging focused on abnormal changes in specific brain regions. However, it is the large-scale interaction of neuronal networks instead of isolated brain regions contributed to the functional recovery after PNI. In the present study, we examined the intra- and internetworks alterations between the related functional resting-state networks (RSNs) in a sciatic nerve injury rat model. METHODS Ninety-six female rats were divided into a control and model group. Unilateral sciatic nerve transection and direct anastomosis were performed in the latter group. We used an independent component analysis (ICA) algorithm to observe the changes in RSNs and assessed functional connectivity between different networks using the functional networks connectivity (FNC) toolbox. RESULTS Six RSNs related to PNI were identified, including the basal ganglia network (BGN), sensorimotor network (SMN), salience network (SN), interoceptive network (IN), cerebellar network (CN), and default mode network (DMN). The model group showed significant changes in whole-brain FC changes within these resting-state networks (RSNs), but four of these RSNs exhibited a conspicuous decrease. The interalterations performed that significantly decreased FNC existed between the BGN and SMN, BGN and IN, and BGN and DMN (p < .05, corrected). A significant increase in FNC existed between DMN and CN and between CN and SN (p < .05, corrected). CONCLUSION The results showed the large-scale functional reorganization at the network level after PNI. This evidence reveals new implications to the pathophysiological mechanisms in brain plasticity of PNI.
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Affiliation(s)
- Xiang-Xin Xing
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xu-Yun Hua
- Department of Traumatology and Orthopedics, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Yangzhi Rehabilitation Hospital, Tongji University, Shanghai, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhen-Zhen Ma
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Bei-Bei Huo
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jia-Jia Wu
- Center of Rehabilitation Medicine, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Shu-Jie Ma
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jie Ma
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Center of Rehabilitation Medicine, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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18
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Ding Y, Ji G, Li G, Zhang W, Hu Y, Liu L, Wang Y, Hu C, von Deneen KM, Han Y, Cui G, Wang H, Wiers CE, Manza P, Tomasi D, Volkow ND, Nie Y, Wang GJ, Zhang Y. Altered Interactions Among Resting-State Networks in Individuals with Obesity. Obesity (Silver Spring) 2020; 28:601-608. [PMID: 32090510 PMCID: PMC7098432 DOI: 10.1002/oby.22731] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 12/03/2019] [Indexed: 12/13/2022]
Abstract
OBJECTIVE The aim of this study was to investigate alterations in functional connectivity (FC) within and interactions between resting-state networks involved in salience, executive control, and interoception in participants with obesity (OB). METHODS Using resting-state functional magnetic resonance imaging with independent component analysis and FC, alterations within and interactions between resting-state networks in 35 OB and 35 normal-weight controls (NW) were investigated. RESULTS Compared with NW, OB showed reduced FC strength in the ventromedial prefrontal cortex and posterior cingulate cortex/precuneus within the default-mode network, dorsal anterior cingulate cortex within the salience network (SN), bilateral dorsolateral prefrontal cortex-angular gyrus within the frontoparietal network (FPN), and increased FC strength in the insula (INS) (Pfamilywise error < 0.0125). The dorsal anterior cingulate cortex FC strength was negatively correlated with craving for food cues, left dorsolateral prefrontal cortex FC strength was negatively correlated with Yale Food Addiction Scale scores, and right INS FC strength was positively correlated with craving for high-calorie food cues. Compared with NW, OB also showed increased FC between the SN and FPN driven by altered FC of bilateral INS and anterior cingulate cortex-angular gyrus. CONCLUSIONS Alterations in FC within and interactions between the SN, default-mode network, and FPN might contribute to the high incentive value of food (craving), lack of control of overeating (compulsive overeating), and increased awareness of hunger (impaired interoception) in OB.
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Affiliation(s)
- Yueyan Ding
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Gang Ji
- State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, Shaanxi, 710032, China
- Corresponding author at: Dr. Yi Zhang, Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China. Tel: +86 29 81891070, Fax: +86 29 81891070, , Dr. Gang Ji, State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, The Fourth Military Medical University, No. 127 Changle West Road, Xi’an, Shaanxi 710032, China. Tel: +86 29 84771620, Fax: +86 29 84771620, , Dr. Gene-Jack Wang, Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, 10 Center Drive, MSC1013, Building 10, Room B2L304, Bethesda, MD, 20892-1013, USA, Tel: +1 301 496 5012, Fax: +1 301 496 5012,
| | - Guanya Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Wenchao Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Yang Hu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Lei Liu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Yuanyuan Wang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Chunxin Hu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Karen M. von Deneen
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
| | - Yu Han
- Department of Radiology, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi 710038, China
| | - Guangbin Cui
- Department of Radiology, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi 710038, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical Univerisity, Xi’an, Shaanxi 710032, China
| | - Corinde E. Wiers
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Peter Manza
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Dardo Tomasi
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Nora D. Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Yongzhan Nie
- State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, Shaanxi, 710032, China
| | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
- Corresponding author at: Dr. Yi Zhang, Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China. Tel: +86 29 81891070, Fax: +86 29 81891070, , Dr. Gang Ji, State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, The Fourth Military Medical University, No. 127 Changle West Road, Xi’an, Shaanxi 710032, China. Tel: +86 29 84771620, Fax: +86 29 84771620, , Dr. Gene-Jack Wang, Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, 10 Center Drive, MSC1013, Building 10, Room B2L304, Bethesda, MD, 20892-1013, USA, Tel: +1 301 496 5012, Fax: +1 301 496 5012,
| | - Yi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
- Corresponding author at: Dr. Yi Zhang, Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China. Tel: +86 29 81891070, Fax: +86 29 81891070, , Dr. Gang Ji, State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, The Fourth Military Medical University, No. 127 Changle West Road, Xi’an, Shaanxi 710032, China. Tel: +86 29 84771620, Fax: +86 29 84771620, , Dr. Gene-Jack Wang, Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, 10 Center Drive, MSC1013, Building 10, Room B2L304, Bethesda, MD, 20892-1013, USA, Tel: +1 301 496 5012, Fax: +1 301 496 5012,
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19
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Sunaga M, Takei Y, Kato Y, Tagawa M, Suto T, Hironaga N, Ohki T, Takahashi Y, Fujihara K, Sakurai N, Ujita K, Tsushima Y, Fukuda M. Frequency-Specific Resting Connectome in Bipolar Disorder: An MEG Study. Front Psychiatry 2020; 11:597. [PMID: 32670117 PMCID: PMC7330711 DOI: 10.3389/fpsyt.2020.00597] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 06/09/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Bipolar disorder (BD) is a serious psychiatric disorder that is associated with a high suicide rate, and for which no clinical biomarker has yet been identified. To address this issue, we investigated the use of magnetoencephalography (MEG) as a new prospective tool. MEG has been used to evaluate frequency-specific connectivity between brain regions; however, no previous study has investigated the frequency-specific resting-state connectome in patients with BD. This resting-state MEG study explored the oscillatory representations of clinical symptoms of BD via graph analysis. METHODS In this prospective case-control study, 17 patients with BD and 22 healthy controls (HCs) underwent resting-state MEG and evaluations for depressive and manic symptoms. After estimating the source current distribution, orthogonalized envelope correlations between multiple brain regions were evaluated for each frequency band. We separated regions-of-interest into seven left and right network modules, including the frontoparietal network (FPN), limbic network (LM), salience network (SAL), and default mode network (DMN), to compare the intra- and inter-community edges between the two groups. RESULTS In the BD group, we found significantly increased inter-community edges of the right LM-right DMN at the gamma band, and decreased inter-community edges of the right SAL-right FPN at the delta band and the left SAL-right SAL at the theta band. Intra-community edges in the left LM at the high beta band were significantly higher in the BD group than in the HC group. The number of connections in the left LM at the high beta band showed positive correlations with the subjective and objective depressive symptoms in the BD group. CONCLUSION We introduced graph theory into resting-state MEG studies to investigate the functional connectivity in patients with BD. To the best of our knowledge, this is a novel approach that may be beneficial in the diagnosis of BD. This study describes the spontaneous oscillatory brain networks that compensate for the time-domain issues associated with functional magnetic resonance imaging. These findings suggest that the connectivity of the LM at the beta band may be a good objective biological biomarker of the depressive symptoms associated with BD.
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Affiliation(s)
- Masakazu Sunaga
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yuichi Takei
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yutaka Kato
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan.,Tsutsuji Mental Hospital, Tatebayashi, Japan
| | - Minami Tagawa
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan.,Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | - Tomohiro Suto
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | - Naruhito Hironaga
- Brain Center, Faculty of Medicine, Kyushu University, Fukuoka, Japan
| | - Takefumi Ohki
- Department of Neurosurgery, Osaka University Medical School, Suita, Japan
| | - Yumiko Takahashi
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kazuyuki Fujihara
- Department of Genetic and Behavioral Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Noriko Sakurai
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Koichi Ujita
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yoshito Tsushima
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Masato Fukuda
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
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20
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Amemiya S, Takao H, Abe O. Global vs. Network-Specific Regulations as the Source of Intrinsic Coactivations in Resting-State Networks. Front Syst Neurosci 2019; 13:65. [PMID: 31736721 PMCID: PMC6829116 DOI: 10.3389/fnsys.2019.00065] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 10/14/2019] [Indexed: 12/02/2022] Open
Abstract
Spontaneous neural activities are endowed with specific patterning characterized by synchronizations within functionally relevant distant regions that are termed as resting-state networks (RSNs). Although the mechanisms that organize the large-scale neural systems are still largely unknown, recent studies have proposed a hypothesis that network-specific coactivations indeed emerge as the result of globally propagating neural activities with specific paths of transmission. However, the extent to which such a centralized global regulation, rather than network-specific control, contributes to the RSN synchronization remains unknown. In the present study, we investigated the contribution from each mechanism by directly identifying the global as well as local component of resting-state functional MRI (fMRI) data provided by human connectome project, using temporal independent component analysis (ICA). Based on the spatial distribution pattern, each ICA component was classified as global or local. Time lag mapping of each IC revealed several paths of global or semi-global propagations that are partially overlapping yet spatially distinct to each other. Consistent with previous studies, the time lag of global oscillation, although being less spatially homogenous than what was assumed to be, contributed to the RSN synchronization. However, an equivalent contribution was also shown on the part of the more locally confined activities that are independent to each other. While allowing the view that network-specific coactivation occurs as part of the sequences of global neural activities, these results further confirm an equally important role of the network-specific regulation for its coactivation, regardless of whether vascular artifacts contaminate the global component in fMRI measures.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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21
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Sala A, Caminiti SP, Iaccarino L, Beretta L, Iannaccone S, Magnani G, Padovani A, Ferini-Strambi L, Perani D. Vulnerability of multiple large-scale brain networks in dementia with Lewy bodies. Hum Brain Mapp 2019; 40:4537-4550. [PMID: 31322307 DOI: 10.1002/hbm.24719] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 06/01/2019] [Accepted: 06/19/2019] [Indexed: 01/08/2023] Open
Abstract
Aberrations of large-scale brain networks are found in the majority of neurodegenerative disorders. The brain connectivity alterations underlying dementia with Lewy bodies (DLB) remain, however, still elusive, with contrasting results possibly due to the pathological and clinical heterogeneity characterizing this disorder. Here, we provide a molecular assessment of brain network alterations, based on cerebral metabolic measurements as proxies of synaptic activity and density, in a large cohort of DLB patients (N = 72). We applied a seed-based interregional correlation analysis approach (p < .01, false discovery rate corrected) to evaluate large-scale resting-state networks' integrity and their interactions. We found both local and long-distance metabolic connectivity alterations, affecting the posterior cortical networks, that is, primary visual and the posterior default mode network, as well as the limbic and attention networks, suggesting a widespread derangement of the brain connectome. Notably, patients with the lowest visual and attention cognitive scores showed the most severe connectivity derangement in regions of the primary visual network. In addition, network-level alterations were differentially associated with the core clinical manifestations, namely, hallucinations with more severe metabolic dysfunction of the attention and visual networks, and rapid eye movement sleep behavior disorder with alterations of connectivity of attention and subcortical networks. These multiple network-level vulnerabilities may modulate the core clinical and cognitive features of DLB and suggest that DLB should be considered as a complex multinetwork disorder.
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Affiliation(s)
- Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Leonardo Iaccarino
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Luca Beretta
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Giuseppe Magnani
- Department of Neurology, IRCCS San Raffaele Hospital, Milan, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Luigi Ferini-Strambi
- Vita-Salute San Raffaele University, Milan, Italy.,Department of Clinical Neurosciences, San Raffaele Scientific Institute, Neurology, Sleep Disorders Center, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
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22
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Aoki Y, Kazui H, Pascual-Marqui RD, Ishii R, Yoshiyama K, Kanemoto H, Suzuki Y, Sato S, Azuma S, Suehiro T, Matsumoto T, Hata M, Canuet L, Iwase M, Ikeda M. EEG Resting-State Networks Responsible for Gait Disturbance Features in Idiopathic Normal Pressure Hydrocephalus. Clin EEG Neurosci 2019; 50:210-218. [PMID: 30417664 DOI: 10.1177/1550059418812156] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric disease characterized by gait disturbance, cognitive dysfunction, and urinary incontinence that affects a large population of elderly people. These symptoms, especially gait disturbance, can potentially be improved by cerebrospinal fluid (CSF) drainage, which is more effective if performed at an early stage of the disease. However, the neurophysiological mechanisms of these symptoms and their recovery by CSF drainage are poorly understood. In this study, using exact low-resolution brain electromagnetic tomography-independent component analysis (eLORETA-ICA) with electroencephalography (EEG) data, we assessed activities of five EEG resting-state networks (EEG-RSNs) in 58 iNPH patients before and after drainage of CSF by lumbar puncture (CSF tapping). In addition, we assessed correlations of changes in these five EEG-RSNs activities with CSF tapping-induced changes in iNPH symptoms. The results reveal that compared with 80 healthy controls, iNPH patients had significantly decreased activities in the occipital alpha rhythm, visual perception network, and self-referential network before CSF tapping. Furthermore, CSF tapping-induced changes in occipital alpha activity correlated with changes in postural sway and frontal lobe function. Changes in visual perception network activity correlated with changes in gait speed. In addition, changes in memory perception network activity correlated with changes in Parkinsonian gait features. These results indicate a recruitment of cognitive networks in gait control, and involvement of the occipital alpha activity in cognitive dysfunction in iNPH patients. Based on these findings, eLORETA-ICA with EEG data can be considered a noninvasive, useful tool for detection of EEG-RSN activities and for understanding the neurophysiological mechanisms underlying this disease.
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Affiliation(s)
- Yasunori Aoki
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.,2 Department of Psychiatry, Nippon Life Hospital, Osaka, Japan
| | - Hiroaki Kazui
- 3 Department of Neuropsychiatry, Kochi University, Kochi, Japan
| | - Roberto D Pascual-Marqui
- 4 The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland.,5 Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
| | - Ryouhei Ishii
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Kenji Yoshiyama
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Hideki Kanemoto
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.,6 Department of Psychiatry, Mizuma Hospital, Osaka, Japan.,7 Cognitive Reserve Research Center, Osaka Kawasaki Rehabilitation University, Osaka, Japan
| | - Yukiko Suzuki
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Shunsuke Sato
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Shingo Azuma
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Takashi Suehiro
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Takuya Matsumoto
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Masahiro Hata
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Leonides Canuet
- 8 Department of Clinical Psychology and Psychobiology, La Laguna University, Tenerife, Spain
| | - Masao Iwase
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Manabu Ikeda
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
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23
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Luan Y, Wang C, Jiao Y, Tang T, Zhang J, Teng GJ. Dysconnectivity of Multiple Resting-State Networks Associated With Higher-Order Functions in Sensorineural Hearing Loss. Front Neurosci 2019; 13:55. [PMID: 30804740 PMCID: PMC6370743 DOI: 10.3389/fnins.2019.00055] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 01/21/2019] [Indexed: 01/12/2023] Open
Abstract
Objects: Sensorineural hearing loss (SNHL) involves wide-ranging functional reorganization, and is associated with accumulating risk of cognitive and emotional dysfunction. The coordination of multiple functional networks supports normal brain functions. Here, we aimed to evaluate the functional connectivity (FC) patterns involving multiple resting-state networks (RSNs), and the correlations between the functional remodeling of RSNs and the potential cognitive or emotional impairments in SNHL. Methods: Thirty long-term bilateral SNHL patients and 39 well-matched healthy controls were recruited for assessment of resting-state functional magnetic resonance imaging and neuropsychological tests. Results: Using independent component analysis, 11 RSNs were identified. Relative to the healthy controls, patients with SNHL presented apparent abnormalities of intra-network FC involving right frontoparietal network, posterior temporal network, and sensory motor network. Disrupted between-network FC was also revealed in the SNHL patients across both higher-order cognitive control networks and multiple sensory networks. Eight of the eleven RSNs showed altered functional synchronization using a seed network to whole brain FC method, particularly in the ventromedial prefrontal cortex. In addition, these functional abnormalities were correlated with cognition- and emotion-related performances. Interpretations: These findings supported our hypotheses that long-term SNHL involves notable dysconnectivity of multiple RSNs. Our study provides important insights into the pathophysiological mechanisms of SNHL, and sheds lights on the neural substrates underlying the possible cognitive and emotional dysfunctions following SNHL.
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Affiliation(s)
- Ying Luan
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Congxiao Wang
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Yun Jiao
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Tianyu Tang
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Jian Zhang
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Gao-Jun Teng
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
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24
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Ezaki T, Sakaki M, Watanabe T, Masuda N. Age-related changes in the ease of dynamical transitions in human brain activity. Hum Brain Mapp 2018; 39:2673-2688. [PMID: 29524289 PMCID: PMC6619404 DOI: 10.1002/hbm.24033] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2017] [Revised: 02/27/2018] [Accepted: 02/27/2018] [Indexed: 01/07/2023] Open
Abstract
Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural systems, the age-related decline in executive functions should be underpinned by alteration of large-scale neural dynamics. However, the effects of age on brain dynamics have not been firmly formulated. Here, we investigate such age-related changes in brain dynamics by applying "energy landscape analysis" to publicly available functional magnetic resonance imaging data from healthy younger and older human adults. We quantified the ease of dynamical transitions between different major patterns of brain activity, and estimated it for the default mode network (DMN) and the cingulo-opercular network (CON) separately. We found that the two age groups shared qualitatively the same trajectories of brain dynamics in both the DMN and CON. However, in both of networks, the ease of transitions was significantly smaller in the older than the younger group. Moreover, the ease of transitions was associated with the performance in executive function tasks in a doubly dissociated manner: for the younger adults, the ability of executive functions was mainly correlated with the ease of transitions in the CON, whereas that for the older adults was specifically associated with the ease of transitions in the DMN. These results provide direct biological evidence for age-related changes in macroscopic brain dynamics and suggest that such neural dynamics play key roles when individuals carry out cognitively demanding tasks.
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Affiliation(s)
- Takahiro Ezaki
- PRESTO, JST, 4‐1‐8 HonchoKawaguchiSaitamaJapan
- National Institute of Informatics, HitotsubashiChiyoda‐kuTokyoJapan
- Kawarabayashi Large Graph Project, ERARO, JST, c/o Global Research Center for Big Data Mathematics, NIIChiyoda‐kuTokyoJapan
| | - Michiko Sakaki
- School of Psychology and Clinical Language SciencesUniversity of Reading, Earley Gate, Whiteknights RoadReadingUnited Kingdom
- Research Institute, Kochi University of TechnologyKamiKochiJapan
| | - Takamitsu Watanabe
- Institute of Cognitive Neuroscience, University College London, 17 Queen SquareLondonWC1N 3AZUnited Kingdom
| | - Naoki Masuda
- Department of Engineering MathematicsUniversity of BristolCliftonBristolUnited Kingdom
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25
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Long H, Liu B, Wang C, Zhang X, Li J, Yu C, Jiang T. Interaction effect between 5-HTTLPR and HTR1A rs6295 polymorphisms on the frontoparietal network. Neuroscience 2017; 362:239-247. [PMID: 28793232 DOI: 10.1016/j.neuroscience.2017.08.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 07/31/2017] [Accepted: 08/01/2017] [Indexed: 10/19/2022]
Abstract
Previous studies have shown a close relationship between the serotonin system and working memory (WM), but the neural mechanism for the role of the serotonin system on the WM is unclear. The frontoparietal network is involved in WM and is associated with the serotonin system. Therefore, this study investigated the interaction effect of the serotonin transporter-linked polymorphic region (5-HTTLPR) and the polymorphism in the serotonin 1A receptor gene (rs6295) on the frontoparietal network obtained from the independent component analysis in a large, young Chinese sample population. The current study found a significant interaction effect of 5-HTTLPR and rs6295 on the connectivity within the right frontoparietal network, specifically in the middle frontal gyrus and inferior parietal lobule. Moreover, the mean connectivity in the right inferior parietal lobule was positively correlated with WM performance. These brain network analysis findings could provide a new perspective on the neural mechanisms of gene-gene interactions and on individual differences in cognitive functions.
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Affiliation(s)
- Haixia Long
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Bing Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Chao Wang
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xiaolong Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia.
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26
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Kim SG, Knösche TR. Resting state functional connectivity of the ventral auditory pathway in musicians with absolute pitch. Hum Brain Mapp 2017; 38:3899-3916. [PMID: 28481006 DOI: 10.1002/hbm.23637] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Revised: 04/06/2017] [Accepted: 04/23/2017] [Indexed: 11/09/2022] Open
Abstract
Absolute pitch (AP) is the ability to recognize pitch chroma of tonal sound without external references, providing a unique model of the human auditory system (Zatorre: Nat Neurosci 6 () 692-695). In a previous study (Kim and Knösche: Hum Brain Mapp () 3486-3501), we identified enhanced intracortical myelination in the right planum polare (PP) in musicians with AP, which could be a potential site for perceptional processing of pitch chroma information. We speculated that this area, which initiates the ventral auditory pathway, might be crucially involved in the perceptual stage of the AP process in the context of the "dual pathway hypothesis" that suggests the role of the ventral pathway in processing nonspatial information related to the identity of an auditory object (Rauschecker: Eur J Neurosci 41 () 579-585). To test our conjecture on the ventral pathway, we investigated resting state functional connectivity (RSFC) using functional magnetic resonance imaging (fMRI) from musicians with varying degrees of AP. Should our hypothesis be correct, RSFC via the ventral pathway is expected to be stronger in musicians with AP, whereas such group effect is not predicted in the RSFC via the dorsal pathway. In the current data, we found greater RSFC between the right PP and bilateral anteroventral auditory cortices in musicians with AP. In contrast, we did not find any group difference in the RSFC of the planum temporale (PT) between musicians with and without AP. We believe that these findings support our conjecture on the critical role of the ventral pathway in AP recognition. Hum Brain Mapp 38:3899-3916, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Seung-Goo Kim
- Research Group for MEG and EEG - Cortical Networks and Cognitive Functions, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Thomas R Knösche
- Research Group for MEG and EEG - Cortical Networks and Cognitive Functions, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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27
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Doucet GE, He X, Sperling MR, Sharan A, Tracy JI. From "rest" to language task: Task activation selects and prunes from broader resting-state network. Hum Brain Mapp 2017; 38:2540-2552. [PMID: 28195438 DOI: 10.1002/hbm.23539] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 01/31/2017] [Accepted: 02/03/2017] [Indexed: 11/09/2022] Open
Abstract
Resting-state networks (RSNs) show spatial patterns generally consistent with networks revealed during cognitive tasks. However, the exact degree of overlap between these networks has not been clearly quantified. Such an investigation shows promise for decoding altered functional connectivity (FC) related to abnormal language functioning in clinical populations such as temporal lobe epilepsy (TLE). In this context, we investigated the network configurations during a language task and during resting state using FC. Twenty-four healthy controls, 24 right and 24 left TLE patients completed a verb generation (VG) task and a resting-state fMRI scan. We compared the language network revealed by the VG task with three FC-based networks (seeding the left inferior frontal cortex (IFC)/Broca): two from the task (ON, OFF blocks) and one from the resting state. We found that, for both left TLE patients and controls, the RSN recruited regions bilaterally, whereas both VG-on and VG-off conditions produced more left-lateralized FC networks, matching more closely with the activated language network. TLE brings with it variability in both task-dependent and task-independent networks, reflective of atypical language organization. Overall, our findings suggest that our RSN captured bilateral activity, reflecting a set of prepotent language regions. We propose that this relationship can be best understood by the notion of pruning or winnowing down of the larger language-ready RSN to carry out specific task demands. Our data suggest that multiple types of network analyses may be needed to decode the association between language deficits and the underlying functional mechanisms altered by disease. Hum Brain Mapp 38:2540-2552, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Gaelle E Doucet
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Xiaosong He
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Michael R Sperling
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Ashwini Sharan
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Joseph I Tracy
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
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28
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Wang Z, Zhang D, Liang B, Chang S, Pan J, Huang R, Liu M. Prediction of Biological Motion Perception Performance from Intrinsic Brain Network Regional Efficiency. Front Hum Neurosci 2016; 10:552. [PMID: 27853427 PMCID: PMC5090005 DOI: 10.3389/fnhum.2016.00552] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2015] [Accepted: 10/17/2016] [Indexed: 01/06/2023] Open
Abstract
Biological motion perception (BMP) refers to the ability to perceive the moving form of a human figure from a limited amount of stimuli, such as from a few point lights located on the joints of a moving body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants, for whom intrinsic brain networks were constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located in the Default Mode Network (DMN). Additionally, discrimination analysis showed that the local efficiency of certain regions such as the thalamus could be used to classify BMP performance across participants. Notably, the association pattern between network nodal efficiency and BMP was different from the association pattern of static directional/gender information perception. Overall, these findings show that intrinsic brain network efficiency may be considered a neural factor that explains BMP inter-individual variability.
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Affiliation(s)
- Zengjian Wang
- Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Center for the Study of Applied Psychology, School of Psychology, South China Normal University Guangzhou, China
| | - Delong Zhang
- Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Center for the Study of Applied Psychology, School of Psychology, South China Normal University Guangzhou, China
| | - Bishan Liang
- Guangdong Polytechnic Normal University Guangzhou, China
| | - Song Chang
- Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Center for the Study of Applied Psychology, School of Psychology, South China Normal University Guangzhou, China
| | | | - Ruiwang Huang
- Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Center for the Study of Applied Psychology, School of Psychology, South China Normal University Guangzhou, China
| | - Ming Liu
- Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Center for the Study of Applied Psychology, School of Psychology, South China Normal University Guangzhou, China
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29
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Abstract
In this work, abundant anticorrelated networks were successfully detected in rest-stating fMRI-BOLD data from 20 subjects. Spatial independent component analysis (sICA) method was applied at both individual and group levels. At the individual level, for each subject, 30 independent components (IC) were estimated, and each IC was transformed using Z-score mapping. The voxels with >5 and < -5 Z-score were denoted as positive signals (PS) and negative signals (NS) respectively. The correlation coefficients between the mean time series of the PS and NS voxels were computed; if the calculated coefficients were <-0.3, the PS and NS voxels were considered to form an anticorrelated PS-NS network. It was found that 36.5% of the ICs contained an anticorrelated PS-NS network. The spatiotemporal patterns of most PS-NS networks varied from subject to subject, but three networks displaying spatial patterns were comparably consistent among different subjects. For group-level analysis, no anticorrelated PS-NS networks were detected. Our results suggest that future investigations adopt a broader approach for negative BOLD signal characterization. Combined consideration of PS and NS systems help to better elucidate hemodynamic and neuronal brain behavior and further develop understanding of neural mechanisms of brain information processing.
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Affiliation(s)
- Yadong Liu
- College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, P.R. China.,State key laboratory of high performance computing, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - Liangming Huang
- College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - Ming Li
- College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - Zongtan Zhou
- College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - Dewen Hu
- College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
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30
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Zimmermann J, Ritter P, Shen K, Rothmeier S, Schirner M, McIntosh AR. Structural architecture supports functional organization in the human aging brain at a regionwise and network level. Hum Brain Mapp 2016; 37:2645-61. [PMID: 27041212 PMCID: PMC6867479 DOI: 10.1002/hbm.23200] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Revised: 03/18/2016] [Accepted: 03/20/2016] [Indexed: 12/13/2022] Open
Abstract
Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age-related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC-FC coupling in human aging as inferred from resting-state blood oxygen-level dependent functional magnetic resonance imaging and diffusion-weighted imaging in a sample of 47 adults with an age range of 18-82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age-dependency of regionwise SC-FC coupling and network-level SC-FC relations. A specific pattern of SC-FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC-FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645-2661, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Joelle Zimmermann
- Baycrest Health SciencesRotman Research Institute3560 Bathurst StTorontoOntarioM6A 2E1Canada
| | - Petra Ritter
- Department of NeurologyCharité ‐ University MedicineCharitéplatz 1Berlin13353Germany
- BrainModes Minerva Research Group Max‐Planck Institute for Cognitive and Brain Science LeipzigCharitéplatz 1Berlin13353Germany
- Bernstein Focus State Dependencies of Learning & Bernstein Center for Computational NeuroscienceCharitéplatz 1Berlin10117Germany
- Berlin School of Mind and Brain & Mind and Brain Institute, Humboldt UniversityLuisenstraße 56, Haus 110117BerlinGermany
| | - Kelly Shen
- Baycrest Health SciencesRotman Research Institute3560 Bathurst StTorontoOntarioM6A 2E1Canada
| | - Simon Rothmeier
- Department of NeurologyCharité ‐ University MedicineCharitéplatz 1Berlin13353Germany
- BrainModes Minerva Research Group Max‐Planck Institute for Cognitive and Brain Science LeipzigCharitéplatz 1Berlin13353Germany
| | - Michael Schirner
- Department of NeurologyCharité ‐ University MedicineCharitéplatz 1Berlin13353Germany
| | - Anthony R. McIntosh
- Baycrest Health SciencesRotman Research Institute3560 Bathurst StTorontoOntarioM6A 2E1Canada
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31
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Choi H, Choi Y, Kim KW, Kang H, Hwang DW, Kim EE, Chung JK, Lee DS. Maturation of metabolic connectivity of the adolescent rat brain. eLife 2015; 4. [PMID: 26613413 PMCID: PMC4718811 DOI: 10.7554/elife.11571] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2015] [Accepted: 11/27/2015] [Indexed: 11/30/2022] Open
Abstract
Neuroimaging has been used to examine developmental changes of the brain. While PET studies revealed maturation-related changes, maturation of metabolic connectivity of the brain is not yet understood. Here, we show that rat brain metabolism is reconfigured to achieve long-distance connections with higher energy efficiency during maturation. Metabolism increased in anterior cerebrum and decreased in thalamus and cerebellum during maturation. When functional covariance patterns of PET images were examined, metabolic networks including default mode network (DMN) were extracted. Connectivity increased between the anterior and posterior parts of DMN and sensory-motor cortices during maturation. Energy efficiency, a ratio of connectivity strength to metabolism of a region, increased in medial prefrontal and retrosplenial cortices. Our data revealed that metabolic networks mature to increase metabolic connections and establish its efficiency between large-scale spatial components from childhood to early adulthood. Neurodevelopmental diseases might be understood by abnormal reconfiguration of metabolic connectivity and efficiency. DOI:http://dx.doi.org/10.7554/eLife.11571.001 The brain consumes a great deal of a sugar called glucose, which is delivered to the brain through blood vessels. Active regions of the brain need more glucose, and so the brain has a metabolic network that controls when and where glucose is metabolized. Yet precisely how this metabolic network changes during brain development is not yet understood. Choi et al. have now monitored the patterns of glucose metabolism in the brains of awake rats as they matured from 'childhood' to early adulthood. The experiments involved injecting the rats with radioactive glucose, and then using a technique called positron emission tomography (commonly known as 'PET scan') to monitor the metabolism of these radioactive sugar molecules in the animals’ brains. Choi et al. showed that the patterns of glucose consumption in the brain shift drastically as the rats mature. Importantly, the findings showed that these shifts in glucose metabolism seem to support the activity of long distance connections that develop as the brain matures. The findings also showed that the increased long distance connections were energy efficient. The results suggest that these metabolic changes are likely a way of maintaining high-energy efficiency that is crucial for the brain to perform normally. Finally, in addition to revealing the changes involved in normal brain development, these findings may have implications in neurological and psychiatric disorders in which the brain fails to achieve efficient metabolic networks as it matures. DOI:http://dx.doi.org/10.7554/eLife.11571.002
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Affiliation(s)
- Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
| | - Yoori Choi
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyu Wan Kim
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hyejin Kang
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Do Won Hwang
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
| | - E Edmund Kim
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
| | - June-Key Chung
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dong Soo Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
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32
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Choi US, Sung YW, Hong S, Chung JY, Ogawa S. Structural and functional plasticity specific to musical training with wind instruments. Front Hum Neurosci 2015; 9:597. [PMID: 26578939 PMCID: PMC4624850 DOI: 10.3389/fnhum.2015.00597] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Accepted: 10/14/2015] [Indexed: 01/19/2023] Open
Abstract
Numerous neuroimaging studies have shown structural and functional changes resulting from musical training. Among these studies, changes in primary sensory areas are mostly related to motor functions. In this study, we looked for some similar functional and structural changes in other functional modalities, such as somatosensory function, by examining the effects of musical training with wind instruments. We found significant changes in two aspects of neuroplasticity, cortical thickness, and resting-state neuronal networks. A group of subjects with several years of continuous musical training and who are currently playing in university wind ensembles showed differences in cortical thickness in lip- and tongue-related brain areas vs. non-music playing subjects. Cortical thickness in lip-related brain areas was significantly thicker and that in tongue-related areas was significantly thinner in the music playing group compared with that in the non-music playing group. Association analysis of lip-related areas in the music playing group showed that the increase in cortical thickness was caused by musical training. In addition, seed-based correlation analysis showed differential activation in the precentral gyrus and supplementary motor areas (SMA) between the music and non-music playing groups. These results suggest that high-intensity training with specific musical instruments could induce structural changes in related anatomical areas and could also generate a new functional neuronal network in the brain.
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Affiliation(s)
- Uk-Su Choi
- Neuroscience Research Institute, Gachon University of Medicine and Science Incheon, South Korea
| | - Yul-Wan Sung
- Kansei Fukushi Research Institute, Tohoku Fukushi University Sendai, Japan
| | - Sujin Hong
- Reid School of Music, Edinburgh College of Art, Institute for Music and Human Society Development, University of Edinburgh Edinburgh, UK
| | - Jun-Young Chung
- Neuroscience Research Institute, Gachon University of Medicine and Science Incheon, South Korea
| | - Seiji Ogawa
- Kansei Fukushi Research Institute, Tohoku Fukushi University Sendai, Japan
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33
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Zhang D, Wang J, Liu X, Chen J, Liu B. Aberrant Brain Network Efficiency in Parkinson's Disease Patients with Tremor: A Multi-Modality Study. Front Aging Neurosci 2015; 7:169. [PMID: 26379547 PMCID: PMC4553412 DOI: 10.3389/fnagi.2015.00169] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2015] [Accepted: 08/17/2015] [Indexed: 01/18/2023] Open
Abstract
The coordination of spontaneous brain activity is widely enhanced relative to compensation activity in Parkinson’s disease (PD) with tremor; however, the associated topological organization remains unclear. This study collected magnetic resonance imaging data from 36 participants [i.e., 16 PD patients and 20 matched normal controls (NCs)] and constructed wavelet-based functional and morphological brain networks for individual participants. Graph-based network analysis indicated that the information translation efficiency in the functional brain network was disrupted within the wavelet scale 2 (i.e., 0.063–0.125 Hz) in PD patients. Compared with the NCs, the network local efficiency was decreased and the network global efficiency was increased in PD patients. Network local efficiency could effectively discriminate PD patients from the NCs using multivariate pattern analysis, and could also describe the variability of tremor based on a multiple linear regression model (MLRM). However, these observations were not identified in the network global efficiency. Notably, the global and local efficiency were both significantly increased in the morphological brain network of PD patients. We further found that the global and local network efficiency both worked well on PD classifications (i.e., using MVPA) and clinical performance descriptions (i.e., using MLRM). More importantly, functional and morphological brain networks were highly associated in terms of network local efficiency in PD patients. This study sheds lights on network disorganization in PD with tremor and helps for understanding the neural basis underlying this type of PD.
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Affiliation(s)
- Delong Zhang
- Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine , Guangzhou , China ; Guangzhou University of Chinese Medicine Postdoctoral Mobile Research Station , Guangzhou , China
| | - Jinhui Wang
- Center for Cognition and Brain Disorders, Hangzhou Normal University , Hangzhou , China ; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments , Hangzhou , China
| | - Xian Liu
- Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine , Guangzhou , China
| | - Jun Chen
- Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine , Guangzhou , China
| | - Bo Liu
- Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine , Guangzhou , China
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34
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Abstract
Intrinsic coupling of neuronal assemblies constitutes a key feature of ongoing brain activity, yielding the rich spatiotemporal patterns observed in neuroimaging data and putatively supporting cognitive processes. Intrinsic coupling has been investigated in electrophysiological recordings using two types of functional connectivity measures: amplitude and phase coupling. These two coupling modes differ in their likely causes and functions, and have been proposed to provide complementary insights into intrinsic neuronal interactions. Here, we investigate the relationship between amplitude and phase coupling in source-reconstructed electroencephalography (EEG). Volume conduction is a key obstacle for connectivity analysis in EEG-we therefore also test the envelope correlation of orthogonalized signals and the phase lag index. Functional connectivity between six seed source regions (bilateral visual, sensorimotor, and auditory cortices) and all other cortical voxels was computed. For all four measures, coupling between homologous sensory areas in both hemispheres was significantly higher than with other voxels at the same physical distance. The frequency of significant coupling differed between sensory areas: 10 Hz for visual, 30 Hz for auditory, and 40 Hz for sensorimotor cortices. By contrasting envelope correlations and phase locking values, we observed two distinct clusters of voxels showing a different relationship between amplitude and phase coupling. Large clusters contiguous to the seed regions showed an identity (1:1) relationship between amplitude and phase coupling, whereas a cluster located around the contralateral homologous regions showed higher phase than amplitude coupling. These results show a relationship between intrinsic coupling modes that is distinct from the effect of volume conduction.
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Affiliation(s)
- Saeid Mehrkanoon
- 1 School of Psychiatry, University of New South Wales , Sydney, Australia
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35
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Pittau F, Mégevand P, Sheybani L, Abela E, Grouiller F, Spinelli L, Michel CM, Seeck M, Vulliemoz S. Mapping epileptic activity: sources or networks for the clinicians? Front Neurol 2014; 5:218. [PMID: 25414692 PMCID: PMC4220689 DOI: 10.3389/fneur.2014.00218] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Accepted: 10/08/2014] [Indexed: 01/03/2023] Open
Abstract
Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity.
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Affiliation(s)
- Francesca Pittau
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Pierre Mégevand
- Laboratory for Multimodal Human Brain Mapping, Hofstra North Shore LIJ School of Medicine , Manhasset, NY , USA
| | - Laurent Sheybani
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Eugenio Abela
- Support Center of Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, University Hospital Inselspital , Bern , Switzerland
| | - Frédéric Grouiller
- Radiology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Neurology Department, 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
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36
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Watanabe T, Hirose S, Wada H, Imai Y, Machida T, Shirouzu I, Konishi S, Miyashita Y, Masuda N. Energy landscapes of resting-state brain networks. Front Neuroinform 2014; 8:12. [PMID: 24611044 PMCID: PMC3933812 DOI: 10.3389/fninf.2014.00012] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Accepted: 01/28/2014] [Indexed: 01/29/2023] Open
Abstract
During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs) including the default-mode network (DMN) and frontoparietal network (FPN). Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics), the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant local minima were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.
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Affiliation(s)
- Takamitsu Watanabe
- Department of Physiology, The University of Tokyo School of Medicine Tokyo, Japan ; Awareness Group, Institute of Cognitive Neuroscience, University College London London, UK
| | - Satoshi Hirose
- Department of Physiology, The University of Tokyo School of Medicine Tokyo, Japan
| | - Hiroyuki Wada
- Department of Radiology, NTT Medical Center Tokyo Tokyo, Japan
| | - Yoshio Imai
- Department of Radiology, NTT Medical Center Tokyo Tokyo, Japan
| | - Toru Machida
- Department of Radiology, NTT Medical Center Tokyo Tokyo, Japan
| | - Ichiro Shirouzu
- Department of Radiology, NTT Medical Center Tokyo Tokyo, Japan
| | - Seiki Konishi
- Department of Physiology, The University of Tokyo School of Medicine Tokyo, Japan
| | - Yasushi Miyashita
- Department of Physiology, The University of Tokyo School of Medicine Tokyo, Japan
| | - Naoki Masuda
- Department of Mathematical Informatics, The University of Tokyo Tokyo, Japan ; CREST, Japan Science and Technology Agency Saitama, Japan
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37
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Liu X, Chang C, Duyn JH. Decomposition of spontaneous brain activity into distinct fMRI co-activation patterns. Front Syst Neurosci 2013; 7:101. [PMID: 24550788 PMCID: PMC3913885 DOI: 10.3389/fnsys.2013.00101] [Citation(s) in RCA: 122] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2013] [Accepted: 11/15/2013] [Indexed: 01/23/2023] Open
Abstract
Recent fMRI studies have shown that analysis of the human brain's spontaneous activity may provide a powerful approach to reveal its functional organization. Dedicated methods have been proposed to investigate co-variation of signals from different brain regions, with the goal of revealing neuronal networks (NNs) that may serve specialized functions. However, these analysis methods generally do not take into account a potential non-stationary (variable) interaction between brain regions, and as a result have limited effectiveness. To address this, we propose a novel analysis method that uses clustering analysis to sort and selectively average fMRI activity time frames to produce a set of co-activation patterns. Compared to the established networks extracted with conventional analysis methods, these co-activation patterns demonstrate novel network features with apparent relevance to the brain's functional organization.
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Affiliation(s)
- Xiao Liu
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health Bethesda, MD, USA
| | - Catie Chang
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health Bethesda, MD, USA
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health Bethesda, MD, USA
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38
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Wang D, Qin W, Liu Y, Zhang Y, Jiang T, Yu C. Altered resting-state network connectivity in congenital blind. Hum Brain Mapp 2013; 35:2573-81. [PMID: 24038713 DOI: 10.1002/hbm.22350] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2012] [Revised: 05/07/2013] [Accepted: 05/28/2013] [Indexed: 11/08/2022] Open
Abstract
The brain of congenital blind (CB) has experienced a series of structural and functional alterations, either undesirable outcomes such as atrophy of the visual pathway due to sight loss from birth, or compensatory plasticity to interact efficiently with the environment. However, little is known, so far, about alterations in the functional architecture of resting-state networks (RSNs) in CB. This study aimed to investigate intra- and internetwork connectivity differences between CB and sighted controls (SC), using independent component analysis (ICA) on resting state functional MRI data. Compared with SC, CB showed significantly increased network connectivity within the salience network (SN) and the occipital cortex. Moreover, CB exhibited enhanced internetwork connectivity between the SN and the frontoparietal network (FPN) and between the FPN and the occipital cortex; however, they showed decreased internetwork connectivity between the occipital cortex and the sensorimotor network. These findings suggest that CB experience large scale reorganization at the level of the functional network. More importantly, the enhanced intra- and internetwork connectivity of the SN, FPN, and occipital cortex in CB may improve their abilities to identify salient stimuli, to initiate the executive function, and to top-down control of attention, which are critical for the CB to guide appropriate behavior and to better adaption to the environment.
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Affiliation(s)
- Dawei Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
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39
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Abstract
Neuroimaging, both structural and functional, serve as useful adjuncts to clinical assessment, and can provide objective, reliable means of assessing disease presence and process in the aging population. In the following review we briefly explain current imaging methodologies. Then, we analyze recent developments in developing neuroimaging biomarkers for two highly prevalent disorders in the elderly population- Alzheimer's disease (AD) and late-life depression (LLD). In AD, efforts are focused on early diagnosis through in vivo visualization of disease pathophysiology. In LLD, recent imaging evidence supports the role of white matter ischemic changes in the pathogenesis of depression in the elderly, the "vascular hypothesis." Finally, we discuss potential roles for neuroimaging biomarkers in geriatric psychiatry in the future.
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Affiliation(s)
- Abhisek C Khandai
- University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
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40
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Li R, Chen K, Fleisher AS, Reiman EM, Yao L, Wu X. Large-scale directional connections among multi resting-state neural networks in human brain: a functional MRI and Bayesian network modeling study. Neuroimage 2011; 56:1035-42. [PMID: 21396456 PMCID: PMC3319766 DOI: 10.1016/j.neuroimage.2011.03.010] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2010] [Revised: 02/25/2011] [Accepted: 03/03/2011] [Indexed: 11/28/2022] Open
Abstract
This study examined the large-scale connectivity among multiple resting-state networks (RSNs) in the human brain. Independent component analysis was first applied to the resting-state functional MRI (fMRI) data acquired from 12 healthy young subjects for the separation of RSNs. Four sensory (lateral and medial visual, auditory, and sensory-motor) RSNs and four cognitive (default-mode, self-referential, dorsal and ventral attention) RSNs were identified. Gaussian Bayesian network (BN) learning approach was then used for the examination of the conditional dependencies among these RSNs and the construction of the network-to-network directional connectivity patterns. The BN based results demonstrated that sensory networks and cognitive networks were hierarchically organized. Specially, we found the sensory networks were highly intra-dependent and the cognitive networks were strongly intra-influenced. In addition, the results depicted dominant bottom-up connectivity from sensory networks to cognitive networks in which the self-referential and the default-mode networks might play respectively important roles in the process of resting-state information transfer and integration. The present study characterized the global connectivity relations among RSNs and delineated more characteristics of spontaneous activity dynamics.
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Affiliation(s)
- Rui Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Kewei Chen
- Banner Alzheimer’s Institute (BAI) & Banner Good Samaritan PET Center, Phoenix, AZ 85006, USA
| | - Adam S. Fleisher
- Banner Alzheimer’s Institute (BAI) & Banner Good Samaritan PET Center, Phoenix, AZ 85006, USA
- Department of Neuroscience, University of California, San Diego, San Diego, CA 92103, USA
| | - Eric M. Reiman
- Banner Alzheimer’s Institute (BAI) & Banner Good Samaritan PET Center, Phoenix, AZ 85006, USA
| | - Li Yao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- School of Information Science and Technology, Beijing Normal University, Beijing 100875, China
| | - Xia Wu
- School of Information Science and Technology, Beijing Normal University, Beijing 100875, China
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