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Yang Y, Tang D, Wang Z, Liu Y, Chen F, Jie B, Ni T, Xu C, Li J, Wang C. Identification of high-functioning autism spectrum disorders based on gray-white matter functional network connectivity. J Psychiatr Res 2024; 178:107-113. [PMID: 39128219 DOI: 10.1016/j.jpsychires.2024.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 08/04/2024] [Accepted: 08/05/2024] [Indexed: 08/13/2024]
Abstract
In the field of autism spectrum disorder (ASD), research on functional connectivity between gray matter and white matter remains under-researched. To address this gap, this study innovatively introduced a nested cross-validation method that integrates gray-white matter functional connectivity with an F-Score algorithm. This method calculates the correlation based on signals extracted from functional magnetic resonance imaging data using gray matter and white matter brain region templates. After applying the method to a New York University Langone Medical Center dataset consisting of 55 individuals with high-functioning ASD and 52 healthy subjects, we achieved a classification accuracy of 72.94%. This study found abnormal functional connectivity, primarily involving the left anterior prefrontal cortex and right superior corona radiata, left retrosplenial cortex and left superior corona radiata, as well as the left ventral anterior cingulate cortex and body of corpus callosum. Besides, we discovered that these abnormal connections are closely related to social impairment and restrictive and repetitive behaviors in ASD. In conclusion, this study provides a gray-white matter functional connectivity perspective for the diagnosis and understanding of ASD.
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Affiliation(s)
- Yang Yang
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Detao Tang
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Zhiwei Wang
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Yifei Liu
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Fulong Chen
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China.
| | - Biao Jie
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Tianjiao Ni
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Chenglong Xu
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Jintao Li
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
| | - Chao Wang
- School of Computer and Information, Anhui Normal University, WuHu, 241002, Anhui, China; Anhui Engineering Research Center of Medical Big Data Intelligent System, WuHu, 241002, Anhui, China
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Zhang X, Wu B, Yang X, Kemp GJ, Wang S, Gong Q. Abnormal large-scale brain functional network dynamics in social anxiety disorder. CNS Neurosci Ther 2024; 30:e14904. [PMID: 39107947 PMCID: PMC11303268 DOI: 10.1111/cns.14904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 07/02/2024] [Accepted: 07/25/2024] [Indexed: 08/10/2024] Open
Abstract
AIMS Although static abnormalities of functional brain networks have been observed in patients with social anxiety disorder (SAD), the brain connectome dynamics at the macroscale network level remain obscure. We therefore used a multivariate data-driven method to search for dynamic functional network connectivity (dFNC) alterations in SAD. METHODS We conducted spatial independent component analysis, and used a sliding-window approach with a k-means clustering algorithm, to characterize the recurring states of brain resting-state networks; then state transition metrics and FNC strength in the different states were compared between SAD patients and healthy controls (HC), and the relationship to SAD clinical characteristics was explored. RESULTS Four distinct recurring states were identified. Compared with HC, SAD patients demonstrated higher fractional windows and mean dwelling time in the highest-frequency State 3, representing "widely weaker" FNC, but lower in States 2 and 4, representing "locally stronger" and "widely stronger" FNC, respectively. In State 1, representing "widely moderate" FNC, SAD patients showed decreased FNC mainly between the default mode network and the attention and perceptual networks. Some aberrant dFNC signatures correlated with illness duration. CONCLUSION These aberrant patterns of brain functional synchronization dynamics among large-scale resting-state networks may provide new insights into the neuro-functional underpinnings of SAD.
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Affiliation(s)
- Xun Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Baolin Wu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
| | - Xun Yang
- School of Public AffairsChongqing UniversityChongqingChina
| | - Graham J. Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical SciencesUniversity of LiverpoolLiverpoolUK
| | - Song Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
- Department of RadiologyWest China Xiamen Hospital of Sichuan UniversityXiamenChina
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Chen F, Chen Q, Zhu Y, Long C, Lu J, Jiang Y, Zhang X, Zhang B. Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease. Transl Stroke Res 2024; 15:580-590. [PMID: 36967436 PMCID: PMC11106163 DOI: 10.1007/s12975-023-01148-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/03/2023] [Accepted: 03/14/2023] [Indexed: 03/28/2023]
Abstract
Cerebral small vessel disease (CSVD) is a common disease that seriously endangers people's health, and is easily overlooked by both patients and clinicians due to its near-silent onset. Dynamic functional connectivity (DFC) is a new concept focusing on the dynamic features and patterns of brain networks that represents a powerful tool for gaining novel insight into neurological diseases. To assess alterations in DFC in CSVD patients, and the correlation of DFC with cognitive function. We enrolled 35 CSVD patients and 31 normal control subjects (NC). Resting-state functional MRI (rs-fMRI) with a sliding-window approach and k-means clustering based on independent component analysis (ICA) was used to evaluate DFC. The temporal properties of fractional windows and the mean dwell time in each state, as well as the number of transitions between each pair of DFC states, were calculated. Additionally, we assessed the functional connectivity (FC) strength of the dynamic states and the associations of altered neuroimaging measures with cognitive performance. A dynamic analysis of all included subjects suggested four distinct functional connectivity states. Compared with the NC group, the CSVD group had more fractional windows and longer mean dwell times in state 4 characterized by sparse FC both inter-network and intra-networks. Additionally, the CSVD group had a reduced number of windows and shorter mean dwell times compared to the NC group in state 3 characterized by highly positive FC between the somatomotor and visual networks, and negative FC in the basal ganglia and somatomotor and visual networks. The number of transitions between state 2 and state 3 and between state 3 and state 4 was significantly reduced in the CSVD group compared to the NC group. Moreover, there was a significant difference in the FC strength between the two groups, and the altered temporal properties of DFC were significantly related to cognitive performance. Our study indicated that CSVD is characterized by altered temporal properties in DFC that may be sensitive neuroimaging biomarkers for early disease identification. Further study of DFC alterations could help us to better understand the progressive dysfunction of networks in CSVD patients.
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Affiliation(s)
- Futao Chen
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
| | - Qian Chen
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Department of Radiology, Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
| | - Yajing Zhu
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Department of Radiology, Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
| | - Cong Long
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
| | - Jiaming Lu
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
| | - Yaoxian Jiang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
| | - Xin Zhang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
| | - Bing Zhang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China.
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China.
- Department of Radiology, Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China.
- Jiangsu Key Laboratory of Molecular Medicine, Nanjing, China.
- Institute of Brain Science, Nanjing University, Nanjing, China.
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Li L, Zheng Q, Xue Y, Bai M, Mu Y. Coactivation pattern analysis reveals altered whole-brain functional transient dynamics in autism spectrum disorder. Eur Child Adolesc Psychiatry 2024:10.1007/s00787-024-02474-y. [PMID: 38814465 DOI: 10.1007/s00787-024-02474-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 05/18/2024] [Indexed: 05/31/2024]
Abstract
Recent studies on autism spectrum disorder (ASD) have identified recurring states dominated by similar coactivation pattern (CAP) and revealed associations between dysfunction in seed-based large-scale brain networks and clinical symptoms. However, the presence of abnormalities in moment-to-moment whole-brain dynamics in ASD remains uncertain. In this study, we employed seed-free CAP analysis to identify transient brain activity configurations and investigate dynamic abnormalities in ASD. We utilized a substantial multisite resting-state fMRI dataset consisting of 354 individuals with ASD and 446 healthy controls (HCs, from HC groups and 2). CAP were generated from a subgroup of all HC subjects (HC group 1) through temporal K-means clustering, identifying four CAPs. These four CAPs exhibited either the activation or inhibition of the default mode network (DMN) and were grouped into two pairs with opposing spatial CAPs. CAPs for HC group 2 and ASD were identified by their spatial similarity to those for HC group 1. Compared with individuals in HC group 2, those with ASD spent more time in CAPs involving the ventral attention network but less time in CAPs related to executive control and the dorsal attention network. Support vector machine analysis demonstrated that the aberrant dynamic characteristics of CAPs achieved an accuracy of 74.87% in multisite classification. In addition, we used whole-brain dynamics to predict symptom severity in ASD. Our findings revealed whole-brain dynamic functional abnormalities in ASD from a single transient perspective, emphasizing the importance of the DMN in abnormal dynamic functional activity in ASD and suggesting that temporally dynamic techniques offer novel insights into time-varying neural processes.
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Affiliation(s)
- Lei Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Qingyu Zheng
- School of Healthcare Technology, Chengdu Neusoft University, Chengdu, People's Republic of China
| | - Yang Xue
- Department of Developmental and Behavioral Pediatrics, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Miaoshui Bai
- Department of Developmental and Behavioral Pediatrics, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Yueming Mu
- Department of Dermatology, The First Hospital of Jilin University, Jilin University, 71 Xinmin Street, Changchun, 130021, People's Republic of China.
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Wang Y, Shu Y, Cai G, Guo Y, Gao J, Chen Y, Lv L, Zeng X. Altered static and dynamic functional network connectivity in primary angle-closure glaucoma patients. Sci Rep 2024; 14:11682. [PMID: 38778225 PMCID: PMC11111766 DOI: 10.1038/s41598-024-62635-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 05/20/2024] [Indexed: 05/25/2024] Open
Abstract
To explore altered patterns of static and dynamic functional brain network connectivity (sFNC and dFNC) in Primary angle-closure glaucoma (PACG) patients. Clinically confirmed 34 PACG patients and 33 age- and gender-matched healthy controls (HCs) underwent evaluation using T1 anatomical and functional MRI on a 3 T scanner. Independent component analysis, sliding window, and the K-means clustering method were employed to investigate the functional network connectivity (FNC) and temporal metrics based on eight resting-state networks. Differences in FNC and temporal metrics were identified and subsequently correlated with clinical variables. For sFNC, compared with HCs, PACG patients showed three decreased interactions, including SMN-AN, SMN-VN and VN-AN pairs. For dFNC, we derived four highly structured states of FC that occurred repeatedly between individual scans and subjects, and the results are highly congruent with sFNC. In addition, PACG patients had a decreased fraction of time in state 3 and negatively correlated with IOP (p < 0.05). PACG patients exhibit abnormalities in both sFNC and dFNC. The high degree of overlap between static and dynamic results suggests the stability of functional connectivity networks in PACG patients, which provide a new perspective to understand the neuropathological mechanisms of optic nerve damage in PACG patients.
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Affiliation(s)
- Yuanyuan Wang
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yongqiang Shu
- Positron Emission Tomography (PET) Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Guoqian Cai
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yu Guo
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Junwei Gao
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Ye Chen
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Lianjiang Lv
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xianjun Zeng
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China.
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6
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Lingwood C. Is cholesterol both the lock and key to abnormal transmembrane signals in Autism Spectrum Disorder? Lipids Health Dis 2024; 23:114. [PMID: 38643132 PMCID: PMC11032007 DOI: 10.1186/s12944-024-02075-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 03/08/2024] [Indexed: 04/22/2024] Open
Abstract
Disturbances in cholesterol homeostasis have been associated with ASD. Lipid rafts are central in many transmembrane signaling pathways (including mTOR) and changes in raft cholesterol content affect their order function. Cholesterol levels are controlled by several mechanisms, including endoplasmic reticulum associated degradation (ERAD) of the rate limiting HMGCoA reductase. A new approach to increase cholesterol via temporary ERAD blockade using a benign bacterial toxin-derived competitor for the ERAD translocon is suggested.A new lock and key model for cholesterol/lipid raft dependent signaling is proposed in which the rafts provide both the afferent and efferent 'tumblers' across the membrane to allow 'lock and key' receptor transmembrane signals.
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Affiliation(s)
- Clifford Lingwood
- Division of Molecular Medicine, Research Institute, Peter Gilgan Centre for Research and Learning, Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada.
- Departments of Biochemistry and Laboratory Medicine & Pathobiology, University of Toronto, Ontario, M5S 1A8, Canada.
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Su T, Chen B, Yang M, Wang Q, Zhou H, Zhang M, Wu Z, Lin G, Wang D, Li Y, Zhong X, Ning Y. Disrupted functional connectivity of the habenula links psychomotor retardation and deficit of verbal fluency and working memory in late-life depression. CNS Neurosci Ther 2024; 30:e14490. [PMID: 37804094 PMCID: PMC11017447 DOI: 10.1111/cns.14490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/02/2023] [Accepted: 09/23/2023] [Indexed: 10/08/2023] Open
Abstract
BACKGROUND Functional abnormalities of the habenula in patients with depression have been demonstrated in an increasing number of studies, and the habenula is involved in cognitive processing. However, whether patients with late-life depression (LLD) exhibit disrupted habenular functional connectivity (FC) and whether habenular FC mediates the relationship between depressive symptoms and cognitive impairment remain unclear. METHODS Overall, 127 patients with LLD and 75 healthy controls were recruited. The static and dynamic FC between the habenula and the whole brain was compared between LLD patients and healthy controls, and the relationships of habenular FC with depressive symptoms and cognitive impairment were explored by correlation and mediation analyses. RESULTS Compared with the controls, patients with LLD exhibited decreased static FC between the right habenula and bilateral inferior frontal gyrus (IFG); there was no significant difference in dynamic FC of the habenula between the two groups. Additionally, the decreased static FC between the right habenula and IFG was associated with more severe depressive symptoms (especially psychomotor retardation) and cognitive impairment (language, memory, and visuospatial skills). Last, static FC between the right habenula and left IFG partially mediated the relationship between depressive symptoms (especially psychomotor retardation) and cognitive impairment (verbal fluency and working memory). CONCLUSIONS Patients with LLD exhibited decreased static FC between the habenula and IFG but intact dynamic FC of the habenula. This decreased static FC mediated the relationship between depressive symptoms and cognitive impairment.
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Affiliation(s)
- Ting Su
- Department of RadiologyThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Ben Chen
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Mingfeng Yang
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Qiang Wang
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Huarong Zhou
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Min Zhang
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Zhangying Wu
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Gaohong Lin
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | | | - Yue Li
- Guangzhou Medical UniversityGuangzhouChina
| | - Xiaomei Zhong
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Yuping Ning
- Geriatric Neuroscience CenterThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China Guangzhou Medical UniversityGuangzhouChina
- The First School of Clinical MedicineSouthern Medical UniversityGuangzhouChina
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental DisordersGuangzhouChina
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Cheng X, Chen J, Zhang X, Wang T, Sun J, Zhou Y, Yang R, Xiao Y, Chen A, Song Z, Chen P, Yang C, QiuxiaWu, Lin T, Chen Y, Cao L, Wei X. Characterizing the temporal dynamics of intrinsic brain activities in depressed adolescents with prior suicide attempts. Eur Child Adolesc Psychiatry 2024; 33:1179-1191. [PMID: 37284850 PMCID: PMC11032277 DOI: 10.1007/s00787-023-02242-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/24/2023] [Indexed: 06/08/2023]
Abstract
Converging evidence has revealed disturbances in the corticostriatolimic system are associated with suicidal behaviors in adults with major depressive disorder. However, the neurobiological mechanism that confers suicidal vulnerability in depressed adolescents is largely unknown. A total of 86 depressed adolescents with and without prior suicide attempts (SA) and 47 healthy controls underwent resting-state functional imaging (R-fMRI) scans. The dynamic amplitude of low-frequency fluctuations (dALFF) was measured using sliding window approach. We identified SA-related alterations in dALFF variability primarily in the left middle temporal gyrus, inferior frontal gyrus, middle frontal gyrus (MFG), superior frontal gyrus (SFG), right SFG, supplementary motor area (SMA) and insula in depressed adolescents. Notably, dALFF variability in the left MFG and SMA was higher in depressed adolescents with recurrent suicide attempts than in those with a single suicide attempt. Moreover, dALFF variability was capable of generating better diagnostic and prediction models for suicidality than static ALFF. Our findings suggest that alterations in brain dynamics in regions involved in emotional processing, decision-making and response inhibition are associated with an increased risk of suicidal behaviors in depressed adolescents. Furthermore, dALFF variability could serve as a sensitive biomarker for revealing the neurobiological mechanisms underlying suicidal vulnerability.
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Affiliation(s)
- Xiaofang Cheng
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Jianshan Chen
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Xiaofei Zhang
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Ting Wang
- The Second Affiliated Hospital, School of Medicine, South China University of Technology, 1 Panfu Road, Yuexiu district, Guangzhou, 510180, Guangdong, People's Republic of China
| | - Jiaqi Sun
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Yanling Zhou
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Ruilan Yang
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Yeyu Xiao
- Guangzhou Integrated Traditional Chinese and Western Medicine, Guangzhou, 510800, Guangdong, People's Republic of China
| | - Amei Chen
- The Second Affiliated Hospital, School of Medicine, South China University of Technology, 1 Panfu Road, Yuexiu district, Guangzhou, 510180, Guangdong, People's Republic of China
| | - Ziyi Song
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Pinrui Chen
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Chanjuan Yang
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - QiuxiaWu
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Taifeng Lin
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Yingmei Chen
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Liping Cao
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China.
| | - Xinhua Wei
- The Second Affiliated Hospital, School of Medicine, South China University of Technology, 1 Panfu Road, Yuexiu district, Guangzhou, 510180, Guangdong, People's Republic of China.
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Sudo Y, Ota J, Takamura T, Kamashita R, Hamatani S, Numata N, Chhatkuli RB, Yoshida T, Takahashi J, Kitagawa H, Matsumoto K, Masuda Y, Nakazato M, Sato Y, Hamamoto Y, Shoji T, Muratsubaki T, Sugiura M, Fukudo S, Kawabata M, Sunada M, Noda T, Tose K, Isobe M, Kodama N, Kakeda S, Takahashi M, Takakura S, Gondo M, Yoshihara K, Moriguchi Y, Shimizu E, Sekiguchi A, Hirano Y. Comprehensive elucidation of resting-state functional connectivity in anorexia nervosa by a multicenter cross-sectional study. Psychol Med 2024:1-14. [PMID: 38500410 DOI: 10.1017/s0033291724000485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
BACKGROUND Previous research on the changes in resting-state functional connectivity (rsFC) in anorexia nervosa (AN) has been limited by an insufficient sample size, which reduced the reliability of the results and made it difficult to set the whole brain as regions of interest (ROIs). METHODS We analyzed functional magnetic resonance imaging data from 114 female AN patients and 135 healthy controls (HC) and obtained self-reported psychological scales, including eating disorder examination questionnaire 6.0. One hundred sixty-four cortical, subcortical, cerebellar, and network parcellation regions were considered as ROIs. We calculated the ROI-to-ROI rsFCs and performed group comparisons. RESULTS Compared to HC, AN patients showed 12 stronger rsFCs mainly in regions containing dorsolateral prefrontal cortex (DLPFC), and 33 weaker rsFCs primarily in regions containing cerebellum, within temporal lobe, between posterior fusiform cortex and lateral part of visual network, and between anterior cingulate cortex (ACC) and thalamus (p < 0.01, false discovery rate [FDR] correction). Comparisons between AN subtypes showed that there were stronger rsFCs between right lingual gyrus and right supracalcarine cortex and between left temporal occipital fusiform cortex and medial part of visual network in the restricting type compared to the binge/purging type (p < 0.01, FDR correction). CONCLUSION Stronger rsFCs in regions containing mainly DLPFC, and weaker rsFCs in regions containing primarily cerebellum, within temporal lobe, between posterior fusiform cortex and lateral part of visual network, and between ACC and thalamus, may represent categorical diagnostic markers discriminating AN patients from HC.
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Affiliation(s)
- Yusuke Sudo
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- Department of Cognitive Behavioral Physiology, Chiba University, Chiba, Japan
- Department of Psychiatry, Chiba University Hospital, Chiba, Japan
| | - Junko Ota
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
| | - Tsunehiko Takamura
- Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Rio Kamashita
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
| | - Sayo Hamatani
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
- Research Center for Child Mental Development, Fukui University, Eiheizi, Japan
| | - Noriko Numata
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
| | - Ritu Bhusal Chhatkuli
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
| | - Tokiko Yoshida
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
| | - Jumpei Takahashi
- Department of Psychiatry, Chiba Aoba Municipal Hospital, Chiba, Japan
| | - Hitomi Kitagawa
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
| | - Koji Matsumoto
- Department of Radiology, Chiba University Hospital, Chiba, Japan
| | - Yoshitada Masuda
- Department of Radiology, Chiba University Hospital, Chiba, Japan
| | - Michiko Nakazato
- Department of Psychiatry, School of Medicine, International University of Health and Welfare, Narita, Japan
| | - Yasuhiro Sato
- Department of Psychosomatic Medicine, Tohoku University Hospital, Sendai, Japan
| | - Yumi Hamamoto
- Department of Psychology, Northumbria University, Newcastle-upon-Tyne, UK
- Department of Human Brain Science, Institute of Development, Aging, and Cancer, Tohoku University, Sendai, Japan
| | - Tomotaka Shoji
- Department of Psychosomatic Medicine, Tohoku University Hospital, Sendai, Japan
- Department of Internal Medicine, Nagamachi Hospital, Sendai, Japan
- Department of Psychosomatic Medicine, Tohoku University School of Medicine, Sendai, Japan
| | - Tomohiko Muratsubaki
- Department of Psychosomatic Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Motoaki Sugiura
- Department of Human Brain Science, Institute of Development, Aging, and Cancer, Tohoku University, Sendai, Japan
- Cognitive Sciences Lab, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Shin Fukudo
- Department of Psychosomatic Medicine, Tohoku University Hospital, Sendai, Japan
- Department of Psychosomatic Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Michiko Kawabata
- Department of Psychiatry, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Momo Sunada
- Department of Psychiatry, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Tomomi Noda
- Department of Psychiatry, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Keima Tose
- Department of Psychiatry, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Masanori Isobe
- Department of Psychiatry, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Naoki Kodama
- Division of Psychosomatic Medicine, Department of Neurology, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Shingo Kakeda
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Masatoshi Takahashi
- Division of Psychosomatic Medicine, Department of Neurology, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Shu Takakura
- Department of Psychosomatic Medicine, Kyushu University Hospital, Fukuoka, Japan
| | - Motoharu Gondo
- Department of Psychosomatic Medicine, Kyushu University Hospital, Fukuoka, Japan
| | - Kazufumi Yoshihara
- Department of Psychosomatic Medicine, Kyushu University Hospital, Fukuoka, Japan
| | - Yoshiya Moriguchi
- Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
- Department of Sleep-Wake Disorders, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Eiji Shimizu
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- Department of Cognitive Behavioral Physiology, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
| | - Atsushi Sekiguchi
- Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
- Center for Eating Disorder Research and Information, National Center of Neurology and Psychiatry, Kodaira, Japan
- Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Yoshiyuki Hirano
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
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Suo X, Lan H, Zuo C, Chen L, Qin K, Li L, Kemp GJ, Wang S, Gong Q. Multilayer analysis of dynamic network reconfiguration in pediatric posttraumatic stress disorder. Cereb Cortex 2024; 34:bhad436. [PMID: 37991275 DOI: 10.1093/cercor/bhad436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/19/2023] [Accepted: 10/20/2023] [Indexed: 11/23/2023] Open
Abstract
Neuroimage studies have reported functional connectome abnormalities in posttraumatic stress disorder (PTSD), especially in adults. However, these studies often treated the brain as a static network, and time-variance of connectome topology in pediatric posttraumatic stress disorder remain unclear. To explore case-control differences in dynamic connectome topology, resting-state functional magnetic resonance imaging data were acquired from 24 treatment-naïve non-comorbid pediatric posttraumatic stress disorder patients and 24 demographically matched trauma-exposed non-posttraumatic stress disorder controls. A graph-theoretic analysis was applied to construct time-varying modular structure of whole-brain networks by maximizing the multilayer modularity. Network switching rate at the global, subnetwork, and nodal levels were calculated and compared between posttraumatic stress disorder and trauma-exposed non-posttraumatic stress disorder groups, and their associations with posttraumatic stress disorder symptom severity and sex interactions were explored. At the global level, individuals with posttraumatic stress disorder exhibited significantly lower network switching rates compared to trauma-exposed non-posttraumatic stress disorder controls. This difference was mainly involved in default-mode and dorsal attention subnetworks, as well as in inferior temporal and parietal brain nodes. Posttraumatic stress disorder symptom severity was negatively correlated with switching rate in the global network and default mode network. No significant differences were observed in the interaction between diagnosis and sex/age. Pediatric posttraumatic stress disorder is associated with dynamic reconfiguration of brain networks, which may provide insights into the biological basis of this disorder.
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Affiliation(s)
- Xueling Suo
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Huan Lan
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Chao Zuo
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Li Chen
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Kun Qin
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45219, United States
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital of Central South University, Changsha 410008, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3BX, United Kingdom
| | - Song Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen 361000, China
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11
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Guo L, Zhao Z, Yang X, Shi W, Wang P, Qin D, Wang J, Yin Y. Alterations of dynamic and static brain functional activities and integration in stroke patients. Front Neurosci 2023; 17:1228645. [PMID: 37965216 PMCID: PMC10641467 DOI: 10.3389/fnins.2023.1228645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/05/2023] [Indexed: 11/16/2023] Open
Abstract
Objective The study aimed to investigate the comprehensive characteristics of brain functional activity and integration in patients with subcortical stroke using dynamic and static analysis methods and to examine whether alterations in brain functional activity and integration were associated with clinical symptoms of patients. Methods Dynamic amplitude of low-frequency fluctuation (dALFF), static amplitude of low-frequency fluctuation (sALFF), dynamic degree centrality (dDC), and static degree centrality (sDC) were calculated for 19 patients with right subcortical stroke, 16 patients with left subcortical stroke, and 25 healthy controls (HC). Furthermore, correlation analysis was performed to investigate the relationships between changes in brain functional measurements of patients and clinical variables. Results Group comparison results showed that significantly decreased dALFF in the left angular (ANG_L) and right inferior parietal gyrus (IPG_R), decreased sALFF in the left precuneus (PCUN_L), and decreased sDC in the left crus II of cerebellar hemisphere (CERCRU2_L) and IPG_R, while significantly increased sDC in the right lobule X of cerebellar hemisphere (CER10_R) were detected in patients with right subcortical stroke relative to HC. Patients with left subcortical stroke showed significantly decreased sALFF in the left precuneus (PCUN_L) but increased sDC in the right hippocampus (HIP_R) compared with HC. Additionally, the altered sDC values in the CER10_R of patients with right subcortical stroke and in the HIP_R of patients with left subcortical stroke were associated with the severity of stroke and lower extremities motor function. A correlation was also found between the altered sALFF values in the PCUN_L of patients with left subcortical stroke and lower extremities motor function. Conclusion These findings suggest that time-varying brain activity analysis may supply complementary information for static brain activity analysis. Dynamic and static brain functional activity and integration analysis may contribute to a more comprehensive understanding of the underlying neuropathology of dysfunction in stroke patients.
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Affiliation(s)
- Li Guo
- Graduate School of Kunming Medical University, Kunming, China
- Department of Rehabilitation Medicine, The Affiliated Hospital of Yunnan University, Kunming, China
| | - Zixuan Zhao
- Graduate School of Kunming Medical University, Kunming, China
- Department of Rehabilitation Medicine, The Affiliated Hospital of Yunnan University, Kunming, China
| | - Xu Yang
- Department of Rehabilitation Medicine, The Affiliated Hospital of Yunnan University, Kunming, China
| | - Weiyang Shi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Peng Wang
- Department of Radiology, The Affiliated Hospital of Yunnan University, Kunming, China
| | - Dongdong Qin
- Key Laboratory of Traditional Chinese Medicine for Prevention and Treatment of Neuropsychiatric Diseases, Yunnan University of Chinese Medicine, Kunming, China
| | - Jiaojian Wang
- Yunnan Key Laboratory of Primate Biomedicine Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
| | - Yong Yin
- Department of Rehabilitation Medicine, The Affiliated Hospital of Yunnan University, Kunming, China
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12
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Xie J, Zhang W, Shen Y, Wei W, Bai Y, Zhang G, Meng N, Yue X, Wang X, Zhang X, Wang M. Abnormal spontaneous brain activity in females with autism spectrum disorders. Front Neurosci 2023; 17:1189087. [PMID: 37521682 PMCID: PMC10379634 DOI: 10.3389/fnins.2023.1189087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 05/08/2023] [Indexed: 08/01/2023] Open
Abstract
Objectives To date, most studies on autism spectrum disorder (ASD) have focused on sample sets that were primarily or entirely composed of males; brain spontaneous activity changes in females remain unclear. The purpose of this study was to explore changes in the brain spontaneous neural activity in females with ASD. Methods In this study, resting-state functional magnetic resonance images (rs-fMRI) of 41 females with ASD and 41 typically developing (TD) controls were obtained from the ABDIE database. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of the two groups were calculated to detect the regional brain activity. A two independent sample t-test was used to analyze differences between the ASD and TD groups and a p-value <0.05 was considered statistically significant after false discovery rate (FDR) correction. Pearson correlation analysis was conducted between social responsiveness scale (SRS) scores and the local activity of significantly different brain regions. Results Compared with the typically developing (TD) group, the values of ALFF and ReHo were significantly increased in the left superior temporal gyrus (STG), while the values of ReHo were significantly decreased in the left superior frontal gyrus (SFG), left middle occipital gyrus (MOG), bilateral superior parietal lobule (SPL), and bilateral precuneus in the females with ASD group. Correlation analysis showed that the ReHo of the right precuneus was positively correlated to the total SRS, social communication, and autistic mannerisms. Conclusion Spontaneous activity changes in females with ASD involved multiple brain regions and were related to clinical characteristics. Our results may provide some help for further exploring the neurobiological mechanism of females with ASD.
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Affiliation(s)
- Jiapei Xie
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Weidong Zhang
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
| | - Yu Shen
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
| | - Wei Wei
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
| | - Yan Bai
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
| | - Ge Zhang
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
| | - Nan Meng
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Xipeng Yue
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Xinhui Wang
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
| | | | - Meiyun Wang
- Department of Medical Imaging, Zhengzhou University People’s Hospital and Henan Provincial People’s Hospital, Zhengzhou, China
- Laboratory of Brain Science and Brain-Like Intelligence Technology, Institute for Integrated Medical Science and Engineering, Henan Academy of Sciences, Zhengzhou, China
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Hu Z, Zhou C, He L. Abnormal dynamic functional network connectivity in patients with early-onset bipolar disorder. Front Psychiatry 2023; 14:1169488. [PMID: 37448493 PMCID: PMC10338119 DOI: 10.3389/fpsyt.2023.1169488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 06/12/2023] [Indexed: 07/15/2023] Open
Abstract
Objective To explore the changes in dynamic functional brain network connectivity (dFNC) in patients with early-onset bipolar disorder (BD). Methods Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 39 patients with early-onset BD and 22 healthy controls (HCs). Four repeated and stable dFNC states were characterised by independent component analysis (ICA), sliding time windows and k-means clustering, and three dFNC temporal metrics (fraction of time, mean dwell time and number of transitions) were obtained. The dFNC temporal metrics and the differences in dFNC between the two groups in different states were evaluated, and the correlations between the differential dFNC metrics and neuropsychological scores were analysed. Results The dFNC analysis showed four connected patterns in all subjects. Compared with the HCs, the dFNC patterns of early-onset BD were significantly altered in all four states, mainly involving impaired cognitive and perceptual networks. In addition, early-onset BD patients had a decreased fraction of time and mean dwell time in state 2 and an increased mean dwell time in state 3 (p < 0.05). The mean dwell time in state 3 of BD showed a positive correlation trend with the HAMA score (r = 0.4049, p = 0.0237 × 3 > 0.05 after Bonferroni correction). Conclusion Patients with early-onset BD had abnormal dynamic properties of brain functional network connectivity, suggesting that their dFNC was unstable, mainly manifesting as impaired coordination between cognitive and perceptual networks. This study provided a new imaging basis for the neuropathological study of emotional and cognitive deficits in early-onset BD.
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Affiliation(s)
- Ziyi Hu
- Department of Radiology, First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Chun Zhou
- Department of Radiology, First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Laichang He
- Department of Radiology, First Affiliated Hospital of Nanchang University, Nanchang, China
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14
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Wan X, Zhang P, Wang W, Wu X, Tan Q, Su X, Zhang S, Yang X, Li S, Shao H, Yue Q, Gong Q. Abnormal brain functional network dynamics in sleep-related hypermotor epilepsy. CNS Neurosci Ther 2022; 29:659-668. [PMID: 36510701 PMCID: PMC9873504 DOI: 10.1111/cns.14048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 11/07/2022] [Accepted: 11/21/2022] [Indexed: 12/15/2022] Open
Abstract
AIMS This study aimed to use resting-state functional magnetic resonance imaging (rs-fMRI) to determine the temporal features of functional connectivity states and changes in connectivity strength in sleep-related hypermotor epilepsy (SHE). METHODS High-resolution T1 and rs-fMRI scanning were performed on all the subjects. We used a sliding-window approach to construct a dynamic functional connectivity (dFC) network. The k-means clustering method was performed to analyze specific FC states and related temporal properties. Finally, the connectivity strength between the components was analyzed using network-based statistics (NBS) analysis. The correlations between the abovementioned measures and disease duration were analyzed. RESULTS After k-means clustering, the SHE patients mainly exhibited two dFC states. The frequency of state 1 was higher, which was characterized by stronger connections within the networks; state 2 occurred at a relatively low frequency, characterized by stronger connections between networks. SHE patients had greater fractional time and a mean dwell time in state 2 and had a larger number of state transitions. The NBS results showed that SHE patients had increased connectivity strength between networks. None of the properties was correlated with illness duration among patients with SHE. CONCLUSION The patterns of dFC patterns may represent an adaptive and protective mode of the brain to deal with epileptic seizures.
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Affiliation(s)
- Xinyue Wan
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina,Department of Radiology, Huashan HospitalFudan UniversityShanghaiChina
| | - Pengfei Zhang
- Second Clinical SchoolLanzhou UniversityLanzhouChina,Department of Magnetic ResonanceLanzhou University Second HospitalLanzhouChina
| | - Weina Wang
- Department of Radiology, The First Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouChina
| | - Xintong Wu
- Department of NeurologyWest China Hospital of Sichuan UniversityChengduChina
| | - Qiaoyue Tan
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina
| | - Xiaorui Su
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina
| | - Simin Zhang
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina
| | - Xibiao Yang
- Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina
| | - Shuang Li
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina
| | - Hanbing Shao
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina
| | - Qiang Yue
- Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduChina,Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina,Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceChengduChina,Department of RadiologyWest China Xiamen Hospital of Sichuan UniversityXiamenFujianChina
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15
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Tian T, Li Y, Li J, Zhang G, Wang J, Wan C, Fang J, Wu D, Zhou Y, Qin Y, Zhu H, Liu D, Zhu W. Genetic influence on brain volume alterations related to self-reported childhood abuse. Front Neurosci 2022; 16:1019718. [PMID: 36203798 PMCID: PMC9530554 DOI: 10.3389/fnins.2022.1019718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 08/30/2022] [Indexed: 11/13/2022] Open
Abstract
As an important predictor of adulthood psychopathology, self-reported childhood abuse appears heritable and is associated with brain abnormalities. However, the specific genetic mechanisms behind these brain alterations remain largely unknown. This study recruited young adults who reported different degrees of childhood abuse from the community. In order to fully understand the influence of genes on brain changes related to self-reported childhood abuse, various experiments were conducted in this study. Firstly, volume changes of gray matter and white matter related to childhood abuse were investigated by using advanced magnetic resonance imaging techniques. After sequencing the whole exons, we further investigated the relationship between polygenic risk score, brain volume alterations, and childhood abuse score. Furthermore, transcription-neuroimaging association analysis was used to identify risk genes whose expressions were associated with brain volume alterations. The gray matter volumes of left caudate and superior parietal lobule, and white matter volumes of left cerebellum and right temporal lobe-basal ganglia region were significantly correlated with the childhood abuse score. More importantly, brain volume changes mediated the influence of polygenic risk on self-reported childhood abuse. Additionally, transcription-neuroimaging association analysis reported 63 risk genes whose expression levels were significantly associated with childhood abuse-related brain volume changes. These genes are involved in multiple biological processes, such as nerve development, synaptic transmission, and cell construction. Combining data from multiple perspectives, our work provides evidence of brain abnormalities associated with childhood abuse, and further indicates that polygene genetic risk and risk gene expression may affect the occurrence of childhood abuse by brain regulation, which provides insights into the molecularpathology and neuromechanism of childhood adversity. Paying attention to the physical and mental health of high-risk children may be a fundamental way to prevent childhood abuse and promote lifelong mental health.
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