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Qiu H, Zhang L, Gao Y, Zhou Z, Li H, Cao L, Wang Y, Hu X, Liang K, Tang M, Kuang W, Huang X, Gong Q. Functional connectivity of the default mode network in first-episode drug-naïve patients with major depressive disorder. J Affect Disord 2024; 361:489-496. [PMID: 38901692 DOI: 10.1016/j.jad.2024.06.063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 06/05/2024] [Accepted: 06/17/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND Alterations in the default mode network (DMN) have been reported in major depressive disorder (MDD), well-replicated robust alterations of functional connectivity (FC) of DMN remain to be established. Investigating the functional connections of DMN at the overall and subsystem level in early MDD patients has the potential to advance our understanding of the physiopathology of this disorder. METHODS We recruited 115 first-episode drug-naïve patients with MDD and 137 demographic-matched healthy controls (HCs). We first compared FC within the DMN, within/between the DMN subsystems, and from DMN subsystems to the whole brain between groups. Subsequently, we explored correlations between clinical features and identified alterations in FC. RESULTS First-episode drug-naïve patients with MDD showed significantly increased FC within the DMN, dorsal DMN and medial DMN. Each subsystem showed a distinct FC pattern with other brain networks. Increased FC between the subsystems (core DMN, dorsal DMN) and other networks was associated with more severe depressive symptoms, while medial DMN-related connectivity correlated with memory performance. LIMITATIONS The relatively large "pure" MDD sample could only be generalized to a limited population. And, atypical asymmetric FCs in the DMN related to MDD might be missed for only left-lateralized ROIs were used to avoid strong correlations between mirrored (right/left) seed regions. CONCLUSION These findings suggest patients with early MDD showed distinct patterns of FC alterations throughout DMN and its subsystems, which were related to illness severity and illness-associated cognitive impairment, highlighting their clinical significance.
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Affiliation(s)
- Hui Qiu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Department of Radiology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Lianqing Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yingxue Gao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Zilin Zhou
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Hailong Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Lingxiao Cao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yingying 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, China
| | - Xinyue Hu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Kaili Liang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Mengyue Tang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
| | - 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, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China.
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Feng S, Huang Y, Lu H, Li H, Zhou S, Lu H, Feng Y, Ning Y, Han W, Chang Q, Zhang Z, Liu C, Li J, Wu K, Wu F. Association between degree centrality and neurocognitive impairments in patients with Schizophrenia: A Longitudinal rs-fMRI Study. J Psychiatr Res 2024; 173:115-123. [PMID: 38520845 DOI: 10.1016/j.jpsychires.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 02/27/2024] [Accepted: 03/04/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Evidence indicates that patients with schizophrenia (SZ) experience significant changes in their functional connectivity during antipsychotic treatment. Despite previous reports of changes in brain network degree centrality (DC) in patients with schizophrenia, the relationship between brain DC changes and neurocognitive improvement in patients with SZ after antipsychotic treatment remains elusive. METHODS A total of 74 patients with acute episodes of chronic SZ and 53 age- and sex-matched healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS), Symbol Digit Modalities Test, digital span test (DST), and verbal fluency test were used to evaluate the clinical symptoms and cognitive performance of the patients with SZ. Patients with SZ were treated with antipsychotics for six weeks starting at baseline and underwent MRI and clinical interviews at baseline and after six weeks, respectively. We then divided the patients with SZ into responding (RS) and non-responding (NRS) groups based on the PANSS scores (reduction rate of PANSS ≥50%). DC was calculated and analyzed to determine its correlation with clinical symptoms and cognitive performance. RESULTS After antipsychotic treatment, the patients with SZ showed significant improvements in clinical symptoms, semantic fluency performance. Correlation analysis revealed that the degree of DC increase in the left anterior inferior parietal lobe (aIPL) after treatment was negatively correlated with changes in the excitement score (r = -0.256, p = 0.048, adjusted p = 0.080), but this correlation failed the multiple test correction. Patients with SZ showed a significant negative correlation between DC values in the left aIPL and DST scores after treatment, which was not observed at the baseline (r = -0.359, p = 0.005, adjusted p = 0.047). In addition, we did not find a significant difference in DC between the RS and NRS groups, neither at baseline nor after treatment. CONCLUSIONS The results suggested that DC changes in patients with SZ after antipsychotic treatment are correlated with neurocognitive performance. Our findings provide new insights into the neuropathological mechanisms underlying antipsychotic treatment of SZ.
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Affiliation(s)
- Shixuan Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hongxin Lu
- Department of Psychiatry, Longyan Third Hospital of Fujian Province, Longyan, China
| | - Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sumiao Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hanna Lu
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yangdong Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuping Ning
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
| | - Wei Han
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qing Chang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziyun Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenyu Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhao Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China; National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China; Key Laboratory of Biomedical Engineering of Guangdong Province, South China University of Technology, Guangzhou, China; Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China; Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China.
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Kang Y, Zhang Y, Huang K, Wang Z. Recurrence quantification analysis of periodic dynamics in the default mode network in first-episode drug-naïve schizophrenia. Psychiatry Res Neuroimaging 2023; 329:111583. [PMID: 36577311 DOI: 10.1016/j.pscychresns.2022.111583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/17/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
Abnormal functional connectivity (FC) within the default model network (DMN) in schizophrenia has been frequently reported in previous studies. However, traditional FC analysis was mostly linear correlations based, with the information on nonlinear or temporally lagged brain signals largely overlooked. Fifty-five first-episode drug-naïve schizophrenia (FES) patients and 53 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging scanning. The DMN was extracted using independent component analysis. Recurrence quantification analysis was used to measure the duration, predictability, and complexity of the periodic processes of the nonlinear DMN time series. The Mann‒Whitney U test was conducted to compare these features between FES patients and HCs. The support vector machine was applied to discriminate FES from HCs based on these features. Determinism, which means predictability of periodic process activity, between the ventromedial prefrontal cortex (vMPFC) and posterior cingulate and between the vMPFC and precuneus, was significantly decreased in FES compared with HCs. Determinism between the vMPFC and precuneus was positively correlated with category fluency scores in FES. The classifier achieved 77% accuracy. Our results suggest that synchronized periodicity among DMN brain regions is dysregulated in FES, and the periodicity in BOLD signals may be a promising indicator of brain functional connectivity.
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Affiliation(s)
- Yafei Kang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China
| | - Youming Zhang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Kexin Huang
- West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Zhenhong Wang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China.
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Fan F, Tan S, Huang J, Chen S, Fan H, Wang Z, Li CSR, Tan Y. Functional disconnection between subsystems of the default mode network in schizophrenia. Psychol Med 2022; 52:2270-2280. [PMID: 33183375 DOI: 10.1017/s003329172000416x] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
BACKGROUND A dysfunctional default mode network (DMN) has been reported in patients with schizophrenia. However, the stability of the deficits has not been determined across different stages of the disorder. METHODS We examined the functional connectivity of the DMN subsystems of 125 patients with first-episode schizophrenia (FES) or recurrent schizophrenia (RES), compared to that of 82 healthy controls. We tested the robustness of the findings in an independent cohort of 158 patients and 39 healthy controls. We performed resting-state functional connectivity analysis, and examined the strength of the connections within and between the three subsystems of the DMN (core, dorsal medial prefrontal cortex [dMPFC], and medial temporal lobe [MTL]). We also analyzed the connectivity correlations to symptoms and illness duration. RESULTS We found reduced connectivity strength between the core and MTL subsystems in schizophrenia patients compared to controls, with no differences between the FES and RES patient groups; these findings were validated in the second sample. Schizophrenia patients also showed a significant reduction in connectivity within the MTL and between the dMPFC-MTL subsystems, similarly between FES and RES groups. The connectivity strength within the core subsystem was negatively correlated with clinical symptoms in schizophrenia. There was no significant correlation between the DMN subsystem connectivity and illness duration. CONCLUSIONS DMN subsystem connectivity deficits are present in schizophrenia, and the homochronicity of their appearance indicates the trait-like nature of these alterations. The DMN deficit may be useful for early diagnosis, and MTL dysfunction may be a crucial mechanism underlying schizophrenia.
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Affiliation(s)
- Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
- State Key Laboratory of Cognitive Neuroscience and Learning & International Data Group/McGovern Institute for Brain Research, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Hongzhen Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
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Di Plinio S, Ebisch SJH. Probabilistically Weighted Multilayer Networks disclose the link between default mode network instability and psychosis-like experiences in healthy adults. Neuroimage 2022; 257:119291. [PMID: 35577023 DOI: 10.1016/j.neuroimage.2022.119291] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 05/01/2022] [Accepted: 05/04/2022] [Indexed: 11/30/2022] Open
Abstract
The brain is a complex system in which the functional interactions among its subunits vary over time. The trajectories of this dynamic variation contribute to inter-individual behavioral differences and psychopathologic phenotypes. Despite many methodological advancements, the study of dynamic brain networks still relies on biased assumptions in the temporal domain. The current paper has two goals. First, we present a novel method to study multilayer networks: by modelling intra-nodal connections in a probabilistic, biologically driven way, we introduce a temporal resolution of the multilayer network based on signal similarity across time series. This new method is tested on synthetic networks by varying the number of modules and the sources of noise in the simulation. Secondly, we implement these probabilistically weighted (PW) multilayer networks to study the association between network dynamics and subclinical, psychosis-relevant personality traits in healthy adults. We show that the PW method for multilayer networks outperforms the standard procedure in modular detection and is less affected by increasing noise levels. Additionally, the PW method highlighted associations between the temporal instability of default mode network connections and psychosis-like experiences in healthy adults. PW multilayer networks allow an unbiased study of dynamic brain functioning and its behavioral correlates.
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Affiliation(s)
- Simone Di Plinio
- Department of Neuroscience, Imaging, and Clinical Sciences, G D'Annunzio University of Chieti-Pescara, Chieti, Italy.
| | - Sjoerd J H Ebisch
- Department of Neuroscience, Imaging, and Clinical Sciences, G D'Annunzio University of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies (ITAB), G D'Annunzio University of Chieti-Pescara, Chieti, Italy
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Lin X, Deng J, Dong G, Li S, Wu P, Sun H, Liu L, Shi J, Fan Y, Lu L, Li P. Effects of Chronic Pharmacological Treatment on Functional Brain Network Connectivity in Patients with Schizophrenia. Psychiatry Res 2021; 295:113338. [PMID: 32768152 DOI: 10.1016/j.psychres.2020.113338] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 07/19/2020] [Accepted: 07/26/2020] [Indexed: 12/19/2022]
Abstract
Schizophrenia is characterized by the dysfunction of various brain networks. Previous studies suggested that pharmacological treatments for schizophrenia induce functional changes in localized brain regions. However, the effects of antipsychotic treatments on brain networks associated with symptom improvement are still elusive. The elucidation of antipsychotic-induced functional brain changes is essential for the development of biologically informed treatment strategies. Forty-five healthy controls and 44 patients with schizophrenia underwent resting-state fMRI scans at baseline. The patients underwent a second scan after 6 weeks of antipsychotic treatment. At baseline, patients exhibited a significant decrease in functional connectivity of the cingulate gyrus in the default mode network compared to healthy controls, and this decrease was negatively correlated with symptom severity. Clinical improvements were observed after 6 weeks treatment, accompanied by an increase in functional connectivity of the cingulate gyrus in the default mode network and the inferior parietal lobule in the executive control network. The changes in functional connectivity of the inferior parietal lobule were significantly correlated with symptom improvement. These longitudinal neuroimaging findings suggest that schizophrenia might be an outcome of the disruption of the optimal balance of brain networks, and reestablishing this balance through antipsychotic treatment may result in clinical symptom improvement.
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Affiliation(s)
- Xiao Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jiahui Deng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Guangheng Dong
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, China
| | - Suxia Li
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China
| | - Ping Wu
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China
| | - Hongqiang Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Lin Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China.
| | - Peng Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
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Wang Y, Jiang Y, Su W, Xu L, Wei Y, Tang Y, Zhang T, Tang X, Hu Y, Cui H, Wang J, Yao D, Luo C, Wang J. Temporal Dynamics in Degree Centrality of Brain Functional Connectome in First-Episode Schizophrenia with Different Short-Term Treatment Responses: A Longitudinal Study. Neuropsychiatr Dis Treat 2021; 17:1505-1516. [PMID: 34079256 PMCID: PMC8166279 DOI: 10.2147/ndt.s305117] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 04/14/2021] [Indexed: 11/23/2022] Open
Abstract
PURPOSE This study investigated temporal dynamics in degree centrality (DC) of the brain functional connectome in first-episode schizophrenia with different short-term treatment responses. METHODS A total of 127 first-episode patients (FEPs) with schizophrenia and 133 healthy controls (HCs) were recruited in this study. All subjects underwent resting-state functional magnetic resonance imaging. FEPs were scanned at baseline (pretreatment) and at follow-up (posttreatment), while HCs were scanned only at baseline. The patients were exposed to naturalistic antipsychotic treatment for 12 weeks, and classified as schizophrenia responders (SRs) or nonresponders (NRs). Voxel-wise dynamic DC analyses were conducted among the SRs (n=75), NRs (n=52), and HCs (n=133) to assess temporal variability in functional connectivity across the entire neuronal network. RESULTS The SRs and NRs showed dissimilar dynamic DC at baseline, with differences mainly involving the temporal lobe. Different DC alteration was observed in the left fusiform gyrus, right fusiform gyrus, left middle cingulate cortex, and left superior parietal gyrus in the SRs and NRs pre- and posttreatment. SRs group and NRs presented opposite changing patterns of dynamic DC in particular regions of the brain. CONCLUSION These findings indicate that dynamic DC abnormalities exist in unmedicated patients with schizophrenia. The NRs differed from the SRs in dynamic DC not only at baseline but in the characteristics of changes before and after treatment as well. Our study may contribute to understanding pathophysiology in schizophrenia with different treatment responses.
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Affiliation(s)
- Yingchan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Wenjun Su
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yanyan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Xiaochen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yegang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Huiru Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Jinhong Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, 200031, People's Republic of China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
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Ma C, Tian F, Ma MG, Su HW, Fan JC, Li ZH, Ren YD. Preferentially Disrupted Core Hubs Within the Default-Mode Network in Patients With End-Stage Renal Disease: A Resting-State Functional Magnetic Resonance Imaging Study. Front Neurol 2020; 11:1032. [PMID: 33250836 PMCID: PMC7674924 DOI: 10.3389/fneur.2020.01032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 08/07/2020] [Indexed: 01/25/2023] Open
Abstract
Neuroimaging evidence implies that cognitive impairment in patients with end-stage renal disease (ESRD) is related to the disruption of the default-mode network (DMN). The DMN can be divided into three functionally independent subsystems, which include the cortical hub subsystem [consisting of the posterior cingulate cortex (PCC) and the anterior medial prefrontal cortex (aMPFC)], the dorsal medial prefrontal cortex (dMPFC) subsystem, and the medial temporal lobe (MTL) subsystem. However, it is unknown how the functional connectivity (FC) in DMN subsystems is differentially impaired in ESRD. This prospective study was carried out at the Affiliated Hospital of Qingdao University, China, between August 2018 and July 2020. Thirty-two ESRD patients and forty-five healthy controls (HCs) were recruited for this study and received resting-state functional magnetic resonance imaging (rs-fMRI) scanning, and FCs on predefined regions of interest (ROIs) were individually calculated in three DMN subsystems using both ROI- and seed-based FC analyses to examine FC alterations within and between DMN subsystems. The two-sample t-test was used for the comparisons between groups. We also tested the associations between FC changes and clinical information using Pearson's correlation analysis. The results demonstrated that ESRD patients, compared with HCs, exhibit reduced FC specifically within the cortical hubs and between the DMN hubs and two subsystems (the dMPFC and MTL subsystems). Moreover, the FC values between the aMPFC and PCC were positively correlated with creatinine and urea levels in the ESRD patients. Our results suggest that the cortical hubs (PCC and aMPFC) are preferentially disrupted and that other subsystems may be progressively damaged to a certain degree as the disease develops.
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Affiliation(s)
- Chi Ma
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Fen Tian
- Department of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Min-Ge Ma
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hua-Wei Su
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jian-Cong Fan
- College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China
| | - Zhan-Hui Li
- College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China
| | - Yan-de Ren
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
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Yao G, Li J, Liu S, Wang J, Cao X, Li X, Cheng L, Chen H, Xu Y. Alterations of Functional Connectivity in Stroke Patients With Basal Ganglia Damage and Cognitive Impairment. Front Neurol 2020; 11:980. [PMID: 33013648 PMCID: PMC7511868 DOI: 10.3389/fneur.2020.00980] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 07/28/2020] [Indexed: 01/01/2023] Open
Abstract
Background: Stroke with basal ganglia damage (SBG) is a neurological disorder characterized by cognitive impairment. The neurobiological mechanism of cognitive impairment in stroke patients with basal ganglia damage (SBG patients) remains unclear. This study aimed to explore the underlying neurobiological mechanism of cognitive impairment in SBG patients using resting-state functional magnetic resonance imaging (rs-fMRI). Methods: The differences in functional connectivity (FC) between 14 SBG patients (average age: 61.00 ± 7.45 years) and 21 healthy controls (HC) (average age: 60.67 ± 6.95 years) were examined using voxel-mirrored homotopic connectivity (VMHC) and degree centrality (DC). Moreover, we compared the cognitive functions of SBG patients with HC using the Chinese Revised Wechsler Adult Intelligence Scale (WAIS-RC) and Wechsler Memory Scale (WMS). Results: Full-scale intelligence quotient (FIQ) (t = 2.810, p < 0.010) and memory quotient (MQ) (t = 2.920, p < 0.010) scores of SBG patients were significantly lower than those of HC. Compared with HC, significantly decreased VMHC values in the bilateral angular gyrus, supramarginal gyrus, inferior frontal gyrus, middle temporal gyrus, hippocampus, precuneus, precentral gyrus, and middle occipital gyrus and decreased DC values in the right supramarginal gyrus, bilateral angular gyrus, and right postcentral gyrus were observed in SBG patients. Moreover, the VMHC values in the angular gyrus, inferior frontal gyrus, supramarginal gyrus, and middle temporal gyrus and the DC values in the right supramarginal gyrus were significantly correlated with cognitive functions in all participants. Conclusion: Our findings may provide a neural basis for cognitive impairments in SBG patients. Furthermore, local abnormalities of functional networks and interhemispheric interaction deficits may provide new ideas and insights for understanding and treating SBG patients' cognitive impairments.
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Affiliation(s)
- Guanqun Yao
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Jing Li
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China.,Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Sha Liu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China.,Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jiaojian Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Xiaohua Cao
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Xinrong Li
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Long Cheng
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China.,Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,MDT Center for Cognitive Impairment and Sleep Disorders, First Hospital of Shanxi Medical University, Taiyuan, China
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