1
|
Ellis CA, Miller RL, Calhoun VD. Explainable fuzzy clustering framework reveals divergent default mode network connectivity dynamics in schizophrenia. Front Psychiatry 2024; 15:1165424. [PMID: 38495909 PMCID: PMC10941842 DOI: 10.3389/fpsyt.2024.1165424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 01/30/2024] [Indexed: 03/19/2024] Open
Abstract
Introduction Dynamic functional network connectivity (dFNC) analysis of resting state functional magnetic resonance imaging data has yielded insights into many neurological and neuropsychiatric disorders. A common dFNC analysis approach uses hard clustering methods like k-means clustering to assign samples to states that summarize network dynamics. However, hard clustering methods obscure network dynamics by assuming (1) that all samples within a cluster are equally like their assigned centroids and (2) that samples closer to one another in the data space than to their centroids are well-represented by their centroids. In addition, it can be hard to compare subjects, as in some cases an individual may not manifest a state strongly enough to enter a hard cluster. Approaches that allow a dimensional approach to connectivity patterns (e.g., fuzzy clustering) can mitigate these issues. In this study, we present an explainable fuzzy clustering framework by combining fuzzy c-means clustering with several explainability metrics and novel summary features. Methods We apply our framework for schizophrenia (SZ) default mode network analysis. Namely, we extract dFNC from individuals with SZ and controls, identify 5 dFNC states, and characterize the dFNC features most crucial to those states with a new perturbation-based clustering explainability approach. We then extract several features typically used in hard clustering and further present a variety of unique features specially designed for use with fuzzy clustering to quantify state dynamics. We examine differences in those features between individuals with SZ and controls and further search for relationships between those features and SZ symptom severity. Results Importantly, we find that individuals with SZ spend more time in states of moderate anticorrelation between the anterior and posterior cingulate cortices and strong anticorrelation between the precuneus and anterior cingulate cortex. We further find that individuals with SZ tend to transition more rapidly than controls between low-magnitude and high-magnitude dFNC states. Conclusion We present a novel dFNC analysis framework and use it to identify effects of SZ upon network dynamics. Given the ease of implementing our framework and its enhanced insight into network dynamics, it has great potential for use in future dFNC studies.
Collapse
Affiliation(s)
- Charles A. Ellis
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Robyn L. Miller
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Georgia Institute of Technology, Emory University, Atlanta, GA, United States
- Department of Computer Science, Georgia State University, Atlanta, GA, United States
| | - Vince D. Calhoun
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Georgia Institute of Technology, Emory University, Atlanta, GA, United States
- Department of Computer Science, Georgia State University, Atlanta, GA, United States
| |
Collapse
|
2
|
Liu C, Duan G, Zhang S, Wei Y, Liang L, Geng B, Piao R, Xu K, Li P, Zeng X, Deng D, Liu P. Altered functional connectivity density and structural covariance networks in women with premenstrual syndrome. Quant Imaging Med Surg 2023; 13:835-851. [PMID: 36819237 PMCID: PMC9929399 DOI: 10.21037/qims-22-506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 11/21/2022] [Indexed: 01/05/2023]
Abstract
Background Premenstrual syndrome (PMS) is a menstrual-related disorder, characterized by physical, emotional, behavioral and cognitive symptoms. However, the neuropathological mechanisms of PMS remain unclear. This study aimed to investigate the frequency-specific functional connectivity density (FCD) and structural covariance in PMS. Methods Functional and T1-weighted structural data were obtained from 35 PMS patients and 36 healthy controls (HCs). This study was a cross-sectional and prospective design. The local/long-range FCD (LFCD/LRFCD) across slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands were computed, and two-way analysis of variance (ANOVA) was performed to ascertain the main effects of group and interaction effects between group and frequency band. Receiver operating characteristic (ROC) curve was performed to investigate reliable biomarkers for identifying PMS from HCs. Based on the ROC results, characterized the changes of whole-brain structural covariance patterns of striatum subregions in two groups. Correlation analysis was applied to examine relationships between the clinical symptoms and abnormal brain regions. Results Compared with HCs, PMS patients exhibited: (I) aberrant functional communication in the middle cingulate cortex and precentral gyrus; (II) significant frequency band-by-group interaction effects of the striatum, thalamus and orbitofrontal cortex; (III) the better classification ability of the LFCD in the striatum in ROC analysis (slow-5); (IV) decreased gray matter volumes in the caudate subregions and decreased structural associations of between the caudate subregions and frontal cortex; (V) the LFCD value in thalamus were significantly negatively correlated with the sleep problems (slow-5). Conclusions Based on multi-modal magnetic resonance imaging (MRI) analysis, this study might imply the aberrant emotional regulation and cognitive function related to menstrual cycle in PMS and improve our understanding of the pathophysiologic mechanism in PMS from novel perspective.
Collapse
Affiliation(s)
- Chengxiang Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Gaoxiong Duan
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Shuming Zhang
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Yichen Wei
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Lingyan Liang
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Bowen Geng
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Ruiqing Piao
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Ke Xu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Pengyu Li
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Xiao Zeng
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Demao Deng
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Peng Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| |
Collapse
|
3
|
Lv D, Ou Y, Chen Y, Ding Z, Ma J, Zhan C, Yang R, Shang T, Zhang G, Bai X, Sun Z, Xiao J, Wang X, Guo W, Li P. Anatomical distance affects functional connectivity at rest in medicine-free obsessive-compulsive disorder. BMC Psychiatry 2022; 22:462. [PMID: 36221076 PMCID: PMC9555180 DOI: 10.1186/s12888-022-04103-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 06/27/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Brain functional abnormalities at rest have been observed in obsessive-compulsive disorder (OCD). However, whether and how anatomical distance influences functional connectivity (FC) at rest is ambiguous in OCD. METHODS Using resting-state functional magnetic resonance imaging data, we calculated the FC of each voxel in the whole-brain and divided FC into short- and long-range FCs in 40 medicine-free patients with OCD and 40 healthy controls (HCs). A support vector machine (SVM) was used to determine whether the altered short- and long-range FCs could be utilized to distinguish OCD from HCs. RESULTS Patients had lower short-range positive FC (spFC) and long-range positive FC (lpFC) in the left precentral/postcentral gyrus (t = -5.57 and -5.43; P < 0.05, GRF corrected) and higher lpFC in the right thalamus/caudate, left thalamus, left inferior parietal lobule (IPL) and left cerebellum CrusI/VI (t = 4.59, 4.61, 4.41, and 5.93; P < 0.05, GRF corrected). Furthermore, lower spFC in the left precentral/postcentral gyrus might be used to distinguish OCD from HCs with an accuracy of 80.77%, a specificity of 81.58%, and a sensitivity of 80.00%. CONCLUSION These findings highlight that anatomical distance has an effect on the whole-brain FC patterns at rest in OCD. Meanwhile, lower spFC in the left precentral/postcentral gyrus might be applied in distinguishing OCD from HCs.
Collapse
Affiliation(s)
- Dan Lv
- grid.412613.30000 0004 1808 3289Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Yangpan Ou
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yunhui Chen
- grid.412613.30000 0004 1808 3289Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Zhenning Ding
- grid.412613.30000 0004 1808 3289Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Jidong Ma
- Department of Psychiatry, Baiyupao Psychiatric Hospital of Harbin, Harbin, China
| | - Chuang Zhan
- Department of Psychiatry, Baiyupao Psychiatric Hospital of Harbin, Harbin, China
| | - Ru Yang
- grid.452708.c0000 0004 1803 0208Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Tinghuizi Shang
- grid.412613.30000 0004 1808 3289Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Guangfeng Zhang
- grid.412613.30000 0004 1808 3289Department of Radiology, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, China
| | - Xiaoyu Bai
- grid.454868.30000 0004 1797 8574CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101 China ,grid.410726.60000 0004 1797 8419Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Zhenghai Sun
- grid.412613.30000 0004 1808 3289Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Jian Xiao
- grid.412613.30000 0004 1808 3289Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Xiaoping Wang
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Wenbin Guo
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China.
| |
Collapse
|
4
|
Bouttier V, Duttagupta S, Denève S, Jardri R. Circular inference predicts nonuniform overactivation and dysconnectivity in brain-wide connectomes. Schizophr Res 2022; 245:59-67. [PMID: 33618940 DOI: 10.1016/j.schres.2020.12.045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 12/22/2020] [Accepted: 12/26/2020] [Indexed: 12/17/2022]
Abstract
Schizophrenia is a severe mental disorder whose neural basis remains difficult to ascertain. Among the available pathophysiological theories, recent work has pointed towards subtle perturbations in the excitation-inhibition (E/I) balance within different neural circuits. Computational approaches have suggested interesting mechanisms that can account for both E/I imbalances and psychotic symptoms. Based on hierarchical neural networks propagating information through a message-passing algorithm, it was hypothesized that changes in the E/I ratio could cause a "circular belief propagation" in which bottom-up and top-down information reverberate. This circular inference (CI) was proposed to account for the clinical features of schizophrenia. Under this assumption, this paper examined the impact of CI on network dynamics in light of brain imaging findings related to psychosis. Using brain-inspired graphical models, we show that CI causes overconfidence and overactivation most specifically at the level of connector hubs (e.g., nodes with many connections allowing integration across networks). By also measuring functional connectivity in these graphs, we provide evidence that CI is able to predict specific changes in modularity known to be associated with schizophrenia. Altogether, these findings suggest that the CI framework may facilitate behavioral and neural research on the multifaceted nature of psychosis.
Collapse
Affiliation(s)
- Vincent Bouttier
- Univ Lille, INSERM U1172, CHU Lille, Lille Neurosciences & Cognition Centre (LiNC), Plasticity & SubjectivitY team, 59037 Lille, France; Group for Neural Theory, Laboratoire de Neurosciences Cognitives et Computationnelles (LNC(2)), Ecole Normale Supérieure, INSERM U960, PSL University, 75005 Paris, France.
| | - Suhrit Duttagupta
- Group for Neural Theory, Laboratoire de Neurosciences Cognitives et Computationnelles (LNC(2)), Ecole Normale Supérieure, INSERM U960, PSL University, 75005 Paris, France
| | - Sophie Denève
- Group for Neural Theory, Laboratoire de Neurosciences Cognitives et Computationnelles (LNC(2)), Ecole Normale Supérieure, INSERM U960, PSL University, 75005 Paris, France
| | - Renaud Jardri
- Univ Lille, INSERM U1172, CHU Lille, Lille Neurosciences & Cognition Centre (LiNC), Plasticity & SubjectivitY team, 59037 Lille, France; Group for Neural Theory, Laboratoire de Neurosciences Cognitives et Computationnelles (LNC(2)), Ecole Normale Supérieure, INSERM U960, PSL University, 75005 Paris, France.
| |
Collapse
|
5
|
Rebouças DB, Sartori JM, Librenza-Garcia D, Rabelo-da-Ponte FD, Massuda R, Czepielewski LS, Passos IC, Gama CS. Accelerated aging signatures in subjects with schizophrenia and their unaffected siblings. J Psychiatr Res 2021; 139:30-37. [PMID: 34022473 DOI: 10.1016/j.jpsychires.2021.04.029] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 04/10/2021] [Accepted: 04/25/2021] [Indexed: 01/19/2023]
Abstract
Schizophrenia (SZ) is a chronic debilitating disease. Subjects with SZ have significant shorter life expectancy. Growing evidence suggests that a process of pathological accelerated aging occurs in SZ, leading to early development of severe clinical diseases and worse morbimortality. Furthermore, unaffected relatives can share certain endophenotypes with subjects with SZ. We aim to characterize accelerated aging as a possible endophenotype of schizophrenia by using a machine learning (ML) model of peripheral biomarkers to accurately differentiate subjects with SZ (n = 35), their unaffected siblings (SB, n = 36) and healthy controls (HC, n = 47). We used a random forest algorithm that included biomarkers related to aging: eotaxins CCL-11 and CCL-24; the oxidative stress markers thiobarbituric acid-reactive substances (TBARS), protein carbonyl content (PCC), glutathione peroxidase (GPx); and telomere length (TL). The ML algorithm of biomarkers was able to distinguish individuals with SZ from HC with prediction accuracy of 79.7%, SZ from SB with 62.5% accuracy and SB from HC with 75.5% accuracy. These results support the hypothesis that a pathological accelerated aging might occur in SZ, and this pathological aging could be an endophenotype of the disease, once this profile was also observed in SB, suggesting that SB might suffer from an accelerated aging in some level.
Collapse
Affiliation(s)
- Diego Barreto Rebouças
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Juliana Mastella Sartori
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Diego Librenza-Garcia
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Francisco Diego Rabelo-da-Ponte
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Raffael Massuda
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Departamento de Psiquiatria, Universidade Federal do Paraná, Curitiba, Brazil
| | - Leticia Sanguinetti Czepielewski
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós- Graduação em Psicologia, Departamento de Psicologia do Desenvolvimento e da Personalidade, Instituto de Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Ives Cavalcante Passos
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Clarissa Severino Gama
- Laboratório de Psiquiatria Molecular, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
| |
Collapse
|
6
|
Jiang L, Qiao K, Li C. Distance-based functional criticality in the human brain: intelligence and emotional intelligence. BMC Bioinformatics 2021; 22:32. [PMID: 33499802 PMCID: PMC7836498 DOI: 10.1186/s12859-021-03973-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 01/18/2021] [Indexed: 12/28/2022] Open
Abstract
Background Anatomical distance has been identified as a key factor in the organizational principles of the human brain. On the other hand, criticality was proposed to accommodate the multiscale properties of human brain dynamics, and functional criticality based on resting-state functional magnetic resonance imaging (rfMRI) is a sensitive neuroimaging marker for human brain dynamics. Hence, to explore the effects of anatomical distance of the human brain on behaviors in terms of functional criticality, we proposed a revised algorithm of functional criticality called the distance-based vertex-wise index of functional criticality, and assessed this algorithm compared with the original neighborhood-based functional criticality. Results We recruited two groups of healthy participants, including young adults and middle-aged participants, for a total of 60 datasets including rfMRI and intelligence as well as emotional intelligence to study how human brain functional criticalities at different spatial scales contribute to individual behaviors. Furthermore, we defined the average distance between the particular behavioral map and vertices with significant functional connectivity as connectivity distance. Our results demonstrated that intelligence and emotional intelligence mapped to different brain regions at different ages. Additionally, intelligence was related to a wider distance range compared to emotional intelligence. Conclusions For different age groups, our findings not only provided a linkage between intelligence/emotional intelligence and functional criticality but also quantitatively characterized individual behaviors in terms of anatomical distance.
Collapse
Affiliation(s)
- Lili Jiang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China. .,Lifespan Connectomics and Behavior Team, Institute of Psychology, Chinese Academy of Sciences, Beijing, China. .,Department of Psychology, University of Chinese Academy of Sciences, Shijingshan, Beijing, China. .,Institute of Psychology, Chinese Academy of Sciences, No. 16 Lincui Road, Chaoyang District, Beijing, 100101, China.
| | - Kaini Qiao
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Lifespan Connectomics and Behavior Team, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Shijingshan, Beijing, China
| | - Chunlin Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Lifespan Connectomics and Behavior Team, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Shijingshan, Beijing, China
| |
Collapse
|
7
|
Yang Y, Cui Q, Pang Y, Chen Y, Tang Q, Guo X, Han S, Ameen Fateh A, Lu F, He Z, Huang J, Xie A, Li D, Lei T, Wang Y, Chen H. Frequency-specific alteration of functional connectivity density in bipolar disorder depression. Prog Neuropsychopharmacol Biol Psychiatry 2021; 104:110026. [PMID: 32621959 DOI: 10.1016/j.pnpbp.2020.110026] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 05/31/2020] [Accepted: 06/21/2020] [Indexed: 11/16/2022]
Abstract
Functional dysconnectivity has been widely reported in bipolar disorder during depressive episodes (BDD). However, the frequency-specific alterations of functional connectivity (FC) in BDD remain poorly understood. To address this issue, the FC patterns across slow-5 (0.01-0.027 Hz) and slow-4 (0.027-0.073 Hz) bands were computed using resting-state functional magnetic resonance imaging data from 37 BDD patients and 56 healthy controls (HCs). Short-range (local) FC density (lfcd) and long-range FC density (lrfcd) were calculated, and two-way analysis of variance was performed to ascertain the main effect of diagnosis and interaction effects between diagnosis and frequency. The BDD patients showed increased lfcd in the midline cerebelum. Meanwhile, the BDD patients showed increased lrfcd in the left supplementary motor cortex and right striatum and decreased lrfcd in the bilateral inferior temporal gyrus and left angular gyrus (AG) compared with the HCs. A significant frequency-by-diagnosis interaction was observed. In the slow-4 band, the BDD patients showed increased lfcd in the left pre-/postcentral gyrus and left fusiform gyrus (FG) and increased lrfcd in the left lingual gyrus (LG). In the slow-5 band, the BDD patients showed decreased lrfcd in the left LG. Moreover, the increased lfcd in the left FG in the slow-4 band was correlated with clinical progression and decreased lrfcd in the left AG was correlated with depressive severity. These results suggest that the presence of aberrant communication in the default mode network, sensory network, and subcortical and limbic modulating regions (striatum and midline cerebelum), which may offer a new framework for the understanding of the pathophysiological mechanisms of BDD.
Collapse
Affiliation(s)
- Yang Yang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China.
| | - Yajing Pang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuyan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaonan Guo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Shaoqiang Han
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ahmed Ameen Fateh
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jing Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ailing Xie
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Di Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ting Lei
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Yifeng Wang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China; Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing, China.
| |
Collapse
|
8
|
Cauda F, Mancuso L, Nani A, Ficco L, Premi E, Manuello J, Liloia D, Gelmini G, Duca S, Costa T. Hubs of long-distance co-alteration characterize brain pathology. Hum Brain Mapp 2020; 41:3878-3899. [PMID: 32562581 PMCID: PMC7469792 DOI: 10.1002/hbm.25093] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Revised: 05/06/2020] [Accepted: 05/26/2020] [Indexed: 12/14/2022] Open
Abstract
It is becoming clearer that the impact of brain diseases is more convincingly represented in terms of co-alterations rather than in terms of localization of alterations. In this context, areas characterized by a long mean distance of co-alteration may be considered as hubs with a crucial role in the pathology. We calculated meta-analytic transdiagnostic networks of co-alteration for the gray matter decreases and increases, and we evaluated the mean Euclidean, fiber-length, and topological distance of its nodes. We also examined the proportion of co-alterations between canonical networks, and the transdiagnostic variance of the Euclidean distance. Furthermore, disease-specific analyses were conducted on schizophrenia and Alzheimer's disease. The anterodorsal prefrontal cortices appeared to be a transdiagnostic hub of long-distance co-alterations. Also, the disease-specific analyses showed that long-distance co-alterations are more able than classic meta-analyses to identify areas involved in pathology and symptomatology. Moreover, the distance maps were correlated with the normative connectivity. Our findings substantiate the network degeneration hypothesis in brain pathology. At the same time, they suggest that the concept of co-alteration might be a useful tool for clinical neuroscience.
Collapse
Affiliation(s)
- Franco Cauda
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| | - Lorenzo Mancuso
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| | - Andrea Nani
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| | - Linda Ficco
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| | - Enrico Premi
- Stroke Unit, Azienda Socio‐Sanitaria Territoriale Spedali CiviliSpedali Civili HospitalBresciaItaly
- Centre for Neurodegenerative Disorders, Neurology Unit, Department of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Jordi Manuello
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| | - Donato Liloia
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| | - Gabriele Gelmini
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| | - Sergio Duca
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
| | - Tommaso Costa
- GCS‐fMRI, Koelliker Hospital and Department of PsychologyUniversity of TurinTurinItaly
- FOCUS Lab, Department of PsychologyUniversity of TurinTurinItaly
| |
Collapse
|
9
|
Individualized Diagnostic and Prognostic Models for Patients With Psychosis Risk Syndromes: A Meta-analytic View on the State of the Art. Biol Psychiatry 2020; 88:349-360. [PMID: 32305218 DOI: 10.1016/j.biopsych.2020.02.009] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/25/2020] [Accepted: 02/06/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND The clinical high risk (CHR) paradigm has facilitated research into the underpinnings of help-seeking individuals at risk for developing psychosis, aiming at predicting and possibly preventing transition to the overt disorder. Statistical methods such as machine learning and Cox regression have provided the methodological basis for this research by enabling the construction of diagnostic models (i.e., distinguishing CHR individuals from healthy individuals) and prognostic models (i.e., predicting a future outcome) based on different data modalities, including clinical, neurocognitive, and neurobiological data. However, their translation to clinical practice is still hindered by the high heterogeneity of both CHR populations and methodologies applied. METHODS We systematically reviewed the literature on diagnostic and prognostic models built on Cox regression and machine learning. Furthermore, we conducted a meta-analysis on prediction performances investigating heterogeneity of methodological approaches and data modality. RESULTS A total of 44 articles were included, covering 3707 individuals for prognostic studies and 1052 individuals for diagnostic studies (572 CHR patients and 480 healthy control subjects). CHR patients could be classified against healthy control subjects with 78% sensitivity and 77% specificity. Across prognostic models, sensitivity reached 67% and specificity reached 78%. Machine learning models outperformed those applying Cox regression by 10% sensitivity. There was a publication bias for prognostic studies yet no other moderator effects. CONCLUSIONS Our results may be driven by substantial clinical and methodological heterogeneity currently affecting several aspects of the CHR field and limiting the clinical implementability of the proposed models. We discuss conceptual and methodological harmonization strategies to facilitate more reliable and generalizable models for future clinical practice.
Collapse
|
10
|
Diao Q, Liu J, Zhang X. Enhanced positive functional connectivity strength in left-sided chronic subcortical stroke. Brain Res 2020; 1733:146727. [PMID: 32061738 DOI: 10.1016/j.brainres.2020.146727] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 02/08/2020] [Accepted: 02/13/2020] [Indexed: 01/20/2023]
Abstract
Patients with stroke often exhibit evidence of abnormal functional connectivity (FC). However, whether and how anatomical distance affects FC at rest remains unclear in patients with chronic subcortical stroke. Eighty-six patients with chronic (more than six months post-onset) subcortical stroke (44 left-sided patients and 42 right-sided patients) with different degrees of functional recovery, and 75 matched healthy controls underwent resting-state functional magnetic resonance imaging scanning. Positive functional connectivity strength (FCS) was computed for each voxel in the brain using a data-driven whole-brain resting state FCS method, which was further divided into short- and long-range FCS. Compared with healthy controls, patients with left-sided infarctions exhibited stronger global- and long-range FCS in the left sensorimotor cortex (SMC), and no significant intergroup difference was found for short-range FCS. No significant differences were found between the patients with right-sided infarctions and healthy controls for global, long- and short-range FCS. These findings suggested that the positive FCS alteration was connection-distance dependent within patients with left-sided chronic subcortical stroke. Also, a positive correlation was found between the FCS in the left SMC and the accuracy of the Flanker test, reflecting a compensatory FCS alteration for altered attention and executive function abilities exhibited by those with left-sided stroke.
Collapse
Affiliation(s)
- Qingqing Diao
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jingchun Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xuejun Zhang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.
| |
Collapse
|
11
|
Guo S, He N, Liu Z, Linli Z, Tao H, Palaniyappan L. Brain-Wide Functional Dysconnectivity in Schizophrenia: Parsing Diathesis, Resilience, and the Effects of Clinical Expression. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2020; 65:21-29. [PMID: 31775531 PMCID: PMC6966251 DOI: 10.1177/0706743719890174] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND The functional dysconnectivity observed from functional magnetic resonance imaging (fMRI) studies in schizophrenia is also seen in unaffected siblings indicating its association with the genetic diathesis. We intended to apportion resting-state dysconnectivity into components that represent genetic diathesis, clinical expression or treatment effect, and resilience. METHODS fMRI data were acquired from 28 schizophrenia patients, 28 unaffected siblings, and 60 healthy controls. Based on Dosenbach's atlas, we extracted time series of 160 regions of interest. After constructing functional network, we investigated between-group differences in strength and diversity of functional connectivity and topological properties of undirected graphs. RESULTS Using analysis of variance, we found 88 dysconnectivities. Post hoc t tests revealed that 62.5% were associated with genetic diathesis and 21.6% were associated with clinical expression. Topologically, we observed increased degree, clustering coefficient, and global efficiency in the sibling group compared to both patients and controls. CONCLUSION A large portion of the resting-state functional dysconnectivity seen in patients represents a genetic diathesis effect. The most prominent network-level disruption is the dysconnectivity among nodes of the default mode and salience networks. Despite their predisposition, unaffected siblings show a pattern of resilience in the emergent connectomic topology. Our findings could potentially help refine imaging genetics approaches currently used in the pursuit of the pathophysiology of schizophrenia.
Collapse
Affiliation(s)
- Shuixia Guo
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, People's Republic of China.,Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, People's Republic of China
| | - Ningning He
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, People's Republic of China
| | - Zhening Liu
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Zeqiang Linli
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, People's Republic of China
| | - Haojuan Tao
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Lena Palaniyappan
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada.,Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.,Lawson Health Research Institute, London, Ontario, Canada
| |
Collapse
|
12
|
Makowski C, Lewis JD, Lepage C, Malla AK, Joober R, Lepage M, Evans AC. Structural Associations of Cortical Contrast and Thickness in First Episode Psychosis. Cereb Cortex 2019; 29:5009-5021. [PMID: 30844050 PMCID: PMC6918925 DOI: 10.1093/cercor/bhz040] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 01/22/2019] [Indexed: 01/22/2023] Open
Abstract
There is growing evidence that psychosis is characterized by brain network abnormalities. Analyzing morphological abnormalities with T1-weighted structural MRI may be limited in discovering the extent of deviations in cortical associations. We assess whether structural associations of either cortical white-gray contrast (WGC) or cortical thickness (CT) allow for a better understanding of brain structural relationships in first episode of psychosis (FEP) patients. Principal component and structural covariance analyses were applied to WGC and CT derived from T1-weighted MRI for 116 patients and 88 controls, to explore sets of brain regions that showed group differences, and associations with symptom severity and cognitive ability in patients. We focused on 2 principal components: one encompassed primary somatomotor regions, which showed trend-like group differences in WGC, and the second included heteromodal cortices. Patients' component scores were related to general psychopathology for WGC, but not CT. Structural covariance analyses with WGC revealed group differences in pairwise correlations across widespread brain regions, mirroring areas derived from PCA. More group differences were uncovered with WGC compared with CT. WGC holds potential as a proxy measure of myelin from commonly acquired T1-weighted MRI and may be sensitive in detecting systems-level aberrations in early psychosis, and relationships with clinical/cognitive profiles.
Collapse
Affiliation(s)
- Carolina Makowski
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
- Department of Psychiatry, McGill University, Verdun, Canada
| | - John D Lewis
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| | - Claude Lepage
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| | - Ashok K Malla
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Ridha Joober
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Martin Lepage
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Alan C Evans
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| |
Collapse
|
13
|
Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG. NEUROIMAGE-CLINICAL 2019; 24:101959. [PMID: 31377556 PMCID: PMC6677917 DOI: 10.1016/j.nicl.2019.101959] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 07/12/2019] [Accepted: 07/21/2019] [Indexed: 01/08/2023]
Abstract
Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. In order to extend fMRI functional connectivity findings, the complementary modality of magnetoencephalography (MEG) can be utilized to capture electrophysiological functional connectivity abnormalities in schizophrenia that are not obtainable with fMRI. Therefore, we implemented a multimodal functional connectivity analysis using resting-state 7 Tesla fMRI and MEG data in a sample of first-episode patients with schizophrenia (n = 19) and healthy controls (n = 24). fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state networks was computed and group differences were observed. In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone.
Collapse
|
14
|
Abstract
BACKGROUND This paper aims to synthesise the literature on machine learning (ML) and big data applications for mental health, highlighting current research and applications in practice. METHODS We employed a scoping review methodology to rapidly map the field of ML in mental health. Eight health and information technology research databases were searched for papers covering this domain. Articles were assessed by two reviewers, and data were extracted on the article's mental health application, ML technique, data type, and study results. Articles were then synthesised via narrative review. RESULTS Three hundred papers focusing on the application of ML to mental health were identified. Four main application domains emerged in the literature, including: (i) detection and diagnosis; (ii) prognosis, treatment and support; (iii) public health, and; (iv) research and clinical administration. The most common mental health conditions addressed included depression, schizophrenia, and Alzheimer's disease. ML techniques used included support vector machines, decision trees, neural networks, latent Dirichlet allocation, and clustering. CONCLUSIONS Overall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. With the majority of studies identified focusing on the detection and diagnosis of mental health conditions, it is evident that there is significant room for the application of ML to other areas of psychology and mental health. The challenges of using ML techniques are discussed, as well as opportunities to improve and advance the field.
Collapse
Affiliation(s)
- Adrian B R Shatte
- Federation University, School of Science, Engineering & Information Technology,Melbourne,Australia
| | - Delyse M Hutchinson
- Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health,Geelong,Australia
| | - Samantha J Teague
- Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health,Geelong,Australia
| |
Collapse
|
15
|
Duan J, Xia M, Womer FY, Chang M, Yin Z, Zhou Q, Zhu Y, Liu Z, Jiang X, Wei S, Anthony O'Neill F, He Y, Tang Y, Wang F. Dynamic changes of functional segregation and integration in vulnerability and resilience to schizophrenia. Hum Brain Mapp 2019; 40:2200-2211. [PMID: 30648317 PMCID: PMC6865589 DOI: 10.1002/hbm.24518] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 01/03/2019] [Accepted: 01/07/2019] [Indexed: 01/05/2023] Open
Abstract
Schizophrenia (SZ) is a highly heritable disease with neurodevelopmental origins and significant functional brain network dysfunction. Functional network is heavily influenced by neurodevelopment processes and can be characterized by the degree of segregation and integration. This study examines functional segregation and integration in SZ and their first-degree relatives (high risk [HR]) to better understand the dynamic changes in vulnerability and resiliency, and disease markers. Resting-state functional magnetic resonance imaging data acquired from 137 SZ, 89 HR, and 210 healthy controls (HCs). Small-worldness σ was computed at voxel level to quantify balance between segregation and integration. Interregional functional associations were examined based on Euclidean distance between regions and reflect degree of segregation and integration. Distance strength maps were used to localize regions of altered distance-based functional connectivity. σ was significantly decreased in SZ compared to HC, with no differences in high risk (HR). In three-group comparison, significant differences were noted in short-range connectivity (primarily in the primary sensory, motor and their association cortices, and the thalamus) and medium/long-range connectivity (in the prefrontal cortices [PFCs]). Decreased short- and increased medium/long-range connectivity was found in SZ. Decreased short-range connectivity was seen in SZ and HR, while HR had decreased medium/long-range connectivity. We observed disrupted balance between segregation and integration in SZ, whereas relatively preserved in HR. Similarities and differences between SZ and HR, specific changes of SZ were found. These might reflect dynamic changes of segregation in primary cortices and integration in PFCs in vulnerability and resilience, and disease markers in SZ.
Collapse
Affiliation(s)
- Jia Duan
- Department of PsychiatryThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| | - Mingrui Xia
- National Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and ConnectomicsBeijing Normal UniversityBeijingChina
- IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
| | - Fay Y. Womer
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouri
| | - Miao Chang
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Department of RadiologyThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| | - Zhiyang Yin
- Department of PsychiatryThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| | - Qian Zhou
- Shanghai Mental Health CenterShanghai Jiao Tong University School of Medicine600 Wan Ping Nan RoadShanghaiChina
| | - Yue Zhu
- Department of PsychiatryThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| | - Zhuang Liu
- School of Public HealthChina Medical UniversityShenyangLiaoningChina
| | - Xiaowei Jiang
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Department of RadiologyThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| | - Shengnan Wei
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Department of RadiologyThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| | | | - Yong He
- National Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and ConnectomicsBeijing Normal UniversityBeijingChina
- IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
| | - Yanqing Tang
- Department of PsychiatryThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| | - Fei Wang
- Department of PsychiatryThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Brain Function Research SectionThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
- Department of RadiologyThe First Affiliated Hospital of China Medical UniversityShenyangLiaoningPeople's Republic of China
| |
Collapse
|
16
|
Guo S, Zhao W, Tao H, Liu Z, Palaniyappan L. The instability of functional connectivity in patients with schizophrenia and their siblings: A dynamic connectivity study. Schizophr Res 2018; 195:183-189. [PMID: 29153446 DOI: 10.1016/j.schres.2017.09.035] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 09/10/2017] [Accepted: 09/23/2017] [Indexed: 01/23/2023]
Abstract
BACKGROUND The distributed connectivity among brain regions is in a constant state of flux, even when a subject is at rest. This instability (temporal variability), when optimal, may contribute to efficient cross-network communications. We investigate the role of this variability in the genetic diathesis and symptom expression of schizophrenia. METHODS Resting state functional MRI data acquired from 116 subjects (28 patients with schizophrenia, 28 siblings and 60 matched healthy controls). Using a sliding-window dynamic connectivity approach, we quantified the variability of whole-brain connectivity (dynamic functional connectivity or dFC) of each of the 90 brain regions obtained using a parcellation scheme that covered all contiguous brain regions of the cerebral cortex. RESULTS We noted a high degree of instability anchored on the precuneus in patients with schizophrenia compared to both healthy controls (t=3.60, p=0.0005) and unaffected siblings (t=3.61, p=0.001) indicating a role for dFC of precuneus in the clinical expression of schizophrenia. Compared to patients, siblings also showed an increase in medial orbitofrontal but reduced putaminal instability; these latter changes were not seen in patients when compared to controls, indicating a lack of specificity for diathesis or expression related effects. CONCLUSIONS Instability in the intrinsic connectivity of precuneus, a functional core hub with a major role in task-free self-processing, is likely to be a core substrate of the clinical expression of schizophrenia.
Collapse
Affiliation(s)
- Shuixia Guo
- College of Mathematics and Computer Science, Key Laboratory of High Performance Computing and Stochastic Information Processing (Ministry of Education of China), Hunan Normal University, Changsha, PR China
| | - Wei Zhao
- College of Mathematics and Computer Science, Key Laboratory of High Performance Computing and Stochastic Information Processing (Ministry of Education of China), Hunan Normal University, Changsha, PR China
| | - Haojuan Tao
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Zhening Liu
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China.
| | - Lena Palaniyappan
- Department of Psychiatry, University of Western Ontario, London, Canada; Robarts Research Institute, University of Western Ontario, London, Canada; Lawson Health Research Institute, London, Ontario, Canada; Prevention and Early Intervention Program for Psychoses (PEPP), London Health Sciences Centre, London, Ontario, Canada.
| |
Collapse
|
17
|
Wang S, Zhan Y, Zhang Y, Lyu L, Lyu H, Wang G, Wu R, Zhao J, Guo W. Abnormal long- and short-range functional connectivity in adolescent-onset schizophrenia patients: A resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2018; 81:445-451. [PMID: 28823850 DOI: 10.1016/j.pnpbp.2017.08.012] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 08/02/2017] [Accepted: 08/15/2017] [Indexed: 01/10/2023]
Abstract
BACKGROUND Human brain is a topologically complex network embedded in anatomical space, and anatomical distance may affect functional connectivity (FC) in schizophrenia. However, little is known if and how this effect occurs in adolescent-onset schizophrenia (AOS). METHODS We explored long- and short-range FC through resting-state functional magnetic resonance imaging in 48 first-episode, drug-naive AOS patients and 31 healthy controls, and we examined if these abnormalities could be utilized to separate patients from controls using receiver operating characteristic curves and support vector machines (SVM). RESULTS Patients had increased long-range positive FC (lpFC) and short-range positive FC (spFC) in the right middle frontal gyrus and right superior medial prefrontal cortex within the anterior default mode network (DMN), decreased lpFC and spFC in several regions of the posterior DMN, and decreased lpFC within the important hubs of salience network (SN). The decreased lpFC in the left superior temporal gyrus was positively correlated with cognitive impairment. We found that SVM has high accuracy (up to 92.4%) in classifying patients and control. CONCLUSION Disrupted anatomical distance would underlie network-level dysconnectivity, highlighting the importance of the DMN and SN in the neurodevelopment of schizophrenia. Abnormalities of long- and short-range FC in brain regions could discriminate patients from controls with high accuracy.
Collapse
Affiliation(s)
- Shuai Wang
- Mental Health Institute of the Second Xiangya Hospital, Central South University, National Clinical Research Center on Mental Health Disorders, National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Yajing Zhan
- Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yan Zhang
- Henan Key Laboratory of Biological Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Luxian Lyu
- Henan Key Laboratory of Biological Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Hailong Lyu
- Mental Health Institute of the Second Xiangya Hospital, Central South University, National Clinical Research Center on Mental Health Disorders, National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Guodong Wang
- Mental Health Institute of the Second Xiangya Hospital, Central South University, National Clinical Research Center on Mental Health Disorders, National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Renrong Wu
- Mental Health Institute of the Second Xiangya Hospital, Central South University, National Clinical Research Center on Mental Health Disorders, National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Jingping Zhao
- Mental Health Institute of the Second Xiangya Hospital, Central South University, National Clinical Research Center on Mental Health Disorders, National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China; Henan Key Laboratory of Biological Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
| | - Wenbin Guo
- Mental Health Institute of the Second Xiangya Hospital, Central South University, National Clinical Research Center on Mental Health Disorders, National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.
| |
Collapse
|
18
|
Guo S, Huang CC, Zhao W, Yang AC, Lin CP, Nichols T, Tsai SJ. Combining multi-modality data for searching biomarkers in schizophrenia. PLoS One 2018; 13:e0191202. [PMID: 29389986 PMCID: PMC5794071 DOI: 10.1371/journal.pone.0191202] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Accepted: 12/30/2017] [Indexed: 12/21/2022] Open
Abstract
Identification of imaging biomarkers for schizophrenia is an important but still challenging problem. Even though considerable efforts have been made over the past decades, quantitative alterations between patients and healthy subjects have not yet provided a diagnostic measure with sufficient high sensitivity and specificity. One of the most important reasons is the lack of consistent findings, which is in part due to single-mode study, which only detects single dimensional information by each modality, and thus misses the most crucial differences between groups. Here, we hypothesize that multimodal integration of functional MRI (fMRI), structural MRI (sMRI), and diffusion tensor imaging (DTI) might yield more power for the diagnosis of schizophrenia. A novel multivariate data fusion method for combining these modalities is introduced without reducing the dimension or using the priors from 161 schizophrenia patients and 168 matched healthy controls. The multi-index feature for each ROI is constructed and summarized with Wilk's lambda by performing multivariate analysis of variance to calculate the significant difference between different groups. Our results show that, among these modalities, fMRI has the most significant featureby calculating the Jaccard similarity coefficient (0.7416) and Kappa index (0.4833). Furthermore, fusion of these modalities provides the most plentiful information and the highest predictive accuracy of 86.52%. This work indicates that multimodal integration can improve the ability of distinguishing differences between groups and might be assisting in further diagnosis of schizophrenia.
Collapse
Affiliation(s)
- Shuixia Guo
- College of Mathematics and Computer Science, Key Laboratory of High Performance Computing and Stochastic Information Processing (Ministry of Education of China), Hunan Normal University, Changsha, P. R. China
| | - Chu-Chung Huang
- Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Wei Zhao
- College of Mathematics and Computer Science, Key Laboratory of High Performance Computing and Stochastic Information Processing (Ministry of Education of China), Hunan Normal University, Changsha, P. R. China
| | - Albert C. Yang
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, United States of America
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Ching-Po Lin
- Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
- Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan
| | - Thomas Nichols
- Department of Statistics, University of Warwick, Coventry, United Kingdom
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| |
Collapse
|
19
|
Ouyang M, Kang H, Detre JA, Roberts TPL, Huang H. Short-range connections in the developmental connectome during typical and atypical brain maturation. Neurosci Biobehav Rev 2017; 83:109-122. [PMID: 29024679 DOI: 10.1016/j.neubiorev.2017.10.007] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2017] [Revised: 09/09/2017] [Accepted: 10/06/2017] [Indexed: 01/10/2023]
Abstract
The human brain is remarkably complex with connectivity constituting its basic organizing principle. Although long-range connectivity has been focused on in most research, short-range connectivity is characterized by unique and spatiotemporally heterogeneous dynamics from infancy to adulthood. Alterations in the maturational dynamics of short-range connectivity has been associated with neuropsychiatric disorders, such as autism and schizophrenia. Recent advances in neuroimaging techniques, especially diffusion magnetic resonance imaging (dMRI), resting-state functional MRI (rs-fMRI), electroencephalography (EEG) and magnetoencephalography (MEG), have made quantification of short-range connectivity possible in pediatric populations. This review summarizes findings on the development of short-range functional and structural connections at the macroscale. These findings suggest an inverted U-shaped pattern of maturation from primary to higher-order brain regions, and possible "hyper-" and "hypo-" short-range connections in autism and schizophrenia, respectively. The precisely balanced short- and long-range connections contribute to the integration and segregation of the connectome during development. The mechanistic relationship among short-range connectivity maturation, the developmental connectome and emerging brain functions needs further investigation, including the refinement of methodological approaches.
Collapse
Affiliation(s)
- Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Huiying Kang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - John A Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Timothy P L Roberts
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States.
| |
Collapse
|
20
|
Guo W, Liu F, Chen J, Wu R, Li L, Zhang Z, Chen H, Zhao J. Anatomical distance affects cortical-subcortical connectivity in first-episode, drug-naive somatization disorder. J Affect Disord 2017; 217:153-158. [PMID: 28411503 DOI: 10.1016/j.jad.2017.04.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Revised: 03/30/2017] [Accepted: 04/07/2017] [Indexed: 01/10/2023]
Abstract
BACKGROUND Brain structural and functional alterations in the cortical-subcortical circuits have been observed in somatization disorder (SD). However, whether and how anatomical distance affects the cortical-subcortical connectivity in SD remain unclear. This study aims to examine whether anatomical distance affects the cortical-subcortical in first-episode, drug-naive SD. METHODS Twenty-five first-episode, drug-naive patients with SD and twenty-eight healthy controls were recruited for a resting-state scan. Regional functional connectivity strength (FCS) was calculated for each voxel in the brain, which was further divided into short- and long-range FCSs. Correlation analyses were conducted between abnormal FCS and clinical/cognitive variables in the patients. RESULTS Compared with the controls, the patients showed increased short-range positive FCS (spFCS) in the right superior frontal gyrus (SFG) and decreased spFCS in the left pallidum, and increased long-range positive FCS (lpFCS) in the left middle frontal gyrus and right inferior temporal gyrus (ITG). Positive correlations were observed between the spFCS values in the right SFG and Eysenck Personality Questionnaire psychoticism scores (r=0.441, p=0.027, uncorrected) and between the lpFCS values in the right ITG and scores of digit symbol-coding of Wechsler Adult Intelligence Scale (r=0.416, p=0.039, uncorrected) in the patients CONCLUSIONS: The patients exhibited increased spFCS/lpFCS in the cortical regions and decreased spFCS in the subcortical regions. The left pallidum is first reported here to show decreased spFCS in SD. The present results suggest that abnormal cortical-subcortical circuits may play an important role in SD neurobiology.
Collapse
Affiliation(s)
- Wenbin Guo
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China; National Technology Institute on Mental Disorders, Changsha, Hunan 410011, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China.
| | - Feng Liu
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Jindong Chen
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China; National Technology Institute on Mental Disorders, Changsha, Hunan 410011, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Renrong Wu
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China; National Technology Institute on Mental Disorders, Changsha, Hunan 410011, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Lehua Li
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China; National Technology Institute on Mental Disorders, Changsha, Hunan 410011, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Zhikun Zhang
- Mental Health Center of the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China
| | - Huafu Chen
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Jingping Zhao
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China; National Technology Institute on Mental Disorders, Changsha, Hunan 410011, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China.
| |
Collapse
|
21
|
Guo W, Liu F, Chen J, Wu R, Li L, Zhang Z, Chen H, Zhao J. Using short-range and long-range functional connectivity to identify schizophrenia with a family-based case-control design. Psychiatry Res Neuroimaging 2017; 264:60-67. [PMID: 28463748 DOI: 10.1016/j.pscychresns.2017.04.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Revised: 04/06/2017] [Accepted: 04/22/2017] [Indexed: 01/10/2023]
Abstract
Abnormal short-range and long-range functional connectivities (FCs) have been implicated in the neurophysiology of schizophrenia. This study was conducted to examine the potential of short-range and long-range FCs for differentiating the patients from the controls with a family-based case-control design. Twenty-eight first-episode, drug-naive patients with schizophrenia, 28 unaffected siblings of the patients (family-based controls, FBCs), and 40 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI) scans. The data were analyzed by short-range and long-range FC analyses, receiver operating characteristic curve (ROC) and support vector machine (SVM). Compared with the FBCs/HCs, the patients exhibit increased short-range positive FC strength (spFCS) and/or long-range positive FC strength (lpFCS) in the default-mode network (DMN) and decreased spFCS and lpFCS in the sensorimotor circuits. Furthermore, a combination of the spFCS values in the right superior parietal lobule and the lpFCS values in the left fusiform gyrus/cerebellum VI can differentiate the patients from the FBCs with high sensitivity and specificity. The findings highlight the importance of the DMN and sensorimotor circuits in the pathogenesis of schizophrenia. Combining with family-based case-control design may be a viable option to limit the confounding effects of environmental risk factors in neuroimaging studies of schizophrenia.
Collapse
Affiliation(s)
- Wenbin Guo
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan, China; National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China.
| | - Feng Liu
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Jindong Chen
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan, China; National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China
| | - Renrong Wu
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan, China; National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China
| | - Lehua Li
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan, China; National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China
| | - Zhikun Zhang
- Mental Health Center of the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China
| | - Huafu Chen
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Jingping Zhao
- Department of Psychiatry of the Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan, China; National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China.
| |
Collapse
|
22
|
Shared and Specific Intrinsic Functional Connectivity Patterns in Unmedicated Bipolar Disorder and Major Depressive Disorder. Sci Rep 2017; 7:3570. [PMID: 28620239 PMCID: PMC5472613 DOI: 10.1038/s41598-017-03777-8] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Accepted: 05/04/2017] [Indexed: 01/10/2023] Open
Abstract
Identifying brain differences and similarities between bipolar disorder (BD) and major depressive disorder (MDD) is necessary for increasing our understanding of the pathophysiology and for developing more effective treatments. However, the features of whole-brain intrinsic functional connectivity underlying BD and MDD have not been directly compared. We collected resting-state fMRI data from 48 BD patients, 48 MDD patients, and 51 healthy subjects. We constructed voxel-wise whole-brain functional networks and computed regional functional connectivity strength (FCS) using graph-theory and further divided the regional FCS into long-range FCS (lFCS) and short-range FCS (sFCS). Relative to the controls, both the BD and MDD patients showed decreased sFCS in the bilateral precuneus. In addition, the BD patients showed increased and the MDD patients showed decreased lFCS and sFCS in the bilateral cerebellum. The BD patients also showed increased lFCS in the right middle temporal gyrus and increased sFCS in the bilateral thalamus compared to either the MDD patients or the controls. These findings suggest that BD and MDD may have some shared as well as a greater number of specific impairments in their functional connectivity patterns, providing new evidence for the pathophysiology of BD and MDD at the large-scale whole brain connectivity level.
Collapse
|
23
|
Olanzapine modulation of long- and short-range functional connectivity in the resting brain in a sample of patients with schizophrenia. Eur Neuropsychopharmacol 2017; 27:48-58. [PMID: 27887859 DOI: 10.1016/j.euroneuro.2016.11.002] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Revised: 10/24/2016] [Accepted: 11/08/2016] [Indexed: 01/12/2023]
Abstract
Treatment effects of antipsychotic drugs on cerebral function are seldom examined. Exploring functional connectivity (FC) in drug-free schizophrenia patients before and after antipsychotic treatment can improve the understanding of antipsychotic drug mechanisms. A total of 17 drug-free patients with recurrent schizophrenia and 24 healthy controls underwent resting-state functional magnetic resonance imaging scans. Long- and short-range FC strengths (FCS) were calculated for each participant. Compared with the controls, the patients at baseline exhibited increased long-range positive FCS (lpFCS) in the bilateral inferior parietal lobule (IPL) and decreased lpFCS in the brain regions of the default-mode network (DMN) regions and sensorimotor circuits of the brain. By contrast, increased short-range positive FCS was observed in the right IPL of the patients at baseline compared with the controls. After treatment with olanzapine, increased FC in the DMN and sensorimotor circuits of the brain was noted, whereas decreased FC was observed in the left superior temporal gyrus (STG). Moreover, the alterations of the FCS values and the reductions in symptom severity among the patients after treatment were correlated. The present study provides evidence that olanzapine normalizes the abnormalities of long- and short-range FCs in schizophrenia. FC reductions in the right IPL may be associated with early treatment response, whereas those in the left STG may be related to poor treatment outcome.
Collapse
|
24
|
Guo S, Palaniyappan L, Liddle PF, Feng J. Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study. Psychol Med 2016; 46:2201-2214. [PMID: 27228263 DOI: 10.1017/s0033291716000994] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND A structural neuroanatomical change indicating a reduction in brain tissue is a notable feature of schizophrenia. Several pathophysiological processes such as aberrant cortical maturation, progressive tissue loss and compensatory tissue increase could contribute to the structural changes seen in schizophrenia. METHOD We studied cortical thickness using surface-based morphometry in 98 clinically stable patients with schizophrenia and 83 controls. Using a pattern classification approach, we studied whether the features that discriminate patients from controls vary across the different stages of the illness. Using a covariance analysis, we also investigated if concurrent increases accompany decreases in cortical thickness. RESULTS Very high levels of accuracy (96.3%), specificity (98.8%) and sensitivity (88%) were noted when classifying patients with <2 years of illness from controls. Within the patient group, reduced thickness was consistently accompanied by increased thickness in distributed brain regions. A pattern of cortical amelioration or normalization (i.e. reduced deviation from controls) was noted with increasing illness duration. While temporo-limbic and fronto-parietal regions showed reduced thickness, the occipital cortex showed increased thickness, especially in those with a long-standing illness. CONCLUSION A compensatory remodelling process might contribute to the cortical thickness variations in different stages of schizophrenia. Subtle cerebral reorganization reflecting the inherent plasticity of brain may occur concomitantly with processes contributing to tissue reduction in adult patients with schizophrenia.
Collapse
Affiliation(s)
- S Guo
- Key Laboratory of High Performance Computing and Stochastic Information Processing (Ministry of Education of China),College of Mathematics and Computer Science,Hunan Normal University,Changsha,People's Republic of China
| | - L Palaniyappan
- Division of Psychiatry & Applied Psychology,Centre for Translational Neuroimaging in Mental Health,Institute of Mental Health,University of Nottingham,Nottingham,UK
| | - P F Liddle
- Division of Psychiatry & Applied Psychology,Centre for Translational Neuroimaging in Mental Health,Institute of Mental Health,University of Nottingham,Nottingham,UK
| | - J Feng
- Department of Computer Science,University of Warwick,Coventry,UK
| |
Collapse
|
25
|
Yao Y, Palaniyappan L, Liddle P, Zhang J, Francis S, Feng J. Variability of structurally constrained and unconstrained functional connectivity in schizophrenia. Hum Brain Mapp 2015; 36:4529-38. [PMID: 26274628 PMCID: PMC4843947 DOI: 10.1002/hbm.22932] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2014] [Revised: 07/25/2015] [Accepted: 08/01/2015] [Indexed: 01/05/2023] Open
Abstract
Spatial variation in connectivity is an integral aspect of the brain's architecture. In the absence of this variability, the brain may act as a single homogenous entity without regional specialization. In this study, we investigate the variability in functional links categorized on the basis of the presence of direct structural paths (primary) or indirect paths mediated by one (secondary) or more (tertiary) brain regions ascertained by diffusion tensor imaging. We quantified the variability in functional connectivity using an unbiased estimate of unpredictability (functional connectivity entropy) in a neuropsychiatric disorder where structure‐function relationship is considered to be abnormal; 34 patients with schizophrenia and 32 healthy controls underwent DTI and resting state functional MRI scans. Less than one‐third (27.4% in patients, 27.85% in controls) of functional links between brain regions were regarded as direct primary links on the basis of DTI tractography, while the rest were secondary or tertiary. The most significant changes in the distribution of functional connectivity in schizophrenia occur in indirect tertiary paths with no direct axonal linkage in both early (P = 0.0002, d = 1.46) and late (P = 1 × 10−17, d = 4.66) stages of schizophrenia, and are not altered by the severity of symptoms, suggesting that this is an invariant feature of this illness. Unlike those with early stage illness, patients with chronic illness show some additional reduction in the distribution of connectivity among functional links that have direct structural paths (P = 0.08, d = 0.44). Our findings address a critical gap in the literature linking structure and function in schizophrenia, and demonstrate for the first time that the abnormal state of functional connectivity preferentially affects structurally unconstrained links in schizophrenia. It also raises the question of a continuum of dysconnectivity ranging from less direct (structurally unconstrained) to more direct (structurally constrained) brain pathways underlying the progressive clinical staging and persistence of schizophrenia. Hum Brain Mapp 36:4529–4538, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Ye Yao
- Centre for Computational Systems Biology, Fudan University, Shanghai, People's Republic of China.,School of Mathematical Sciences, Fudan University, Shanghai, People's Republic of China.,Department of Computer Science, University of Warwick, Coventry, United Kingdom
| | - Lena Palaniyappan
- Translational Neuroimaging in Mental Health, Division of Psychiatry & Applied Psychology, Institute of Mental Health, Nottingham, United Kingdom.,Early Intervention in Psychosis, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom
| | - Peter Liddle
- Translational Neuroimaging in Mental Health, Division of Psychiatry & Applied Psychology, Institute of Mental Health, Nottingham, United Kingdom
| | - Jie Zhang
- Centre for Computational Systems Biology, Fudan University, Shanghai, People's Republic of China.,Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, People's Republic of China
| | - Susan Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, United Kingdom
| | - Jianfeng Feng
- Centre for Computational Systems Biology, Fudan University, Shanghai, People's Republic of China.,School of Mathematical Sciences, Fudan University, Shanghai, People's Republic of China.,Department of Computer Science, University of Warwick, Coventry, United Kingdom.,Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, People's Republic of China.,School of Life Sciences and Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, People's Republic of China
| |
Collapse
|
26
|
Guo W, Liu F, Xiao C, Liu J, Yu M, Zhang Z, Zhang J, Zhao J. Increased short-range and long-range functional connectivity in first-episode, medication-naive schizophrenia at rest. Schizophr Res 2015; 166:144-50. [PMID: 25982002 DOI: 10.1016/j.schres.2015.04.034] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2014] [Revised: 03/26/2015] [Accepted: 04/22/2015] [Indexed: 01/10/2023]
Abstract
OBJECTIVE Schizophrenia is conceived as a disconnection syndrome and anatomical distance may affect functional connectivity (FC) in schizophrenia patients. However, whether and how anatomical distance affects FC remains unclear in first-episode, medication-naive schizophrenia at rest. METHODS Forty-nine schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent resting-state functional magnetic resonance imaging scanning. Regional FC strength was computed for each voxel in the brain, which was further divided into short-range and long-range FC strength. RESULTS The patients exhibited increased short-range positive FC strength in the left superior medial frontal gyrus, and increased long-range positive FC strength in the right angular gyrus and bilateral posterior cingulate cortex (PCC)/precuneus compared with the controls. Further seed-based FC analysis showed that the left superior medial frontal gyrus had increased short-range FC with the right inferior frontal gyrus, while the right angular gyrus and bilateral PCC/precuneus had increased long-range FC with the prefrontal gyrus. No significant correlation was observed between abnormal FC strength and clinical variables in the patient group. CONCLUSIONS The findings reveal a pattern of increased anatomical distance affecting FC in the patients, with the results of increased short-range positive FC strength in the anterior default-mode network (DMN) and increased long-range positive FC strength in the posterior DMN in schizophrenia, and highlight the importance of the DMN in the neurobiology of schizophrenia.
Collapse
Affiliation(s)
- Wenbin Guo
- Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan 410011, China.
| | - Feng Liu
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
| | - Changqing Xiao
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Jianrong Liu
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Miaoyu Yu
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Zhikun Zhang
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Jian Zhang
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Jingping Zhao
- Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan 410011, China
| |
Collapse
|
27
|
Wang D, Zhou Y, Zhuo C, Qin W, Zhu J, Liu H, Xu L, Yu C. Altered functional connectivity of the cingulate subregions in schizophrenia. Transl Psychiatry 2015; 5:e575. [PMID: 26035059 PMCID: PMC4490280 DOI: 10.1038/tp.2015.69] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Revised: 03/06/2015] [Accepted: 04/23/2015] [Indexed: 01/21/2023] Open
Abstract
Schizophrenia patients have shown altered resting-state functional connectivity (rsFC) of the cingulate cortex; however, it is unknown whether rsFCs of the cingulate subregions are differentially affected in this disorder. We aimed to clarify the issue by comparing rsFCs of each cingulate subregion between healthy controls and schizophrenia patients. A total of 102 healthy controls and 94 schizophrenia patients underwent resting-state functional magnetic resonance imaging with a sensitivity-encoded spiral-in imaging sequence to reduce susceptibility-induced signal loss and distortion. The cingulate cortex was divided into nine subregions, including the subgenual anterior cingulate cortex (ACC), areas 24 and 32 of the pregenual ACC, areas 24 and 32 of the anterior mid-cingulate cortex (aMCC), posterior MCC (pMCC), dorsal (dPCC) and ventral (vPCC) posterior cingulate cortex (PCC) and retrosplenial cortex (RSC). The rsFCs of each cingulate subregion were compared between the two groups and the atrophy effect was considered. Results with and without global signal regression were reported. Most cingulate subregions exhibited decreased rsFCs in schizophrenia after global signal regression (GSR). Without GSR, only increased rsFC was found in schizophrenia, which primarily restricted to the aMCC, PCC and RSC. Some of these increased rsFCs were also significant after GSR. These findings suggest that GSR can greatly affect between-group differences in rsFCs and the consistently increased rsFCs may challenge the functional disconnection hypothesis of schizophrenia.
Collapse
Affiliation(s)
- D Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Y Zhou
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - C Zhuo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Anding Hospital (Tianjin Mental Health Center), Tianjin, China
- Tianjin Anning Hospital, Tianjin, China
| | - W Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - J Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - H Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - L Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - C Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin 300052, China. E-mail:
| |
Collapse
|
28
|
Local-to-remote cortical connectivity in early- and adulthood-onset schizophrenia. Transl Psychiatry 2015; 5:e566. [PMID: 25966366 PMCID: PMC4471290 DOI: 10.1038/tp.2015.59] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2014] [Revised: 02/12/2015] [Accepted: 02/23/2015] [Indexed: 12/18/2022] Open
Abstract
Schizophrenia is increasingly thought of as a brain network or connectome disorder and is associated with neurodevelopmental processes. Previous studies have suggested the important role of anatomical distance in developing a connectome with optimized performance regarding both the cost and efficiency of information processing. Distance-related disturbances during development have not been investigated in schizophrenia. To test the distance-related miswiring profiles of connectomes in schizophrenia, we acquired resting-state images from 20 adulthood-onset (AOS) and 26 early-onset schizophrenia (EOS) patients, as well as age-matched healthy controls. All patients were drug naive and had experienced their first psychotic episode. A novel threshold-free surface-based analytic framework was developed to examine local-to-remote functional connectivity profiles in both AOS and EOS patients. We observed consistent increases of local connectivity across both EOS and AOS patients in the right superior frontal gyrus, where the connectivity strength was correlated with a positive syndrome score in AOS patients. In contrast, EOS but not AOS patients exhibited reduced local connectivity within the right postcentral gyrus and the left middle occipital cortex. These regions' remote connectivity with their interhemispheric areas and brain network hubs was altered. Diagnosis-age interactions were detectable for both local and remote connectivity profiles. The functional covariance between local and remote homotopic connectivity was present in typically developing controls, but was absent in EOS patients. These findings suggest that a distance-dependent miswiring pattern may be one of the key neurodevelopmental features of the abnormal connectome organization in schizophrenia.
Collapse
|
29
|
Li HJ, Xu Y, Zhang KR, Hoptman MJ, Zuo XN. Homotopic connectivity in drug-naïve, first-episode, early-onset schizophrenia. J Child Psychol Psychiatry 2015; 56:432-43. [PMID: 25130214 PMCID: PMC4333112 DOI: 10.1111/jcpp.12307] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/10/2014] [Indexed: 12/21/2022]
Abstract
BACKGROUND The disconnection hypothesis of schizophrenia has been extensively tested in adults. Recent studies have reported the presence of brain disconnection in younger patients, adding evidence to support the neurodevelopmental hypothesis of schizophrenia. Because of drug confounds in chronic and medicated patients, it has been extremely challenging for researchers to directly investigate abnormalities in the development of connectivity and their role in the pathophysiology of schizophrenia. The present study aimed to examine functional homotopy - a measure of interhemispheric connection - and its relevance to clinical symptoms in first-episode drug-naïve early-onset schizophrenia (EOS) patients. METHODS Resting-state functional magnetic resonance imaging was performed in 26 first-episode drug-naïve EOS patients (age: 14.5 ± 1.94, 13 males) and 25 matched typically developing controls (TDCs) (age: 14.4 ± 2.97, 13 males). We were mainly concerned with the functional connectivity between any pair of symmetric interhemispheric voxels (i.e., functional homotopy) measured by voxel-mirrored homotopic connectivity (VMHC). RESULTS Early-onset schizophrenia patients exhibited both global and regional VMHC reductions in comparison with TDCs. Reduced VMHC values were observed within the superior temporal cortex and postcentral gyrus. These interhemispheric synchronization deficits were negatively correlated with negative symptom of the Positive and Negative Syndrome Scale. Moreover, regions of interest analyses based on left and right clusters of temporal cortex and postcentral gyrus revealed abnormal heterotopic connectivity in EOS patients. CONCLUSIONS Our findings provide novel neurodevelopmental evidence for the disconnection hypothesis of schizophrenia and suggest that these alterations occur early in the course of the disease and are independent of medication status.
Collapse
Affiliation(s)
- Hui-Jie Li
- Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Chinese Academy of Sciences, Beijing, China,Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Yong Xu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Ke-Rang Zhang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Matthew J. Hoptman
- Department of Psychiatry, New York University School of Medicine, New York, USA,Schizophrenia Research Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, USA
| | - Xi-Nian Zuo
- Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Chinese Academy of Sciences, Beijing, China,Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| |
Collapse
|