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Wang H, Zhan X, Xu J, Yu M, Guo Z, Zhou G, Ren J, Zhang R, Liu W. Disrupted topologic efficiency of brain functional connectome in de novo Parkinson's disease with depression. Eur J Neurosci 2023; 58:4371-4383. [PMID: 37857484 DOI: 10.1111/ejn.16176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 09/23/2023] [Accepted: 10/05/2023] [Indexed: 10/21/2023]
Abstract
Growing evidence supports that depression in Parkinson's disease (PD) depends on disruptions in specific neural networks rather than regional dysfunction. According to the resting-state functional magnetic resonance imaging data, the study attempted to decipher the alterations in the topological properties of brain networks in de novo depression in PD (DPD). The study also explored the neural network basis for depressive symptoms in PD. We recruited 20 DPD, 37 non-depressed PD and 41 healthy controls (HC). The Graph theory and network-based statistical methods helped analyse the topological properties of brain functional networks and anomalous subnetworks across these groups. The relationship between altered properties and depression severity was also investigated. DPD revealed significantly reduced nodal efficiency in the left superior temporal gyrus. Additionally, DPD decreased five hubs, primarily located in the temporal-occipital cortex, and increased seven hubs, mainly distributed in the limbic cortico-basal ganglia circuit. The betweenness centrality of the left Medio Ventral Occipital Cortex was positively associated with depressive scores in DPD. In contrast to HC, DPD had a multi-connected subnetwork with significantly lower connectivity, primarily distributed in the visual, somatomotor, dorsal attention and default networks. Regional topological disruptions in the temporal-occipital region are critical in the DPD neurological mechanism. It might suggest a potential network biomarker among newly diagnosed DPD patients.
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Affiliation(s)
- Hui Wang
- Department of Neurology, Lianyungang Hospital of Traditional Chinese Medicine, Lianyungang Affiliated Hospital of Nanjing University of Chinese Medicine, Lianyungang, China
| | - Xiaoyan Zhan
- Department of Clinical Laboratory, Jiangsu Province Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Jianxia Xu
- Department of Neurology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, China
| | - Miao Yu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zhiying Guo
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Gaiyan Zhou
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jingru Ren
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Ronggui Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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Li X, Huang Y, Liu M, Zhang M, Liu Y, Teng T, Liu X, Yu Y, Jiang Y, Ouyang X, Xu M, Lv F, Long Y, Zhou X. Childhood trauma is linked to abnormal static-dynamic brain topology in adolescents with major depressive disorder. Int J Clin Health Psychol 2023; 23:100401. [PMID: 37584055 PMCID: PMC10423886 DOI: 10.1016/j.ijchp.2023.100401] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 07/24/2023] [Indexed: 08/17/2023] Open
Abstract
Childhood trauma is a leading risk factor for adolescents developing major depressive disorder (MDD); however, the underlying neuroimaging mechanisms remain unclear. This study aimed to investigate the association among childhood trauma, MDD and brain dysfunctions by combining static and dynamic brain network models. We recruited 46 first-episode drug-naïve adolescent MDD patients with childhood trauma (MDD-CT), 53 MDD patients without childhood trauma (MDD-nCT), and 90 healthy controls (HCs) for resting-state functional magnetic resonance imaging (fMRI) scans; all participants were aged 13-18 years. Compared to the HCs and MDD-nCT groups, the MDD-CT group exhibited significantly higher global and local efficiency in static brain networks and significantly higher temporal correlation coefficients in dynamic brain network models at the whole-brain level, and altered the local efficiency of default mode network (DMN) and temporal correlation coefficients of DMN, salience (SAN), and attention (ATN) networks at the local perspective. Correlation analysis indicated that altered brain network features and clinical symptoms, childhood trauma, and particularly emotional neglect were highly correlated in adolescents with MDD. This study may provide new evidence for the dysconnectivity hypothesis regarding the associations between childhood trauma and MDD in adolescents from the perspectives of both static and dynamic brain topology.
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Affiliation(s)
- Xuemei Li
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yang Huang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Mengqi Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Manqi Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yang Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Teng Teng
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xueer Liu
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ying Yu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuanliang Jiang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xuan Ouyang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ming Xu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Fajin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yicheng Long
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xinyu Zhou
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Wang H, Xu J, Yu M, Ma X, Li Y, Pan C, Ren J, Liu W. Altered functional connectivity of ventral striatum subregions in de-novo parkinson’s disease with depression. Neuroscience 2022; 491:13-22. [DOI: 10.1016/j.neuroscience.2022.03.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 10/18/2022]
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Yun JY, Kim YK. Graph theory approach for the structural-functional brain connectome of depression. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110401. [PMID: 34265367 DOI: 10.1016/j.pnpbp.2021.110401] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 06/30/2021] [Accepted: 07/07/2021] [Indexed: 01/22/2023]
Abstract
To decipher the organizational styles of neural underpinning in major depressive disorder (MDD), the current article reviewed recent neuroimaging studies (published during 2015-2020) that applied graph theory approach to the diffusion tensor imaging data or functional brain activation data acquired during task-free resting state. The global network organization of resting-state functional connectivity network in MDD were diverse according to the onset age and medication status. Intra-modular functional connections were weaker in MDD compared to healthy controls (HC) for default mode and limbic networks. Weaker local graph metrics of default mode, frontoparietal, and salience network components in MDD compared to HC were also found. On the contrary, brain regions comprising the limbic, sensorimotor, and subcortical networks showed higher local graph metrics in MDD compared to HC. For the brain white matter-based structural connectivity network, the global network organization was comparable to HC in adult MDD but was attenuated in late-life depression. Local graph metrics of limbic, salience, default-mode, subcortical, insular, and frontoparietal network components in structural connectome were affected from the severity of depressive symptoms, burden of perceived stress, and treatment effects. Collectively, the current review illustrated changed global network organization of structural and functional brain connectomes in MDD compared to HC and were varied according to the onset age and medication status. Intra-modular functional connectivity within the default mode and limbic networks were weaker in MDD compared to HC. Local graph metrics of structural connectome for MDD reflected severity of depressive symptom and perceived stress, and were also changed after treatments. Further studies that explore the graph metrics-based neural correlates of clinical features, cognitive styles, treatment response and prognosis in MDD are required.
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Affiliation(s)
- Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea; Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Yong-Ku Kim
- Department of Psychiatry, College of Medicine, Korea University, Seoul, South Korea
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Xu SX, Deng WF, Qu YY, Lai WT, Huang TY, Rong H, Xie XH. The integrated understanding of structural and functional connectomes in depression: A multimodal meta-analysis of graph metrics. J Affect Disord 2021; 295:759-770. [PMID: 34517250 DOI: 10.1016/j.jad.2021.08.120] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 07/26/2021] [Accepted: 08/28/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND From the perspective of information processing, an integrated understanding of the structural and functional connectomes in depression patients is important, a multimodal meta-analysis is required to detect the robust alterations in graph metrics across studies. METHODS Following a systematic search, 952 depression patients and 1447 controls in nine diffusion magnetic resonance imaging (dMRI) and twelve rest state functional MRI (rs-fMRI) studies with high methodological quality met the inclusion criteria and were included in the meta-analysis. RESULTS Regarding the dMRI results, no significant differences of meta-analytic metrics were found; regarding the rs-fMRI results, the modularity and local efficiency were found to be significantly lower in the depression group than in the controls (Hedge's g = -0.330 and -0.349, respectively). CONCLUSION Our findings suggested a lower modularity and network efficiency in the rs-fMRI network in depression patients, indicating that the pathological imbalances in brain connectomes needs further exploration. LIMITATIONS Included number of trials was low and heterogeneity should be noted.
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Affiliation(s)
- Shu-Xian Xu
- Brain Function and Psychosomatic Medicine Institute, Second People's Hospital of Huizhou, Huizhou, Guangdong, China; Department of Psychiatry, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China; Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wen-Feng Deng
- Huizhou Center for Disease Control and Prevention, Huizhou, Guangdong, China
| | - Ying-Ying Qu
- Center of Acute Psychiatry Service, Second People's Hospital of Huizhou, Huizhou, Guangdong, China
| | - Wen-Tao Lai
- Department of Radiology, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China
| | - Tan-Yu Huang
- Department of Radiology, Second People's Hospital of Huizhou, Huizhou, Guangdong, China
| | - Han Rong
- Department of Psychiatry, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China; Affiliated Shenzhen Clinical College of Psychiatry, Jining Medical University, Jining, Shandong, China
| | - Xin-Hui Xie
- Brain Function and Psychosomatic Medicine Institute, Second People's Hospital of Huizhou, Huizhou, Guangdong, China; Department of Psychiatry, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China; Center of Acute Psychiatry Service, Second People's Hospital of Huizhou, Huizhou, Guangdong, China.
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Disrupted intrinsic functional brain topology in patients with major depressive disorder. Mol Psychiatry 2021; 26:7363-7371. [PMID: 34385597 PMCID: PMC8873016 DOI: 10.1038/s41380-021-01247-2] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 07/15/2021] [Accepted: 07/23/2021] [Indexed: 02/06/2023]
Abstract
Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.
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Alonso Martínez S, Deco G, Ter Horst GJ, Cabral J. The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample. Front Neural Circuits 2020; 14:570583. [PMID: 33071760 PMCID: PMC7530893 DOI: 10.3389/fncir.2020.570583] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 08/26/2020] [Indexed: 12/17/2022] Open
Abstract
Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.
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Affiliation(s)
- Sonsoles Alonso Martínez
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Gert J Ter Horst
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Joana Cabral
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Center for Music in the Brain, Aarhus University, Aarhus, Denmark.,Life and Health Sciences Research Institute (ICVS), University of Minho, Minho, Portugal
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Gao X, Xiao Y, Lv P, Zhang W, Gong Y, Wang T, Gong Q, Ji Y, Lui S. Altered brain network integrity in patients with asthma: A structural connectomic diffusion tensor imaging study. Respir Physiol Neurobiol 2019; 266:89-94. [PMID: 31085322 DOI: 10.1016/j.resp.2019.05.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 05/05/2019] [Accepted: 05/06/2019] [Indexed: 02/05/2023]
Abstract
Brain functional deficits had been reported in asthma patients. These deficits may be related to treatment resistance, inaccurate self-assessment and poor self-management. However, changes of the structural brain network in asthma patients remain largely unclear. Diffusion tensor imaging were acquired from 54 asthmatic patients and 44 controls. Then we calculated all the participants' structural network metrics. All the participants underwent the test of Hamilton Rating Scale for Depression and Anxiety as well as a lung function. Multiple linear correlation analyses were conducted. At the global level, asthma patients had a higher path length and lower global efficiency than controls, implying a shift toward regular networks. At the local level, asthma patients exhibited abnormal nodal connectivity with other nodes involved the fronto-limbic regions. Our findings highlight more locally segregated but less efficiently integrated structural networks, particularly involving frontal-limbic networks, in asthmatic patients. These findings provide important evidence to support the role of brain networks in the pathophysiology of asthma.
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Affiliation(s)
- Xin Gao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China; Department of Radiology, People's Hospital of Deyang City, Deyang, China
| | - Yuan Xiao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Peilin Lv
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yao Gong
- The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Ting Wang
- Department of Respiratory Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yulin Ji
- Department of Respiratory Medicine, West China Hospital, Sichuan University, Chengdu, China.
| | - Su Lui
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
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Walter M, Alizadeh S, Jamalabadi H, Lueken U, Dannlowski U, Walter H, Olbrich S, Colic L, Kambeitz J, Koutsouleris N, Hahn T, Dwyer DB. Translational machine learning for psychiatric neuroimaging. Prog Neuropsychopharmacol Biol Psychiatry 2019; 91:113-121. [PMID: 30290208 DOI: 10.1016/j.pnpbp.2018.09.014] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 09/14/2018] [Accepted: 09/30/2018] [Indexed: 11/19/2022]
Abstract
Despite its initial promise, neuroimaging has not been widely translated into clinical psychiatry to assist in the prediction of diagnoses, prognoses, and optimal therapeutic strategies. Machine learning approaches may enhance the translational potential of neuroimaging because they specifically focus on overcoming biases by optimizing the generalizability of pipelines that measure complex brain patterns to predict targets at a single-subject level. This article introduces some fundamentals of a translational machine learning approach before selectively reviewing literature to-date. Promising initial results are then balanced by the description of limitations that should be considered in order to interpret existing research and maximize the possibility of future translation. Future directions are then presented in order to inspire further research and progress the field towards clinical translation.
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Affiliation(s)
- Martin Walter
- Department of Psychiatry and Psychotherapy, Eberhard Karls University Tuebingen, Germany.
| | - Sarah Alizadeh
- Department of Psychiatry and Psychotherapy, Eberhard Karls University Tuebingen, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, Eberhard Karls University Tuebingen, Germany
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Udo Dannlowski
- Department of Psychiatry, University of Muenster, Muenster, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Sebastian Olbrich
- Department for Psychiatry, Psychotherapy and Psychosomatic Medicine, Zürich, Switzerland
| | - Lejla Colic
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Germany
| | | | - Tim Hahn
- Department of Psychiatry, University of Muenster, Muenster, Germany
| | - Dominic B Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Germany
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Chen H, Liu K, Zhang B, Zhang J, Xue X, Lin Y, Zou D, Chen M, Kong Y, Wen G, Yan J, Deng Y. More optimal but less regulated dorsal and ventral visual networks in patients with major depressive disorder. J Psychiatr Res 2019; 110:172-178. [PMID: 30654314 DOI: 10.1016/j.jpsychires.2019.01.005] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 12/24/2018] [Accepted: 01/04/2019] [Indexed: 01/25/2023]
Abstract
Previous studies indicate that major depressive disorder (MDD) can profoundly modify the visual cortices as well as the visuo-attentional systems of brain. However, little is known on the specific pattern of the whole-network-level abnormalities. In this study, resting-state functional magnetic resonance imaging data were collected from 159 participants, including 86 medication-free MDD patients and 73 matched healthy controls. The dorsal/ventral visual networks were defined based on our previously published brain coordinates from activation likelihood estimation analyses. The static and dynamic network properties were respectively calculated and compared between MDD and control groups. Moreover, the inter-network connectivities quantified using the multivariate distance correlation between the dorsal attention network (DAN) and the two visual networks were also analyzed. Results indicated that both of the two visual networks in MDD were found with significantly increased clustering coefficient (dorsal: p = 0.002; ventral: p = 0.004) and higher small-worldness (dorsal: p = 0.001; ventral: p = 0.002) as compared with control group. A higher mean variability of dynamic functional connectivity was found in both two networks in MDDs (dorsal: p < 0.001; ventral: p = 0.001). Moreover, the two visual networks in MDD group showed decreased inter-network connectivities to DAN (dorsal: p = 0.004; ventral: p = 0.013). Taken together, these results may support that the ventral and dorsal visual systems under the pathological effect of depression are possibly characterized by a status of increased autonomy, i.e., a more optimal, economical, and efficient intra-network organization combining with increased independency and receiving less outside regulation from attention network, thus indicating the increased functional role of the brain visual systems in MDD.
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Affiliation(s)
- Hui Chen
- Medical Imaging Department, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kai Liu
- Medical Imaging Department, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Bin Zhang
- Department of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jingyu Zhang
- Medical Imaging Department, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xiang Xue
- Department of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yong Lin
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, China
| | - Danfeng Zou
- Overseas Patient Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Menglin Chen
- Medical Imaging Department, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Youyong Kong
- Lab of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Ge Wen
- Medical Imaging Department, Nanfang Hospital, Southern Medical University, Guangzhou, China.
| | - Jingdong Yan
- Information Department, Nanfang Hospital, Southern Medical University, Guangzhou, China.
| | - Yanjia Deng
- Medical Imaging Department, Nanfang Hospital, Southern Medical University, Guangzhou, China.
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Suo X, Lei D, Li L, Li W, Dai J, Wang S, He M, Zhu H, Kemp GJ, Gong Q. Psychoradiological patterns of small-world properties and a systematic review of connectome studies of patients with 6 major psychiatric disorders. J Psychiatry Neurosci 2018; 43:427. [PMID: 30375837 PMCID: PMC6203546 DOI: 10.1503/jpn.170214] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Revised: 01/07/2018] [Accepted: 01/28/2018] [Indexed: 02/05/2023] Open
Abstract
Background Brain connectome research based on graph theoretical analysis shows that small-world topological properties play an important role in the structural and functional alterations observed in patients with psychiatric disorders. However, the reported global topological alterations in small-world properties are controversial, are not consistently conceptualized according to agreed-upon criteria, and are not critically examined for consistent alterations in patients with each major psychiatric disorder. Methods Based on a comprehensive PubMed search, we systematically reviewed studies using noninvasive neuroimaging data and graph theoretical approaches for 6 major psychiatric disorders: schizophrenia, major depressive disorder (MDD), attention-deficit/hyperactivity disorder (ADHD), bipolar disorder (BD), obsessive–compulsive disorder (OCD) and posttraumatic stress disorder (PTSD). Here, we describe the main patterns of altered small-world properties and then systematically review the evidence for these alterations in the structural and functional connectome in patients with these disorders. Results We selected 40 studies of schizophrenia, 33 studies of MDD, 5 studies of ADHD, 5 studies of BD, 7 studies of OCD and 5 studies of PTSD. The following 4 patterns of altered small-world properties are defined from theperspectives of segregation and integration: "regularization," "randomization," "stronger small-worldization" and "weaker small-worldization." Although more differences than similarities are noted in patients with these disorders, a prominent trend is the structural regularization versus functional randomization in patients with schizophrenia. Limitations Differences in demographic and clinical characteristics, preprocessing steps and analytical methods can produce contradictory results, increasing the difficulty of integrating results across different studies. Conclusion Four psychoradiological patterns of altered small-world properties are proposed. The analysis of altered smallworld properties may provide novel insights into the pathophysiological mechanisms underlying psychiatric disorders from a connectomic perspective. In future connectome studies, the global network measures of both segregation and integration should be calculated to fully evaluate altered small-world properties in patients with a particular disease.
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Affiliation(s)
- Xueling Suo
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Du Lei
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Lei Li
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Wenbin Li
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Jing Dai
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Song Wang
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Manxi He
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Hongyan Zhu
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Graham J. Kemp
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
| | - Qiyong Gong
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041 China (Suo, Lei, Li, Gong); the Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK (Lei); the Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, Sichuan, China (Dai, Wang, He); the Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Zhu); the Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK (Kemp); and the Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China (Gong)
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12
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Shaffer JJ, Johnson CP, Fiedorowicz JG, Christensen GE, Wemmie JA, Magnotta VA. Impaired sensory processing measured by functional MRI in Bipolar disorder manic and depressed mood states. Brain Imaging Behav 2018; 12:837-847. [PMID: 28674759 PMCID: PMC5752628 DOI: 10.1007/s11682-017-9741-8] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Bipolar disorder is characterized by recurring episodes of depression and mania. Defining differences in brain function during these states is an important goal of bipolar disorder research. However, few imaging studies have directly compared brain activity between bipolar mood states. Herein, we compare functional magnetic resonance imaging (fMRI) responses during a flashing checkerboard stimulus between bipolar participants across mood states (euthymia, depression, and mania) in order to identify functional differences between these states. 40 participants with bipolar I disorder and 33 healthy controls underwent fMRI during the presentation of the stimulus. A total of 23 euthymic-state, 16 manic-state, 15 depressed-state, and 32 healthy control imaging sessions were analyzed in order to compare functional activation during the stimulus between mood states and with healthy controls. A reduced response was identified in the visual cortex in both the depressed and manic groups compared to euthymic and healthy participants. Functional differences between bipolar mood states were also observed in the cerebellum, thalamus, striatum, and hippocampus. Functional differences between mood states occurred in several brain regions involved in visual and other sensory processing. These differences suggest that altered visual processing may be a feature of mood states in bipolar disorder. The key limitations of this study are modest mood-state group size and the limited temporal resolution of fMRI which prevents the segregation of primary visual activity from regulatory feedback mechanisms.
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Affiliation(s)
- Joseph J Shaffer
- Department of Radiology, University of Iowa, Iowa City, IA, USA.
- , PBDB L420, 169 Newton Rd., Iowa City, IA, 52242, USA.
| | - Casey P Johnson
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - Jess G Fiedorowicz
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
- Department of Epidemiology, University of Iowa, Iowa City, IA, USA
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
- Abboud Cardiovascular Research Center, University of Iowa, Iowa City, IA, USA
| | - Gary E Christensen
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John A Wemmie
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
- Department of Veterans Affairs Medical Center, Iowa City, IA, USA
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
- Department of Neurosurgery, University of Iowa, Iowa City, IA, USA
- Pappajohn Biomedical Institute, University of Iowa, Iowa City, IA, USA
| | - Vincent A Magnotta
- Department of Radiology, University of Iowa, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
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13
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Borgsted C, Ozenne B, Mc Mahon B, Madsen MK, Hjordt LV, Hageman I, Baaré WFC, Knudsen GM, Fisher PM. Amygdala response to emotional faces in seasonal affective disorder. J Affect Disord 2018; 229:288-295. [PMID: 29329062 DOI: 10.1016/j.jad.2017.12.097] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 11/29/2017] [Accepted: 12/31/2017] [Indexed: 12/28/2022]
Abstract
BACKGROUND Seasonal affective disorder (SAD) is characterized by seasonally recurring depression. Heightened amygdala activation to aversive stimuli is associated with major depressive disorder but its relation to SAD is unclear. We evaluated seasonal variation in amygdala activation in SAD and healthy controls (HC) using a longitudinal design targeting the asymptomatic/symptomatic phases of SAD. We hypothesized increased amygdala activation to aversive stimuli in the winter in SAD individuals (season-by-group interaction). METHODS Seventeen SAD individuals and 15 HCs completed an implicit emotional faces BOLD-fMRI paradigm during summer and winter. We computed amygdala activation (SPM5) to an aversive contrast (angry & fearful minus neutral) and angry, fearful and neutral faces, separately. Season-by-group and main effects were evaluated using Generalized Least Squares. In SAD individuals, we correlated change in symptom severity, assessed with The Hamilton Rating Scale for Depression - Seasonal Affective Disorder version (SIGH-SAD), with change in amygdala activation. RESULTS We found no season-by-group, season or group effect on our aversive contrast. Independent of season, SAD individuals showed significantly lower amygdala activation to all faces compared to healthy controls, with no evidence for a season-by-group interaction. Seasonal change in amygdala activation was unrelated to change in SIGH-SAD. LIMITATIONS Small sample size, lack of positive valence stimuli. CONCLUSIONS Amygdala activation to aversive faces is not increased in symptomatic SAD individuals. Instead, we observed decreased amygdala activation across faces, independent of season. Our findings suggest that amygdala activation to angry, fearful and neutral faces is altered in SAD individuals, independent of the presence of depressive symptoms.
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Affiliation(s)
- Camilla Borgsted
- Neurobiology Research Unit, Rigshospitalet and Center for Integrated Molecular Brain Imaging, Section 6931, Blegdamsvej 9, 2100 Copenhagen, Denmark
| | - Brice Ozenne
- Neurobiology Research Unit, Rigshospitalet and Center for Integrated Molecular Brain Imaging, Section 6931, Blegdamsvej 9, 2100 Copenhagen, Denmark; Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, 1014 Copenhagen, Denmark
| | - Brenda Mc Mahon
- Neurobiology Research Unit, Rigshospitalet and Center for Integrated Molecular Brain Imaging, Section 6931, Blegdamsvej 9, 2100 Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Martin K Madsen
- Neurobiology Research Unit, Rigshospitalet and Center for Integrated Molecular Brain Imaging, Section 6931, Blegdamsvej 9, 2100 Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Liv V Hjordt
- Neurobiology Research Unit, Rigshospitalet and Center for Integrated Molecular Brain Imaging, Section 6931, Blegdamsvej 9, 2100 Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Ida Hageman
- Psychiatric Centre Copenhagen, Blegdamsvej 9, 2100 Copenhagen, Denmark
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Kettegård Allé 30, 2650 Hvidovre, Denmark
| | - Gitte M Knudsen
- Neurobiology Research Unit, Rigshospitalet and Center for Integrated Molecular Brain Imaging, Section 6931, Blegdamsvej 9, 2100 Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Patrick M Fisher
- Neurobiology Research Unit, Rigshospitalet and Center for Integrated Molecular Brain Imaging, Section 6931, Blegdamsvej 9, 2100 Copenhagen, Denmark.
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14
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Topologically convergent and divergent functional connectivity patterns in unmedicated unipolar depression and bipolar disorder. Transl Psychiatry 2017; 7:e1165. [PMID: 28675389 PMCID: PMC5538109 DOI: 10.1038/tp.2017.117] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Revised: 04/06/2017] [Accepted: 04/25/2017] [Indexed: 01/08/2023] Open
Abstract
Bipolar disorder (BD), particularly BD II, is frequently misdiagnosed as unipolar depression (UD), leading to inappropriate treatment and poor clinical outcomes. Although depressive symptoms may be expressed similarly in UD and BD, the similarities and differences in the architecture of brain functional networks between the two disorders are still unknown. In this study, we hypothesized that UD and BD II patients would show convergent and divergent patterns of disrupted topological organization of the functional connectome, especially in the default mode network (DMN) and the limbic network. Brain resting-state functional magnetic resonance imaging (fMRI) data were acquired from 32 UD-unmedicated patients, 31 unmedicated BD II patients (current episode depressed) and 43 healthy subjects. Using graph theory, we systematically studied the topological organization of their whole-brain functional networks at the following three levels: whole brain, modularity and node. First, both the UD and BD II patients showed increased characteristic path length and decreased global efficiency compared with the controls. Second, both the UD and BD II patients showed disrupted intramodular connectivity within the DMN and limbic system network. Third, decreased nodal characteristics (nodal strength and nodal efficiency) were found predominantly in brain regions in the DMN, limbic network and cerebellum of both the UD and BD II patients, whereas differences between the UD and BD II patients in the nodal characteristics were also observed in the precuneus and temporal pole. Convergent deficits in the topological organization of the whole brain, DMN and limbic networks may reflect overlapping pathophysiological processes in unipolar and bipolar depression. Our discovery of divergent regional connectivity that supports emotion processing could help to identify biomarkers that will aid in differentiating these disorders.
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15
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Lord AR, Li M, Demenescu LR, van den Meer J, Borchardt V, Krause AL, Heinze HJ, Breakspear M, Walter M. Richness in Functional Connectivity Depends on the Neuronal Integrity within the Posterior Cingulate Cortex. Front Neurosci 2017; 11:184. [PMID: 28439224 PMCID: PMC5384321 DOI: 10.3389/fnins.2017.00184] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Accepted: 03/20/2017] [Indexed: 12/19/2022] Open
Abstract
The brain's connectivity skeleton-a rich club of strongly interconnected members-was initially shown to exist in human structural networks, but recent evidence suggests a functional counterpart. This rich club typically includes key regions (or hubs) from multiple canonical networks, reducing the cost of inter-network communication. The posterior cingulate cortex (PCC), a hub node embedded within the default mode network, is known to facilitate communication between brain networks and is a key member of the "rich club." Here, we assessed how metabolic signatures of neuronal integrity and cortical thickness influence the global extent of a functional rich club as measured using the functional rich club coefficient (fRCC). Rich club estimation was performed on functional connectivity of resting state brain signals acquired at 3T in 48 healthy adult subjects. Magnetic resonance spectroscopy was measured in the same session using a point resolved spectroscopy sequence. We confirmed convergence of functional rich club with a previously established structural rich club. N-acetyl aspartate (NAA) in the PCC is significantly correlated with age (p = 0.001), while the rich club coefficient showed no effect of age (p = 0.106). In addition, we found a significant quadratic relationship between fRCC and NAA concentration in PCC (p = 0.009). Furthermore, cortical thinning in the PCC was correlated with a reduced rich club coefficient after accounting for age and NAA. In conclusion, we found that the fRCC is related to a marker of neuronal integrity in a key region of the cingulate cortex. Furthermore, cortical thinning in the same area was observed, suggesting that both cortical thinning and neuronal integrity in the hub regions influence functional integration of at a whole brain level.
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Affiliation(s)
- Anton R Lord
- Department of Behavioral Neurology, Leibniz Institute for NeurobiologyMagdeburg, Germany.,Clinical Affective Neuroimaging Laboratory, Otto-von-Guericke UniversityMagdeburg, Germany.,QIMR Berghofer Medical Research InstituteBrisbane, QLD, Australia
| | - Meng Li
- Clinical Affective Neuroimaging Laboratory, Otto-von-Guericke UniversityMagdeburg, Germany.,Department of Neurology, Otto-von-Guericke UniversityMagdeburg, Germany
| | - Liliana R Demenescu
- Department of Behavioral Neurology, Leibniz Institute for NeurobiologyMagdeburg, Germany.,Clinical Affective Neuroimaging Laboratory, Otto-von-Guericke UniversityMagdeburg, Germany
| | - Johan van den Meer
- Clinical Affective Neuroimaging Laboratory, Otto-von-Guericke UniversityMagdeburg, Germany.,Department of Neurology, Otto-von-Guericke UniversityMagdeburg, Germany.,Department of Cognition and Emotion, Netherlands Institute for Neuroscience, An Institute of the Royal Academy of Arts and SciencesAmsterdam, Netherlands
| | - Viola Borchardt
- Clinical Affective Neuroimaging Laboratory, Otto-von-Guericke UniversityMagdeburg, Germany
| | - Anna Linda Krause
- Clinical Affective Neuroimaging Laboratory, Otto-von-Guericke UniversityMagdeburg, Germany.,Department of Psychiatry and Psychotherapy, Otto-von-Guericke UniversityMagdeburg, Germany
| | - Hans-Jochen Heinze
- Department of Behavioral Neurology, Leibniz Institute for NeurobiologyMagdeburg, Germany.,Department of Neurology, Otto-von-Guericke UniversityMagdeburg, Germany.,Center of Behavioral Brain Sciences, Otto-von-Guericke UniversityMagdeburg, Germany
| | - Michael Breakspear
- QIMR Berghofer Medical Research InstituteBrisbane, QLD, Australia.,Metro North Mental Health Service, Royal Brisbane and Women's HospitalBrisbane, QLD, Australia
| | - Martin Walter
- Department of Behavioral Neurology, Leibniz Institute for NeurobiologyMagdeburg, Germany.,Clinical Affective Neuroimaging Laboratory, Otto-von-Guericke UniversityMagdeburg, Germany.,Department of Psychiatry and Psychotherapy, Otto-von-Guericke UniversityMagdeburg, Germany.,Center of Behavioral Brain Sciences, Otto-von-Guericke UniversityMagdeburg, Germany.,Department of Psychiatry, Eberhad Karls University TuebingenTuebingen, Germany
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16
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A spectroscopic approach toward depression diagnosis: local metabolism meets functional connectivity. Eur Arch Psychiatry Clin Neurosci 2017; 267:95-105. [PMID: 27561792 DOI: 10.1007/s00406-016-0726-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Accepted: 08/16/2016] [Indexed: 01/06/2023]
Abstract
Abnormal anterior insula (AI) response and functional connectivity (FC) is associated with depression. In addition to clinical features, such as severity, AI FC and its metabolism further predicted therapeutic response. Abnormal FC between anterior cingulate and AI covaried with reduced glutamate level within cingulate cortex. Recently, deficient glial glutamate conversion was found in AI in major depression disorder (MDD). We therefore postulate a local glutamatergic mechanism in insula cortex of depressive patients, which is correlated with symptoms severity and itself influences AI's network connectivity in MDD. Twenty-five MDD patients and 25 healthy controls (HC) matched on age and sex underwent resting state functional magnetic resonance imaging and magnetic resonance spectroscopy scans. To determine the role of local glutamate-glutamine complex (Glx) ratio on whole brain AI FC, we conducted regression analysis with Glx relative to creatine (Cr) ratio as factor of interest and age, sex, and voxel tissue composition as nuisance factors. We found that in MDD, but not in HC, AI Glx/Cr ratio correlated positively with AI FC to right supramarginal gyrus and negatively with AI FC toward left occipital cortex (p < 0.05 family wise error). AI Glx/Cr level was negatively correlated with HAMD score (p < 0.05) in MDD patients. We showed that the local AI ratio of glutamatergic-creatine metabolism is an underlying candidate subserving functional network disintegration of insula toward low level and supramodal integration areas, in MDD. While causality cannot directly be inferred from such correlation, our finding helps to define a multilevel network of response-predicting regions based on local metabolism and connectivity strength.
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17
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Zhao Y, Du M, Gao X, Xiao Y, Shah C, Sun H, Chen F, Yang L, Yan Z, Fu Y, Lui S. Altered brain network topology in left-behind children: A resting-state functional magnetic resonance imaging study. CHILD ABUSE & NEGLECT 2016; 62:89-99. [PMID: 27794245 DOI: 10.1016/j.chiabu.2016.10.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Revised: 10/16/2016] [Accepted: 10/17/2016] [Indexed: 06/06/2023]
Abstract
Whether a lack of direct parental care affects brain function in children is an important question, particularly in developing countries where hundreds of millions of children are left behind when their parents migrate for economic or political reasons. In this study, we investigated changes in the topological architectures of brain functional networks in left-behind children (LBC). Resting-state functional magnetic resonance imaging data were obtained from 26 LBC and 21 children living within their nuclear family (non-LBC). LBC showed a significant increase in the normalized characteristic path length (λ), suggesting a decrease in efficiency in information access, and altered nodal centralities in the fronto-limbic regions and motor and sensory systems. Moreover, a decreased nodal degree and the nodal betweenness of the right rectus gyrus were positively correlated with annual family income. The present study provides the first empirical evidence that suggests that a lack of direct parental care could affect brain functional development in children, particularly involving emotional networks.
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Affiliation(s)
- Youjin Zhao
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Zhejiang 325035, PR China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Meimei Du
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Zhejiang 325035, PR China
| | - Xin Gao
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Zhejiang 325035, PR China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Chandan Shah
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Huaiqiang Sun
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Fuqin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Lili Yang
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Zhejiang 325035, PR China
| | - Zhihan Yan
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Zhejiang 325035, PR China
| | - Yuchuan Fu
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Zhejiang 325035, PR China
| | - Su Lui
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Zhejiang 325035, PR China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China.
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18
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Quevedo K, Ng R, Scott H, Martin J, Smyda G, Keener M, Oppenheimer CW. The neurobiology of self-face recognition in depressed adolescents with low or high suicidality. JOURNAL OF ABNORMAL PSYCHOLOGY 2016; 125:1185-1200. [PMID: 27618278 PMCID: PMC5858689 DOI: 10.1037/abn0000200] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
This study sought to test whether the neurobiology of self-processing differentiated depressed adolescents with high suicidality (HS) from those with low suicidality (LS) and healthy controls (HC; N = 119, MAGE = 14.79, SD = 1.64, Min = 11.3, Max = 17.8). Participants completed a visual self-recognition task in the scanner during which they identified their own or an unfamiliar adolescent face across 3 emotional expressions (happy, neutral or sad). A 3-group (HS, LS, HC) by 2 within-subject factors (2 Self conditions [self, other] and 3 Emotions [happy, neutral, sad]) GLM yielded (a) a main effect of Self condition with all participants showing higher activity in the right occipital, precuneus and fusiform during the self- versus other-face conditions; (b) a main effect of Group where all depressed youth showed higher dorsolateral prefrontal cortex activity than HC across all conditions, and with HS showing higher cuneus and occipital activity versus both LS and HC; and (c) a Group by Self by Emotion interaction with HS showing lower activity in both mid parietal, limbic, and prefrontal areas in the Happy self versus other-face condition relative to the LS group, who in turn had less activity compared to HC youth. Covarying for depression severity replicated all results except the third finding; In this subsequent analysis, a Group by Self interaction showed that although HC had similar midline cortical structure (MCS) activity for all faces, LS showed higher MCS activity for the self versus other faces, whereas HS showed the opposite pattern. Results suggest that the neurophysiology of emotionally charged self-referential information can distinguish depressed, suicidal youth versus nonsuicidal depressed and healthy adolescents. Neurophysiological differences and implications for the prediction of suicidality in youth are discussed. (PsycINFO Database Record
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Affiliation(s)
| | - Rowena Ng
- University of Minnesota Institute of Child Development
| | - Hannah Scott
- University of Minnesota, Department of Psychiatry
| | - Jodi Martin
- University of Minnesota Institute of Child Development
| | - Garry Smyda
- University of Pittsburgh, School of Public Health
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Manelis A, Almeida JRC, Stiffler R, Lockovich JC, Aslam HA, Phillips ML. Anticipation-related brain connectivity in bipolar and unipolar depression: a graph theory approach. Brain 2016; 139:2554-66. [PMID: 27368345 DOI: 10.1093/brain/aww157] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Accepted: 05/15/2016] [Indexed: 11/14/2022] Open
Abstract
Bipolar disorder is often misdiagnosed as major depressive disorder, which leads to inadequate treatment. Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipolar disorder may differ from those with major depressive disorder in neural mechanisms underlying anticipation processes. Graph theory methods for neuroimaging data analysis allow the identification of connectivity between multiple brain regions without prior model specification, and may help to identify neurobiological markers differentiating these disorders, thereby facilitating development of better therapeutic interventions. This study aimed to compare brain connectivity among regions involved in win/loss anticipation in depressed individuals with bipolar disorder (BDD) versus depressed individuals with major depressive disorder (MDD) versus healthy control subjects using graph theory methods. The study was conducted at the University of Pittsburgh Medical Center and included 31 BDD, 39 MDD, and 36 healthy control subjects. Participants were scanned while performing a number guessing reward task that included the periods of win and loss anticipation. We first identified the anticipatory network across all 106 participants by contrasting brain activation during all anticipation periods (win anticipation + loss anticipation) versus baseline, and win anticipation versus loss anticipation. Brain connectivity within the identified network was determined using the Independent Multiple sample Greedy Equivalence Search (IMaGES) and Linear non-Gaussian Orientation, Fixed Structure (LOFS) algorithms. Density of connections (the number of connections in the network), path length, and the global connectivity direction ('top-down' versus 'bottom-up') were compared across groups (BDD/MDD/healthy control subjects) and conditions (win/loss anticipation). These analyses showed that loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy control subjects. In summary, this is the first study to demonstrate that BDD and MDD with comparable levels of current depression differed from each other and healthy control subjects in density of connections, connectivity path length, and connectivity direction as a function of win or loss anticipation. These findings suggest that different neurobiological mechanisms may underlie aberrant anticipation processes in BDD and MDD, and that distinct therapeutic strategies may be required for these individuals to improve coping strategies during expectation of positive and negative outcomes.
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Affiliation(s)
- Anna Manelis
- 1 Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jorge R C Almeida
- 2 Department of Psychiatry and Human Behaviour, Alpert Medical School of Brown University, Providence, RI 02912, USA
| | - Richelle Stiffler
- 1 Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jeanette C Lockovich
- 1 Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Haris A Aslam
- 1 Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mary L Phillips
- 1 Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
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Altered functional connectivity density in major depressive disorder at rest. Eur Arch Psychiatry Clin Neurosci 2016; 266:239-48. [PMID: 26265034 DOI: 10.1007/s00406-015-0614-0] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Accepted: 06/28/2015] [Indexed: 12/22/2022]
Abstract
Major depressive disorder is characterized by abnormal brain connectivity at rest. Currently, most studies investigating resting-state activity rely on a priori restrictions on specific networks or seed regions, which may bias observations. We hence sought to elicit functional alterations in a hypothesis-free approach. We applied functional connectivity density (FCD) to identify abnormal connectivity for each voxel in the whole brain separately. Comparing resting-state fMRI in 21 MDD patients and 23 matched healthy controls, we identified atypical connections for regions exhibiting abnormal FCD and compared our results to those of an independent component analysis (ICA) on networks previously investigated in MDD. Patients showed reduced FCD in mid-cingulate cortex (MCC) and increased FCD in occipital cortex (OCC). These changes in global FCD were driven by abnormal local connectivity changes and reduced functional connectivity (FC) toward the left amygdala for MCC, and increased FC toward the right supplementary motor area for OCC. The altered connectivity was not reflected in ICA comparison of the salience and visual networks. Abnormal FC in MDD is present in cingulate and OCC in terms of global FCD. This converges with previous structural and metabolic findings; however, these particular changes in connectivity would not have been identified using canonical seed regions or networks. This implies the importance of FC measures in the investigation of brain pathophysiology in depression.
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Lord A, Ehrlich S, Borchardt V, Geisler D, Seidel M, Huber S, Murr J, Walter M. Brain parcellation choice affects disease-related topology differences increasingly from global to local network levels. Psychiatry Res Neuroimaging 2016; 249:12-19. [PMID: 27000302 DOI: 10.1016/j.pscychresns.2016.02.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2015] [Revised: 01/15/2016] [Accepted: 02/04/2016] [Indexed: 11/17/2022]
Abstract
Network-based analyses of deviant brain function have become extremely popular in psychiatric neuroimaging. Underpinning brain network analyses is the selection of appropriate regions of interest (ROIs). Although ROI selection is fundamental in network analysis, its impact on detecting disease effects remains unclear. We investigated the impact of parcellation choice when comparing results from different studies. We investigated the effects of anatomical (AAL) and literature-based (Dosenbach) parcellation schemes on comparability of group differences in 35 female patients with anorexia nervosa and 35 age- and sex-matched healthy controls. Global and local network properties, including network-based statistics (NBS), were assessed on resting state functional magnetic resonance imaging data obtained at 3T. Parcellation schemes were comparably consistent on global network properties, while NBS and local metrics differed in location, but not metric type. Location of local metric alterations varied for AAL (parietal and cingulate cortices) versus Dosenbach (insula, thalamus) parcellation approaches. However, consistency was observed for the occipital cortex. Patient-specific global network properties can be robustly observed using different parcellation schemes, while graph metrics characterizing impairments of individual nodes vary considerably. Therefore, the impact of parcellation choice on specific group differences varies depending on the level of network organization.
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Affiliation(s)
- Anton Lord
- Leibniz Institute for Neurobiology, Magdeburg, Saxony-Anhalt, Germany; Clinical Affective Neuroimaging Laboratory, Magdeburg, Saxony-Anhalt, Germany
| | - Stefan Ehrlich
- Department of Child and Adolescent Psychiatry, Eating Disorder Research and Treatment Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany; MGH/MIT/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States; Department of Psychosomatic Medicine and Psychotherapy, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Viola Borchardt
- Leibniz Institute for Neurobiology, Magdeburg, Saxony-Anhalt, Germany; Clinical Affective Neuroimaging Laboratory, Magdeburg, Saxony-Anhalt, Germany
| | - Daniel Geisler
- Department of Child and Adolescent Psychiatry, Eating Disorder Research and Treatment Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany; Department of Psychosomatic Medicine and Psychotherapy, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Maria Seidel
- Department of Child and Adolescent Psychiatry, Eating Disorder Research and Treatment Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany; Department of Psychosomatic Medicine and Psychotherapy, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Stefanie Huber
- Department of Child and Adolescent Psychiatry, Eating Disorder Research and Treatment Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany; Department of Psychosomatic Medicine and Psychotherapy, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Julia Murr
- Department of Psychiatry and Psychotherapy, Otto von Guericke University, Magdeburg, Germany; Department of Psychosomatic Medicine and Psychotherapy, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Martin Walter
- Leibniz Institute for Neurobiology, Magdeburg, Saxony-Anhalt, Germany; Clinical Affective Neuroimaging Laboratory, Magdeburg, Saxony-Anhalt, Germany; Department of Psychiatry and Psychotherapy, Otto von Guericke University, Magdeburg, Germany; Center for Behavioral Brain Sciences (CBBS), Magdeburg, Saxony-Anhalt, Germany; Department of Psychosomatic Medicine and Psychotherapy, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany.
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22
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Borchardt V, Lord AR, Li M, van der Meer J, Heinze HJ, Bogerts B, Breakspear M, Walter M. Preprocessing strategy influences graph-based exploration of altered functional networks in major depression. Hum Brain Mapp 2016; 37:1422-42. [PMID: 26888761 DOI: 10.1002/hbm.23111] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Revised: 12/11/2015] [Accepted: 12/23/2015] [Indexed: 12/16/2022] Open
Abstract
Resting-state fMRI studies have gained widespread use in exploratory studies of neuropsychiatric disorders. Graph metrics derived from whole brain functional connectivity studies have been used to reveal disease-related variations in many neuropsychiatric disorders including major depression (MDD). These techniques show promise in developing diagnostics for these often difficult to identify disorders. However, the analysis of resting-state datasets is increasingly beset by a myriad of approaches and methods, each with underlying assumptions. Choosing the most appropriate preprocessing parameters a priori is difficult. Nevertheless, the specific methodological choice influences graph-theoretical network topologies as well as regional metrics. The aim of this study was to systematically compare different preprocessing strategies by evaluating their influence on group differences between healthy participants (HC) and depressive patients. We thus investigated the effects of common preprocessing variants, including global mean-signal regression (GMR), temporal filtering, detrending, and network sparsity on group differences between brain networks of HC and MDD patients measured by global and nodal graph theoretical metrics. Occurrence of group differences in global metrics was absent in the majority of tested preprocessing variants, but in local graph metrics it is sparse, variable, and highly dependent on the combination of preprocessing variant and sparsity threshold. Sparsity thresholds between 16 and 22% were shown to have the greatest potential to reveal differences between HC and MDD patients in global and local network metrics. Our study offers an overview of consequences of methodological decisions and which neurobiological characteristics of MDD they implicate, adding further caution to this rapidly growing field.
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Affiliation(s)
- Viola Borchardt
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany.,Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany
| | - Anton Richard Lord
- Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany.,QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.,University of Queensland, St Lucia, Queensland, Australia
| | - Meng Li
- Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany.,Department of Neurology, Otto Von Guericke University, Magdeburg, Germany
| | - Johan van der Meer
- Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany.,Department of Psychiatry and Psychotherapy, Otto Von Guericke University, Magdeburg, Germany.,Department of Cognition and Emotion, Netherlands Institute for Neuroscience, an Institute of the Royal Academy of Arts and Sciences, Amsterdam, Netherlands
| | - Hans-Jochen Heinze
- Department of Neurology, Otto Von Guericke University, Magdeburg, Germany.,Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
| | - Bernhard Bogerts
- Department of Psychiatry and Psychotherapy, Otto Von Guericke University, Magdeburg, Germany
| | - Michael Breakspear
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.,Metro North Mental Health Service, Brisbane, Queensland, Australia
| | - Martin Walter
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany.,Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany.,Department of Psychiatry and Psychotherapy, Otto Von Guericke University, Magdeburg, Germany.,Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany.,Department of Psychiatry, University Tübingen
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23
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Borchardt V, Krause AL, Li M, van Tol MJ, Demenescu LR, Buchheim A, Metzger CD, Sweeney-Reed CM, Nolte T, Lord AR, Walter M. Dynamic disconnection of the supplementary motor area after processing of dismissive biographic narratives. Brain Behav 2015; 5:e00377. [PMID: 26516612 PMCID: PMC4614061 DOI: 10.1002/brb3.377] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 07/10/2015] [Accepted: 07/14/2015] [Indexed: 11/16/2022] Open
Abstract
INTRODUCTION To understand the interplay between affective social information processing and its influence on mental states we investigated changes in functional connectivity (FC) patterns after audio exposure to emotional biographic narratives. METHODS While lying in the 7T MR scanner, 23 male participants listened to narratives of early childhood experiences of three persons, each having either a secure, dismissing, or preoccupied attachment representation. Directly after having listened to each of the prototypical narratives, participants underwent a 10-minute resting-state fMRI scan. To study changes in FC patterns between experimental conditions, three post-task conditions were compared to a baseline condition. Specific local alterations, as well as differences in connectivity patterns between distributed brain regions, were quantified using Network-based statistics (NBS) and graph metrics. RESULTS Using NBS, a nine-region subnetwork showing reduced FC after having listened to the dismissing narrative was identified. Of this subnetwork, only the left Supplementary Motor Area (SMA) exhibited a decrease in the nodal graph metrics degree and strength exclusively after listening to the dismissing narrative. No other region showed post-task changes in nodal metrics. A post hoc analysis of dynamic characteristics of FC of the left SMA showed a significant decrease in the dismissing condition when compared with the other conditions in the first three minutes of the scan, but faded away in the two subsequent intervals the differences. CONCLUSIONS Nodal metrics and NBS converge on reduced connectivity measures exclusively in left SMA in the dismissing condition, which may specifically reflect ongoing network changes underlying prolonged emotional reactivity to attachment-related processing.
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Affiliation(s)
- Viola Borchardt
- Leibniz Institute for Neurobiology Magdeburg Germany ; Clinical Affective Neuroimaging Laboratory Magdeburg Germany
| | - Anna L Krause
- Clinical Affective Neuroimaging Laboratory Magdeburg Germany ; Department of Psychiatry and Psychotherapy Otto von Guericke University Magdeburg Germany
| | - Meng Li
- Clinical Affective Neuroimaging Laboratory Magdeburg Germany ; Department of Neurology Otto von Guericke University Magdeburg Germany
| | - Marie-José van Tol
- University of Groningen University Medical Center Groningen Neuroimaging Center Groningen the Netherlands
| | - Liliana Ramona Demenescu
- Clinical Affective Neuroimaging Laboratory Magdeburg Germany ; Department of Neurology Otto von Guericke University Magdeburg Germany
| | - Anna Buchheim
- Institute of Psychology University of Innsbruck Innsbruck Austria
| | - Coraline D Metzger
- Leibniz Institute for Neurobiology Magdeburg Germany ; Department of Psychiatry and Psychotherapy Otto von Guericke University Magdeburg Germany ; Institute for Cognitive Neurology and Dementia Research (IKND) Magdeburg Germany ; German Center for Neurodegenerative Diseases (DZNE) Magdeburg Germany
| | - Catherine M Sweeney-Reed
- Department of Neurology Otto von Guericke University Magdeburg Germany ; Neurocybernetics and Rehabilitation Department for Neurology and Stereotactic Neurosurgery Otto von Guericke University Magdeburg Germany
| | - Tobias Nolte
- Anna Freud Centre London UK ; Wellcome Trust Centre for Neuroimaging University College of London London UK
| | - Anton R Lord
- Leibniz Institute for Neurobiology Magdeburg Germany ; Clinical Affective Neuroimaging Laboratory Magdeburg Germany
| | - Martin Walter
- Leibniz Institute for Neurobiology Magdeburg Germany ; Clinical Affective Neuroimaging Laboratory Magdeburg Germany ; Department of Psychiatry and Psychotherapy Otto von Guericke University Magdeburg Germany ; Center for Behavioral Brain Sciences (CBBS) Magdeburg Germany
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24
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Ehrlich S, Lord AR, Geisler D, Borchardt V, Boehm I, Seidel M, Ritschel F, Schulze A, King JA, Weidner K, Roessner V, Walter M. Reduced functional connectivity in the thalamo-insular subnetwork in patients with acute anorexia nervosa. Hum Brain Mapp 2015; 36:1772-81. [PMID: 25611053 DOI: 10.1002/hbm.22736] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2014] [Accepted: 01/05/2015] [Indexed: 12/17/2022] Open
Abstract
The neural underpinnings of anorexia nervosa (AN) are poorly understood. Results from existing functional brain imaging studies using disorder-relevant food- or body-stimuli have been heterogeneous and may be biased due to varying compliance or strategies of the participants. In this study, resting state functional connectivity imaging was used. To explore the distributed nature and complexity of brain function we characterized network patterns in patients with acute AN. Thirty-five unmedicated female acute AN patients and 35 closely matched healthy female participants underwent resting state functional magnetic resonance imaging. We used a network-based statistic (NBS) approach [Zalesky et al., 2010a] to identify differences between groups by isolating a network of interconnected nodes with a deviant connectivity pattern. Group comparison revealed a subnetwork of connections with decreased connectivity including the amygdala, thalamus, fusiform gyrus, putamen and the posterior insula as the central hub in the patient group. Results were not driven by changes in intranodal or global connectivity. No network could be identified where AN patients had increased coupling. Given the known involvement of the identified thalamo-insular subnetwork in interoception, decreased connectivity in AN patients in these nodes might reflect changes in the propagation of sensations that alert the organism to urgent homeostatic imbalances and pain-processes that are known to be severely disturbed in AN and might explain the striking discrepancy between patient's actual and perceived internal body state.
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Affiliation(s)
- Stefan Ehrlich
- Department of Child and Adolescent Psychiatry, Eating Disorder Services and Research Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C. G. Carus, Dresden, Germany; MGH/MIT/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts; Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts
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