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Cattarinussi G, Heidari-Foroozan M, Jafary H, Mohammadi E, Sambataro F, Ferro A, Barone Y, Delvecchio G. Resting-state functional magnetic resonance imaging alterations in first-degree relatives of individuals with bipolar disorder: A systematic review. J Affect Disord 2024; 365:321-331. [PMID: 39142577 DOI: 10.1016/j.jad.2024.08.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 07/25/2024] [Accepted: 08/11/2024] [Indexed: 08/16/2024]
Abstract
BACKGROUND Relatives of individuals with bipolar disorder (BD) are at higher risk of developing the disorder. Identifying brain alterations associated with familial vulnerability in BD can help discover endophenotypes, which are quantifiable biological traits more prevalent in unaffected relatives of BD (BD-RELs) than the general population. This review aimed at expanding our knowledge on endophenotypes of BD by providing an overview of resting-state functional magnetic resonance imaging (rs-fMRI) alterations in BD-RELs. METHODS A systematic search of PubMed, Scopus, and Web of Science was performed to identify all available rs-fMRI studies conducted in BD-RELs up to January 2024. A total of 18 studies were selected. Six included BD-RELs with no history of psychiatric disorders and 10 included BD-RELs that presented psychiatric disorders. Two investigations examined rs-fMRI alterations in BD-RELs with and without subthreshold symptoms for BD. RESULTS BD-RELs presented rs-fMRI alterations in the cortico-limbic network, fronto-thalamic-striatal circuit, fronto-occipital network, and, to a lesser extent, in the default mode network. This was true both for BD-RELs with no history of psychopathology and for BD-RELs that presented psychiatric disorders. The direct comparison of rs-fMRI alterations in BD-RELs with and without psychiatric symptoms displayed largely non-overlapping patterns of rs-fMRI abnormalities. LIMITATIONS Small sample sizes and the clinical heterogeneity of BD-RELs limit the generalizability of our findings. CONCLUSIONS The current literature suggests that first-degree BD-RELs exhibit rs-fMRI alterations in brain circuits involved in emotion regulation, cognition, reward processing, and psychosis susceptibility. Future studies are needed to validate these findings and to explore their potential as biomarkers for early detection and intervention.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Mahsa Heidari-Foroozan
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hosein Jafary
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Esmaeil Mohammadi
- Department of Neurological Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Fabio Sambataro
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Adele Ferro
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Ylenia Barone
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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Pan N, Qin K, Patino LR, Tallman MJ, Lei D, Lu L, Li W, Blom TJ, Bruns KM, Welge JA, Strawn JR, Gong Q, Sweeney JA, Singh MK, DelBello MP. Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task-based fMRI connectome study. J Child Psychol Psychiatry 2024; 65:1072-1086. [PMID: 38220469 PMCID: PMC11246494 DOI: 10.1111/jcpp.13946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/26/2023] [Indexed: 01/16/2024]
Abstract
BACKGROUND Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. METHODS Depressed and/or anxious youth (n = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls (n = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. RESULTS High-risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency (Elocal, p = .022) and clustering coefficient (Cp, p = .029) and nodal metrics of the right superior frontal gyrus (SFG) (Elocal: p < .001; Cp: p = .001) in the high-risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p = .004; betweenness: p = .005; age-by-group interaction, p = .038) and right hippocampus (degree: p = .003; betweenness: p = .003). The case-control classifier achieved a cross-validation accuracy of 78.4%. CONCLUSIONS Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at-risk youth.
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Affiliation(s)
- Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Kun Qin
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Luis R. Patino
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Maxwell J. Tallman
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing, China
| | - Lu Lu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Thomas J. Blom
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Kaitlyn M. Bruns
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Jeffrey A. Welge
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Jeffrey R. Strawn
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - John A. Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Manpreet K. Singh
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, California, USA
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Theis N, Bahuguna J, Rubin JE, Cape J, Iyengar S, Prasad KM. Diagnostically distinct resting state fMRI energy distributions: A subject-specific maximum entropy modeling study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576937. [PMID: 38328170 PMCID: PMC10849576 DOI: 10.1101/2024.01.23.576937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Objective Existing neuroimaging studies of psychotic and mood disorders have reported brain activation differences (first-order properties) and altered pairwise correlation-based functional connectivity (second-order properties). However, both approaches have certain limitations that can be overcome by integrating them in a pairwise maximum entropy model (MEM) that better represents a comprehensive picture of fMRI signal patterns and provides a system-wide summary measure called energy. This study examines the applicability of individual-level MEM for psychiatry and identifies image-derived model coefficients related to model parameters. Method MEMs are fit to resting state fMRI data from each individual with schizophrenia/schizoaffective disorder, bipolar disorder, and major depression (n=132) and demographically matched healthy controls (n=132) from the UK Biobank to different subsets of the default mode network (DMN) regions. Results The model satisfactorily explained observed brain energy state occurrence probabilities across all participants, and model parameters were significantly correlated with image-derived coefficients for all groups. Within clinical groups, averaged energy level distributions were higher in schizophrenia/schizoaffective disorder but lower in bipolar disorder compared to controls for both bilateral and unilateral DMN. Major depression energy distributions were higher compared to controls only in the right hemisphere DMN. Conclusions Diagnostically distinct energy states suggest that probability distributions of temporal changes in synchronously active nodes may underlie each diagnostic entity. Subject-specific MEMs allow for factoring in the individual variations compared to traditional group-level inferences, offering an improved measure of biologically meaningful correlates of brain activity that may have potential clinical utility.
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Affiliation(s)
- Nicholas Theis
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jyotika Bahuguna
- Department of Neuroscience, Laboratoire de Neurosciences Cognitive et Adaptive, University of Strasbourg, France
| | | | - Joshua Cape
- Department of Statistics, University of Wisconsin-Madison, WI, USA
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, PA, USA
| | - Konasale M. Prasad
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, PA, USA
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
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Macoveanu J, Fortea L, Kjærstad HL, Coello K, Faurholt-Jepsen M, Fisher PM, Knudsen GM, Radua J, Vieta E, Frangou S, Vinberg M, Kessing LV, Miskowiak KW. Longitudinal changes in resting-state functional connectivity as markers of vulnerability or resilience in first-degree relatives of patients with bipolar disorder. Psychol Med 2024:1-9. [PMID: 38634498 DOI: 10.1017/s0033291724000898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
BACKGROUND There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives. METHODS In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years. RESULTS At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker. CONCLUSION Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.
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Affiliation(s)
- Julian Macoveanu
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark
- Neurocogntion and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, and Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Fundació Clínic per la Recerca Biomèdica (FCRB), Barcelona, Spain
- Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Hanne Lie Kjærstad
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark
- Neurocogntion and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, and Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Klara Coello
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark
| | - Maria Faurholt-Jepsen
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Patrick M Fisher
- Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Gitte Moos Knudsen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Fundació Clínic per la Recerca Biomèdica (FCRB), Barcelona, Spain
- Centro de Investigacisón Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Fundació Clínic per la Recerca Biomèdica (FCRB), Barcelona, Spain
- Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
- Centro de Investigacisón Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, US
| | - Maj Vinberg
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- The Early Multimodular Prevention and Intervention Research Institution (EMPIRI), Psychiatric Center Northern Zealand, Denmark
| | - Lars Vedel Kessing
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Kamilla Woznica Miskowiak
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark
- Neurocogntion and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, and Department of Psychology, University of Copenhagen, Copenhagen, Denmark
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Chang JR, Yao ZF, Hsieh S, Nordling TEM. Age Prediction Using Resting-State Functional MRI. Neuroinformatics 2024; 22:119-134. [PMID: 38341830 DOI: 10.1007/s12021-024-09653-x] [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] [Accepted: 12/21/2023] [Indexed: 02/13/2024]
Abstract
The increasing lifespan and large individual differences in cognitive capability highlight the importance of comprehending the aging process of the brain. Contrary to visible signs of bodily ageing, like greying of hair and loss of muscle mass, the internal changes that occur within our brains remain less apparent until they impair function. Brain age, distinct from chronological age, reflects our brain's health status and may deviate from our actual chronological age. Notably, brain age has been associated with mortality and depression. The brain is plastic and can compensate even for severe structural damage by rewiring. Functional characterization offers insights that structural cannot provide. Contrary to the multitude of studies relying on structural magnetic resonance imaging (MRI), we utilize resting-state functional MRI (rsfMRI). We also address the issue of inclusion of subjects with abnormal brain ageing through outlier removal. In this study, we employ the Least Absolute Shrinkage and Selection Operator (LASSO) to identify the 39 most predictive correlations derived from the rsfMRI data. The data is from a cohort of 176 healthy right-handed volunteers, aged 18-78 years (95/81 male/female, mean age 48, SD 17) collected at the Mind Research Imaging Center at the National Cheng Kung University. We establish a normal reference model by excluding 68 outliers, which achieves a leave-one-out mean absolute error of 2.48 years. By asking which additional features that are needed to predict the chronological age of the outliers with a smaller error, we identify correlations predictive of abnormal aging. These are associated with the Default Mode Network (DMN). Our normal reference model has the lowest prediction error among published models evaluated on adult subjects of almost all ages and is thus a candidate for screening for abnormal brain aging that has not yet manifested in cognitive decline. This study advances our ability to predict brain aging and provides insights into potential biomarkers for assessing brain age, suggesting that the role of DMN in brain aging should be studied further.
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Affiliation(s)
- Jose Ramon Chang
- Department of Mechanical Engineering, National Cheng Kung University, No. 1 University Rd., Tainan, 701, Taiwan
| | - Zai-Fu Yao
- College of Education, National Tsing Hua University, Hsinchu, 30013, Taiwan
- Research Center for Education and Mind Sciences, National Tsing Hua University, Hsinchu, 30013, Taiwan
- Department of Kinesiology, National Tsing Hua University, Hsinchu, 30013, Taiwan
- Basic Psychology Group, Department of Educational Psychology and Counseling, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | - Shulan Hsieh
- Department of Psychology, National Cheng Kung University, No. 1 University Rd., Tainan, 701, Taiwan
- Institute of Allied Health Sciences, National Cheng Kung University, No. 1 University Rd., Tainan, 701, Taiwan
- Department of Public Health, College of Medicine, National Cheng Kung University, No. 1 University Rd., Tainan, 701, Taiwan
| | - Torbjörn E M Nordling
- Department of Mechanical Engineering, National Cheng Kung University, No. 1 University Rd., Tainan, 701, Taiwan.
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Shu Z, Wang J, Cheng Y, Lu J, Lin J, Wang Y, Zhang X, Yu Y, Zhu Z, Han J, Wu J, Yu N. fNIRS-based graph frequency analysis to identify mild cognitive impairment in Parkinson's disease. J Neurosci Methods 2024; 402:110031. [PMID: 38040127 DOI: 10.1016/j.jneumeth.2023.110031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/23/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023]
Abstract
BACKGROUND Early identification of mild cognitive impairment (MCI) is essential for its treatment and the prevention of dementia in Parkinson's disease (PD). Existing approaches are mostly based on neuropsychological assessments, while brain activation and connection have not been well considered. NEW METHOD This paper presents a neuroimaging-based graph frequency analysis method and the generated features to quantify the brain functional neurodegeneration and distinguish between PD-MCI patients and healthy controls. The Stroop color-word experiment was conducted with 20 PD-MCI patients and 34 healthy controls, and the brain activation was recorded with functional near-infrared spectroscopy (fNIRS). Then, the functional brain network was constructed based on Pearson's correlation coefficient calculation between every two fNIRS channels. Next, the functional brain network was represented as a graph and decomposed in the graph frequency domain through the graph Fourier transform (GFT) to obtain the eigenvector matrix. Total variation and weighted zero crossings of eigenvectors were defined and integrated to quantify functional interaction between brain regions and the spatial variability of the brain network in specific graph frequency ranges, respectively. After that, the features were employed in training a support vector machine (SVM) classifier. RESULTS The presented method achieved a classification accuracy of 0.833 and an F1 score of 0.877, significantly outperforming existing methods and features. COMPARISON WITH EXISTING METHODS Our method provided improved classification performance in the identification of PD-MCI. CONCLUSION The results suggest that the presented graph frequency analysis method well identify PD-MCI patients and the generated features promise functional brain biomarkers for PD-MCI diagnosis.
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Affiliation(s)
- Zhilin Shu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China
| | - Jin Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin 300350, China; Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin 300370, China
| | - Yuanyuan Cheng
- Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin 300370, China; Department of Rehabilitation Medicine, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Jiewei Lu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China
| | - Jianeng Lin
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China
| | - Yue Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Xinyuan Zhang
- Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin 300370, China
| | - Yang Yu
- Department of Rehabilitation Medicine, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Zhizhong Zhu
- Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin 300370, China; Department of Rehabilitation Medicine, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Jianda Han
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China; Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China.
| | - Jialing Wu
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin 300350, China; Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases, Tianjin Neurosurgical Institute, Tianjin 300350, China.
| | - Ningbo Yu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China; Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China.
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7
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Rupert PE, Pogue-Geile M. Familial Risk for Schizophrenia vs Bipolar Disorder and Task-Based Neural Activation: A functional Magnetic Resonance Imaging Meta-Analysis. Schizophr Bull 2024; 50:177-186. [PMID: 37606284 PMCID: PMC10754177 DOI: 10.1093/schbul/sbad115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/23/2023]
Abstract
BACKGROUND AND HYPOTHESIS Individuals at familial risk for developing schizophrenia (FRSZ) or bipolar disorder (FRBD) have shared and unique genetic risks. Few studies have compared neural activation between these two groups. Therefore, the present meta-analysis investigated functional brain similarities and differences between FRSZ and FRBD individuals. STUDY DESIGN A systematic literature review was conducted of articles that compared FRSZ or FRBD individuals to healthy controls (31 FRSZ and 22 FRBD). Seed-based d mapping was used to conduct the meta-analysis. Analyses included comparisons of FRSZ to controls, FRBD to controls, and both relative groups to each other. STUDY RESULTS Using a highly conservative family-wise error rate correction, there were no significant findings. Using a less conservative threshold, FRSZ compared to controls had lower activation in the left precuneus (Puncorrected = .02) across all studies and in the left middle frontal gyrus (Puncorrected = .03) in nonsocial cognition studies. FRBD compared to controls had lower activation in the left superior parietal gyrus (Puncorrected = .03) and right angular gyrus (Puncorrected = .03) in nonsocial cognition studies, and higher activation in the left superior frontal gyrus (Puncorrected = .01) in social tasks. Differences between FRSZ and FRBD were not significant. CONCLUSIONS There were few robust differences between FRSZ or FRBD compared to controls. This suggests only weak support for neural activation differences between individuals at genetic risk for schizophrenia or bipolar disorder and controls. The tentative findings observed were in different brain regions for FRSZ and FRBD, with no strong evidence for shared effects between schizophrenia and bipolar genetic risk on neural activation.
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Affiliation(s)
- Petra E Rupert
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael Pogue-Geile
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
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Wang H, Zhu R, Tian S, Shao J, Dai Z, Xue L, Sun Y, Chen Z, Yao Z, Lu Q. Classification of bipolar disorders using the multilayer modularity in dynamic minimum spanning tree from resting state fMRI. Cogn Neurodyn 2023; 17:1609-1619. [PMID: 37974586 PMCID: PMC10640554 DOI: 10.1007/s11571-022-09907-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 07/19/2022] [Accepted: 10/28/2022] [Indexed: 12/04/2022] Open
Abstract
The diagnosis of bipolar disorders (BD) mainly depends on the clinical history and behavior observation, while only using clinical tools often limits the diagnosis accuracy. The study aimed to create a novel BD diagnosis framework using multilayer modularity in the dynamic minimum spanning tree (MST). We collected 45 un-medicated BD patients and 47 healthy controls (HC). The sliding window approach was utilized to construct dynamic MST via resting-state functional magnetic resonance imaging (fMRI) data. Firstly, we used three null models to explore the effectiveness of multilayer modularity in dynamic MST. Furthermore, the module allegiance exacted from dynamic MST was applied to train a classifier to discriminate BD patients. Finally, we explored the influence of the FC estimator and MST scale on the performance of the model. The findings indicated that multilayer modularity in the dynamic MST was not a random process in the human brain. And the model achieved an accuracy of 83.70% for identifying BD patients. In addition, we found the default mode network, subcortical network (SubC), and attention network played a key role in the classification. These findings suggested that the multilayer modularity in dynamic MST could highlight the difference between HC and BD patients, which opened up a new diagnostic tool for BD patients. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09907-x.
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Affiliation(s)
- Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Rongxin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029 China
| | - Shui Tian
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Yurong Sun
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhilu Chen
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029 China
| | - Zhijian Yao
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029 China
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093 China
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
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9
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Hu Z, Tan Y, Zhou F, He L. Aberrant functional connectivity within and between brain networks in patients with early-onset bipolar disorder. J Affect Disord 2023; 338:41-51. [PMID: 37257780 DOI: 10.1016/j.jad.2023.05.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 05/11/2023] [Accepted: 05/18/2023] [Indexed: 06/02/2023]
Abstract
OBJECTIVE This study used independent component analysis (ICA) to investigate the connectivity patterns of resting-state functional large-scale brain networks in patients with early-onset bipolar disorder (BD). METHODS ICA was used to extract brain functional network components from 43 early-onset BD patients and 21 healthy controls (HCs). Then, the functional connectivity (FC) and functional network connectivity (FNC) within and between the independent brain networks was calculated, and the correlation between the connectivity changes and neuropsychological scale was evaluated. RESULTS Compared with HCs, FC increased in the right hippocampus and inferior temporal gyrus, and left triangular inferior frontal gyrus of the anterior default mode network (aDMN); right median cingulate and paracingulate gyri, and inferior parietal lobule of the posterior DMN (pDMN); and right precentral and postcentral gyrus of the sensorimotor network (SMN) in early-onset BD patients. However, FC decreased in the left superior frontal gyrus of the aDMN, left paracentral lobule of the SMN, and left lingual gyrus and calcarine of the visual network in early-onset BD patients. There was no significant correlation between FC values of differential brain regions within resting-state networks (RSNs) and neuropsychological scores (uncorrected p > 0.05). In addition, the FNC among the pDMN-auditory network, pDMN-visual network, left frontoparietal network (lFPN)-visual network, lFPN-aDMN and dorsal attention network-ventral attention network (DAN-VAN) were increased in early-onset BD patients. The zFNC of the pDMN-visual network was positively correlated with the anxiety/somatization score (r = 0.5833, p < 0.0001) and sleep disorders (r = 0.6150, p < 0.0001). The zFNC of the lFPN-aDMN was positively correlated with despair (r = 0.4505, p = 0.004 × 10 < 0.05 after Bonferroni correction). The zFNC of the DAN-VAN was positively correlated with cognitive impairment (r = 0.4598, p = 0.0032 × 10 < 0.05 after Bonferroni correction). The zFNC of the DAN-VAN showed a positive correlation trend with the Hamilton Depression Scale (HAMD) total score (r = 0.4404, p = 0.005 × 10 = 0.05 after Bonferroni correction). CONCLUSIONS Patients with early-onset BD showed changes in a wide range of neural functional networks, involving changes in executive control, attention, perceptual regulation, cognition and other neural networks, which may provide new imaging evidence for understanding the pathogenesis of early-onset BD and for therapeutic intervention targets.
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Affiliation(s)
- Ziyi Hu
- Department of Radiology, the First Affiliated Hospital of Nanchang university, Nanchang 330006, China
| | - Yongming Tan
- Department of Radiology, the First Affiliated Hospital of Nanchang university, Nanchang 330006, China
| | - Fuqing Zhou
- Department of Radiology, the First Affiliated Hospital of Nanchang university, Nanchang 330006, China
| | - Laichang He
- Department of Radiology, the First Affiliated Hospital of Nanchang university, Nanchang 330006, China.
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10
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Han Z, Liu T, Shi Z, Zhang J, Suo D, Wang L, Chen D, Wu J, Yan T. Investigating the heterogeneity within the somatosensory-motor network and its relationship with the attention and default systems. PNAS NEXUS 2023; 2:pgad276. [PMID: 37693210 PMCID: PMC10485902 DOI: 10.1093/pnasnexus/pgad276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 06/23/2023] [Accepted: 08/14/2023] [Indexed: 09/12/2023]
Abstract
The somatosensory-motor network (SMN) not only plays an important role in primary somatosensory and motor processing but is also central to many disorders. However, the SMN heterogeneity related to higher-order systems still remains unclear. Here, we investigated SMN heterogeneity from multiple perspectives. To characterize the SMN substructures in more detail, we used ultra-high-field functional MRI to delineate a finer-grained cortical parcellation containing 430 parcels that is more homogenous than the state-of-the-art parcellation. We personalized the new parcellation to account for individual differences and identified multiscale individual-specific brain structures. We found that the SMN subnetworks showed distinct resting-state functional connectivity (RSFC) patterns. The Hand subnetwork was central within the SMN and exhibited stronger RSFC with the attention systems than the other subnetworks, whereas the Tongue subnetwork exhibited stronger RSFC with the default systems. This two-fold differentiation was observed in the temporal ordering patterns within the SMN. Furthermore, we characterized how the distinct attention and default streams were carried forward into the functions of the SMN using dynamic causal modeling and identified two behavioral domains associated with this SMN fractionation using meta-analytic tools. Overall, our findings provided important insights into the heterogeneous SMN organization at the system level and suggested that the Hand subnetwork may be preferentially involved in exogenous processes, whereas the Tongue subnetwork may be more important in endogenous processes.
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Affiliation(s)
- Ziteng Han
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Tiantian Liu
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Zhongyan Shi
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Jian Zhang
- School of Mechatronical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Dingjie Suo
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Li Wang
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Duanduan Chen
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Tianyi Yan
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
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11
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Petro NM, Picci G, Embury CM, Ott LR, Penhale SH, Rempe MP, Johnson HJ, Willett MP, Wang YP, Stephen JM, Calhoun VD, Doucet GE, Wilson TW. Developmental differences in functional organization of multispectral networks. Cereb Cortex 2023; 33:9175-9185. [PMID: 37279931 PMCID: PMC10505424 DOI: 10.1093/cercor/bhad193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 05/11/2023] [Accepted: 05/17/2023] [Indexed: 06/08/2023] Open
Abstract
Assessing brain connectivity during rest has become a widely used approach to identify changes in functional brain organization during development. Generally, previous works have demonstrated that brain activity shifts from more local to more distributed processing from childhood into adolescence. However, the majority of those works have been based on functional magnetic resonance imaging measures, whereas multispectral functional connectivity, as measured using magnetoencephalography (MEG), has been far less characterized. In our study, we examined spontaneous cortical activity during eyes-closed rest using MEG in 101 typically developing youth (9-15 years old; 51 females, 50 males). Multispectral MEG images were computed, and connectivity was estimated in the canonical delta, theta, alpha, beta, and gamma bands using the imaginary part of the phase coherence, which was computed between 200 brain regions defined by the Schaefer cortical atlas. Delta and alpha connectivity matrices formed more communities as a function of increasing age. Connectivity weights predominantly decreased with age in both frequency bands; delta-band differences largely implicated limbic cortical regions and alpha band differences in attention and cognitive networks. These results are consistent with previous work, indicating the functional organization of the brain becomes more segregated across development, and highlight spectral specificity across different canonical networks.
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Affiliation(s)
- Nathan M Petro
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Giorgia Picci
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, United States
| | - Christine M Embury
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Lauren R Ott
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - Samantha H Penhale
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Maggie P Rempe
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, United States
| | - Hallie J Johnson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Madelyn P Willett
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, United States
| | | | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, United States
| | - Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, United States
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, United States
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12
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Liu X, Zhao Y, Suo X, Zhang X, Pan N, Kemp GJ, Gong Q, Wang S. Psychological resilience mediates the protective role of default-mode network functional connectivity against COVID-19 vicarious traumatization. Transl Psychiatry 2023; 13:231. [PMID: 37380702 DOI: 10.1038/s41398-023-02525-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 06/12/2023] [Accepted: 06/13/2023] [Indexed: 06/30/2023] Open
Abstract
Vicarious traumatization (VT), a negative reaction to witnessing others' trauma, has been experienced by some people during the COVID-19 pandemic, and can lead to mental health problems. This study aimed to identify functional brain markers of COVID-specific VT and explore the psychological mechanism underlying the brain-VT link. One hundred healthy participants underwent resting-state functional magnetic resonance imaging before the pandemic (October 2019-January 2020) and completed VT measurement during the pandemic (February-April 2020). Whole-brain correlation analysis based on global functional connectivity density (FCD) mapping revealed that VT was negatively correlated with FCD in the right inferior temporal gyrus (ITG) (i.e., the lower FCD in ITG, the worse the VT), identified by mapping onto known large-scale networks as part of the default-mode network (DMN). Resting-state functional connectivity (RSFC) analysis using ITG as seed found that VT was predicted by lower functional connectivity between ITG and other DMN regions including left medial prefrontal cortex, left orbitofrontal cortex, right superior frontal gyrus, right inferior parietal lobule and bilateral precuneus (i.e., the lower the ITG-DMN connectivity, the worse the VT). Mediation analyses suggested that psychological resilience served as a mediator in these associations of ITG FCD and ITG-DMN RSFC with VT. Our results provide novel evidence on the brain basis of VT and emphasize psychological resilience as an important link from DMN functional connectivity to COVID-specific-VT. This may facilitate public health interventions by helping identify individuals at risk of stress- and trauma-related psychopathologies.
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Affiliation(s)
- Xiqin Liu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yajun Zhao
- School of Education and Psychology, Southwest Minzu University, Chengdu, China
| | - Xueling Suo
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Xun Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Nanfang Pan
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Song Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.
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13
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Holmes SE, Asch RH, Davis MT, DellaGioia N, Pashankar N, Gallezot JD, Nabulsi N, Matuskey D, Sanacora G, Carson RE, Blumberg HP, Esterlis I. Differences in Quantification of the Metabotropic Glutamate Receptor 5 Across Bipolar Disorder and Major Depressive Disorder. Biol Psychiatry 2023; 93:1099-1107. [PMID: 36764853 PMCID: PMC10164841 DOI: 10.1016/j.biopsych.2022.10.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/06/2022] [Accepted: 10/30/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Understanding the neurobiology underlying bipolar disorder (BD) versus major depressive disorder (MDD) is crucial for accurate diagnosis and for driving the discovery of novel treatments. A promising target is the metabotropic glutamate receptor 5 (mGluR5), a modulator of glutamate transmission associated with synaptic plasticity. We measured mGluR5 availability in individuals with MDD and BD for the first time using positron emission tomography. METHODS Individuals with BD (n = 17 depressed; n = 10 euthymic) or MDD (n = 17) and healthy control (HC) individuals (n = 18) underwent imaging with [18F]FPEB positron emission tomography to quantify mGluR5 availability in regions of the prefrontal cortex, which was compared across groups and assessed in relation to depressive symptoms and cognitive function. RESULTS Prefrontal cortex mGluR5 availability was significantly different across groups (F6,116 = 2.18, p = .050). Specifically, mGluR5 was lower in BD versus MDD and HC groups, with no difference between MDD and HC groups. Furthermore, after dividing the BD group, mGluR5 was lower in both BD-depression and BD-euthymia groups versus both MDD and HC groups across regions of interest. Interestingly, lower dorsolateral prefrontal cortex mGluR5 was associated with worse depression in MDD (r = -0.67, p = .005) but not in BD. Significant negative correlations were observed between mGluR5 and working memory in MDD and BD-depression groups. CONCLUSIONS This work suggests that mGluR5 could be helpful in distinguishing BD and MDD as a possible treatment target for depressive symptoms in MDD and for cognitive alterations in both disorders. Further work is needed to confirm differentiating roles for mGluR5 in BD and MDD and to probe modulation of mGluR5 as a preventive/treatment strategy.
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Affiliation(s)
- Sophie E Holmes
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Ruth H Asch
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Margaret T Davis
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut; Department of Psychology, Yale University, New Haven, Connecticut
| | - Nicole DellaGioia
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Neha Pashankar
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Jean-Dominique Gallezot
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Nabeel Nabulsi
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - David Matuskey
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Gerard Sanacora
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Hilary P Blumberg
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - Irina Esterlis
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut; Child Study Center, Yale School of Medicine, New Haven, Connecticut; Clinical Neurosciences Division, U.S. Department of Veteran Affairs National Center for Posttraumatic Stress Disorder, VA Connecticut Healthcare System, West Haven, Connecticut.
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14
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Romeo Z, Marino M, Mantini D, Angrilli A, Spironelli C. Language Network Connectivity of Euthymic Bipolar Patients Is Altered at Rest and during a Verbal Fluency Task. Biomedicines 2023; 11:1647. [PMID: 37371743 DOI: 10.3390/biomedicines11061647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/25/2023] [Accepted: 05/31/2023] [Indexed: 06/29/2023] Open
Abstract
Abnormalities of the Language Network (LN) have been found in different psychiatric conditions (e.g., schizophrenia and bipolar disorder), supporting the hypothesis that language plays a central role in a high-level integration/connectivity of second-level cognitive processes and the underlying cortical regions. This view implies a continuum of shared neural alterations along the psychotic disorder spectrum. In particular, bipolar disorder (BD) patients were recently documented to have an altered LN asymmetry during resting state. The extent to which the LN architecture is altered and stable also during a language task has yet to be investigated. To address this question, we analyzed fMRI data recorded during an open-eyes resting state session and a silent verbal fluency task in 16 euthymic BD patients and 16 matched healthy controls (HC). Functional connectivity in the LN of both groups was computed using spatial independent component analysis, and group comparisons were carried out to assess the network organization during both rest and active linguistic task conditions. The LN of BD patients involved left and right brain areas during both resting state and linguistic task. Compared to the left-lateralized network found in HC, the BD group was characterized by two anterior clusters (in left frontal and right temporo-insular regions) and the disengagement of the posterior language areas, especially during the verbal fluency task. Our findings support the hypothesis that reduced language lateralization may represent a biological marker across different psychotic disorders and that the altered language network connectivity found at rest in bipolar patients is stable and pervasive as it is also impaired during a verbal fluency task.
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Affiliation(s)
- Zaira Romeo
- Department of General Psychology, University of Padova, 35131 Padova, Italy
| | - Marco Marino
- Department of General Psychology, University of Padova, 35131 Padova, Italy
- Movement Control and Neuroplasticity Research Group, KU Leuven, 3001 Leuven, Belgium
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, 3001 Leuven, Belgium
| | - Alessandro Angrilli
- Department of General Psychology, University of Padova, 35131 Padova, Italy
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Chiara Spironelli
- Department of General Psychology, University of Padova, 35131 Padova, Italy
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
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15
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Lei W, Xiao Q, Wang C, Cai Z, Lu G, Su L, Zhong Y. The disruption of functional connectome gradient revealing networks imbalance in pediatric bipolar disorder. J Psychiatr Res 2023; 164:72-79. [PMID: 37331260 DOI: 10.1016/j.jpsychires.2023.05.084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/17/2023] [Accepted: 05/30/2023] [Indexed: 06/20/2023]
Abstract
OBJECTIVE Pediatric bipolar disorder (PBD) is a psychiatric disorder marked by alteration of brain networks. However, the understanding of these alterations in topological organization still unclear. This study aims to leverage the functional connectome gradient to examine changes in functional network hierarchy in PBD. METHOD Connectome gradients were used to scrutinize the differences between functional gradient map in PBD patients (n = 68, aged 11 to 18) and healthy controls (HC, n = 37, aged 11 to 18). The association between regional altered gradient scores and clinical factors was examined. We further used Neurosynth to determine the correlation of the cognitive terms with the PBD principal gradient changes. RESULTS Global topographic alterations were exhibited in the connectome gradient in PBD patients, involving gradient variance, explanation ratio, gradient range, and gradient dispersion in the principal gradient. Regionally, PBD patients revealed that the default mode network (DMN) held the most majority of the brain areas with higher gradient scores, whereas a higher proportion of brain regions with lower gradient scores in the sensorimotor network (SMN). These regional gradient differences exhibited significant correlation with clinical features and meta-analysis terms including cognitive behavior and sensory processing. CONCLUSION Functional connectome gradient presents a thorough investigation of large-scale networks hierarchy in PBD patients. This exhibited excessive segregation between DMN and SMN supports the theory of imbalance in top-down control and bottom-up in PBD and provides a possible biomarker for diagnostic assessment.
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Affiliation(s)
- Wenkun Lei
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, 210097, China; Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing, Jiangsu, 210097, China; International Joint Laboratory of Child and Adolescent Psychological Development and Crisis Intervention, Nanjing, Jiangsu, 210097, China
| | - Qian Xiao
- Mental Health Centre of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Chun Wang
- Department of Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Zhen Cai
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, 210097, China; Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing, Jiangsu, 210097, China; International Joint Laboratory of Child and Adolescent Psychological Development and Crisis Intervention, Nanjing, Jiangsu, 210097, China
| | - Guangming Lu
- Department of Medical Imaging, Nanjing General Hospital of Nanjing Military Command, Nanjing, Jiangsu, 210002, China
| | - Linyan Su
- The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410008, China
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, 210097, China; Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing, Jiangsu, 210097, China; International Joint Laboratory of Child and Adolescent Psychological Development and Crisis Intervention, Nanjing, Jiangsu, 210097, China.
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16
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Massalha Y, Maggioni E, Callari A, Brambilla P, Delvecchio G. A review of resting-state fMRI correlations with executive functions and social cognition in bipolar disorder. J Affect Disord 2023; 334:337-351. [PMID: 37003435 DOI: 10.1016/j.jad.2023.03.084] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 03/20/2023] [Accepted: 03/25/2023] [Indexed: 04/03/2023]
Abstract
BACKGROUND Deficits in executive functions (EF) and social cognition (SC) are often observed in bipolar disorder (BD), leading to a severe impairment in engaging a functional interaction with the others and the surrounding environment. Therefore, in recent years, resting-state functional magnetic resonance imaging (rs-fMRI) studies on BD tried to identify the neural underpinnings of these cognitive domains by exploring the association between the intrinsic functional connectivity (FC) and the scores in clinical scales evaluating these domains. METHODS A bibliographic search on PubMed and Scopus of studies evaluating the correlations between rs-fMRI findings and EF and/or SC in BD was conducted until March 2022. Ten studies met the inclusion criteria. RESULTS Overall, the results of the reviewed studies showed that BD patients had FC deficits compared to healthy controls (HC) in selective resting-state networks involved in EF and SC, which include the default mode network, especially the link between medial prefrontal cortex and posterior cingulate cortex, and the sensory-motor network. Finally, it also emerged the predominant role of alterations in prefrontal connections in explaining the cognitive deficits in BD patients. LIMITATIONS The heterogeneity of the reviewed studies, in terms of cognitive domains explored and neuroimaging acquisitions, limited the comparability of the findings. CONCLUSIONS rs-fMRI studies could help deepen the brain network alterations underlying EF and SC deficits in BD, pointing the attention on the neuronal underpinning of cognition, whose knowledge may lead to the development of new neurobiological-based approaches to improve the quality of life of these patients.
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Affiliation(s)
- Yara Massalha
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
| | - Eleonora Maggioni
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20122 Milan, Italy
| | - Antonio Callari
- Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, 20122 Milan, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy; Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, 20122 Milan, Italy
| | - Giuseppe Delvecchio
- Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, 20122 Milan, Italy.
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17
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Liang S, Cao B, Deng W, Kong X, Zhao L, Jin Y, Ma X, Wang Y, Li X, Wang Q, Guo W, Du X, Sham PC, Greenshaw AJ, Li T. Functional dysconnectivity of anterior cingulate subregions in schizophrenia and psychotic and nonpsychotic bipolar disorder. Schizophr Res 2023; 254:155-162. [PMID: 36889182 DOI: 10.1016/j.schres.2023.02.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 04/20/2022] [Accepted: 02/20/2023] [Indexed: 03/10/2023]
Abstract
Aberrant resting-state functional connectivity (FC) of anterior cingulate cortex (ACC) has been implicated in the pathophysiology of schizophrenia and bipolar disorder (BP). This study investigated the subregional FC of ACC across schizophrenia and psychotic (PBP) and nonpsychotic BP (NPBP) and the relationship between brain functional alterations and clinical manifestations. A total of 174 first-episode medication-naive patients with schizophrenia (FES), 80 patients with PBP, 77 patients with NPBP and 173 demographically matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Brain-wide FC of ACC subregions was computed for each individual, and compared between the groups. General intelligence was evaluated using the short version of the Wechsler Adult Intelligence Scale. Relationships between FC and various clinical and cognitive variables were estimated using the skipped correlation. The FES, PBP and NPBP groups showed differing connectivity patterns in the left caudal, dorsal and perigenual ACC. Transdiagnostic dysconnectivity was found in the subregional ACC associated with cortical, limbic, striatal and cerebellar regions. Disorder-specific dysconnectivity in FES was identified between the left perigenual ACC and bilateral orbitofrontal cortex, and the left caudal ACC coupling with the default mode network (DMN) and visual processing region was correlated with psychotic symptoms. In the PBP group, FC between the left dorsal ACC and the right caudate was correlated with psychotic symptoms, and FC connected with the DMN was associated with affective symptoms. The current findings confirmed that subregional ACC dysconnectivity could be a key transdiagnostic feature and associated with differing clinical symptomology across schizophrenia and PBP.
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Affiliation(s)
- Sugai Liang
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang, China; Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Bo Cao
- Department of Psychiatry, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Wei Deng
- Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Xiangzhen Kong
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China
| | - Liansheng Zhao
- Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yan Jin
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang, China
| | - Xiaohong Ma
- Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yingcheng Wang
- Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Xiaojing Li
- Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Qiang Wang
- Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Wanjun Guo
- Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Xiangdong Du
- Suzhou Psychiatry Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu, China
| | - Pak C Sham
- State Key Laboratory of Brain and Cognitive Sciences, Centre for Genomic Sciences, & Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam 999077, Hong Kong, China
| | - Andrew J Greenshaw
- Department of Psychiatry, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Tao Li
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang, China; Mental Health Centre & West China Brain Research Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China; Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, China.
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18
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Chang Z, Wang X, Wu Y, Lin P, Wang R. Segregation, integration and balance in resting-state brain functional networks associated with bipolar disorder symptoms. Hum Brain Mapp 2023; 44:599-611. [PMID: 36161679 PMCID: PMC9842930 DOI: 10.1002/hbm.26087] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/19/2022] [Accepted: 09/02/2022] [Indexed: 01/25/2023] Open
Abstract
Bipolar disorder (BD) is a serious mental disorder involving widespread abnormal interactions between brain regions, and it is believed to be associated with imbalanced functions in the brain. However, how this brain imbalance underlies distinct BD symptoms remains poorly understood. Here, we used a nested-spectral partition (NSP) method to study the segregation, integration, and balance in resting-state brain functional networks in BD patients and healthy controls (HCs). We first confirmed that there was a high deviation in the brain functional network toward more segregation in BD patients than in HCs and that the limbic system had the largest alteration. Second, we demonstrated a network balance of segregation and integration that corresponded to lower anxiety in BD patients but was not related to other symptoms. Subsequently, based on a machine-learning approach, we identified different system-level mechanisms underlying distinct BD symptoms and found that the features related to the brain network balance could predict BD symptoms better than graph theory analyses. Finally, we studied attention-deficit/hyperactivity disorder (ADHD) symptoms in BD patients and identified specific patterns that distinctly predicted ADHD and BD scores, as well as their shared common domains. Our findings supported an association of brain imbalance with anxiety symptom in BD patients and provided a potential network signature for diagnosing BD. These results contribute to further understanding the neuropathology of BD and to screening ADHD in BD patients.
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Affiliation(s)
- Zhao Chang
- College of ScienceXi'an University of Science and TechnologyXi'anChina
| | - Xinrui Wang
- College of ScienceXi'an University of Science and TechnologyXi'anChina
| | - Ying Wu
- State Key Laboratory for Strength and Vibration of Mechanical StructuresSchool of Aerospace Engineering, Xi'an Jiaotong UniversityXi'anChina
- National Demonstration Center for Experimental Mechanics EducationXi'an Jiaotong UniversityXi'anChina
| | - Pan Lin
- Center for Mind & Brain Sciences and Cognition and Human Behavior Key Laboratory of Hunan ProvinceHunan Normal UniversityChangshaHunanChina
| | - Rong Wang
- College of ScienceXi'an University of Science and TechnologyXi'anChina
- State Key Laboratory for Strength and Vibration of Mechanical StructuresSchool of Aerospace Engineering, Xi'an Jiaotong UniversityXi'anChina
- National Demonstration Center for Experimental Mechanics EducationXi'an Jiaotong UniversityXi'anChina
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19
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Zhang Q, Li X, Yan H, Wang Y, Ou Y, Yu Y, Liang J, Liao H, Wu W, Mai X, Xie G, Guo W. Associations between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential indicators in major depressive disorder. Front Neurosci 2023; 16:1056868. [PMID: 36711124 PMCID: PMC9875062 DOI: 10.3389/fnins.2022.1056868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/26/2022] [Indexed: 01/13/2023] Open
Abstract
Background This study aimed to investigate the correlations between abnormal spontaneous neural activity measured with fractional amplitude of low-frequency fluctuations (fALFF) and clinical variables, eye movements, and event-related potential indicators in patients with major depressive disorder (MDD). Methods We recruited 42 patients with MDD and 42 healthy controls (HCs) and collected their clinical variables, eye movement, event-related potential, and resting-state functional magnetic resonance imaging (rs-fMRI) data. The fALFF, support vector machine (SVM), and correlation analysis were used to analyze the data. Results The results of the study showed that the fALFF values of the sensorimotor network, including the right middle temporal gyrus, right cerebellar Crus2, left occipital gyrus, and left middle temporal gyrus, were significantly higher compared to HCs. Correlation analysis showed that the abnormal fALFF value of the right cerebellar Crus2 was inversely correlated with the active coping scores of the Simplified Coping Style Questionnaire in the patients (r = -0.307, p = 0.048). No correlation was observed between abnormal fALFF values and other clinical symptoms, neuropsychological tests, eye movements, and event-related potential-related indicators in patients with MDD. fALFF values in the left middle temporal gyrus could be used to distinguish patients with MDD from HCs with an accuracy of 78.57%. Conclusions Patients with MDD exhibited enhanced spontaneous neural activity in the sensorimotor network. No associations were found between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential related indicators in MDD.
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Affiliation(s)
- Qinqin Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiaoling Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yun Wang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yang Yu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Hairong Liao
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wanting Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiancong Mai
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China,*Correspondence: Guojun Xie ✉
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China,Wenbin Guo ✉
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20
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Xi C, Liu Z, Zeng C, Tan W, Sun F, Yang J, Palaniyappan L. The centrality of working memory networks in differentiating bipolar type I depression from unipolar depression: A task-fMRI study. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2023; 68:22-32. [PMID: 35244484 PMCID: PMC9720478 DOI: 10.1177/07067437221078646] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVES Up to 70%-80% of patients with bipolar disorder are misdiagnosed as having major depressive disorder (MDD), leading to both delayed intervention and worsening disability. Differences in the cognitive neurophysiology may serve to distinguish between the depressive phase of type 1 bipolar disorder (BDD-I) from MDD, though this remains to be demonstrated. To this end, we investigate the discriminatory signal in the topological organization of the functional connectome during a working memory (WM) task in BDD-I and MDD, as a candidate identification approach. METHODS We calculated and compared the degree centrality (DC) at the whole-brain voxel-wise level in 31 patients with BDD-I, 35 patients with MDD, and 80 healthy controls (HCs) during an n-back task. We further extracted the distinct DC patterns in the two patient groups under different WM loads and used machine learning approaches to determine the distinguishing ability of the DC map. RESULTS Patients with BDD-I had lower accuracy and longer reaction time (RT) than HCs at high WM loads. BDD-I is characterized by decreased DC in the default mode network (DMN) and the sensorimotor network (SMN) when facing high WM load. In contrast, MDD is characterized by increased DC in the DMN during high WM load. Higher WM load resulted in better classification performance, with the distinct aberrant DC maps under 2-back load discriminating the two disorders with 90.91% accuracy. CONCLUSIONS The distributed brain connectivity during high WM load provides novel insights into the neurophysiological mechanisms underlying cognitive impairment of depression. This could potentially distinguish BDD-I from MDD if replicated in future large-scale evaluations of first-episode depression with longitudinal confirmation of diagnostic transition.
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Affiliation(s)
- Chang Xi
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Zhening Liu
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Can Zeng
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Wenjian Tan
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Fuping Sun
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Jie Yang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Lena Palaniyappan
- 113611Robarts Research Institute, Western University, London, Canada.,Departments of Psychiatry and Medical Biophysics, Schulich School of Medicine, Western University, London, Canada
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21
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Zou W, Song P, Lu W, Shao R, Zhang R, Yau SY, Yuan TF, Wang Y, Lin K. Global hippocampus functional connectivity as a predictive neural marker for conversion to future mood disorder in unaffected offspring of bipolar disorder parents. Asian J Psychiatr 2022; 78:103307. [PMID: 36332319 DOI: 10.1016/j.ajp.2022.103307] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Revised: 09/06/2022] [Accepted: 09/17/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Hippocampus-related functional alteration in genetically at-risk individuals may reflect an endophenotype of a mood disorder. Herein, we performed a prospective study to investigate whether baseline hippocampus functional connectivity (FC) in offspring of patients with bipolar disorder (BD) would predict subsequent conversion to mood disorder. METHODS Eighty bipolar offspring and 40 matched normal controls (NC) underwent resting state functional MRI (rsfMRI) scanning on a 3.0 Tesla MR scanner. The offspring were subdivided into asymptomatic offspring (AO) (n = 41) and symptomatic offspring (SO) (n = 39) according to whether they manifested subthreshold mood symptoms. After identifying the different hippocampus FCs between the AO and SO, a logistic regression analysis was conducted to investigate whether the baseline hippocampus FCs predicted a future mood disorder during a 6-year follow-up. RESULTS We identified seven baseline para/hippocampus FCs that showed differences between AO and SO, which were entered as predictive features in the logistic regressive model. Of the 80 bipolar offspring entering the analysis, the FCs between left hippocampus and left precuneus, and between right hippocampus and left posterior cingulate, showed a discriminative capacity for predicting future mood disorder (area-under-curve, or AUC=75.76 % and 75.00 % respectively), and for predicting BD onset (AUC=77.46 % and 81.63 %, respectively). CONCLUSIONS The present findings revealed high predictive utility of the hippocampus resting state FCs for future mood disorder and BD onset in individuals at familial risk. These neural markers can potentially improve early detection of individuals carrying particularly high risk for future mood disorder.
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Affiliation(s)
- Wenjin Zou
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Peilun Song
- School of Information Engineering, Zhengzhou University, Zhengzhou, China
| | - Weicong Lu
- Department of Affective Disorders, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Robin Shao
- Laboratory of Neuropsychology and Laboratory of Social Cognitive Affective, Neuroscience, Department of Psychology, University of Hong Kong, Hong Kong
| | - Ruoxi Zhang
- Department of Affective Disorders, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Suk-Yu Yau
- Department of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong
| | - Ti-Fei Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China.
| | - Yaping Wang
- School of Information Engineering, Zhengzhou University, Zhengzhou, China.
| | - Kangguang Lin
- Department of Affective Disorders, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; School of Health and Life Sciences, University of Health and Rehabilitation Sciences, No. 17, Shandong Road, Shinan district, Qingdao City, Shandong Province, China.
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22
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Riedel P, Lee J, Watson CG, Jimenez AM, Reavis EA, Green MF. Reorganization of the functional connectome from rest to a visual perception task in schizophrenia and bipolar disorder. Psychiatry Res Neuroimaging 2022; 327:111556. [PMID: 36327867 PMCID: PMC10611423 DOI: 10.1016/j.pscychresns.2022.111556] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 09/13/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022]
Abstract
Functional connectome organization is altered in schizophrenia (SZ) and bipolar disorder (BD). However, it remains unclear whether network reorganization during a task relative to rest is also altered in these disorders. This study examined connectome organization in patients with SZ (N = 43) and BD (N = 42) versus healthy controls (HC; N = 39) using fMRI data during a visual object-perception task and at rest. Graph analyses were conducted for the whole-brain network using indices selected a priori: three reflecting network segregation (clustering coefficient, local efficiency, modularity), two reflecting integration (characteristic path length, global efficiency). Group differences were limited to network segregation and were more evident in SZ (clustering coefficient, modularity) than in BD (clustering coefficient) compared to HC. State differences were found across groups for segregation (local efficiency) and integration (characteristic path length). There was no group-by-state interaction for any graph index. In summary, aberrant network organization compared to HC was confirmed, and was more evident in SZ than in BD. Yet, reorganization was largely intact in both disorders. These findings help to constrain models of dysconnection in SZ and BD, suggesting that the extent of functional dysconnectivity in these disorders tends to persist across changes in mental state.
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Affiliation(s)
- Philipp Riedel
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90024, USA; Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Würzburger Straße 35, Dresden 01187, Germany.
| | - Junghee Lee
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90024, USA; Desert Pacific Mental Illness Research, Education, and Clinical Center, Greater Los Angeles VA Healthcare System, Bldg. 210, 11301 Wilshire Blvd, Los Angeles, CA 90073, USA; Department of Psychiatry and Behavioral Neurobiology, School of Medicine, The University of Alabama at Birmingham, SC 560, 1720 2nd Ave S, Birmingham, AL 35294-0017, USA
| | - Christopher G Watson
- Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Amy M Jimenez
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90024, USA; Desert Pacific Mental Illness Research, Education, and Clinical Center, Greater Los Angeles VA Healthcare System, Bldg. 210, 11301 Wilshire Blvd, Los Angeles, CA 90073, USA
| | - Eric A Reavis
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90024, USA; Desert Pacific Mental Illness Research, Education, and Clinical Center, Greater Los Angeles VA Healthcare System, Bldg. 210, 11301 Wilshire Blvd, Los Angeles, CA 90073, USA
| | - Michael F Green
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90024, USA; Desert Pacific Mental Illness Research, Education, and Clinical Center, Greater Los Angeles VA Healthcare System, Bldg. 210, 11301 Wilshire Blvd, Los Angeles, CA 90073, USA
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23
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Altered language network lateralization in euthymic bipolar patients: a pilot study. Transl Psychiatry 2022; 12:435. [PMID: 36202786 PMCID: PMC9537562 DOI: 10.1038/s41398-022-02202-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 09/20/2022] [Accepted: 09/22/2022] [Indexed: 11/09/2022] Open
Abstract
Bipolar patients (BD) in the euthymic phase show almost no symptoms, nevertheless possibility of relapse is still present. We expected to find a psychobiological trace of their vulnerability by analyzing a specific network-the Language Network (LN)-connecting many high-level processes and brain regions measured at rest. According to Crow's hypothesis on the key role of language in the origin of psychoses, we expected an altered asymmetry of the LN in euthymic BDs. Eighteen euthymic BD patients (10 females; age = 54.50 ± 11.38 years) and 16 healthy controls (HC) (8 females; age = 51.16 ± 11.44 years) underwent a functional magnetic resonance imaging scan at rest. The LN was extracted through independent component analysis. Then, LN time series was used to compute the fractional amplitude of the low-frequency fluctuation (fALFF) index, which was then correlated with clinical scales. Compared with HC, euthymic patients showed an altered LN with greater activation of Broca's area right homologous and anterior insula together with reduced activation of left middle temporal gyrus. The normalized fALFF analysis on BD patients' LN time series revealed that the Slow-5 fALFF band was positively correlated with residual mania symptoms but negatively associated with depression scores. In line with Crow's hypothesis postulating an altered language hemispheric asymmetry in psychoses, we revealed, in euthymic BD patients, a right shift involving both the temporal and frontal linguistic hubs. The fALFF applied to LN allowed us to highlight a number of significant correlations of this measure with residual mania and depression psychiatric symptoms.
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Dai P, Xiong T, Zhou X, Ou Y, Li Y, Kui X, Chen Z, Zou B, Li W, Huang Z, The Rest-Meta-Mdd Consortium. The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data. Behav Brain Res 2022; 435:114058. [PMID: 35995263 DOI: 10.1016/j.bbr.2022.114058] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 08/07/2022] [Accepted: 08/10/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND The current diagnosis of major depressive disorder (MDD) is mainly based on the patient's self-report and clinical symptoms. Machine learning methods are used to identify MDD using resting-state functional magnetic resonance imaging (rs-fMRI) data. However, due to large site differences in multisite rs-fMRI data and the difficulty of sample collection, most of the current machine learning studies use small sample sizes of rs-fMRI datasets to detect the alterations of functional connectivity (FC) or network attribute (NA), which may affect the reliability of the experimental results. METHODS Multisite rs-fMRI data were used to increase the size of the sample, and then we extracted the functional connectivity (FC) and network attribute (NA) features from 1611 rs-fMRI data (832 patients with MDD (MDDs) and 779 healthy controls (HCs)). ComBat algorithm was used to harmonize the data variances caused by the multisite effect, and multivariate linear regression was used to remove age and sex covariates. Two-sample t-test and wrapper-based feature selection methods (support vector machine recursive feature elimination with cross-validation (SVM-RFECV) and LightGBM's "feature_importances_" function) were used to select important features. The Shapley additive explanations (SHAP) method was used to assign the contribution of features to the best classification effect model. RESULTS The best result was obtained from the LinearSVM model trained with the 136 important features selected by SVMRFE-CV. In the nested five-fold cross-validation (consisting of an outer and an inner loop of five-fold cross-validation) of 1611 data, the model achieved the accuracy, sensitivity, and specificity of 68.90 %, 71.75 %, and 65.84 %, respectively. The 136 important features were tested in a small dataset and obtained excellent classification results after balancing the ratio between patients with depression and HCs. CONCLUSIONS The combined use of FC and NA features is effective for classifying MDDs and HCs. The important FC and NA features extracted from the large sample dataset have some generalization performance and may be used as a reference for the altered brain functional connectivity networks in MDD.
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Affiliation(s)
- Peishan Dai
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Tong Xiong
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Xiaoyan Zhou
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Yilin Ou
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Yang Li
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Xiaoyan Kui
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Zailiang Chen
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Beiji Zou
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
| | - Weihui Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | - Zhongchao Huang
- Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China.
| | - The Rest-Meta-Mdd Consortium
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China; Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
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25
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Roberts G, Perry A, Ridgway K, Leung V, Campbell M, Lenroot R, Mitchell PB, Breakspear M. Longitudinal Changes in Structural Connectivity in Young People at High Genetic Risk for Bipolar Disorder. Am J Psychiatry 2022; 179:350-361. [PMID: 35343756 DOI: 10.1176/appi.ajp.21010047] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Recent studies of patients with bipolar disorder or at high genetic risk reveal structural dysconnections among key brain networks supporting cognitive and affective processes. Understanding the longitudinal trajectories of these networks across the peak age range of bipolar disorder onset could inform mechanisms of illness onset or resilience. METHODS Longitudinal diffusion-weighted MRI and phenotypic data were acquired at baseline and after 2 years in 183 individuals ages 12-30 years in two cohorts: 97 unaffected individuals with a first-degree relative with bipolar disorder (the high-risk group) and 86 individuals with no family history of mental illness (the control group). Whole-brain structural networks were derived using tractography, and longitudinal changes in these networks were studied using network-based statistics and mixed linear models. RESULTS Both groups showed widespread longitudinal changes, comprising both increases and decreases in structural connectivity, consistent with a shared neurodevelopmental process. On top of these shared changes, high-risk participants showed weakening of connectivity in a network encompassing the left inferior and middle frontal areas, left striatal and thalamic structures, the left fusiform, and right parietal and occipital regions. Connections among these regions strengthened in the control group, whereas they weakened in the high-risk group, shifting toward a cohort with established bipolar disorder. There was marginal evidence for even greater network weakening in those who had their first manic or hypomanic episode before follow-up. CONCLUSIONS Neurodevelopment from adolescence into early adulthood is associated with a substantial reorganization of structural brain networks. Differences in these maturational processes occur in a multisystem network in individuals at high genetic risk of bipolar disorder. This may represent a novel candidate to understand resilience and predict conversion to bipolar disorder.
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Affiliation(s)
- Gloria Roberts
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
| | - Alistair Perry
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
| | - Kate Ridgway
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
| | - Vivian Leung
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
| | - Megan Campbell
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
| | - Rhoshel Lenroot
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
| | - Philip B Mitchell
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
| | - Michael Breakspear
- School of Psychiatry, University of New South Wales, Randwick, Australia (Roberts, Ridgway, Leung, Mitchell); Department of Clinical Neurosciences, University of Cambridge, and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, U.K. (Perry); Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, U.K. (Perry); QIMR Berghofer Medical Research Institute, Brisbane, Australia (Perry, Breakspear); School of Psychology, College of Science, and Discipline of Psychiatry, College of Health and Medicine, University of Newcastle, Newcastle, Australia (Campbell, Breakspear); Neuroscience Research Australia, Randwick, Australia (Lenroot); University of New Mexico, Albuquerque (Lenroot)
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26
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Ping L, Zhou C, Sun S, Wang W, Zheng Q, You Z. Alterations in resting-state whole-brain functional connectivity pattern similarity in bipolar disorder patients. Brain Behav 2022; 12:e2580. [PMID: 35451228 PMCID: PMC9120726 DOI: 10.1002/brb3.2580] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 02/04/2022] [Accepted: 03/20/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Previous neuroimaging studies have extensively demonstrated many signs of functionally spontaneous local neural activity abnormalities in bipolar disorder (BD) patients using resting-state functional magnetic resonance imaging (rs-fMRI). However, how to identify the changes of voxel-wise whole-brain functional connectivity pattern and its corresponding functional connectivity changes remain largely unclear in BD patients. The current study aimed to investigate the voxel-wise changes of functional connectivity patterns in BD patients using publicly available data from the UCLA CNP LA5c Study. METHODS A total of 45 BD patients and 115 healthy control subjects were finally included and whole-brain functional connectivity homogeneity (FcHo) was calculated from their rs-fMRI. Moreover, the alterations of corresponding functional connectivity were subsequently identified using seed-based resting-state functional connectivity analysis. RESULTS Individuals with BD exhibited significantly lower FcHo values in the left middle temporal gyrus (MTG) when compared with controls. Functional connectivity findings further indicated decreased functional connectivities between left MTG and cluster 1 (left superior temporal gyrus, extend to middle temporal gyrus, rolandic operculum), cluster 2 (right postcentral, extend to right precentral) in BD patients. The mean FcHo values of left MTG were positively correlated with insomnia, middle scores and appetite increase scores. The mean functional connectivities of left MTG to cluster 1 were negatively correlated with grandiose delusions scores. While the functional connections between left MTG with cluster 2 were negatively correlated with delusions of reference and positively correlated with insomnia, middle scores in BD patients. CONCLUSIONS Our findings suggested that abnormal FcHo and functional connections in those areas of the brain involving DMN and SMN networks might play a crucial role in the neuropathology of BD.
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Affiliation(s)
| | - Cong Zhou
- School of Mental HealthJining Medical UniversityJiningChina
| | - Shan Sun
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
| | - Wenqiang Wang
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
| | - Qi Zheng
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
| | - Zhiyi You
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
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27
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Alteration of cortical functional networks in mood disorders with resting-state electroencephalography. Sci Rep 2022; 12:5920. [PMID: 35396563 PMCID: PMC8993886 DOI: 10.1038/s41598-022-10038-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 03/24/2022] [Indexed: 01/10/2023] Open
Abstract
Studies comparing bipolar disorder (BD) and major depressive disorder (MDD) are scarce, and the neuropathology of these disorders is poorly understood. This study investigated source-level cortical functional networks using resting-state electroencephalography (EEG) in patients with BD and MDD. EEG was recorded in 35 patients with BD, 39 patients with MDD, and 42 healthy controls (HCs). Graph theory-based source-level weighted functional networks were assessed via strength, clustering coefficient (CC), and path length (PL) in six frequency bands. At the global level, patients with BD and MDD showed higher strength and CC, and lower PL in the high beta band, compared to HCs. At the nodal level, compared to HCs, patients with BD showed higher high beta band nodal CCs in the right precuneus, left isthmus cingulate, bilateral paracentral, and left superior frontal; however, patients with MDD showed higher nodal CC only in the right precuneus compared to HCs. Although both MDD and BD patients had similar global level network changes, they had different nodal level network changes compared to HCs. Our findings might suggest more altered cortical functional network in patients with BD than in those with MDD.
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28
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Bi B, Che D, Bai Y. Neural network of bipolar disorder: Toward integration of neuroimaging and neurocircuit-based treatment strategies. Transl Psychiatry 2022; 12:143. [PMID: 35383150 PMCID: PMC8983759 DOI: 10.1038/s41398-022-01917-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 01/23/2023] Open
Abstract
Bipolar disorder (BD) is a complex psychiatric disorder characterized by dysfunctions in three domains including emotional processing, cognitive processing, and psychomotor dimensions. However, the neural underpinnings underlying these clinical profiles are not well understood. Based on the reported data, we hypothesized that (i) the core neuropathology in BD is damage in fronto-limbic network, which is associated with emotional dysfunction; (ii) changes in intrinsic brain network, such as sensorimotor network, salience network, default-mode network, central executive network are associated with impaired cognition function; and (iii) beyond the dopaminergic-driven basal ganglia-thalamo-cortical motor circuit modulated by other neurotransmitter systems, such as serotonin (subcortical-cortical modulation), the sensorimotor network and related motor function modulated by other non-motor networks such as the default-mode network are involved in psychomotor function. In this review, we propose a neurocircuit-based clinical characteristics and taxonomy to guide the treatment of BD. We draw on findings from neuropsychological and neuroimaging studies in BD and link variations in these clinical profiles to underlying neurocircuit dysfunctions. We consider pharmacological, psychotherapy, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions in BD. Finally, it is suggested that the methods of testing the neurocircuit-based taxonomy and important limitations to this approach should be considered in future.
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Affiliation(s)
- Bo Bi
- Department of Clinical Psychology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China.
| | - Dongfang Che
- grid.452787.b0000 0004 1806 5224Neurosurgery department, Shenzhen Children’s Hospital, Shenzhen, China
| | - Yuyin Bai
- grid.12981.330000 0001 2360 039XDepartment of Clinical Psychology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
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29
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Haas SS, Doucet GE, Antoniades M, Modabbernia A, Corcoran CM, Kahn RS, Kambeitz J, Kambeitz-Ilankovic L, Borgwardt S, Brambilla P, Upthegrove R, Wood SJ, Salokangas RK, Hietala J, Meisenzahl E, Koutsouleris N, Frangou S. Evidence of discontinuity between psychosis-risk and non-clinical samples in the neuroanatomical correlates of social function. Schizophr Res Cogn 2022; 29:100252. [PMID: 35391789 PMCID: PMC8980307 DOI: 10.1016/j.scog.2022.100252] [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: 01/06/2022] [Revised: 03/26/2022] [Accepted: 03/27/2022] [Indexed: 11/28/2022]
Abstract
Objective Social dysfunction is a major feature of clinical-high-risk states for psychosis (CHR-P). Prior research has identified a neuroanatomical pattern associated with impaired social function outcome in CHR-P. The aim of the current study was to test whether social dysfunction in CHR-P is neurobiologically distinct or in a continuum with the lower end of the normal distribution of individual differences in social functioning. Methods We used a machine learning classifier to test for the presence of a previously validated brain structural pattern associated with impaired social outcome in CHR-P (CHR-outcome-neurosignature) in the neuroimaging profiles of individuals from two non-clinical samples (total n = 1763) and examined its association with social function, psychopathology and cognition. Results Although the CHR-outcome-neurosignature could be detected in a subset of the non-clinical samples, it was not associated was adverse social outcomes or higher psychopathology levels. However, participants whose neuroanatomical profiles were highly aligned with the CHR-outcome-neurosignature manifested subtle disadvantage in fluid (PFDR = 0.004) and crystallized intelligence (PFDR = 0.01), cognitive flexibility (PFDR = 0.02), inhibitory control (PFDR = 0.01), working memory (PFDR = 0.0005), and processing speed (PFDR = 0.04). Conclusions We provide evidence of divergence in brain structural underpinnings of social dysfunction derived from a psychosis-risk enriched population when applied to non-clinical samples. This approach appears promising in identifying brain mechanisms bound to psychosis through comparisons of patient populations to non-clinical samples with the same neuroanatomical profiles.
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Affiliation(s)
- Shalaila S. Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - Gaelle E. Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, 14090 Mother Teresa Lane, Boys Town, NE 68010, USA
| | - Mathilde Antoniades
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, USA
| | - Amirhossein Modabbernia
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - Cheryl M. Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - René S. Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - Joseph Kambeitz
- University of Cologne, Faculty of Medicine and University Hospital of Cologne, Kerpener Strasse 62, 50937 Cologne, Germany
| | - Lana Kambeitz-Ilankovic
- University of Cologne, Faculty of Medicine and University Hospital of Cologne, Kerpener Strasse 62, 50937 Cologne, Germany,Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Nussbaumstraße 7, 80336 München, Germany
| | - Stefan Borgwardt
- Department of Psychiatry, University Psychiatric Clinics (UPK), University of Basel, Wilhelm Klein-Strasse 27, 4002 Basel, Switzerland,Department of Psychiatry, Psychosomatics and Psychotherapy, Translational Psychiatry Unit, University of Lübeck, Lübeck 23538, Germany
| | - Paolo Brambilla
- Department of Neuroscience and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza, 35, 20122 Milano, Italy,Department of Pathophysiology and Mental Health, University of Milan, Via Francesco Sforza 35, 20122 Milano, Italy
| | - Rachel Upthegrove
- Early Intervention Service, Birmingham Womens and Childrens NHS Trust, Steelhouse Lane, Birmingham, B4 6NH, UK,Institute for Mental Health and Centre for Human Brain Health, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Stephen J. Wood
- Department of Pathophysiology and Mental Health, University of Milan, Via Francesco Sforza 35, 20122 Milano, Italy,Orygen, 35 Poplar Rd, Parkville, VIC 3052, Australia,Centre for Youth Mental Health, University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia
| | - Raimo K.R. Salokangas
- Department of Psychiatry, University of Turku and Turku University Hospital, FI-20014 Turun yliopisto, Finland
| | - Jarmo Hietala
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University, Moorenstrße 5, 40225 Düsseldorf, Germany
| | - Eva Meisenzahl
- Max-Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804 München, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Nussbaumstraße 7, 80336 München, Germany,Max-Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804 München, Germany,Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, SE5 8AF London, UK
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA,Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada,Corresponding author at: Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, NY, 10029, NY, USA.
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30
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Li L, Han X, Ji E, Tao X, Shen M, Zhu D, Zhang L, Li L, Yang H, Zhang Z. Altered task-modulated functional connectivity during emotional face processing in euthymic bipolar patients: A whole-brain psychophysiological interaction study. J Affect Disord 2022; 301:162-171. [PMID: 35031332 DOI: 10.1016/j.jad.2022.01.045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 12/10/2021] [Accepted: 01/10/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND Patients with bipolar disorder (BD) show deficits of facial emotion processing even in the euthymic phase. However, the large-scale functional brain network mechanism underlying the emotional deficit of BD remains unclear. Specifically, it is of importance to understand how the task-modulated functional connectivity (FC) was alternated over distributed brain networks in BD. METHODS In this study, we analyzed functional MRI data of a face-matching task from 29 euthymic BD patients and 29 healthy controls (HC), and performed whole-brain psychophysiological interaction (PPI) analysis to obtain task-modulated FC. Abnormal FC patterns were identified through support vector machine-based classification. The topological organization of task-modulated FC networks was estimated by the graph theoretical analysis and compared between BD and HC. RESULTS BD exhibited widely distributed aberrant task-modulated FC patterns not only in core neurocognitive intrinsic brain networks (the fronto-parietal, cingulo-opercular, and default mode networks), but also in the cerebellum and primary processing networks (sensorimotor and visual). Furthermore, the local efficiency of the frontal-parietal network was significantly increased in BD. LIMITATIONS The modest sample size. Only face pictures with negative emotion were used. Only unidirectional task-modulated FC was investigated. CONCLUSIONS BD patients showed a widely distributed aberrant task-modulated FC pattern. Particularly, the fronto-parietal network, as one of the core neurocognitive intrinsic brain networks, was the primary network that demonstrated changes of both FC strength and local efficiency in BD. These findings on the task-modulated FC between these intrinsic brain networks might be considered an endophenotype of the BD condition persistent in the euthymic state.
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Affiliation(s)
- Linling Li
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China.
| | - Xue Han
- Department of Mental Health, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518060, China.
| | - Erni Ji
- Department for Bipolar Disorders, Shenzhen Mental Health Centre, Shenzhen Key Lab for Psychological Healthcare, Shenzhen 518020, China.
| | - Xiangrong Tao
- Department for Depression, Shenzhen Mental Health Centre, Shenzhen Key Lab for Psychological Healthcare, Shenzhen 518020, China
| | - Manjun Shen
- Department of Mental Health, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518060, China
| | - Dongjian Zhu
- Department of Mental Health, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518060, China
| | - Li Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China.
| | - Lingjiang Li
- Department of Mental Health, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518060, China; National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Haichen Yang
- Department for Bipolar Disorders, Shenzhen Mental Health Centre, Shenzhen Key Lab for Psychological Healthcare, Shenzhen 518020, China.
| | - Zhiguo Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China; Peng Cheng Laboratory, Shenzhen 518055, China; Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen 518055, China.
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31
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Chen G, Chen P, Gong J, Jia Y, Zhong S, Chen F, Wang J, Luo Z, Qi Z, Huang L, Wang Y. Shared and specific patterns of dynamic functional connectivity variability of striato-cortical circuitry in unmedicated bipolar and major depressive disorders. Psychol Med 2022; 52:747-756. [PMID: 32648539 DOI: 10.1017/s0033291720002378] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Accumulating studies have found structural and functional abnormalities of the striatum in bipolar disorder (BD) and major depressive disorder (MDD). However, changes in intrinsic brain functional connectivity dynamics of striato-cortical circuitry have not been investigated in BD and MDD. This study aimed to investigate the shared and specific patterns of dynamic functional connectivity (dFC) variability of striato-cortical circuitry in BD and MDD. METHODS Brain resting-state functional magnetic resonance imaging data were acquired from 128 patients with unmedicated BD II (current episode depressed), 140 patients with unmedicated MDD, and 132 healthy controls (HCs). Six pairs of striatum seed regions were selected: the ventral striatum inferior (VSi) and the ventral striatum superior (VSs), the dorsal-caudal putamen (DCP), the dorsal-rostral putamen (DRP), and the dorsal caudate and the ventral-rostral putamen (VRP). The sliding-window analysis was used to evaluate dFC for each seed. RESULTS Both BD II and MDD exhibited increased dFC variability between the left DRP and the left supplementary motor area, and between the right VRP and the right inferior parietal lobule. The BD II had specific increased dFC variability between the right DCP and the left precentral gyrus compared with MDD and HCs. The MDD had increased dFC variability between the left VSi and the left medial prefrontal cortex compared with BD II and HCs. CONCLUSIONS The patients with BD and MDD shared common dFC alteration in the dorsal striatal-sensorimotor and ventral striatal-cognitive circuitries. The patients with MDD had specific dFC alteration in the ventral striatal-affective circuitry.
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Affiliation(s)
- Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - JiaYing Gong
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou 510655, China
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Feng Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Jurong Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Zhenye Luo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Zhangzhang Qi
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
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32
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Gu S, Fotiadis P, Parkes L, Xia CH, Gur RC, Gur RE, Roalf DR, Satterthwaite TD, Bassett DS. Network controllability mediates the relationship between rigid structure and flexible dynamics. Netw Neurosci 2022; 6:275-297. [PMID: 36605890 PMCID: PMC9810281 DOI: 10.1162/netn_a_00225] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 12/15/2021] [Indexed: 01/07/2023] Open
Abstract
Precisely how the anatomical structure of the brain supports a wide range of complex functions remains a question of marked importance in both basic and clinical neuroscience. Progress has been hampered by the lack of theoretical frameworks explaining how a structural network of relatively rigid interareal connections can produce a diverse repertoire of functional neural dynamics. Here, we address this gap by positing that the brain's structural network architecture determines the set of accessible functional connectivity patterns according to predictions of network control theory. In a large developmental cohort of 823 youths aged 8 to 23 years, we found that the flexibility of a brain region's functional connectivity was positively correlated with the proportion of its structural links extending to different cognitive systems. Notably, this relationship was mediated by nodes' boundary controllability, suggesting that a region's strategic location on the boundaries of modules may underpin the capacity to integrate information across different cognitive processes. Broadly, our study provides a mechanistic framework that illustrates how temporal flexibility observed in functional networks may be mediated by the controllability of the underlying structural connectivity.
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Affiliation(s)
- Shi Gu
- Brain and Intelligence Group, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Panagiotis Fotiadis
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Linden Parkes
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Cedric H. Xia
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Raquel E. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David R. Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
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33
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A unified model of the pathophysiology of bipolar disorder. Mol Psychiatry 2022; 27:202-211. [PMID: 33859358 DOI: 10.1038/s41380-021-01091-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 03/17/2021] [Accepted: 03/29/2021] [Indexed: 02/02/2023]
Abstract
This work provides an overview of the most consistent alterations in bipolar disorder (BD), attempting to unify them in an internally coherent working model of the pathophysiology of BD. Data on immune-inflammatory changes, structural brain abnormalities (in gray and white matter), and functional brain alterations (from neurotransmitter signaling to intrinsic brain activity) in BD were reviewed. Based on the reported data, (1) we hypothesized that the core pathological alteration in BD is a damage of the limbic network that results in alterations of neurotransmitter signaling. Although heterogeneous conditions can lead to such damage, we supposed that the main pathophysiological mechanism is traceable to an immune/inflammatory-mediated alteration of white matter involving the limbic network connections, which destabilizes the neurotransmitter signaling, such as dopamine and serotonin signaling. Then, (2) we suggested that changes in such neurotransmitter signaling (potentially triggered by heterogeneous stressors onto a structurally-damaged limbic network) lead to phasic (and often recurrent) reconfigurations of intrinsic brain activity, from abnormal subcortical-cortical coupling to changes in network activity. We suggested that the resulting dysbalance between networks, such as sensorimotor networks, salience network, and default-mode network, clinically manifest in combined alterations of psychomotricity, affectivity, and thought during the manic and depressive phases of BD. Finally, (3) we supposed that an additional contribution of gray matter alterations and related cognitive deterioration characterize a clinical-biological subgroup of BD. This model may provide a general framework for integrating the current data on BD and suggests novel specific hypotheses, prompting for a better understanding of the pathophysiology of BD.
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Nabulsi L, McPhilemy G, O'Donoghue S, Cannon DM, Kilmartin L, O'Hora D, Sarrazin S, Poupon C, D'Albis MA, Versace A, Delavest M, Linke J, Wessa M, Phillips ML, Houenou J, McDonald C. Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis. Cereb Cortex 2021; 32:2254-2264. [PMID: 34607352 DOI: 10.1093/cercor/bhab356] [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: 05/22/2021] [Revised: 08/31/2021] [Accepted: 09/01/2021] [Indexed: 11/14/2022] Open
Abstract
Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.
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Affiliation(s)
- Leila Nabulsi
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Lab, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway H91 TK33, Ireland.,Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA 90292, USA
| | - Genevieve McPhilemy
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Lab, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway H91 TK33, Ireland
| | - Stefani O'Donoghue
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Lab, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway H91 TK33, Ireland
| | - Dara M Cannon
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Lab, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway H91 TK33, Ireland
| | - Liam Kilmartin
- College of Engineering and Informatics, National University of Ireland Galway, Galway H91 TK33, Ireland
| | - Denis O'Hora
- School of Psychology, National University of Ireland Galway, Galway H91 TK33, Ireland
| | - Samuel Sarrazin
- APHP, Hôpitaux Universitaires Mondor, Pôle de psychiatrie, DHU PePsy, INSERM U955, Equipe 15, Faculté de medicine de Créteil, Université Paris Est, Créteil, France.,NeuroSpin, CEA Saclay, Gif-Sur-Yvette, France
| | | | - Marc-Antoine D'Albis
- APHP, Hôpitaux Universitaires Mondor, Pôle de psychiatrie, DHU PePsy, INSERM U955, Equipe 15, Faculté de medicine de Créteil, Université Paris Est, Créteil, France.,NeuroSpin, CEA Saclay, Gif-Sur-Yvette, France
| | - Amelia Versace
- Department of Psychiatry, Pittsburgh University Medicine School, Pittsburgh, PA, USA.,Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, PA, USA
| | - Marine Delavest
- APHP, GH Fernand Widal-Lariboisière, Service de psychiatrie, Paris, France
| | - Julia Linke
- Department of Clinical Psychology and Neuropsychology, Institute for Psychology, Johannes Gutenberg-University Mainz, Wallstraße 3, Mainz 55122, Germany
| | - Michèle Wessa
- Department of Clinical Psychology and Neuropsychology, Institute for Psychology, Johannes Gutenberg-University Mainz, Wallstraße 3, Mainz 55122, Germany
| | - Mary L Phillips
- Department of Psychiatry, Pittsburgh University Medicine School, Pittsburgh, PA, USA.,Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, PA, USA
| | - Josselin Houenou
- APHP, Hôpitaux Universitaires Mondor, Pôle de psychiatrie, DHU PePsy, INSERM U955, Equipe 15, Faculté de medicine de Créteil, Université Paris Est, Créteil, France.,NeuroSpin, CEA Saclay, Gif-Sur-Yvette, France
| | - Colm McDonald
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Lab, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway H91 TK33, Ireland
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Zhang L, Wu H, Zhang A, Bai T, Ji GJ, Tian Y, Wang K. Aberrant brain network topology in the frontoparietal-limbic circuit in bipolar disorder: a graph-theory study. Eur Arch Psychiatry Clin Neurosci 2021; 271:1379-1391. [PMID: 33386961 DOI: 10.1007/s00406-020-01219-7] [Citation(s) in RCA: 6] [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: 07/14/2020] [Accepted: 12/02/2020] [Indexed: 12/21/2022]
Abstract
Characterizing the properties of brain networks across mood states seen in bipolar disorder (BP) can provide a deeper insight into the mechanisms involved in this type of affective disorder. In this study, graph theoretical methods were used to examine global, modular and nodal brain network topology in the resting state using functional magnetic resonance imaging data acquired from 95 participants, including those with bipolar depression (BPD; n = 30) and bipolar mania (BPM; n = 39) and healthy control (HC) subjects (n = 26). The threshold value of the individual subjects' connectivity matrix varied from 0.15 to 0.30 with steps of 0.01. We found that: (1) at the global level, BP patients showed a significantly increased global efficiency and synchronization and a decreased path length; (2) at the nodal level, BP patients showed impaired nodal parameters, predominantly within the frontoparietal and limbic sub-network; (3) at the module level, BP patients were characterized by denser FCs (edges) between Module III (the front-parietal system) and Module V (limbic/paralimbic systems); (4) at the nodal level, the BPD and BPM groups showed state-specific differences in the orbital part of the left superior-frontal gyrus, right putamen, right parahippocampal gyrus and left fusiform gyrus. These results revealed abnormalities in topological organization in the whole brain, especially in the frontoparietal-limbic circuit in both BPD and BPM. These deficits may reflect the pathophysiological processes occurring in BP. In addition, state-specific regional nodal alterations in BP could potentially provide biomarkers of conversion across different mood states.
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Affiliation(s)
- Li Zhang
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
- Anhui Mental Health Center, Hefei, Anhui Province, China
| | - Huiling Wu
- Anhui Mental Health Center, Hefei, Anhui Province, China
| | - Aiguo Zhang
- Anhui Mental Health Center, Hefei, Anhui Province, China
| | - Tongjian Bai
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
| | - Gong-Jun Ji
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, 230022, China
- Department of Medical Psychology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
- Department of Medical Psychology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China.
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China.
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, 230022, China.
- Department of Medical Psychology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
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36
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Elton A, Garbutt JC, Boettiger CA. Risk and resilience for alcohol use disorder revealed in brain functional connectivity. NEUROIMAGE-CLINICAL 2021; 32:102801. [PMID: 34482279 PMCID: PMC8416942 DOI: 10.1016/j.nicl.2021.102801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/15/2021] [Accepted: 08/18/2021] [Indexed: 01/22/2023]
Abstract
A family history of alcoholism (FH) increases risk for alcohol use disorder (AUD), yet many at-risk individuals never develop alcohol use problems. FH is associated with intermediate levels of risk phenotypes, whereas distinct, compensatory brain changes likely promote resilience. Although several cognitive, behavioral, and personality factors have been associated with AUD, the relative contributions of these processes and their neural underpinnings to risk or resilience processes remains less clear. We examined whole-brain resting-state functional connectivity (FC) and behavioral metrics from 841 young adults from the Human Connectome Project, including healthy controls, individuals with AUD, and their unaffected siblings. First, we identified functional connections in which unaffected siblings were intermediate between controls and AUD, indicating AUD risk, and those in which siblings diverged, indicating resilience. Canonical correlations relating brain risk and resilience FC to behavioral patterns revealed AUD risk and resilience phenotypes. Risk phenotypes primarily implicated frontal-parietal networks corresponding with executive function, impulsivity, externalizing behaviors, and social-emotional intelligence. Conversely, resilience-related phenotypes were underpinned by networks of medial prefrontal, striatal, temporal, brainstem and cerebellar connectivity, which associated with high trait attention and low antisocial behavior. Additionally, we calculated "polyphenotypic" risk and resilience scores, to investigate how the relative load of risk and resilience phenotypes influenced the probability of an AUD diagnosis. Polyphenotypic scores predicted AUD in a dose-dependent manner. Moreover, resilience phenotypes interacted with risk phenotypes, reducing their effects. The hypothesis-generating results revealed interpretable AUD-related phenotypes and offer brain-informed targets for developing more effective interventions.
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Affiliation(s)
- Amanda Elton
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC 27599, USA; Bowles Center for Alcohol Studies, University of North Carolina, Chapel Hill, NC 27599, USA; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - James C Garbutt
- Bowles Center for Alcohol Studies, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Psychiatry, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Charlotte A Boettiger
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC 27599, USA; Bowles Center for Alcohol Studies, University of North Carolina, Chapel Hill, NC 27599, USA; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC 27599, USA
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37
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Luciw NJ, Toma S, Goldstein BI, MacIntosh BJ. Correspondence between patterns of cerebral blood flow and structure in adolescents with and without bipolar disorder. J Cereb Blood Flow Metab 2021; 41:1988-1999. [PMID: 33487070 PMCID: PMC8323335 DOI: 10.1177/0271678x21989246] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 12/06/2020] [Accepted: 12/23/2020] [Indexed: 11/16/2022]
Abstract
Adolescence is a period of rapid development of the brain's inherent functional and structural networks; however, little is known about the region-to-region organization of adolescent cerebral blood flow (CBF) or its relationship to neuroanatomy. Here, we investigate both the regional covariation of CBF MRI and the covariation of structural MRI, in adolescents with and without bipolar disorder. Bipolar disorder is a disease with increased onset during adolescence, putative vascular underpinnings, and evidence of anomalous CBF and brain structure. In both groups, through hierarchical clustering, we found CBF covariance was principally described by clusters of regions circumscribed to the left hemisphere, right hemisphere, and the inferior brain; these clusters were spatially reminiscent of cerebral vascular territories. CBF covariance was associated with structural covariance in both the healthy group (n = 56; r = 0.20, p < 0.0001) and in the bipolar disorder group (n = 68; r = 0.36, p < 0.0001), and this CBF-structure correspondence was higher in bipolar disorder (p = 0.0028). There was lower CBF covariance in bipolar disorder compared to controls between the left angular gyrus and pre- and post-central gyri. Altogether, CBF covariance revealed distinct brain organization, had modest correspondence to structural covariance, and revealed evidence of differences in bipolar disorder.
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Affiliation(s)
- Nicholas J Luciw
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Simina Toma
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Benjamin I Goldstein
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Canada
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada
- Departments of Pharmacology and Psychiatry, University of Toronto, Toronto, Canada
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
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38
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Wang Y, Sun K, Liu Z, Chen G, Jia Y, Zhong S, Pan J, Huang L, Tian J. Classification of Unmedicated Bipolar Disorder Using Whole-Brain Functional Activity and Connectivity: A Radiomics Analysis. Cereb Cortex 2021; 30:1117-1128. [PMID: 31408101 DOI: 10.1093/cercor/bhz152] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 06/17/2019] [Accepted: 06/17/2019] [Indexed: 01/02/2023] Open
Abstract
The aim of this study was to develop and validate a method of disease classification for bipolar disorder (BD) by functional activity and connectivity using radiomics analysis. Ninety patients with unmedicated BD II as well as 117 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI). A total of 4 types of 7018 features were extracted after preprocessing, including mean regional homogeneity (mReHo), mean amplitude of low-frequency fluctuation (mALFF), resting-state functional connectivity (RSFC), and voxel-mirrored homotopic connectivity (VMHC). Then, predictive features were selected by Mann-Whitney U test and removing variables with a high correlation. Least absolute shrinkage and selection operator (LASSO) method was further used to select features. At last, support vector machine (SVM) model was used to estimate the state of each subject based on the selected features after LASSO. Sixty-five features including 54 RSFCs, 7 mALFFs, 1 mReHo, and 3 VMHCs were selected. The accuracy and area under curve (AUC) of the SVM model built based on the 65 features is 87.3% and 0.919 in the training dataset, respectively, and the accuracy and AUC of this model validated in the validation dataset is 80.5% and 0.838, respectively. These findings demonstrate a valid radiomics approach by rs-fMRI can identify BD individuals from healthy controls with a high classification accuracy, providing the potential adjunctive approach to clinical diagnostic systems.
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Affiliation(s)
- Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.,Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Kai Sun
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, 710071, China.,CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Zhenyu Liu
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,University of Chinese Academy of Science, Beijing, 100190, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.,Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Shuming Zhong
- University of Chinese Academy of Science, Beijing, 100190, China
| | - Jiyang Pan
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.,Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Jie Tian
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, 710071, China.,CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,University of Chinese Academy of Science, Beijing, 100190, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, 100191, China
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Frangou S. Resilience Embodied: A Paradigm Shift for Biological Research in Psychiatry. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:139-140. [PMID: 33558038 DOI: 10.1016/j.bpsc.2020.11.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 11/18/2020] [Indexed: 01/17/2023]
Affiliation(s)
- Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada.
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Qin K, Lei D, Yang J, Li W, Tallman MJ, Duran LRP, Blom TJ, Bruns KM, Cotton S, Sweeney JA, Gong Q, DelBello MP. Network-level functional topological changes after mindfulness-based cognitive therapy in mood dysregulated adolescents at familial risk for bipolar disorder: a pilot study. BMC Psychiatry 2021; 21:213. [PMID: 33910549 PMCID: PMC8080341 DOI: 10.1186/s12888-021-03211-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 04/09/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Given that psychopharmacological approaches routinely used to treat mood-related problems may result in adverse outcomes in mood dysregulated adolescents at familial risk for bipolar disorder (BD), Mindfulness-Based Cognitive Therapy for Children (MBCT-C) provides an alternative effective and safe option. However, little is known about the brain mechanisms of beneficial outcomes from this intervention. Herein, we aimed to investigate the network-level neurofunctional effects of MBCT-C in mood dysregulated adolescents. METHODS Ten mood dysregulated adolescents at familial risk for BD underwent a 12-week MBCT-C intervention. Resting-state functional magnetic resonance imaging (fMRI) was performed prior to and following MBCT-C. Topological metrics of three intrinsic functional networks (default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON)) were investigated respectively using graph theory analysis. RESULTS Following MBCT-C, mood dysregulated adolescents showed increased global efficiency and decreased characteristic path length within both CON and FPN. Enhanced functional connectivity strength of frontal and limbic areas were identified within the DMN and CON. Moreover, change in characteristic path length within the CON was suggested to be significantly related to change in the Emotion Regulation Checklist score. CONCLUSIONS 12-week MBCT-C treatment in mood dysregulated adolescents at familial risk for BD yield network-level neurofunctional effects within the FPN and CON, suggesting enhanced functional integration of the dual-network. Decreased characteristic path length of the CON may be associated with the improvement of emotion regulation following mindfulness training. However, current findings derived from small sample size should be interpreted with caution. Future randomized controlled trials including larger samples are critical to validate our findings.
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Affiliation(s)
- Kun Qin
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Du Lei
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Jing Yang
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Wenbin Li
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China ,grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Maxwell J. Tallman
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Luis Rodrigo Patino Duran
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Thomas J. Blom
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Kaitlyn M. Bruns
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Sian Cotton
- grid.24827.3b0000 0001 2179 9593Department of Family and Community Medicine, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - John A. Sweeney
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China ,grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China. .,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China. .,Functional and Molecular Imaging Key Laboratory of Sichuan Province, Chengdu, China.
| | - Melissa P. DelBello
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
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Singh MK, Nimarko AF, Garrett AS, Gorelik AJ, Roybal DJ, Walshaw PD, Chang KD, Miklowitz DJ. Changes in Intrinsic Brain Connectivity in Family-Focused Therapy Versus Standard Psychoeducation Among Youths at High Risk for Bipolar Disorder. J Am Acad Child Adolesc Psychiatry 2021; 60:458-469. [PMID: 32745598 PMCID: PMC7854810 DOI: 10.1016/j.jaac.2020.07.892] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 04/22/2020] [Accepted: 07/24/2020] [Indexed: 01/12/2023]
Abstract
OBJECTIVE We compared intrinsic network connectivity in symptomatic youths at high risk (HR) for bipolar disorder (BD) and healthy comparison (HC) youths. In HR youths, we also investigated treatment-related changes in intrinsic connectivity after family-focused therapy for high-risk youths (FFT-HR) vs standardized family psychoeducation. METHOD HR youths (N = 34; age 9-17 years; mean 14 years, 56% girls and 44% boys) with depressive and/or hypomanic symptoms and at least 1 first- or second-degree relative with BD I or II were randomly assigned to 4 months of FFT-HR (12 sessions of psychoeducation, communication, and problem-solving skills training) or enhanced care (EC; 3 family and 3 individual psychoeducation sessions). Before and after 4 months of treatment, participants underwent resting state functional magnetic resonance imaging (rs-fMRI). A whole-brain independent component analysis compared rs-fMRI networks in HR youths and 30 age-matched HC youths at a pretreatment baseline. Then we identified pretreatment to posttreatment (4-month) changes in network connectivity in HR youths receiving FFT-HR (n = 16) or EC (n = 18) and correlated these changes with depression improvement. RESULTS At baseline, HR youths had greater connectivity between the ventrolateral prefrontal cortex (VLPFC) and the anterior default mode network (aDMN) than did HCs (p = .004). Over 4 months of treatment, FFT-HR-assigned HR youths had increased VLPFC-aDMN connectivity from pre- to posttreatment (p = .003), whereas HR youths in EC showed no significant change over time (p = .11) (treatment by time interaction, t31 = 3.33, 95% CI = 0.27-1.14, p = .002]. Reduction in depression severity over 4 months inversely correlated with enhanced anterior DMN (r = -0.71) connectivity in the FFT-HR but not in the EC (r = -0.07) group (z = -2.17, p = .015). CONCLUSION Compared to standard psychoeducation, FFT-HR is associated with stronger connectivity between the VLPFC and aDMN, suggesting possible enhancements of self-awareness, illness awareness, and emotion regulation. CLINICAL TRIAL REGISTRATION INFORMATION Early Intervention for Youth at Risk for Bipolar Disorder; https://clinicaltrials.gov/; NCT01483391.
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Affiliation(s)
| | | | - Amy S. Garrett
- University of Texas, Health Science Center at San Antonio
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42
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Common and distinct global functional connectivity density alterations in patients with bipolar disorder with and without auditory verbal hallucination during major depressive episodes. Brain Imaging Behav 2021; 14:2724-2730. [PMID: 31900890 DOI: 10.1007/s11682-019-00222-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Although an increasing number of studies has explored the neural mechanisms of auditory verbal hallucination (AVH) using many modalities, including neuroimaging, neurotransmitters, and electroencephalography, the etiology of AVH remains unclear. In this study, we investigated the neuroimaging characteristics of AVH in patients with bipolar disorder (BD) experiencing depressive episodes with and without AVH. For this study, we recruited 80 patients with BD and depressive status (40 with and 40 without AVH), and 40 healthy individuals. Their global functional connectivity density (gFCD) was screened by functional magnetic resonance imaging. Differences in gFCD among the three groups were tested using voxel-wise one-way analysis of covariance. Patients in both BD groups demonstrated increased gFCD in the central parietal lobe, insular lobe, and middle cingulate cortex, and decreased gFCD in the posterior parietal cortex, lateral prefrontal cortex, and occipital lobe (all bilateral). We defined these alterations as the common aberrant gFCD pattern for BD with and without AVH. Compared with the other two groups, patients in the BD with AVH group demonstrated increased gFCD in the Broca and Wernicke regions, and decreased gFCD in the hippocampus (all bilateral). We defined these alterations as the distinct aberrant gFCD pattern for BD with AVH. To our knowledge, this report is the first to date to describe gFCD alterations in patients with BD with and without AVH. Our findings suggest that disturbances in brain activity and information communication capacity in patients with BD and AVH are located mainly in the left frontoparietal network, control network, and memory circuit. However, these observations were made only in patients with BD during depressive episodes, and without consideration of many factors, such as the treatment mode, symptom relapse, and BD subtype. Hence, the conclusions of this study merely provide clues for further study, and do not fully represent brain alterations in patients with BD and AVH. Further large-sample cohort studies are needed to clarify and expand on these findings.
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Inferior frontal gyrus seed-based resting-state functional connectivity and sustained attention across manic/hypomanic, euthymic and depressive phases of bipolar disorder. J Affect Disord 2021; 282:930-938. [PMID: 33601737 DOI: 10.1016/j.jad.2020.12.199] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/20/2020] [Accepted: 12/31/2020] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Seed-based resting-state functional connectivity (rs-FC) of inferior frontal gyrus (IFG), as well as sustained attention cognitive deficit are consistently reported to be impaired in bipolar disorders. However, whether these deficits exist across mood states and euthymic state are lacking. We compared rs-FC of IFG and sustained attention of bipolar patients in (hypo) mania, depression and euthymia, with controls. We also explored the interrelationships between clinical, cognitive, and imaging measurements. METHODS Participants included 110 bipolar subjects: 46 manic/hypomanic, 35 euthymic, and 29 depressed, matched with 41 healthy controls (HCs) underwent structural magnetic resonance imaging (MRI) and resting-state functional MRI scans. Seed-based functional connectivity analyses were performed focused on bilateral IFG seeds. Clinical symptoms and sustained attention function were measured. Stepwise linear regression analysis was conducted to explore predictors of sustained attention measurements. RESULTS Increased rs-FC between right IFG and bilateral frontal pole/superior frontal gyrus, precuneus, and posterior cingulate gyrus, as well as decreased rs-FC between right IFG and sensorimotor areas, anterior middle cingulate gyrus were found in all three bipolar subgroups compared with HCs. Impaired sustained attention measurement was found in bipolar manic/hypomanic and depressive subgroups compared with HCs. Linear regression analyses revealed a significant impact of the manic symptoms and psychotic symptoms on the performance of sustained attention task. CONCLUSIONS Our results revealed that IFG seed-based resting-state functional networks involved in emotion regulation and cognitive function were trait-like deficit in bipolar patients. Higher manic levels and psychotic symptoms were predictors of a worse sustained attention performance.
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Bora E, Can G, Zorlu N, Ulas G, Inal N, Ozerdem A. Structural dysconnectivity in offspring of individuals with bipolar disorder: The effect of co-existing clinical-high-risk for bipolar disorder. J Affect Disord 2021; 281:109-116. [PMID: 33310660 DOI: 10.1016/j.jad.2020.11.122] [Citation(s) in RCA: 6] [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: 07/14/2020] [Revised: 11/22/2020] [Accepted: 11/26/2020] [Indexed: 12/29/2022]
Abstract
BACKGROUND Bipolar disorder (BD) might be associated in disturbances in brain networks. However, little is known about the abnormalities in structural brain connectivity which might be related to vulnerability to BD and predictive of the emergence of manic symptoms. No previous study has investigated the effect of subthreshold syndromes on structural dysconnectivity in offspring of parents with BD (BDoff). METHODS We investigated diffusion weighted images of 70 BDoff and 48 healthy controls (HC). Nineteen of the 70 BDoff had presented with subthreshold syndromes indicating a clinical high-risk (BDoff-CHR) and other 51 BDoff had no such history (BDoff-non-CHR). Global and regional network properties, rich club organization and inter-regional connectivity in BDoff and healthy controls were investigated using graph analytical methods and network-based-statistics (NBS). RESULTS Global properties of WM networks appeared to be intact in BDoff-CHR and BDoff-non-CHR. However, decreased regional connectivity in right occipito-parietal areas and cerebellum was a common feature of both BDoff groups. Importantly, decreased interregional connectivity between nodes in right and left prefrontal regions, nodes in right prefrontal lobe and right temporal lobe and nodes in left occipital area and left cerebellum were evident in BDoff-CHR but not BDoff-non-CHR. LIMITATIONS The cross-sectional nature of the study was the main consideration. CONCLUSION Decreased regional connectivity in right posterior brain regions might be related to vulnerability to BD. On the other hand, interregional dysconnectivity in anterior frontal and limbic regions and left posterior brain regions might be evident in individuals genetically at risk for developing BD who had experienced subthreshold mood symptoms.
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Affiliation(s)
- Emre Bora
- Dokuz Eylul University, Faculty of Medicine, Department of Psychiatry, Izmir, Turkey; Dokuz Eylul University, Institute of Neuroscience, Izmir, Turkey; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne.
| | - Gunes Can
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Nabi Zorlu
- Department of Psychiatry, Faculty of Medicine, Ataturk Training and Research Hospital, Izmir Katip Celebi University, İzmir, Turkey
| | - Gozde Ulas
- Department of Child and Adolescent Psychiatry, Tepecik Research and Training Hospital, İzmir, Turkey
| | - Neslihan Inal
- Dokuz Eylul University Faculty of Medicine, Department of Child and Adolescent Psychiatry, Izmir, Turkey
| | - Aysegul Ozerdem
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
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Doucet GE, Labache L, Thompson PM, Joliot M, Frangou S. Atlas55+: Brain Functional Atlas of Resting-State Networks for Late Adulthood. Cereb Cortex 2021; 31:1719-1731. [PMID: 33188411 PMCID: PMC7869083 DOI: 10.1093/cercor/bhaa321] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 09/21/2020] [Accepted: 10/09/2020] [Indexed: 11/14/2022] Open
Abstract
Currently, several human brain functional atlases are used to define the spatial constituents of the resting-state networks (RSNs). However, the only brain atlases available are derived from samples of young adults. As brain networks are continuously reconfigured throughout life, the lack of brain atlases derived from older populations may influence RSN results in late adulthood. To address this gap, the aim of the study was to construct a reliable brain atlas derived only from older participants. We leveraged resting-state functional magnetic resonance imaging data from three cohorts of healthy older adults (total N = 563; age = 55-95 years) and a younger-adult cohort (N = 128; age = 18-35 years). We identified the major RSNs and their subdivisions across all older-adult cohorts. We demonstrated high spatial reproducibility of these RSNs with an average spatial overlap of 67%. Importantly, the RSNs derived from the older-adult cohorts were spatially different from those derived from the younger-adult cohort (P = 2.3 × 10-3). Lastly, we constructed a novel brain atlas, called Atlas55+, which includes the consensus of the major RSNs and their subdivisions across the older-adult cohorts. Thus, Atlas55+ provides a reliable age-appropriate template for RSNs in late adulthood and is publicly available. Our results confirm the need for age-appropriate functional atlases for studies investigating aging-related brain mechanisms.
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Affiliation(s)
- Gaelle E Doucet
- Boys Town National Research Hospital, Omaha, NE 68131, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Loic Labache
- GIN, UMR5293, CEA, CNRS, Bordeaux University, Bordeaux 33000, France
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90033, USA
| | - Marc Joliot
- GIN, UMR5293, CEA, CNRS, Bordeaux University, Bordeaux 33000, France
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Centre for Brain Health, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
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Wackerhagen C, Veer IM, Erk S, Mohnke S, Lett TA, Wüstenberg T, Romanczuk-Seiferth NY, Schwarz K, Schweiger JI, Tost H, Meyer-Lindenberg A, Heinz A, Walter H. Amygdala functional connectivity in major depression - disentangling markers of pathology, risk and resilience. Psychol Med 2020; 50:2740-2750. [PMID: 31637983 DOI: 10.1017/s0033291719002885] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
BACKGROUND Limbic-cortical imbalance is an established model for the neurobiology of major depressive disorder (MDD), but imaging genetics studies have been contradicting regarding potential risk and resilience mechanisms. Here, we re-assessed previously reported limbic-cortical alterations between MDD relatives and controls in combination with a newly acquired sample of MDD patients and controls, to disentangle pathology, risk, and resilience. METHODS We analyzed functional magnetic resonance imaging data and negative affectivity (NA) of MDD patients (n = 48), unaffected first-degree relatives of MDD patients (n = 49) and controls (n = 109) who performed a faces matching task. Brain response and task-dependent amygdala functional connectivity (FC) were compared between groups and assessed for associations with NA. RESULTS Groups did not differ in task-related brain activation but activation in the superior frontal gyrus (SFG) was inversely correlated with NA in patients and controls. Pathology was associated with task-independent decreases of amygdala FC with regions of the default mode network (DMN) and decreased amygdala FC with the medial frontal gyrus during faces matching, potentially reflecting a task-independent DMN predominance and a limbic-cortical disintegration during faces processing in MDD. Risk was associated with task-independent decreases of amygdala-FC with fronto-parietal regions and reduced faces-associated amygdala-fusiform gyrus FC. Resilience corresponded to task-independent increases in amygdala FC with the perigenual anterior cingulate cortex (pgACC) and increased FC between amygdala, pgACC, and SFG during faces matching. CONCLUSION Our results encourage a refinement of the limbic-cortical imbalance model of depression. The validity of proposed risk and resilience markers needs to be tested in prospective studies. Further limitations are discussed.
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Affiliation(s)
- Carolin Wackerhagen
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Ilya M Veer
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Susanne Erk
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Sebastian Mohnke
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Tristram A Lett
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Torsten Wüstenberg
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Nina Y Romanczuk-Seiferth
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Kristina Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany
| | - Janina I Schweiger
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
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Person-based similarity in brain structure and functional connectivity in bipolar disorder. J Affect Disord 2020; 276:38-44. [PMID: 32697714 PMCID: PMC7568424 DOI: 10.1016/j.jad.2020.06.041] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 05/26/2020] [Accepted: 06/16/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Bipolar disorder shows significant variability in clinical presentation. Here we adopt a personalized approach to quantify the brain structural and functional similarity of each individual patient to other patients and to healthy individuals. METHODS Brain morphometric and resting-state functional connectivity measures from two independent samples of patients with bipolar disorder and healthy individuals (total number of participants=215) were modeled as single vectors to generated individualized morphometric and connectivity profiles. These profiles were then used to compute a person-based similarity indices which quantified the similarity in neuroimaging profiles amongst patients and between patients and health individuals. RESULTS The morphometric and connectivity profiles of patients showed within-diagnosis similarity which was comparable to that observed in healthy individuals. They also showed minimal deviance from those of healthy individuals; the correlation between the profiles of patients and healthy individuals was high (range: 0.71-0.94, p<10-5). The degree of similarity between imaging profiles was associated with IQ (for cortical thickness) and age (functional integration) rather than clinical variables. Patients who were prescribed lithium, compared to those who were not, showed greater similarity to healthy individuals in terms of network integration (t = 2.2, p = 0.03). LIMITATIONS We focused on patients with Bipolar disorder, type I only. CONCLUSIONS High inter-individual similarity in neuroimaging profiles was observed amongst patients with bipolar disorder and between patients and healthy individuals. We infer that brain alterations associated with bipolar disorder may be nested within the normal biological diversity consistent with the high prevalence of mood symptoms in the general population.
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Fan Z, Yang J, Zeng C, Xi C, Wu G, Guo S, Xue Z, Liu Z, Tao H. Bipolar Mood State Reflected in Functional Connectivity of the Hate Circuit: A Resting-State Functional Magnetic Resonance Imaging Study. Front Psychiatry 2020; 11:556126. [PMID: 33192670 PMCID: PMC7652934 DOI: 10.3389/fpsyt.2020.556126] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 08/28/2020] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Previous studies suggested bipolar disorder caused an aberrant alteration in the insular, putamen, and left superior frontal gyrus, which are the main components of the hate circuit. However, the relationship between the hate circuit and the pathophysiologic substrate underlying different phases of bipolar disorder remain unclear. In this study, we aimed to identify group differences of resting-state functional connectivity within the hate circuit in healthy controls (HCs) and bipolar patients in different mood states. METHODS Resting-state functional magnetic resonance imaging of the brain were acquired from 54 HCs and 81 patients with bipolar disorder including 20 with bipolar mania (BM), 35 with bipolar depression (BD), and 26 with bipolar euthymia (BE). We selected bilateral insula (L.INS and R.INS), bilateral putamen (L.PUT and R.PUT), and left superior frontal gyrus (L.SFGd) as seed regions, and conducted the seed-based functional connectivity analysis to identify group differences of connectivity strength within the hate circuit. Spearman correlations were performed to evaluate the relationship between the hate circuit and manic/depressive symptoms. RESULTS Significant group differences of connectivity strength within the hate circuit were found in links of the R.INS-L.SFGd, R.PUT-L.SFGd, and L.INS- R.PUT after false discovery rate was corrected. The BM group showed an opposite hate circuit pattern to BD, BE, and HCs. The BD group showed decreased hate circuit connectivity in the L.INS-R.PUT compared with the BE group. No significant difference was detected among BD, BE, and HCs. Furthermore, functional connectivity of the R.INS-L.SFGd and R.PUT-L.SFGd were positively correlated with manic symptoms, while the L.INS- R.PUT was negatively correlated with depressive symptoms. CONCLUSIONS Our preliminary findings suggest that altered functional connectivity of the hate circuit in different mood phases may be related to state markers and underpin the neuropathological basis of bipolar disorder.
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Affiliation(s)
- Zebin Fan
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
| | - Jie Yang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
| | - Can Zeng
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
| | - Chang Xi
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
| | - Guowei Wu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
| | - Shuixia Guo
- Mathematics and Computer Science College, Hunan Normal University, Changsha, China
| | - Zhimin Xue
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
| | - Zhening Liu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
| | - Haojuan Tao
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, Changsha, China
- National Technology Institute on Mental Disorders, Changsha, China
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Aberrant functional connectivity and graph properties in bipolar II disorder with suicide attempts. J Affect Disord 2020; 275:202-209. [PMID: 32734909 DOI: 10.1016/j.jad.2020.07.016] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 06/10/2020] [Accepted: 07/05/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE The physiological mechanism of suicide attempt (SA) in bipolar II disorder (BD-II) remains only partially understood. The study seeks to identify the dysfunction pattern in suicide brain for BD-II patients. METHODS Graph theory was utilized to explore topological properties at whole-brain, module and region levels based on resting-state functional MRI (rs-fMRI) data, which acquired from 38 un-medicated BD-II patients with at least one SA, 60 none SA (NSA) patients and 69 healthy controls (HCs). Finally, the correlation relationship between graph metrics and clinical variables were estimated. RESULTS Compared with NSA patients and HCs, the functional connectivity strength between limbic/sub-cortical (LIMB/SubC) and frontoparietal network (FPN) were significantly weakened. Nodal strength in left head of caudate nucleus (HCN), raphe nucleus (RN), right nucleus accumbens (NAcc), right subgenual anterior cingulate cortex (sgACC) and nodal efficiency in right sgACC, right HCN for SA patients were significantly reduced relative to NSA and HCs. In particular, nodal strength in RN and nodal efficiency in right sgACC showed a significant negative correlation with Nurses' Global Assessment of Suicide Risk (NGASR) scores. LIMITATIONS This is a single-mode cross-sectional study, the results were not verified by multi-center data. CONCLUSIONS The abnormal disrupted FC between LIMB/SubC and FPN is associated with SA in BD-II patients, which increased the susceptibility of suicide. Especially, the dysfunction in RN and right sgACC predict a higher suicide risk in BD-II patients.The results can help us to understand the suicide mechanism and early judgment of suicidal behaviors for BD-II patients.
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McPhilemy G, Nabulsi L, Kilmartin L, Whittaker JR, Martyn FM, Hallahan B, McDonald C, Murphy K, Cannon DM. Resting-State Network Patterns Underlying Cognitive Function in Bipolar Disorder: A Graph Theoretical Analysis. Brain Connect 2020; 10:355-367. [PMID: 32458698 DOI: 10.1089/brain.2019.0709] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Background: Synchronous and antisynchronous activity between neural elements at rest reflects the physiological processes underlying complex cognitive ability. Regional and pairwise connectivity investigations suggest that perturbations in these activity patterns may relate to widespread cognitive impairments seen in bipolar disorder (BD). Here we take a network-based perspective to more meaningfully capture interactions among distributed brain regions compared to focal measurements and examine network-cognition relationships across a range of commonly affected cognitive domains in BD in relation to healthy controls. Methods: Resting-state networks were constructed as matrices of correlation coefficients between regionally averaged resting-state time series from 86 cortical/subcortical brain regions (FreeSurferv5.3.0). Cognitive performance measured using the Wechsler Adult Intelligence Scale, Cambridge Automated Neuropsychological Test Battery (CANTAB), and Reading the Mind in the Eyes tests was examined in relation to whole-brain connectivity measures and patterns of connectivity using a permutation-based statistical approach. Results: Faster response times in controls (n = 49) related to synchronous activity between frontal, parietal, cingulate, temporal, and occipital regions, while a similar response times in BD (n = 35) related to antisynchronous activity between regions of this subnetwork. Across all subjects, antisynchronous activity between the frontal, parietal, temporal, occipital, cingulate, insula, and amygdala regions related to improved memory performance. No resting-state subnetworks related to intelligence, executive function, short-term memory, or social cognition performance in the overall sample or in a manner that would explain deficits in these facets in BD. Conclusions: Our results demonstrate alterations in the intrinsic connectivity patterns underlying response timing in BD that are not specific to performance or errors on the same tasks. Across all individuals, no strong effects of resting-state global topology on cognition are found, while distinct functional networks supporting episodic and spatial memory highlight intrinsic inhibitory influences present in the resting state that facilitate memory processing. Impact Statement Regional and pairwise-connectivity investigations suggest altered interactions between brain areas may contribute to impairments in cognition that are observed in bipolar disorder. However, the distributed nature of these interactions across the brain remains poorly understood. Using recent advances in network neuroscience, we examine functional connectivity patterns associated with multiple cognitive domains in individuals with and without bipolar disorder. We discover distinct patterns of connectivity underlying response-timing performance uniquely in bipolar disorder and, independent of diagnosis, inhibitory interactions that relate to memory performance.
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Affiliation(s)
- Genevieve McPhilemy
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Leila Nabulsi
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Liam Kilmartin
- College of Science and Engineering, National University of Ireland Galway, Galway, Republic of Ireland
| | - Joseph R Whittaker
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Fiona M Martyn
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Brian Hallahan
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Kevin Murphy
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Dara M Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
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