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Więcławski W, Bielski K, Jani M, Binder M, Adamczyk P. Dysconnectivity of the cerebellum and somatomotor network correlates with the severity of alogia in chronic schizophrenia. Psychiatry Res Neuroimaging 2024; 345:111883. [PMID: 39241534 DOI: 10.1016/j.pscychresns.2024.111883] [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: 04/15/2024] [Revised: 08/13/2024] [Accepted: 08/26/2024] [Indexed: 09/09/2024]
Abstract
Recent fMRI resting-state findings show aberrant functional connectivity within somatomotor network (SMN) in schizophrenia. Moreover, functional connectivity aberrations of the motor system are often reported to be related to the severity of psychotic symptoms. Thus, it is important to validate those findings and confirm their relationship with psychopathology. Therefore, we decided to take an entirely data-driven approach in our fMRI resting-state study of 30 chronic schizophrenia outpatients and 30 matched control subjects. We used independent component analysis (ICA), dual regression, and seed-based connectivity analysis. We found reduced functional connectivity within SMN in schizophrenia patients compared to controls and SMN hypoconnectivity with the cerebellum in schizophrenia patients. The latter was strongly correlated with the severity of alogia, one of the main psychotic symptoms, i.e. poverty of speech and reduction in spontaneous speech,. Our results are consistent with the recent knowledge about the role of the cerebellum in cognitive functioning and its abnormalities in psychiatric disorders, e.g. schizophrenia. In conclusion, the presented results, for the first time clearly showed the involvement of the cerebellum hypoconnectivity with SMN in the persistence and severity of alogia symptoms in schizophrenia.
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Affiliation(s)
| | | | - Martin Jani
- Institute of Psychology, Jagiellonian University, Krakow, Poland; Department of Psychiatry, Faculty of Medicine, Masaryk University and University Hospital Brno, Brno, Czech Republic
| | - Marek Binder
- Institute of Psychology, Jagiellonian University, Krakow, Poland
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Xing Y, van Erp TG, Pearlson GD, Kochunov P, Calhoun VD, Du Y. More reliable biomarkers and more accurate prediction for mental disorders using a label-noise filtering-based dimensional prediction method. iScience 2024; 27:109319. [PMID: 38482500 PMCID: PMC10933544 DOI: 10.1016/j.isci.2024.109319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/17/2023] [Accepted: 02/19/2024] [Indexed: 04/26/2024] Open
Abstract
The integration of neuroimaging with artificial intelligence is crucial for advancing the diagnosis of mental disorders. However, challenges arise from incomplete matching between diagnostic labels and neuroimaging. Here, we propose a label-noise filtering-based dimensional prediction (LAMP) method to identify reliable biomarkers and achieve accurate prediction for mental disorders. Our method proposes to utilize a label-noise filtering model to automatically filter out unclear cases from a neuroimaging perspective, and then the typical subjects whose diagnostic labels align with neuroimaging measures are used to construct a dimensional prediction model to score independent subjects. Using fMRI data of schizophrenia patients and healthy controls (n = 1,245), our method yields consistent scores to independent subjects, leading to more distinguishable relabeled groups with an enhanced classification accuracy of 31.89%. Additionally, it enables the exploration of stable abnormalities in schizophrenia. In summary, our LAMP method facilitates the identification of reliable biomarkers and accurate diagnosis of mental disorders using neuroimages.
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Affiliation(s)
- Ying Xing
- School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
| | - Theo G.M. van Erp
- Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, Irvine, CA 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA 92617, USA
| | - Godfrey D. Pearlson
- Departments of Psychiatry and of Neurobiology, Yale University, New Haven, CT 06519, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT 06106, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center and Department of Psychiatry, University of Maryland, School of Medicine, Baltimore, MD 21201, USA
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30030, USA
| | - Yuhui Du
- School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
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Chen J, Jiang S, Lu B, Liao J, Yang Z, Li H, Pei H, Li J, Iturria-Medina Y, Yao D, Luo C. The role of the primary sensorimotor system in generalized epilepsy: Evidence from the cerebello-cerebral functional integration. Hum Brain Mapp 2024; 45:e26551. [PMID: 38063289 PMCID: PMC10789200 DOI: 10.1002/hbm.26551] [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: 05/29/2023] [Revised: 11/12/2023] [Accepted: 11/16/2023] [Indexed: 01/16/2024] Open
Abstract
The interaction between cerebellum and cerebrum participates widely in function from motor processing to high-level cognitive and affective processing. Because of the motor symptom, idiopathic generalized epilepsy (IGE) patients with generalized tonic-clonic seizure have been recognized to associate with motor abnormalities, but the functional interaction in the cerebello-cerebral circuit is still poorly understood. Resting-state functional magnetic resonance imaging data were collected for 101 IGE patients and 106 healthy controls. The voxel-based functional connectivity (FC) between cerebral cortex and the cerebellum was contacted. The functional gradient and independent components analysis were applied to evaluate cerebello-cerebral functional integration on the voxel-based FC. Cerebellar motor components were further linked to cerebellar gradient. Results revealed cerebellar motor functional modules were closely related to cerebral motor components. The altered mapping of cerebral motor components to cerebellum was observed in motor module in patients with IGE. In addition, patients also showed compression in cerebello-cerebral functional gradient between motor and cognition modules. Interestingly, the contribution of the motor components to the gradient was unbalanced between bilateral primary sensorimotor components in patients: the increase was observed in cerebellar cognitive module for the dominant hemisphere primary sensorimotor, but the decrease was found in the cerebellar cognitive module for the nondominant hemisphere primary sensorimotor. The present findings suggest that the cerebral primary motor system affects the hierarchical architecture of cerebellum, and substantially contributes to the functional integration evidence to understand the motor functional abnormality in IGE patients.
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Affiliation(s)
- Junxia Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Bao Lu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Jiangyan Liao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Zhihuan Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yasser Iturria-Medina
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, P. R. China
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Hinkley LBN, Haas SS, Cheung SW, Nagarajan SS, Subramaniam K. Reduced neural connectivity in the caudate anterior head predicts hallucination severity in schizophrenia. Schizophr Res 2023; 261:1-5. [PMID: 37678144 PMCID: PMC10878029 DOI: 10.1016/j.schres.2023.08.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 06/13/2023] [Accepted: 08/31/2023] [Indexed: 09/09/2023]
Abstract
BACKGROUND Caudate functional abnormalities have been identified as one critical neural substrate underlying sensory gating impairments that lead to auditory phantom hallucinations in both patients with schizophrenia (SZ) and tinnitus, characterized by the perception of internally generated sounds in the absence of external environmental auditory stimuli. In this study, we tested the hypothesis as to whether functional connectivity abnormalities in distinct caudate subdivisions implicated in sensory gating and auditory phantom percepts in tinnitus, which are currently being localized for neuromodulation targeting using deep brain stimulation techniques, would be associated with auditory phantom hallucination severity in SZ. METHODS Twenty five SZ and twenty eight demographically-matched healthy control (HC) participants, completed this fMRI resting-state study and clinical assessments. RESULTS Between-group seed-to-voxel analyses revealed only one region, the caudate anterior head, which showed reduced functional connectivity with the thalamus that survived whole-brain multiple comparison corrections. Importantly, connectivity between the caudate anterior head with thalamus negatively correlated with hallucination severity. CONCLUSIONS In the present study, we deliver the first evidence of caudate subdivision specificity for the neural pathophysiology underlying hallucinations in schizophrenia within a sensory gating framework that has been developed for auditory phantoms in patients with tinnitus. Our findings provide transdiagnostic convergent evidence for the role of the caudate in the gating of auditory phantom hallucinations, observed across patients with SZ and tinnitus by specifying the anterior caudate division is key to mediation of hallucinations, and creating a path towards personalized treatment approaches to arrest auditory phantom hallucinations from reaching perceptual awareness.
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Affiliation(s)
- Leighton B N Hinkley
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Steven W Cheung
- Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, CA 94143, USA; Surgical Services, San Francisco Veterans Health Care System, San Francisco, CA 94121, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
| | - Karuna Subramaniam
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA.
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5
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Hou C, Jiang S, Liu M, Li H, Zhang L, Duan M, Yao G, He H, Yao D, Luo C. Spatiotemporal dynamics of functional connectivity and association with molecular architecture in schizophrenia. Cereb Cortex 2023:7179746. [PMID: 37231204 DOI: 10.1093/cercor/bhad185] [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: 01/25/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/27/2023] Open
Abstract
Schizophrenia is a self-disorder characterized by disrupted brain dynamics and architectures of multiple molecules. This study aims to explore spatiotemporal dynamics and its association with psychiatric symptoms. Resting-state functional magnetic resonance imaging data were collected from 98 patients with schizophrenia. Brain dynamics included the temporal and spatial variations in functional connectivity density and association with symptom scores were evaluated. Moreover, the spatial association between dynamics and receptors/transporters according to prior molecular imaging in healthy subjects was examined. Patients demonstrated decreased temporal variation and increased spatial variation in perceptual and attentional systems. However, increased temporal variation and decreased spatial variation were revealed in higher order networks and subcortical networks in patients. Specifically, spatial variation in perceptual and attentional systems was associated with symptom severity. Moreover, case-control differences were associated with dopamine, serotonin and mu-opioid receptor densities, serotonin reuptake transporter density, dopamine transporter density, and dopamine synthesis capacity. Therefore, this study implicates the abnormal dynamic interactions between the perceptual system and cortical core networks; in addition, the subcortical regions play a role in the dynamic interaction among the cortical regions in schizophrenia. These convergent findings support the importance of brain dynamics and emphasize the contribution of primary information processing to the pathological mechanism underlying schizophrenia.
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Affiliation(s)
- Changyue Hou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, 611731, P. R. China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, 611731, P. R. China
| | - Mei Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, 611731, P. R. China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, 611731, P. R. China
| | - Lang Zhang
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, 611731, P. R. China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
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6
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Jiang Y, Li W, Qin Y, Zhang L, Tong X, Xiao F, Jiang S, Li Y, Gong Q, Zhou D, An D, Yao D, Luo C. In vivo characterization of magnetic resonance imaging-based T1w/T2w ratios reveals myelin-related changes in temporal lobe epilepsy. Hum Brain Mapp 2023; 44:2323-2335. [PMID: 36692056 PMCID: PMC10028664 DOI: 10.1002/hbm.26212] [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: 03/16/2022] [Revised: 12/12/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is the most common type of intractable epilepsy in adults. Although brain myelination alterations have been observed in TLE, it remains unclear how the myelination network changes in TLE. This study developed a novel method in characterization of myelination structural covariance network (mSCN) by T1-weighted and T2-weighted magnetic resonance imaging (MRI). The mSCNs were estimated in 42 left TLE (LTLE), 42 right TLE (RTLE) patients, and 41 healthy controls (HCs). The topology of mSCN was analyzed by graph theory. Voxel-wise comparisons of myelination laterality were also examined among the three groups. Compared to HC, both patient groups showed decreased myelination in frontotemporal regions, amygdala, and thalamus; however, the LTLE showed lower myelination in left medial temporal regions than RTLE. Moreover, the LTLE exhibited decreased global efficiency compared with HC and more increased connections than RTLE. The laterality in putamen was differently altered between the two patient groups: higher laterality at posterior putamen in LTLE and higher laterality at anterior putamen in RTLE. The putamen may play a transfer station role in damage spreading induced by epileptic seizures from the hippocampus. This study provided a novel workflow by combination of T1-weighted and T2-weighted MRI to investigate in vivo the myelin-related microstructural feature in epileptic patients first time. Disconnections of mSCN implicate that TLE is a system disorder with widespread disruptions at regional and network levels.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Le Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Xin Tong
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Fenglai Xiao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Yunfang Li
- Southern Medical District, Chinese People's Liberation Army General Hospital, Beijing, People's Republic of China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, People's Republic of China
- Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, People's Republic of China
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7
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Hancock F, Rosas FE, McCutcheon RA, Cabral J, Dipasquale O, Turkheimer FE. Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology. PLoS One 2023; 18:e0282707. [PMID: 36952467 PMCID: PMC10035891 DOI: 10.1371/journal.pone.0282707] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 02/21/2023] [Indexed: 03/25/2023] Open
Abstract
The disconnection hypothesis of schizophrenia proposes that symptoms of the disorder arise as a result of aberrant functional integration between segregated areas of the brain. The concept of metastability characterizes the coexistence of competing tendencies for functional integration and functional segregation in the brain, and is therefore well suited for the study of schizophrenia. In this study, we investigate metastability as a candidate neuromechanistic biomarker of schizophrenia pathology, including a demonstration of reliability and face validity. Group-level discrimination, individual-level classification, pathophysiological relevance, and explanatory power were assessed using two independent case-control studies of schizophrenia, the Human Connectome Project Early Psychosis (HCPEP) study (controls n = 53, non-affective psychosis n = 82) and the Cobre study (controls n = 71, cases n = 59). In this work we extend Leading Eigenvector Dynamic Analysis (LEiDA) to capture specific features of dynamic functional connectivity and then implement a novel approach to estimate metastability. We used non-parametric testing to evaluate group-level differences and a naïve Bayes classifier to discriminate cases from controls. Our results show that our new approach is capable of discriminating cases from controls with elevated effect sizes relative to published literature, reflected in an up to 76% area under the curve (AUC) in out-of-sample classification analyses. Additionally, our new metric showed explanatory power of between 81-92% for measures of integration and segregation. Furthermore, our analyses demonstrated that patients with early psychosis exhibit intermittent disconnectivity of subcortical regions with frontal cortex and cerebellar regions, introducing new insights about the mechanistic bases of these conditions. Overall, these findings demonstrate reliability and face validity of metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.
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Affiliation(s)
- Fran Hancock
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, London, United Kingdom
| | - Fernando E. Rosas
- Department of Informatics, University of Sussex, Brighton, United Kingdom
- Centre for Psychedelic Research, Department of Brain Science, Imperial College London, London, United Kingdom
- Centre for Complexity Science, Imperial College London, London, United Kingdom
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
| | - Robert A. McCutcheon
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, De Crespigny Park, London, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Joana Cabral
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Life and Health Sciences Research Institute School of Medicine, University of Minho, Braga, Portugal
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, London, United Kingdom
| | - Federico E. Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, London, United Kingdom
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8
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Zhou J, Guo X, Liu X, Luo Y, Chang X, He H, Duan M, Li S, Li Q, Tan Y, Yao G, Yao D, Luo C. Intrinsic Therapeutic Link between Recuperative Cerebellar Con-Nectivity and Psychiatry Symptom in Schizophrenia Patients with Comorbidity of Metabolic Syndrome. LIFE (BASEL, SWITZERLAND) 2023; 13:life13010144. [PMID: 36676092 PMCID: PMC9863013 DOI: 10.3390/life13010144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 12/23/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023]
Abstract
Components of metabolic syndrome might be predictors of the therapeutic outcome of psychiatric symptom in schizophrenia, whereas clinical results are inconsistent and an intrinsic therapeutic link between weaker psychiatric symptoms and emergent metabolic syndrome remains unclear. This study aims to reveal the relationship and illustrate potential mechanism by exploring the alteration of cerebellar functional connectivity (FC) in schizophrenia patients with comorbidity metabolic syndrome. Thirty-six schizophrenia patients with comorbidity of metabolic syndrome (SCZ-MetS), 45 schizophrenia patients without metabolic syndrome (SCZ-nMetS) and 39 healthy controls (HC) were recruited in this study. We constructed FC map of cerebello-cortical circuit and used moderation effect analysis to reveal complicated relationship among FC, psychiatric symptom and metabolic disturbance. Components of metabolic syndrome were significantly correlated with positive symptom score and negative symptom score. Importantly, the dysconnectivity between cognitive module of cerebellum and left middle frontal gyrus in SCZ-nMetS was recuperative increased in SCZ-MetS, and was significantly correlated with general symptom score. Finally, we observed significant moderation effect of body mass index on this correlation. The present findings further supported the potential relationship between emergence of metabolic syndrome and weaker psychiatric symptom, and provided neuroimaging evidence. The mechanism of intrinsic therapeutic link involved functional change of cerebello-cortical circuit.
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Affiliation(s)
- Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xiao Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xiaoli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Shicai Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Qifu Li
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
| | - Ying Tan
- The Key Laboratory for Computer Systems of State Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610093, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
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9
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Giordano GM, Pezzella P, Giuliani L, Fazio L, Mucci A, Perrottelli A, Blasi G, Amore M, Rocca P, Rossi A, Bertolino A, Galderisi S. Resting-State Brain Activity Dysfunctions in Schizophrenia and Their Associations with Negative Symptom Domains: An fMRI Study. Brain Sci 2023; 13:brainsci13010083. [PMID: 36672064 PMCID: PMC9856573 DOI: 10.3390/brainsci13010083] [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: 11/21/2022] [Revised: 12/07/2022] [Accepted: 12/22/2022] [Indexed: 01/03/2023] Open
Abstract
The aim of the present study was to examine the neurobiological correlates of the two negative symptom domains of schizophrenia, the Motivational Deficit domain (including avolition, anhedonia, and asociality) and the Expressive Deficit domain (including blunted affect and alogia), focusing on brain areas that are most commonly found to be associated with negative symptoms in previous literature. Resting-state (rs) fMRI data were analyzed in 62 subjects affected by schizophrenia (SZs) and 46 healthy controls (HCs). The SZs, compared to the HCs, showed higher rs brain activity in the right inferior parietal lobule and the right temporoparietal junction, and lower rs brain activity in the right dorsolateral prefrontal cortex, the bilateral anterior dorsal cingulate cortex, and the ventral and dorsal caudate. Furthermore, in the SZs, the rs brain activity in the left orbitofrontal cortex correlated with negative symptoms (r = -0.436, p = 0.006), in particular with the Motivational Deficit domain (r = -0.424, p = 0.002), even after controlling for confounding factors. The left ventral caudate correlated with negative symptoms (r = -0.407, p = 0.003), especially with the Expressive Deficit domain (r = -0.401, p = 0.003); however, these results seemed to be affected by confounding factors. In line with the literature, our results demonstrated that the two negative symptom domains might be underpinned by different neurobiological mechanisms.
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Affiliation(s)
- Giulia Maria Giordano
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
| | - Pasquale Pezzella
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
| | - Luigi Giuliani
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
- Correspondence: ; Tel.: +39-0815666512
| | - Leonardo Fazio
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, 70124 Bari, Italy
- Department of Medicine and Surgery, LUM University, 70010 Casamassima, Italy
| | - Armida Mucci
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
| | - Andrea Perrottelli
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
| | - Giuseppe Blasi
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, 70124 Bari, Italy
| | - Mario Amore
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, Section of Psychiatry, University of Genoa, 16132 Genoa, Italy
| | - Paola Rocca
- Department of Neuroscience, Section of Psychiatry, University of Turin, 10126 Turin, Italy
| | - Alessandro Rossi
- Department of Biotechnological and Applied Clinical Sciences, Section of Psychiatry, University of L’Aquila, 67100 L’Aquila, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, 70124 Bari, Italy
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
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10
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Feng S, Zheng S, Zou H, Dong L, Zhu H, Liu S, Wang D, Ning Y, Jia H. Altered functional connectivity of cerebellar networks in first-episode schizophrenia. Front Cell Neurosci 2022; 16:1024192. [PMID: 36439199 PMCID: PMC9692071 DOI: 10.3389/fncel.2022.1024192] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction Abnormalities of the cerebellum have been displayed to be a manifestation of schizophrenia (SCH) which is a detrimental psychiatric disorder. It has been recognized that the cerebellum contributes to motor function, sensorimotor function, cognition, and other brain functions in association with cerebral functions. Multiple studies have observed that abnormal alterations in cerebro-cerebellar functional connectivity (FC) were shown in patients with SCH. However, the FC of cerebellar networks in SCH remains unclear. Methods In this study, we explored the FC of cerebellar networks of 45 patients with first-episode SCH and 45 healthy control (HC) subjects by using a defined Yeo 17 network parcellation system. Furthermore, we performed a correlation analysis between cerebellar networks' FC and positive and negative symptoms in patients with first-episode SCH. Finally, we established the classification model to provide relatively suitable features for patients with first-episode SCH concerning the cerebellar networks. Results We found lower between-network FCs between 14 distinct cerebellar network pairs in patients with first-episode SCH, compared to the HCs. Significantly, the between-network FC in N2-N15 was positively associated with positive symptom severity; meanwhile, N4-N15 was negatively associated with negative symptom severity. Besides, our results revealed a satisfactory classification accuracy (79%) of these decreased between-network FCs of cerebellar networks for correctly identifying patients with first-episode SCH. Conclusion Conclusively, between-network abnormalities in the cerebellum are closely related to positive and negative symptoms of patients with first-episode SCH. In addition, the classification results suggest that the cerebellar networks can be a potential target for further elucidating the underlying mechanisms in first-episode SCH.
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Affiliation(s)
- Sitong Feng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Sisi Zheng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Haoming Zou
- Department of Electronic Engineering, Tsinghua University, Beijing, China
| | - Linrui Dong
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Hong Zhu
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Shanshan Liu
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Dan Wang
- Inner Mongolia Autonomous Region Mental Health Center, Hohhot, China
| | - Yanzhe Ning
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Hongxiao Jia
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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11
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Hancock F, Cabral J, Luppi AI, Rosas FE, Mediano PAM, Dipasquale O, Turkheimer FE. Metastability, fractal scaling, and synergistic information processing: What phase relationships reveal about intrinsic brain activity. Neuroimage 2022; 259:119433. [PMID: 35781077 PMCID: PMC9339663 DOI: 10.1016/j.neuroimage.2022.119433] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 06/25/2022] [Accepted: 06/29/2022] [Indexed: 12/21/2022] Open
Abstract
Dynamic functional connectivity (dFC) in resting-state fMRI holds promise to deliver candidate biomarkers for clinical applications. However, the reliability and interpretability of dFC metrics remain contested. Despite a myriad of methodologies and resulting measures, few studies have combined metrics derived from different conceptualizations of brain functioning within the same analysis - perhaps missing an opportunity for improved interpretability. Using a complexity-science approach, we assessed the reliability and interrelationships of a battery of phase-based dFC metrics including tools originating from dynamical systems, stochastic processes, and information dynamics approaches. Our analysis revealed novel relationships between these metrics, which allowed us to build a predictive model for integrated information using metrics from dynamical systems and information theory. Furthermore, global metastability - a metric reflecting simultaneous tendencies for coupling and decoupling - was found to be the most representative and stable metric in brain parcellations that included cerebellar regions. Additionally, spatiotemporal patterns of phase-locking were found to change in a slow, non-random, continuous manner over time. Taken together, our findings show that the majority of characteristics of resting-state fMRI dynamics reflect an interrelated dynamical and informational complexity profile, which is unique to each acquisition. This finding challenges the interpretation of results from cross-sectional designs for brain neuromarker discovery, suggesting that individual life-trajectories may be more informative than sample means.
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Affiliation(s)
- Fran Hancock
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Portugal
| | - Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge; Department of Clinical Neurosciences, University of Cambridge; Leverhulme Centre for the Future of Intelligence, University of Cambridge; Alan Turing Institute, London, United Kingdom
| | - Fernando E Rosas
- Centre for Psychedelic Research, Department of Brain Science, Imperial College London, London SW7 2DD, United Kingdom; Data Science Institute, Imperial College London, London SW7 2AZ, United Kingdom; Centre for Complexity Science, Imperial College London, London SW7 2AZ, United Kingdom
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom; Department of Psychology, Queen Mary University of London, London E1 4NS, United Kingdom
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Federico E Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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12
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Jiang Y, Yao D, Zhou J, Tan Y, Huang H, Wang M, Chang X, Duan M, Luo C. Characteristics of disrupted topological organization in white matter functional connectome in schizophrenia. Psychol Med 2022; 52:1333-1343. [PMID: 32880241 DOI: 10.1017/s0033291720003141] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Neuroimaging characteristics have demonstrated disrupted functional organization in schizophrenia (SZ), involving large-scale networks within grey matter (GM). However, previous studies have ignored the role of white matter (WM) in supporting brain function. METHODS Using resting-state functional MRI and graph theoretical approaches, we investigated global topological disruptions of large-scale WM and GM networks in 93 SZ patients and 122 controls. Six global properties [clustering coefficient (Cp), shortest path length (Lp), local efficiency (Eloc), small-worldness (σ), hierarchy (β) and synchronization (S) and three nodal metrics [nodal degree (Knodal), nodal efficiency (Enodal) and nodal betweenness (Bnodal)] were utilized to quantify the topological organization in both WM and GM networks. RESULTS At the network level, both WM and GM networks exhibited reductions in Eloc, Cp and S in SZ. The SZ group showed reduced σ and β only for the WM network. Furthermore, the Cp, Eloc and S of the WM network were negatively correlated with negative symptoms in SZ. At the nodal level, the SZ showed nodal disturbances in the corpus callosum, optic radiation, posterior corona radiata and tempo-occipital WM tracts. For GM, the SZ manifested increased nodal centralities in frontoparietal regions and decreased nodal centralities in temporal regions. CONCLUSIONS These findings provide the first evidence for abnormal global topological properties in SZ from the perspective of a substantial whole brain, including GM and WM. Nodal centralities enhance GM areas, along with a reduction in adjacent WM, suggest that WM functional alterations may be compensated for adjacent GM impairments in SZ.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, P. R. China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yue Tan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - MeiLin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Department of Psychiatry, Chengdu Mental Health Center, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
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13
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Cabana-Domínguez J, Torrico B, Reif A, Fernàndez-Castillo N, Cormand B. Comprehensive exploration of the genetic contribution of the dopaminergic and serotonergic pathways to psychiatric disorders. Transl Psychiatry 2022; 12:11. [PMID: 35013130 PMCID: PMC8748838 DOI: 10.1038/s41398-021-01771-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 09/08/2021] [Accepted: 10/13/2021] [Indexed: 12/13/2022] Open
Abstract
Psychiatric disorders are highly prevalent and display considerable clinical and genetic overlap. Dopaminergic and serotonergic neurotransmission have been shown to play an important role in many psychiatric disorders. Here we aim to assess the genetic contribution of these systems to eight psychiatric disorders (attention-deficit hyperactivity disorder (ADHD), anorexia nervosa (ANO), autism spectrum disorder (ASD), bipolar disorder (BIP), major depression (MD), obsessive-compulsive disorder (OCD), schizophrenia (SCZ) and Tourette's syndrome (TS)) using publicly available GWAS analyses performed by the Psychiatric Genomics Consortium that include more than 160,000 cases and 275,000 controls. To do so, we elaborated four different gene sets: two 'wide' selections for dopamine (DA) and for serotonin (SERT) using the Gene Ontology and KEGG pathways tools, and two'core' selections for the same systems, manually curated. At the gene level, we found 67 genes from the DA and/or SERT gene sets significantly associated with one of the studied disorders, and 12 of them were associated with two different disorders. Gene-set analysis revealed significant associations for ADHD and ASD with the wide DA gene set, for BIP with the wide SERT gene set, and for MD with the core SERT set. Interestingly, interrogation of a cross-disorder GWAS meta-analysis of the eight psychiatric conditions displayed association with the wide DA gene set. To our knowledge, this is the first systematic examination of genes encoding proteins essential to the function of these two neurotransmitter systems in these disorders. Our results support a pleiotropic contribution of the dopaminergic and serotonergic systems in several psychiatric conditions.
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Affiliation(s)
- Judit Cabana-Domínguez
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Barcelona, Catalonia, Spain
| | - Bàrbara Torrico
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Barcelona, Catalonia, Spain
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Noèlia Fernàndez-Castillo
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain.
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain.
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Barcelona, Catalonia, Spain.
| | - Bru Cormand
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain.
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain.
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Barcelona, Catalonia, Spain.
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14
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Brakowski J, Manoliu A, Homan P, Bosch OG, Herdener M, Seifritz E, Kaiser S, Kirschner M. Aberrant striatal coupling with default mode and central executive network relates to self-reported avolition and anhedonia in schizophrenia. J Psychiatr Res 2022; 145:263-275. [PMID: 33187692 DOI: 10.1016/j.jpsychires.2020.10.047] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Revised: 10/13/2020] [Accepted: 10/30/2020] [Indexed: 11/17/2022]
Abstract
BACKGROUND Avolition and anhedonia are common symptoms in schizophrenia and are related to poor long-term prognosis. There is evidence for aberrant cortico-striatal function and connectivity as neural substrate of avolition and anhedonia. However, it remains unclear how both relate to shared or distinct striatal coupling with large-scale intrinsic networks. Using resting state functional magnetic resonance imaging (rs-fMRI) this study investigated the association of large-scale cortico-striatal functional connectivity with self-reported and clinician-rated avolition and anhedonia in subjects with schizophrenia. METHODS Seventeen subjects with schizophrenia (SZ) and 28 healthy controls (HC) underwent rs-fMRI. Using Independent Component Analysis (ICA), we assessed Independent Components (ICs) reflecting intrinsic connectivity networks (ICNs), intra intrinsic functional connectivity within the ICs (intra-iFC), and intrinsic functional connectivity between different ICs (inter-iFC). Avolition and anhedonia were assessed using the Self Evaluation Scale for Negative Symptoms and the Brief Negative Symptom Scale. RESULTS ICA revealed three striatal components and six cortical ICNs. Both self-rated avolition and anhedonia correlated with increased inter-iFC between the caudate and posterior Default Mode Network (pDMN) and between the caudate and Central Executive Network (CEN). In contrast, clinician-rated avolition and anhedonia were not correlated with cortico-striatal connectivity. Group comparison revealed trend-wise decreased inter-iFC between the caudate and Salience Network (SN) in schizophrenia patients compared to HC. DISCUSSION Self-rated, but not clinician-rated, avolition and anhedonia was associated with aberrant striatal coupling with the default mode and the central executive network. These findings suggest that self-reported and clinician-rated scores might capture different aspects of motivational and hedonic deficits in schizophrenia and therefore relate to different cortico-striatal functional abnormalities.
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Affiliation(s)
- Janis Brakowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Lenggstrasse 31, 8032, Zurich, Switzerland.
| | - Andrei Manoliu
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Lenggstrasse 31, 8032, Zurich, Switzerland; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Russell Square House, 10-12, Russell Square London, WC1B 5EH, United Kingdom
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Lenggstrasse 31, 8032, Zurich, Switzerland
| | - Oliver G Bosch
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Lenggstrasse 31, 8032, Zurich, Switzerland
| | - Marcus Herdener
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Lenggstrasse 31, 8032, Zurich, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Lenggstrasse 31, 8032, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Chemin Du Petit-Bel-Air, 1226, Thônex, Switzerland
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Lenggstrasse 31, 8032, Zurich, Switzerland; Montreal Neurological Institute, McGill University, 3801 University St, Montréal, QC, H3A 2B4, Canada.
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15
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Zhu T, Wang Z, Zhou C, Fang X, Huang C, Xie C, Ge H, Yan Z, Zhang X, Chen J. Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation. Front Psychiatry 2022; 13:957685. [PMID: 36238945 PMCID: PMC9552970 DOI: 10.3389/fpsyt.2022.957685] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 09/05/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Persistent negative symptoms (PNS) include both primary and secondary negative symptoms that persist after adequate treatment, and represent an unmet therapeutic need. Published magnetic resonance imaging (MRI) evidence of structural and resting-state functional brain abnormalities in schizophrenia with PNS has been inconsistent. Thus, the purpose of this meta-analysis is to identify abnormalities in structural and functional brain regions in patients with PNS compared to healthy controls. METHODS We systematically searched PubMed, Web of Science, and Embase for structural and functional imaging studies based on five research methods, including voxel-based morphometry (VBM), diffusion tensor imaging (DTI), functional connectivity (FC), the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo). Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm. RESULTS Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. Our analysis revealed the presence of structural alterations in patients with PNS in some brain regions including the bilateral insula, medial frontal gyrus, anterior cingulate gyrus, left amygdala, superior temporal gyrus, inferior frontal gyrus, cingulate gyrus and middle temporal gyrus, as well as functional differences in some brain regions including the bilateral precuneus, thalamus, left lentiform nucleus, posterior cingulate gyrus, medial frontal gyrus, and superior frontal gyrus. CONCLUSION Our study suggests that structural brain abnormalities are consistently located in the prefrontal, temporal, limbic and subcortical regions, and functional alterations are concentrated in the thalamo-cortical circuits and the default mode network (DMN). This study provides new insights for targeted treatment and intervention to delay further progression of negative symptoms. SYSTEMATIC REVIEW REGISTRATION [https://www.crd.york.ac.uk/prospero/], identifier [CRD42022338669].
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Affiliation(s)
- Tingting Zhu
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zixu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Zhou
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xinyu Fang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chengbing Huang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Department of Psychiatry, The Third People's Hospital of Huai'an, Huaian, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine Southeast University, Nanjing, China
| | - Honglin Ge
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zheng Yan
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, China
| | - Jiu Chen
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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Yamamoto M, Bagarinao E, Shimamoto M, Iidaka T, Ozaki N. Involvement of cerebellar and subcortical connector hubs in schizophrenia. NEUROIMAGE: CLINICAL 2022; 35:103140. [PMID: 36002971 PMCID: PMC9421528 DOI: 10.1016/j.nicl.2022.103140] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 07/29/2022] [Accepted: 07/30/2022] [Indexed: 11/14/2022] Open
Abstract
Hubs with altered connectivity to multiple networks were identified in patients. Identified hubs were located in the cerebellum, midbrain, thalamus, and insula. In controls, these hubs were strongly connected with the basal ganglia network. Hubs’ connections to large-scale networks were associated with clinical data. Their connections were also highly predictive of patients from controls.
Background Schizophrenia is considered a brain connectivity disorder in which functional integration within the brain fails. Central to the brain’s integrative function are connector hubs, brain regions characterized by strong connections with multiple networks. Given their critical role in functional integration, we hypothesized that connector hubs, including those located in the cerebellum and subcortical regions, are severely impaired in patients with schizophrenia. Methods We identified brain voxels with significant connectivity alterations in patients with schizophrenia (n = 76; men = 43) compared to healthy controls (n = 80; men = 43) across multiple large-scale resting state networks (RSNs) using a network metric called functional connectivity overlap ratio (FCOR). From these voxels, candidate connector hubs were identified and verified using seed-based connectivity analysis. Results We found that most networks exhibited connectivity alterations in the patient group. Specifically, connectivity with the basal ganglia and high visual networks was severely affected over widespread brain areas in patients, affecting subcortical and cerebellar regions and the regions involved in visual and sensorimotor processing. Furthermore, we identified critical connector hubs in the cerebellum, midbrain, thalamus, insula, and calcarine with connectivity to multiple RSNs affected in the patients. FCOR values of these regions were also associated with clinical data and could classify patient and control groups with > 80 % accuracy. Conclusions These findings highlight the critical role of connector hubs, particularly those in the cerebellum and subcortical regions, in the pathophysiology of schizophrenia and the potential role of FCOR as a clinical biomarker for the disorder.
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Abnormal within- and cross-networks functional connectivity in different outcomes of herpes zoster patients. Brain Imaging Behav 2021; 16:366-378. [PMID: 34549378 DOI: 10.1007/s11682-021-00510-y] [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] [Accepted: 07/16/2021] [Indexed: 12/23/2022]
Abstract
Neuroimaging studies have displayed aberrant brain activities in individual sensory- and emotional-linked regions in postherpetic neuralgia (PHN) patients. However, multi-dimensional dysfunction in chronic pain may rely on the interplay between networks. Little is known about the changes in the functional architecture of resting state networks (RSNs) in PHN. In this cross-sectional study, we recruited 31 PHN patients, 33 RHZ patients and 34 HCs; all participants underwent resting-state functional magnetic resonance imaging scans. We investigated the differences of within- and cross-network connectivities between different outcomes of HZ patients [including PHN and recuperation from herpes zoster (RHZ)] and healthy controls (HCs) so as to extract a characteristic network pattern of PHN. The abnormal network connectivities were then correlated with clinical variables in respective groups. PHN and RHZ patients could be similarly characterized by abnormal within-default mode network (DMN), DMN-salience network (SN) and SN-basal ganglia network (BGN) connectivity relative to HCs. Of note, compared with RHZ patients, PHN patients could be characterized by abnormal DMN-BGN and within-BGN connectivity. Furthermore, the within-DMN connectivity was associated with pain-induced emotional scores among PHN patients. Our study presented that network-level imbalance could account for the pain-related dysfunctions in different outcomes of herpes zoster patients. These insights are potentially useful for understanding neuromechanism of PHN and providing central therapeutic targets for PHN.
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Cuesta MJ, Lecumberri P, Moreno-Izco L, López-Ilundain JM, Ribeiro M, Cabada T, Lorente-Omeñaca R, de Erausquin G, García-Martí G, Sanjuan J, Sánchez-Torres AM, Gómez M, Peralta V. Motor abnormalities and basal ganglia in first-episode psychosis (FEP). Psychol Med 2021; 51:1625-1636. [PMID: 32114994 DOI: 10.1017/s0033291720000343] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Motor abnormalities (MAs) are the primary manifestations of schizophrenia. However, the extent to which MAs are related to alterations of subcortical structures remains understudied. METHODS We aimed to investigate the associations of MAs and basal ganglia abnormalities in first-episode psychosis (FEP) and healthy controls. Magnetic resonance imaging was performed on 48 right-handed FEP and 23 age-, gender-, handedness-, and educational attainment-matched controls, to obtain basal ganglia shape analysis, diffusion tensor imaging techniques (fractional anisotropy and mean diffusivity), and relaxometry (R2*) to estimate iron load. A comprehensive motor battery was applied including the assessment of parkinsonism, catatonic signs, and neurological soft signs (NSS). A fully automated model-based segmentation algorithm on 1.5T MRI anatomical images and accurate corregistration of diffusion and T2* volumes and R2* was used. RESULTS FEP patients showed significant local atrophic changes in left globus pallidus nucleus regarding controls. Hypertrophic changes in left-side caudate were associated with higher scores in sensory integration, and in right accumbens with tremor subscale. FEP patients showed lower fractional anisotropy measures than controls but no significant differences regarding mean diffusivity and iron load of basal ganglia. However, iron load in left basal ganglia and right accumbens correlated significantly with higher extrapyramidal and motor coordination signs in FEP patients. CONCLUSIONS Taken together, iron load in left basal ganglia may have a role in the emergence of extrapyramidal signs and NSS of FEP patients and in consequence in the pathophysiology of psychosis.
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Affiliation(s)
- Manuel J Cuesta
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Pablo Lecumberri
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Movalsys S. L., NavarraBiomed, Pamplona, Spain
| | - Lucia Moreno-Izco
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Jose M López-Ilundain
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - María Ribeiro
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Teresa Cabada
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Department of Neuroradiology, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Ruth Lorente-Omeñaca
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Gabriel de Erausquin
- Zachry Foundation, The Glenn Biggs Institute of Alzheimer's & Neurodegenerative Disorders, UT Heath San Antonio, Texas, USA
| | - Gracian García-Martí
- Radiology Department, CIBERSAM, Valencia, España, Quirón Salud Hospital, Valencia, España
| | - Julio Sanjuan
- Research Institute of Clinic University Hospital of Valencia (INCLIVA), Valencia, Spain
- CIBERSAM, Biomedical Research Network on Mental Health Area, Madrid, Spain
- Department of Psychiatric, University of Valencia School of Medicine, Valencia, Spain
| | - Ana M Sánchez-Torres
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Marisol Gómez
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Movalsys S. L., NavarraBiomed, Pamplona, Spain
- Department of Statistics, Computer Science and Mathematics, Universidad Pública de Navarra (UPNA), Pamplona, Spain
| | - Victor Peralta
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud, Pamplona, Spain
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Abstract
Basal ganglia, which include the striatum and thalamus, have key roles in motivation, emotion, motor function, also contribute to higher-order cognitive function. Previous researches have documented structural and functional alterations in basal ganglia in schizophrenia. While few studies have assessed asymmetries of these characters in basal ganglia of schizophrenia. The current study investigated this issue by using diffusion tensor imaging, anatomic T1-weight image and resting-state functional data from 88 chronic schizophrenic subjects and 92 healthy controls. The structural characteristic, including fractional anisotropy, mean diffusivity (MD) and volume, were extracted and quantified from the subregions of basal ganglia, including caudate, putamen, pallidum and thalamus, through automated atlas-based method. The resting-state functional maps of these regions were also calculated through seed-based functional connectivity. Then, the laterality indexes of structural and functional features were calculated. Compared with healthy controls, schizophrenic subjects showed increased left laterality of volume in striatum and reduced left laterality of volume in thalamus. Furthermore, the difference of laterality of subregions in thalamus is compensatory in schizophrenic subjects. Importantly, the severity of patients' positive symptom was negative corelated with reduced left laterality of volume in thalamus. Our findings provide preliminary evidence demonstrating that the possibility of aberrant laterality in neural pathways and connectivity patterns related to the basal ganglia in schizophrenia.
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20
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Hu Q, Huang H, Jiang Y, Jiao X, Zhou J, Tang Y, Zhang T, Sun J, Yao D, Luo C, Li C, Wang J. Temporoparietal Connectivity Within Default Mode Network Associates With Clinical Improvements in Schizophrenia Following Modified Electroconvulsive Therapy. Front Psychiatry 2021; 12:768279. [PMID: 35058815 PMCID: PMC8763790 DOI: 10.3389/fpsyt.2021.768279] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 12/02/2021] [Indexed: 12/19/2022] Open
Abstract
Although modified electroconvulsive therapy (ECT) has been reported to be effective for the treatment of schizophrenia (SCZ), its action mechanism is unclear. To elucidate the underlying ECT mechanisms of SCZ, this study used a longitudinal cohort including 21 SCZ patients receiving only antipsychotics (DSZ group) and 21 SCZ patients receiving a regular course of ECT combining with antipsychotics (MSZ group) for 4 weeks. All patients underwent magnetic resonance imaging (MRI) scans at baseline (t1) and follow-up (t2) time points. A matched healthy control (HC) group included 23 individuals who were only scanned at baseline. Functional connectivity (FC) within the default mode network (DMN) was evaluated before and after ECT. Significant interaction of the group over time was found in FC between angular gyrus (AG) and middle temporal gyrus (MTG). Post-hoc analysis showed a significantly enhanced FC of left AG(AG.L) and right MTG (MTG.R) in the MSZ group relative to the DSZ group. In addition, the right AG (AG.R) showed significantly enhanced FC between MTG.R and left MTG (MTG.L) after ECT in the MSZ group, but no in the DSZ group. In particular, the FCs change in AG.L-MTG.R and AG.R-MTG.R were positively correlated with the Positive and Negative Syndrome Scale (PANSS) negative score reduction. Furthermore, the FC change in AG.L-MTG.R was also positively correlated with the PANSS general psychopathology score reduction. These findings confirmed a potential relationship between ECT inducing hyperconnectivity within DMN and improvements in symptomatology of SCZ, suggesting that ECT controls mental symptoms by regulating the temporoparietal connectivity within DMN.
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Affiliation(s)
- Qiang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiong Jiao
- School of BIomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zhou
- School of BIomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junfeng Sun
- School of BIomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China.,Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
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21
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Dong D, Duan M, Wang Y, Zhang X, Jia X, Li Y, Xin F, Yao D, Luo C. Reconfiguration of Dynamic Functional Connectivity in Sensory and Perceptual System in Schizophrenia. Cereb Cortex 2020; 29:3577-3589. [PMID: 30272139 DOI: 10.1093/cercor/bhy232] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 08/01/2018] [Indexed: 12/17/2022] Open
Abstract
Schizophrenia is thought as a self-disorder with dysfunctional brain connectivity. This self-disorder is often attributed to high-order cognitive impairment. Yet due to the frequent report of sensorial and perceptual deficits, it has been hypothesized that self-disorder in schizophrenia is dysfunctional communication between sensory and cognitive processes. To further verify this assumption, the present study comprehensively examined dynamic reconfigurations of resting-state functional connectivity (rsFC) in schizophrenia at voxel level, region level, and network levels (102 patients vs. 124 controls). We found patients who show consistently increased rsFC variability in sensory and perceptual system, including visual network, sensorimotor network, attention network, and thalamus at all the three levels. However, decreased variability in high-order networks, such as default mode network and frontal-parietal network were only consistently observed at region and network levels. Taken together, these findings highlighted the rudimentary role of elevated instability of information communication in sensory and perceptual system and attenuated whole-brain integration of high-order network in schizophrenia, which provided novel neural evidence to support the hypothesis of disrupted perceptual and cognitive function in schizophrenia. The foci of effects also highlighted that targeting perceptual deficits can be regarded as the key to enhance our understanding of pathophysiology in schizophrenia and promote new treatment intervention.
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Affiliation(s)
- Debo Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China.,Department of Psychiatry, The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Yulin Wang
- Department of Experimental and Applied Psychology, Faculty of Psychological and Educational Sciences, Vrije Universiteit Brussel, Brussels, Belgium.,Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Henri Dunantlaan 2, Ghent, Belgium
| | - Xingxing Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China
| | - Xiaoyan Jia
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China
| | - Yingjia Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China
| | - Fei Xin
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, Chengdu, China
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22
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Wang J, Jiang Y, Tang Y, Xia M, Curtin A, Li J, Sheng J, Zhang T, Li C, Hui L, Zhu H, Biswal BB, Jia Q, Luo C, Wang J. Altered functional connectivity of the thalamus induced by modified electroconvulsive therapy for schizophrenia. Schizophr Res 2020; 218:209-218. [PMID: 31956007 DOI: 10.1016/j.schres.2019.12.044] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 12/29/2019] [Accepted: 12/31/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) has been shown to be effective in schizophrenia (SZ), particularly in drug-refractory cases or when rapid symptom relief is needed. However, its precise mechanisms of action remain largely unclear. To clarify the mechanisms underlying modified electroconvulsive therapy (mECT) for SZ, we conducted a longitudinal cohort study evaluating functional connectivity of the thalamus before and after mECT treatment using sub-regions of thalamus as regions of interest (ROIs). METHODS Twenty-one SZ individuals taking only antipsychotics (DSZ group) for 4 weeks and 21 SZ patients receiving a regular course of mECT combining with antipsychotics (MSZ group) were observed in parallel. All patients underwent magnetic resonance imaging scans at baseline (t1) and follow-up (t2, ~4 weeks) time points. Data were compared to a matched healthy control group (HC group) consisting of 23 persons who were only scanned at baseline. Group differences in changes of thalamic functional connectivity between two SZ groups over time, as well as in functional connectivity among two SZ groups and HC group were assessed. RESULTS Significant interaction of group by time was found in functional connectivity of the right thalamus to right putamen during the course of about 4-week treatment. Post-hoc analysis showed a significantly enhanced functional connectivity of the right thalamus to right putamen in the MSZ group contrasting to the DSZ group. In addition, a decreased and an increased functional connectivity of the thalamus to sensory cortex were observed within the MSZ and DSZ group after 4-week treatment trial, respectively. CONCLUSION Our findings suggest that changes in functional connectivity of the thalamus may be associated with the brain mechanisms of mECT for schizophrenia.
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Affiliation(s)
- Junjie Wang
- Institute of Mental Health, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu 215137, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Yuchao Jiang
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
| | - Mengqing Xia
- Institute of Mental Health, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu 215137, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Adrian Curtin
- School of Biomedical Engineering & Health Sciences, Drexel University, Philadelphia, PA 19104, USA; Med-X Institute, Shanghai Jiaotong University, Shanghai 200300, China
| | - Jin Li
- Institute of Mental Health, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu 215137, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Jianhua Sheng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, China; Brain Science and Technology Research Center, Shanghai Jiaotong University, Shanghai 200030, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiaotong University, Shanghai 200030, China
| | - Li Hui
- Institute of Mental Health, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu 215137, China
| | - Hongliang Zhu
- Institute of Mental Health, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu 215137, China
| | - Bharat B Biswal
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Qiufang Jia
- Institute of Mental Health, Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu 215137, China.
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, China; Brain Science and Technology Research Center, Shanghai Jiaotong University, Shanghai 200030, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiaotong University, Shanghai 200030, China
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Large-Scale Neuronal Network Dysfunction in Diabetic Retinopathy. Neural Plast 2020; 2020:6872508. [PMID: 32399026 PMCID: PMC7204201 DOI: 10.1155/2020/6872508] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 12/26/2019] [Indexed: 12/19/2022] Open
Abstract
Diabetic retinopathy (DR) patients are at an increased risk of cognitive decline and dementia. There is accumulating evidence that specific functional and structural architecture changes in the brain are related to cognitive impairment in DR patients. However, little is known regarding whether the functional architecture of resting-state networks (RSNs) changes in DR patients. The purpose of this study was to investigate the intranetwork functional connectivity (FC) and functional network connectivity (FNC) of RSN changes in DR patients using independent component analysis (ICA). Thirty-four DR patients (18 men and 16 women; mean age, 53.53 ± 8.67 years) and 38 nondiabetic healthy controls (HCs) (15 men and 23 women; mean age, 48.63 ± 11.83 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the nine RSNs. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within nine RSNs between the two groups. The FNC toolbox was used to assess interactions among RSNs. Pearson correlation analysis was conducted to explore the relationship between intranetwork FCs and clinical variables in the DR group. A receiver operating characteristic (ROC) curve was conducted to assess the ability of the intranetwork FCs of RSNs in discriminating between the two groups. Compared to the HC group, DR patients showed significant decreased intranetwork FCs within the basal ganglia network (BGN), visual network (VN), ventral default mode network (vDMN), right executive control network (rECN), salience network (SN), left executive control network (lECN), auditory network (AN), and dorsal default mode network (dDMN). In addition, FNC analysis showed increased VN-BGN, VN-vDMN, VN-dDMN, vDMN-lECN, SN-BGN, lECN-dDMN, and AN-BGN FNCs in the DR group, relative to the HC group. Furthermore, altered intranetwork FCs of RSNs were significantly correlated with the glycosylated hemoglobin (HbA1c) level in DR patients. A ROC curve showed that these specific intranetwork FCs of RSNs discriminated between the two groups with a high degree of sensitivity and specificity. Our study highlighted that DR patients had widespread deficits in both low-level perceptual and higher-order cognitive networks. Our results offer important insights into the neural mechanisms of visual loss and cognitive decline in DR patients.
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Tarcijonas G, Foran W, Haas GL, Luna B, Sarpal DK. Intrinsic Connectivity of the Globus Pallidus: An Uncharted Marker of Functional Prognosis in People With First-Episode Schizophrenia. Schizophr Bull 2020; 46:184-192. [PMID: 31150557 PMCID: PMC6942165 DOI: 10.1093/schbul/sbz034] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
There is growing evidence suggesting that abnormalities in cortical-basal ganglia circuitry may play a significant role in determining outcomes in schizophrenia. The globus pallidus (GP), a critical structure within this circuitry, unique in its role as a mediator of competing inputs through the striatum, has not been well characterized in schizophrenia. The following study examined functional interactions of the GP in individuals with first-episode schizophrenia (FES). To probe the large-scale intrinsic connectivity of the GP, resting-state fMRI scans were obtained from patients with FES and sex and age-matched healthy controls. Participants with FES were also evaluated after 6 months via the Strauss-Carpenter Outcomes Scale to assess overall functional trajectory. The GP was parcellated to generate seeds within its substructures, and connectivity maps were generated. Our FES cohort showed significantly lower functional connectivity between the left GP interna and a network of regions including the dorsolateral prefrontal cortex, caudate, and cerebellum at baseline. In addition, FES participants with lower overall scores of functioning at 6 months showed significantly decreased connectivity between the GP interna and the dorsal anterior cingulate and bilateral insula, all regions important for motivational salience. These results provide novel evidence for unique abnormalities in functional interactions of the GP with key prefrontal cortical regions in FES. Our findings also suggest that reduced prefrontal-pallidal connectivity may serve as a predictor of early functional outcome.
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Affiliation(s)
- Goda Tarcijonas
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - Gretchen L Haas
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA,Department of Psychology, University of Pittsburgh, Pittsburgh, PA,Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA
| | - Deepak K Sarpal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA,To whom correspondence should be addressed; Department of Psychiatry, University of Pittsburgh, 3501 Forbes Avenue, Suite 530, Pittsburgh, PA 15213, US; tel: 412-246-5618, fax: 412-246-5007, e-mail:
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Common increased hippocampal volume but specific changes in functional connectivity in schizophrenia patients in remission and non-remission following electroconvulsive therapy: A preliminary study. NEUROIMAGE-CLINICAL 2019; 24:102081. [PMID: 31734526 PMCID: PMC6861644 DOI: 10.1016/j.nicl.2019.102081] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 10/10/2019] [Accepted: 11/06/2019] [Indexed: 01/21/2023]
Abstract
Electroconvulsive therapy (ECT) is considered a treatment option in patients with drug-resistant schizophrenia (SZ). However, approximately one-third of patients do not benefit from ECT in the clinic. Thus, it is critical to investigate differences between ECT responders and non-responders. Accumulated evidence has indicated that one region of ECT action is the hippocampus, which also plays an important role in SZ pathophysiology. To date, no studies have investigated differences in ECT effects in the hippocampus between treatment responders and non-responders. This study recruited twenty-one SZ patients treated for four weeks with ECT (MSZ, n = 21) and twenty-one SZ patients who received pharmaceutical therapy (DSZ, n = 21). The MSZ group was further categorized into responders (MSR, n = 10) or non-responders (MNR, n = 11) based on treatment outcomes by the criterion of a 50% reduction in the Positive and Negative Syndrome Scale total scores. Using structural and resting-state functional MRI, we measured the hippocampal volume and functional connectivity (FC) in all SZ patients (before and after treatment) and 23 healthy controls. In contrast to pharmaceutical therapy, ECT induced bilateral hippocampal volume increases in the MSZ. Both the MSR and MNR exhibited hippocampal expansion after ECT, whereas a lower baseline volume in one of hippocampal subfield (hippocampus-amygdala transition area) was found in the MNR. After ECT, increased FC between the hippocampus and brain networks associated with cognitive function was only observed in the MSR. The mechanism of action of ECT in schizophrenia is complex. A combination of baseline impairment level, ECT-introduced morphological changes and post-ECT FC increases in the hippocampus may jointly contribute to the post-ECT symptom improvements in patients with SZ.
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Li S, Hu N, Zhang W, Tao B, Dai J, Gong Y, Tan Y, Cai D, Lui S. Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity. Front Psychiatry 2019; 10:482. [PMID: 31354545 PMCID: PMC6639431 DOI: 10.3389/fpsyt.2019.00482] [Citation(s) in RCA: 103] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 06/19/2019] [Indexed: 02/05/2023] Open
Abstract
Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.
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Affiliation(s)
- Siyi Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Na Hu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Dai
- Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, China
| | - Yao Gong
- Department of Geriatric Psychiatry, The Fourth People’s Hospital of Chengdu, Chengdu, China
| | - Youguo Tan
- Department of Psychiatry, Zigong Mental Health Center, Zigong, China
| | - Duanfang Cai
- Department of Psychiatry, Zigong Mental Health Center, Zigong, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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Jiang Y, Song L, Li X, Zhang Y, Chen Y, Jiang S, Hou C, Yao D, Wang X, Luo C. Dysfunctional white-matter networks in medicated and unmedicated benign epilepsy with centrotemporal spikes. Hum Brain Mapp 2019; 40:3113-3124. [PMID: 30937973 PMCID: PMC6865396 DOI: 10.1002/hbm.24584] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 03/11/2019] [Accepted: 03/18/2019] [Indexed: 12/18/2022] Open
Abstract
Benign epilepsy with centrotemporal spikes (BECT) is the most common childhood idiopathic focal epilepsy syndrome, which characterized with white-matter abnormalities in the rolandic cortex. Although diffusion tensor imaging research could characterize white-matter structural architecture, it cannot detect neural activity or white-matter functions. Recent studies demonstrated the functional organization of white-matter by using functional magnetic resonance imaging (fMRI), suggesting that it is feasible to investigate white-matter dysfunctions in BECT. Resting-state fMRI data were collected from 24 new-onset drug-naive (unmedicated [NMED]), 21 medicated (MED) BECT patients, and 27 healthy controls (HC). Several white-matter functional networks were obtained using a clustering analysis on voxel-by-voxel correlation profiles. Subsequently, conventional functional connectivity (FC) was calculated in four frequency sub-bands (Slow-5:0.01-0.027, Slow-4:0.027-0.073, Slow-3:0.073-0.198, and Slow-2:0.198-0.25 Hz). We also employed a functional covariance connectivity (FCC) to estimate the covariant relationship between two white-matter networks based on their correlations with multiple gray-matter regions. Compared with HC, the NMED showed increased FC and/or FCC in rolandic network (RN) and precentral/postcentral network, and decreased FC and/or FCC in dorsal frontal network, while these alterations were not observed in the MED group. Moreover, the changes exhibited frequency-specific properties. Specifically, only two alterations were shared in at least two frequency bands. Most of these alterations were observed in the frequency bands of Slow-3 and Slow-4. This study provided further support on the existence of white-matter functional networks which exhibited frequency-specific properties, and extended abnormalities of rolandic area from the perspective of white-matter dysfunction in BECT.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Li Song
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Xuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Yaodan Zhang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
- Chengdu University of Traditional Chinese MedicineChengdu, SichuanChina
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Changyue Hou
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xiaoming Wang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
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Jiang Y, Luo C, Li X, Li Y, Yang H, Li J, Chang X, Li H, Yang H, Wang J, Duan M, Yao D. White-matter functional networks changes in patients with schizophrenia. Neuroimage 2019; 190:172-181. [DOI: 10.1016/j.neuroimage.2018.04.018] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 03/26/2018] [Accepted: 04/09/2018] [Indexed: 10/17/2022] Open
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29
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Liu S, Wang H, Song M, Lv L, Cui Y, Liu Y, Fan L, Zuo N, Xu K, Du Y, Yu Q, Luo N, Qi S, Yang J, Xie S, Li J, Chen J, Chen Y, Wang H, Guo H, Wan P, Yang Y, Li P, Lu L, Yan H, Yan J, Wang H, Zhang H, Zhang D, Calhoun VD, Jiang T, Sui J. Linked 4-Way Multimodal Brain Differences in Schizophrenia in a Large Chinese Han Population. Schizophr Bull 2019; 45:436-449. [PMID: 29897555 PMCID: PMC6403093 DOI: 10.1093/schbul/sby045] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with synchronous changes in both functional and structural regions, especially the basal ganglia network, salience network (SAN), and the frontoparietal network. Such a multimodal coalteration was also replicated in another independent Chinese sample (40 SZs, 66 HCs). Our results on auditory verbal hallucination (AVH) also provide evidence for the hypothesis that prefrontal hypoactivation and temporal hyperactivation in SZ may lead to failure of executive control and inhibition, which is relevant to AVH. In addition, impaired working memory performance was found associated with GM reduction and FA decrease in SZ in prefrontal and superior temporal area, in both discovery and replication datasets. In summary, by leveraging multiple imaging and clinical information into one framework to observe brain in multiple views, we can integrate multiple inferences about SZ from large-scale population and offer unique perspectives regarding the missing links between the brain function and structure that may not be achieved by separate unimodal analyses.
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Affiliation(s)
- Shengfeng Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China,School of Automation, Harbin University of Science and Technology, Harbin, China,University of Chinese Academy of Sciences, Beijing, China,National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Haiying Wang
- School of Automation, Harbin University of Science and Technology, Harbin, China
| | - Ming Song
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| | - Yue Cui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Yong Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Nianming Zuo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Kaibin Xu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Yuhui Du
- The Mind Research Network, Albuquerque, NM,School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - Qingbao Yu
- The Mind Research Network, Albuquerque, NM
| | - Na Luo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China,University of Chinese Academy of Sciences, Beijing, China
| | - Shile Qi
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China,University of Chinese Academy of Sciences, Beijing, China
| | - Jian Yang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, China
| | - Sangma Xie
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jian Li
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, Zhumadian, China
| | - Ping Wan
- Zhumadian Psychiatric Hospital, Zhumadian, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China,Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Peng Li
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Lin Lu
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China,Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Jun Yan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China,Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Dai Zhang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China,Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM,Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China,University of Chinese Academy of Sciences, Beijing, China,Queensland Brain Institute, University of Queensland, Brisbane, Australia,CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China,University of Chinese Academy of Sciences, Beijing, China,The Mind Research Network, Albuquerque, NM,CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China,To whom correspondence should be addressed; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; tel: +86-10-8254-4518; fax: +86-10-8254-4777; e-mail:
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30
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He H, Luo C, Luo Y, Duan M, Yi Q, Biswal BB, Yao D. Reduction in gray matter of cerebellum in schizophrenia and its influence on static and dynamic connectivity. Hum Brain Mapp 2019; 40:517-528. [PMID: 30240503 PMCID: PMC6865738 DOI: 10.1002/hbm.24391] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 08/27/2018] [Accepted: 08/30/2018] [Indexed: 12/14/2022] Open
Abstract
Pathophysiological and atrophic changes in the cerebellum have been well-documented in schizophrenia. Reduction of gray matter (GM) in the cerebellum was confirmed across cognitive and motor cerebellar modules in schizophrenia. Such abnormalities in the cerebellum could potentially have widespread effects on both sensorimotor and cognitive symptoms. In this study, we investigated how reduction change in the cerebellum affects the static and the dynamic functional connectivity (FC) between the cerebellum and cortical/subcortical networks in schizophrenia. Reduction of GM in the cerebellum was confirmed across the cognitive and motor cerebellar modules in schizophrenic subjects. Results from this study demonstrates that the extent of reduction of GM within cerebellum correlated with increased static FCs between the cerebellum and the cortical/subcortical networks, including frontoparietal network (FPN), and thalamus in patients with schizophrenia. Decreased GM in the cerebellum was also associated with a declined dynamic FC between the cerebellum and the FPN in schizophrenic subjects. The severity of patients' positive symptom was related to these structural-functional coupling score of cerebellum. These findings identified potential cerebellar driven functional changes associated with positive symptom deficits. A post hoc analysis exploring the effect of changed FC within cerebellum, confirmed that a significant positive relationship, between dynamic FCs of cerebellum-thalamus and intracerebellum existed in patients, but not in controls. The reduction of GM within the cerebellum might be associated with modulation of cerebellum-thalamus, and contributes to the dysfunctional cerebellar-cortical communication in schizophrenia. Our results provide a new insight into the role of cerebellum in understanding the pathophysiological of schizophrenia.
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Affiliation(s)
- Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Qizhong Yi
- Psychological Medicine CenterThe First Affiliated Hospital of Xinjiang Medical UniversityXinjiangPeople's Republic of China
| | - Bharat B. Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Biomedical EngineeringNew Jersey Institute of TechnologyNewarkNJ07102USA
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
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31
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Kumar M, Rana P, Modi S, Tyagi R, Kaur P, Kanwar R, Sekhri T, D'souza M, Khushu S. Aberrant intra and inter network resting state functional connectivity in thyrotoxicosis. J Neuroendocrinol 2019; 31:e12683. [PMID: 30600576 DOI: 10.1111/jne.12683] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 12/02/2018] [Accepted: 12/28/2018] [Indexed: 11/28/2022]
Abstract
Thyroid hormones epigenetically play an important role in the regularisation of neural networks and in neural differentiation during brain development. The present study aimed to explore the intra and inter network resting state functional connectivity changes underlying the neurobehavioural symptoms in thyrotoxicosis. To understand the pathophysiological changes, we investigated the correlation between functional connectivity and clinical and behavioural measures. Twenty-eight freshly diagnosed thyrotoxicosis patients suffering with symptoms such as palpitation, loss of weight, trembling and heat intolerance from days to weeks and 28 healthy controls were recruited for the study. Thyrotoxicosis patients showed significantly decreased functional connectivity in sensorimotor network, fronto-temporal network, default mode network, right fronto-parietal network, left fronto-parietal network and salience network. Inter network functional connectivity was significantly reduced between the basal ganglia network and sensorimotor network and increased between the salience network and fronto-temporal network in thyrotoxicosis. Cognitive functions such as visual retention, recognition of objects, mental balance and performance on neuropsychological tests (ie, the Bender Gestalt test, Nahar-Benson test and Mini Mental State Examination) also showed significant decline in thyrotoxicosis patients. The altered intrinsic resting state functional connectivity might underlie these cognitive deficits. The increased functional connectivity between the salience network and fronto-temporal network suggests the recruitment of additional neuronal circuitry needed to compensate for the neuropathology in the primary neural network in thyrotoxicosis.
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Affiliation(s)
- Mukesh Kumar
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, New Delhi, India
| | - Poonam Rana
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, New Delhi, India
| | - Shilpi Modi
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, New Delhi, India
| | - Ritu Tyagi
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, New Delhi, India
| | - Prabhjot Kaur
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, New Delhi, India
| | | | - Tarun Sekhri
- Thyroid Research Centre, INMAS, DRDO, New Delhi, India
| | - Maria D'souza
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, New Delhi, India
| | - Subash Khushu
- NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, New Delhi, India
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32
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Griffanti L, Stratmann P, Rolinski M, Filippini N, Zsoldos E, Mahmood A, Zamboni G, Douaud G, Klein JC, Kivimäki M, Singh-Manoux A, Hu MT, Ebmeier KP, Mackay CE. Exploring variability in basal ganglia connectivity with functional MRI in healthy aging. Brain Imaging Behav 2018; 12:1822-1827. [PMID: 29442271 PMCID: PMC6302142 DOI: 10.1007/s11682-018-9824-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Changes in functional connectivity (FC) measured using resting state fMRI within the basal ganglia network (BGN) have been observed in pathologies with altered neurotransmitter systems and conditions involving motor control and dopaminergic processes. However, less is known about non-disease factors affecting FC in the BGN. The aim of this study was to examine associations of FC within the BGN with dopaminergic processes in healthy older adults. We explored the relationship between FC in the BGN and variables related to demographics, impulsive behavior, self-paced tasks, mood, and motor correlates in 486 participants in the Whitehall-II imaging sub-study using both region-of-interest- and voxel-based approaches. Age was the only correlate of FC in the BGN that was consistently significant with both analyses. The observed adverse effect of aging on FC may relate to alterations of the dopaminergic system, but no unique dopamine-related function seemed to have a link with FC beyond those detectable in and linearly correlated with healthy aging.
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Affiliation(s)
- Ludovica Griffanti
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
| | - Philipp Stratmann
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Informatics, Germany and Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Technical University of Munich, Wessling, Germany
| | - Michal Rolinski
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Institute of Clinical Neurosciences, University of Bristol, Bristol, UK
| | - Nicola Filippini
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Abda Mahmood
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Giovanna Zamboni
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Gwenaëlle Douaud
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, UK
- INSERM, U 1018, Hôpital Paul-Brousse, Villejuif, France
| | - Michele T Hu
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Clare E Mackay
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK.
- Oxford Health NHS Foundation Trust, Oxford, UK.
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK.
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33
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Yukawa T, Iwakura Y, Takei N, Saito M, Watanabe Y, Toyooka K, Igarashi M, Niizato K, Oshima K, Kunii Y, Yabe H, Matsumoto J, Wada A, Hino M, Iritani S, Niwa SI, Takeuchi R, Takahashi H, Kakita A, Someya T, Nawa H. Pathological alterations of chondroitin sulfate moiety in postmortem hippocampus of patients with schizophrenia. Psychiatry Res 2018; 270:940-946. [PMID: 30551347 DOI: 10.1016/j.psychres.2018.10.062] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Revised: 08/27/2018] [Accepted: 10/23/2018] [Indexed: 12/20/2022]
Abstract
Perineuronal nets comprise chondroitin sulfate moieties and their core proteins, and their neuropathological alterations have been implicated in schizophrenia. To explore the molecular mechanism of the perineuronal net impairments in schizophrenia, we measured the immunoreactivity of chondroitin sulfate moieties, major components of perineuronal nets, in three brain regions (postmortem dorsolateral prefrontal cortex, caudate nucleus, and hippocampus) of schizophrenia patients and control subjects. Immunoblotting for chondroitin 4-sulfate and chondroitin 6-sulfate moieties revealed a significant increase in intensity of a 180 kD band of chondroitin 4-sulfate immunoreactivity in the hippocampus of patients, although we detected no significant alteration in their immunoreactivities with any other molecular sizes or in other brain regions. The levels of immunoreactivity were not correlated with postmortem interval, age, or storage time. We failed to find such an increase in a similar molecular range of the chondroitin 4-sulfate immunoreactivity in the hippocampus of the rats chronically treated with haloperidol. These results suggest that the level alteration of the chondroitin 4-sulfate moiety might contribute to the perineuronal net abnormality found in patients with schizophrenia.
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Affiliation(s)
- Takayuki Yukawa
- Department of Molecular Neurobiology, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan; Department of Psychiatry, Graduate School of Medical and Dental Sciences, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8510, Japan
| | - Yuriko Iwakura
- Department of Molecular Neurobiology, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan
| | - Nobuyuki Takei
- Department of Molecular Neurobiology, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan
| | - Mami Saito
- Department of Molecular Neurobiology, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan; Department of Psychiatry, Graduate School of Medical and Dental Sciences, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8510, Japan
| | - Yuichiro Watanabe
- Department of Psychiatry, Graduate School of Medical and Dental Sciences, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8510, Japan
| | - Kazuhiko Toyooka
- Minamihama Hospital, 4540, Shimami-cho, Kita-ku Niigata, Niigata 950-3102, Japan
| | - Michihiro Igarashi
- Department of Neurochemistry and Molecular Cell Biology, Graduate School of Medical and Dental Sciences and Trans-disciplinary Research Program, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8510, Japan
| | - Kazuhiro Niizato
- Tokyo Metropolitan Matsuzawa Hospital, 2-1-1, Kamikitazawa, Setagaya-ku, Tokyo 156-0057, Japan
| | - Kenichi Oshima
- Tokyo Metropolitan Matsuzawa Hospital, 2-1-1, Kamikitazawa, Setagaya-ku, Tokyo 156-0057, Japan
| | - Yasuto Kunii
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, 1- Hikarigaoka, Fukushima, Fukushima 960-1295, Japan
| | - Hirooki Yabe
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, 1- Hikarigaoka, Fukushima, Fukushima 960-1295, Japan
| | - Junya Matsumoto
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, 1- Hikarigaoka, Fukushima, Fukushima 960-1295, Japan
| | - Akira Wada
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, 1- Hikarigaoka, Fukushima, Fukushima 960-1295, Japan
| | - Mizuki Hino
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, 1- Hikarigaoka, Fukushima, Fukushima 960-1295, Japan
| | - Shuji Iritani
- Tokyo Metropolitan Matsuzawa Hospital, 2-1-1, Kamikitazawa, Setagaya-ku, Tokyo 156-0057, Japan; Department of Mental Health, Nagoya University Graduate School of Medicine, 65, Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan
| | - Shin-Ichi Niwa
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, 1- Hikarigaoka, Fukushima, Fukushima 960-1295, Japan
| | - Ryoko Takeuchi
- Pathology and Brain Disease Research Center, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan
| | - Hitoshi Takahashi
- Pathology and Brain Disease Research Center, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan
| | - Akiyoshi Kakita
- Pathology and Brain Disease Research Center, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan
| | - Toshiyuki Someya
- Department of Psychiatry, Graduate School of Medical and Dental Sciences, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8510, Japan
| | - Hiroyuki Nawa
- Department of Molecular Neurobiology, Brain Research Institute, Niigata University, 1-757, Asahimachi-dori, Chuo-ku Niigata, Niigata 951-8585, Japan.
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Fairlie-Clarke K, Barbour M, Wilson C, Hridi SU, Allan D, Jiang HR. Expression and Function of IL-33/ST2 Axis in the Central Nervous System Under Normal and Diseased Conditions. Front Immunol 2018; 9:2596. [PMID: 30515150 PMCID: PMC6255965 DOI: 10.3389/fimmu.2018.02596] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Accepted: 10/22/2018] [Indexed: 12/11/2022] Open
Abstract
Interleukin-33 (IL-33) is a well-recognized immunomodulatory cytokine which plays critical roles in tissue function and immune-mediated diseases. The abundant expression of IL-33 in brain and spinal cord prompted many scientists to explore its unique role in the central nervous system (CNS) under physiological and pathological conditions. Indeed emerging evidence from over a decade's research suggests that IL-33 acts as one of the key molecular signaling cues coordinating the network between the immune and CNS systems, particularly during the development of neurological diseases. Here, we highlight the recent advances in our knowledge regarding the distribution and cellular localization of IL-33 and its receptor ST2 in specific CNS regions, and more importantly the key roles IL-33/ST2 signaling pathway play in CNS function under normal and diseased conditions.
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Affiliation(s)
| | | | | | | | | | - Hui-Rong Jiang
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
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Huang H, Jiang Y, Xia M, Tang Y, Zhang T, Cui H, Wang J, Li Y, Xu L, Curtin A, Sheng J, Jia Y, Yao D, Li C, Luo C, Wang J. Increased resting-state global functional connectivity density of default mode network in schizophrenia subjects treated with electroconvulsive therapy. Schizophr Res 2018; 197:192-199. [PMID: 29117910 DOI: 10.1016/j.schres.2017.10.044] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Revised: 10/26/2017] [Accepted: 10/29/2017] [Indexed: 01/01/2023]
Abstract
Modified electroconvulsive therapy (MECT) has been widely applied to help treat schizophrenia patients who are treatment-resistant to pharmaceutical therapy. Although the technique is increasingly prevalent, the underlying neural mechanisms have not been well clarified. We conducted a longitudinal study to investigate the alteration of global functional connectivity density (gFCD) in schizophrenia patients undergoing MECT using resting state fMRI (functional magnetic resonance imaging). Two groups of schizophrenia inpatients were recruited. One group received a four-week MECT together with antipsychotic drugs (ECT+Drug, n=21); the other group only received antipsychotic drugs (Drug, n=21). Both groups were compared to a sample of healthy controls (HC, n=23). fMRI scans were obtained from the schizophrenia patients twice at baseline (t1) and after 4-week treatment (t2), and from healthy controls at baseline. gFCD was computed using resting state fMRI. Repeated ANCOVA showed a significant interaction effect of group×time in the schizophrenia patients in left precuneus (Pcu), ventral medial prefrontal cortex (vMPFC), and dorsal medial prefrontal cortex (dMPFC) (GRF-corrected P<0.05), which are mainly located within the default mode network (DMN). Post-hoc analysis revealed that compared with baseline (t1), an increased gFCD was found in the ECT+Drug group in the dMPFC (t=3.87, p=0.00095), vMPFC (t=3.95, p=0.00079) and left Pcu (t=3.33, p=0.0034), but no significant effect was identified in the Drug group. The results suggested that increased global functional connectivity density within the DMN might be one important neural mechanism of MECT in schizophrenia.
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Affiliation(s)
- Huan Huang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Yuchao Jiang
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Mengqing Xia
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Huiru Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Junjie Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Yu Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Adrian Curtin
- School of Biomedical Engineering & Health Sciences, Drexel University, Philadelphia, PA 19104, United States; Med-X Institute, Shanghai Jiao Tong University, Shanghai 200300, China
| | - Jianhua Sheng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Yuping Jia
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiaotong University, Shanghai 200030, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiaotong University, Shanghai 200030, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200030, China.
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Shon SH, Yoon W, Kim H, Joo SW, Kim Y, Lee J. Deterioration in Global Organization of Structural Brain Networks in Schizophrenia: A Diffusion MRI Tractography Study. Front Psychiatry 2018; 9:272. [PMID: 29997531 PMCID: PMC6028716 DOI: 10.3389/fpsyt.2018.00272] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2018] [Accepted: 06/05/2018] [Indexed: 02/03/2023] Open
Abstract
Schizophrenia is a heterogenous neuropsychiatric disorder with varying degrees of altered connectivity in a wide range of brain areas. Network analysis using graph theory allows researchers to integrate and quantify relationships between widespread changes in a network system. This study examined the organization of brain structural networks by applying diffusion MRI, probabilistic tractography, and network analysis to 48 schizophrenia patients and 24 healthy controls. T1-weighted MR images obtained from all participants were parcellated into 87 regions of interests (ROIs) according to a prior anatomical template and registered to diffusion-weighted images (DWI) of the same subjects. Probabilistic tractography was performed to obtain sets of white matter tracts between any two ROIs and determine the connection probabilities between them. Connectivity matrices were constructed using these estimated connectivity probabilities, and several network properties related to network effectiveness were calculated. Global efficiency, local efficiency, clustering coefficient, and mean connectivity strength were significantly lower in schizophrenia patients (p = 0.042, p = 0.011, p = 0.013, p = 0.046). Mean betweenness centrality was significantly higher in schizophrenia (p = 0.041). Comparisons of node wise properties showed trends toward differences in several brain regions. Nodal local efficiency was consistently lower in the basal ganglia, frontal, temporal, cingulate, diencephalon, and precuneus regions in the schizophrenia group. Inter-group differences in nodal degree and nodal betweenness centrality varied by region and showed inconsistent results. Robustness was not significantly different between the study groups. Significant positive correlations were found between t-score of color trails test part-1 and local efficiency and mean connectivity strength in the patient group. The findings of this study suggest that schizophrenia results in deterioration of the global network organization of the brain and reduced ability for information processing.
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Affiliation(s)
- Seung-Hyun Shon
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Woon Yoon
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Harin Kim
- Korea Armed Forces Capital Hospital, Department of Psychiatry, Seongnam, South Korea
| | - Sung Woo Joo
- Republic of Korea Marine Corps, Pohang, South Korea
| | - Yangsik Kim
- Graduated School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology, Daejeon, South Korea
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
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The Effects of Music Intervention on Functional Connectivity Strength of the Brain in Schizophrenia. Neural Plast 2018; 2018:2821832. [PMID: 29853841 PMCID: PMC5954893 DOI: 10.1155/2018/2821832] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2017] [Revised: 01/18/2018] [Accepted: 02/25/2018] [Indexed: 02/01/2023] Open
Abstract
Schizophrenia is often associated with behavior abnormality in the cognitive and affective domain. Music intervention is used as a complementary treatment for improving symptoms in patients with schizophrenia. However, the neurophysiological correlates of these remissions remain poorly understood. Here, we investigated the effects of music intervention in neural circuits through functional magnetic resonance imaging (fMRI) study in schizophrenic subjects. Under the standard care, patients were randomly assigned to music and non-music interventions (MTSZ, UMTSZ) for 1 month. Resting-state fMRI were acquired over three time points (baseline, 1 month, and 6 months later) in patients and analyzed using functional connectivity strength (FCS) and seed-based functional connection (FC) approaches. At baseline, compared with healthy controls, decreased FCS in the right middle temporal gyrus (MTG) was observed in patients. However, after music intervention, the functional circuitry of the right MTG, which was related with the function of emotion and sensorimotor, was improved in MTSZ. Furthermore, the FC increments were significantly correlated with the improvement of symptoms, while vanishing 6 months later. Together, these findings provided evidence that music intervention might positively modulate the functional connectivity of MTG in patients with schizophrenia; such changes might be associated with the observed therapeutic effects of music intervention on neurocognitive function. This trial is registered with ChiCTR-OPC-14005339.
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Jiang Y, Luo C, Li X, Duan M, He H, Chen X, Yang H, Gong J, Chang X, Woelfer M, Biswal BB, Yao D. Progressive Reduction in Gray Matter in Patients with Schizophrenia Assessed with MR Imaging by Using Causal Network Analysis. Radiology 2018; 287:633-642. [DOI: 10.1148/radiol.2017171832] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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Delvecchio G, Pigoni A, Perlini C, Barillari M, Versace A, Ruggeri M, Altamura AC, Bellani M, Brambilla P. A diffusion weighted imaging study of basal ganglia in schizophrenia. Int J Psychiatry Clin Pract 2018. [PMID: 28643537 DOI: 10.1080/13651501.2017.1340650] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVES Several magnetic resonance imaging (MRI) studies provided evidence of selective brain abnormalities in schizophrenia, both in cortical and subcortical structures. Basal ganglia are of particular interest, given not only the high concentration of dopaminergic neurons and receptors, but also for their crucial role in cognitive functions, commonly impaired in schizophrenia. To date, very few studies explored basal ganglia using diffusion imaging, which is sensitive to microstructural organization in brain tissues. The aim of our study is to explore basal ganglia structures with diffusion imaging in a sizeable sample of patients affected by schizophrenia and healthy controls. METHODS We enrolled 52 subjects affected by schizophrenia according to DMS-IV-R criteria and 46 healthy controls. Diffusion weighted images were obtained using a 1.5 Tesla scanner and apparent diffusion coefficient (ADC) values were determined in axial and coronal sections at the level of basal ganglia. RESULTS Patients affected by schizophrenia showed a significantly higher ADC compared to healthy controls in the left anterior lenticular nucleus (F = 3.9, p = .05). A significant positive correlation between right anterior lenticular nucleus and psychotropic dosages was found (r = 0.4, p = .01). CONCLUSIONS Our study provides evidence of lenticular nucleus microstructure alterations in schizophrenia, potentially sustaining cognitive and motor deficits in schizophrenia. Key points The basal ganglia structures was explored with diffusion imaging in a sizeable sample of patients affected by schizophrenia and healthy controls. Patients affected by schizophrenia showed a significantly higher ADC compared to healthy controls in the left anterior lenticular nucleus. Our study provides evidence of lenticular nucleus microstructure alterations in schizophrenia, potentially sustaining cognitive and motor deficits in schizophrenia.
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Affiliation(s)
- Giuseppe Delvecchio
- a IRCCS "E. Medea" Scientific Institute , San Vito al Tagliamento (PN) , Italy
| | - Alessandro Pigoni
- b Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico , University of Milan , Milan , Italy
| | - Cinzia Perlini
- c Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology , University of Verona , Verona , Italy.,d InterUniversity Centre for Behavioural Neurosciences, University of Verona , Verona , Italy
| | - Marco Barillari
- e Section of Neurology, Department of Neurological and Movement Sciences , University Hospital of Verona , Verona , Italy
| | - Amelia Versace
- f Department of Psychiatry, Western Psychiatric Institute and Clinic , University of Pittsburgh Medical Center, University of Pittsburgh , Pittsburgh , PA , USA
| | - Mirella Ruggeri
- d InterUniversity Centre for Behavioural Neurosciences, University of Verona , Verona , Italy.,g Department of Public Health and Community Medicine , University of Verona , Verona , Italy
| | - A Carlo Altamura
- b Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico , University of Milan , Milan , Italy
| | - Marcella Bellani
- d InterUniversity Centre for Behavioural Neurosciences, University of Verona , Verona , Italy.,g Department of Public Health and Community Medicine , University of Verona , Verona , Italy
| | - Paolo Brambilla
- b Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico , University of Milan , Milan , Italy.,h Department of Psychiatry and Behavioural Neurosciences , University of Texas at Houston , TX , USA
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Dong D, Wang Y, Chang X, Luo C, Yao D. Dysfunction of Large-Scale Brain Networks in Schizophrenia: A Meta-analysis of Resting-State Functional Connectivity. Schizophr Bull 2018; 44:168-181. [PMID: 28338943 PMCID: PMC5767956 DOI: 10.1093/schbul/sbx034] [Citation(s) in RCA: 304] [Impact Index Per Article: 50.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Schizophrenia is a complex mental disorder with disorganized communication among large-scale brain networks, as demonstrated by impaired resting-state functional connectivity (rsFC). Individual rsFC studies, however, vary greatly in their methods and findings. We searched for consistent patterns of network dysfunction in schizophrenia by using a coordinate-based meta-analysis. Fifty-six seed-based voxel-wise rsFC datasets from 52 publications (2115 patients and 2297 healthy controls) were included in this meta-analysis. Then, coordinates of seed regions of interest (ROI) and between-group effects were extracted and coded. Seed ROIs were categorized into seed networks by their location within an a priori template. Multilevel kernel density analysis was used to identify brain networks in which schizophrenia was linked to hyper-connectivity or hypo-connectivity with each a priori network. Our results showed that schizophrenia was characterized by hypo-connectivity within the default network (DN, self-related thought), affective network (AN, emotion processing), ventral attention network (VAN, processing of salience), thalamus network (TN, gating information) and somatosensory network (SS, involved in sensory and auditory perception). Additionally, hypo-connectivity between the VAN and TN, VAN and DN, VAN and frontoparietal network (FN, external goal-directed regulation), FN and TN, and FN and DN were found in schizophrenia. Finally, the only instance of hyper-connectivity in schizophrenia was observed between the AN and VAN. Our meta-analysis motivates an empirical foundation for a disconnected large-scale brain networks model of schizophrenia in which the salience processing network (VAN) plays the core role, and its imbalanced communication with other functional networks may underlie the core difficulty of patients to differentiate self-representation (inner world) and environmental salience processing (outside world).
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Affiliation(s)
- Debo Dong
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yulin Wang
- Faculty of Psychological and Educational Sciences, Department of Experimental and Applied Psychology, Research Group of Biological Psychology, Vrije Universiteit Brussel, Brussels, Belgium
- Faculty of Psychology and Educational Sciences, Department of Data Analysis, Ghent University, Ghent, Belgium
| | - Xuebin Chang
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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Jiang Y, Duan M, Chen X, Chang X, He H, Li Y, Luo C, Yao D. Common and distinct dysfunctional patterns contribute to triple network model in schizophrenia and depression: A preliminary study. Prog Neuropsychopharmacol Biol Psychiatry 2017; 79:302-310. [PMID: 28705767 DOI: 10.1016/j.pnpbp.2017.07.007] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Revised: 07/05/2017] [Accepted: 07/08/2017] [Indexed: 12/20/2022]
Abstract
BACKGROUND Schizophrenia (SCH) and depression (DEP) are prevalent psychiatric disorders and share common and distinguished elements in their pathophysiology. A triple network model composed of the default mode network (DMN), salience network (SN) and central executive network (CEN) may represent a major abnormality across several psychiatric disorders including SCH and DEP. However, common and distinct dysfunctional patterns between SCH and DEP across three core networks remain unclear. METHOD Resting-state functional magnetic resonance imaging (fMRI) was obtained in 20 patients with SCH, 20 patients with DEP and 20 healthy controls (HC). Both functional connectivity (FC) and Granger causal connectivity across DMN, SN and CEN were evaluated to uncover common and distinct dysfunctional patterns between SCH and DEP. RESULTS Two patient groups showed identical abnormal causal connectivity between key nodes of DMN and SN, as well as opposing aberrant FC of DMN-CEN and SN-CEN. Compared with HC, the FC between CEN and DMN was increased in SCH while decreased in DEP. Conversely, DEP showed enhanced FC between CEN and SN, whereas SCH showed decreased FC. LIMITATIONS The sample size was relatively small, and all participants were taking medication. CONCLUSIONS Our results identified common patterns including dysconnectivity between DMN and SN, which may contribute to shared cognitive and affective impairment in DEP and SCH. Moreover, opposing dysconnectivity patterns of DMN-CEN may be associated with different self-referential processing abnormalities. These opposing dysconnectivity patterns may indicate an unbalanced recruitment between SN and CEN. Therefore, this study provides dysconnectivity patterns to advance the understanding of the triple network model with regard to psychiatric disorders.
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Affiliation(s)
- Yuchao Jiang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of psychiatry, Chengdu Mental Health Center, Institute of Chengdu Brain Science, Chengdu, China
| | - Xi Chen
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xin Chang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hui He
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - YingJia Li
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
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Ma S, Jiang S, Peng R, Zhu Q, Sun H, Li J, Jia X, Goldberg I, Yu L, Luo C. Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures. Front Comput Neurosci 2017; 11:90. [PMID: 29033811 PMCID: PMC5627153 DOI: 10.3389/fncom.2017.00090] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2017] [Accepted: 09/20/2017] [Indexed: 01/09/2023] Open
Abstract
The purpose of this study was to evaluate the spatiotemporal Consistency of spontaneous activities in local brain regions in patients with generalized tonic-clonic seizures (GTCS). The resting-state fMRI data were acquired from nineteen patients with GTCS and twenty-two matched healthy subjects. FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) metric was used to analyze the spontaneous activity in whole brain. The FOCA difference between two groups were detected using a two sample t-test analysis. Correlations between the FOCA values and features of seizures were analyzed. The findings of this study showed that patients had significantly increased FOCA in motor-related cortex regions, including bilateral supplementary motor area, paracentral lobule, precentral gyrus and left basal ganglia, as well as a substantial reduction of FOCA in regions of default mode network (DMN) and parietal lobe. In addition, several brain regions in DMN demonstrated more reduction with longer duration of epilepsy and later onset age, and the motor-related regions showed higher FOCA value in accompany with later onset age. These findings implicated the abnormality of motor-related cortical network in GTCS which were associated with the genesis and propagation of epileptiform activity. And the decreased FOCA in DMN might reflect the intrinsic disturbance of brain activity. Moreover, our study supported that the FOCA might be potential tool to investigate local brain spontaneous activity related with the epileptic activity, and to provide important insights into understanding the underlying pathophysiological mechanisms of GTCS.
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Affiliation(s)
- Shuai Ma
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Sisi Jiang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Rui Peng
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qiong Zhu
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Hongbin Sun
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Jianfu Li
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoyan Jia
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ilan Goldberg
- Neurology Department, Wolfson Medical Center, Holon, Israel
| | - Liang Yu
- Neurology Department, Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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Chen X, Liu C, He H, Chang X, Jiang Y, Li Y, Duan M, Li J, Luo C, Yao D. Transdiagnostic differences in the resting-state functional connectivity of the prefrontal cortex in depression and schizophrenia. J Affect Disord 2017; 217:118-124. [PMID: 28407554 DOI: 10.1016/j.jad.2017.04.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 02/22/2017] [Accepted: 04/02/2017] [Indexed: 01/06/2023]
Abstract
BACKGROUND Depression and schizophrenia are two of the most serious psychiatric disorders. They share similar symptoms but the pathology-specific commonalities and differences remain unknown. This study was conducted to acquire a full picture of the functional alterations in schizophrenia and depression patients. METHODS The resting-state fMRI data from 20 patients with schizophrenia, 20 patients with depression and 20 healthy control subjects were collected. A data-driven approach that included local functional connectivity density (FCD) analysis combined with multivariate pattern analysis (MVPA) was used to compare the three groups. RESULTS Based on the results of the MVPA, the local FCD value in the orbitofrontal cortex (OFC) can differentiate depression patients from schizophrenia patients. The patients with depression had a higher local FCD value in the medial and anterior parts of the OFC than the subjects in the other two groups, which suggested altered abstract and reward reinforces processing in depression patients. Subsequent functional connectivity analysis indicated that the connection in the prefrontal cortex was significantly lower in people with schizophrenia compared to people with depression and healthy controls. LIMITATION The systematically different medications for schizophrenia and depression may have different effects on functional connectivity. CONCLUSIONS These results suggested that the resting-state functional connectivity pattern in the prefrontal cortex may be a transdiagnostic difference between depression and schizophrenia patients.
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Affiliation(s)
- Xi Chen
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chang Liu
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; College of Information Science and Engineering, Chengdu University, Chengdu 610106, China
| | - Hui He
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xin Chang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuchao Jiang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yingjia Li
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of psychiatry, Chengdu Mental Health Center, Chengdu, China
| | - Jianfu Li
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
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Chen X, Duan M, He H, Yang M, Klugah-Brown B, Xu H, Lai Y, Luo C, Yao D. Functional abnormalities of the right posterior insula are related to the altered self-experience in schizophrenia. Psychiatry Res Neuroimaging 2016; 256:26-32. [PMID: 27662482 DOI: 10.1016/j.pscychresns.2016.09.006] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2016] [Revised: 09/13/2016] [Accepted: 09/15/2016] [Indexed: 01/29/2023]
Abstract
The insula is involved in detecting the salience of internal and external stimuli, and it plays a critical role in psychosis. Previous studies have demonstrated the structural and functional alterations of the insula in schizophrenia. To acquire a full picture of the functional alterations of the insula in schizophrenia, the resting-state fMRI data of 46 patients with schizophrenia and 46 healthy control subjects were collected. We used clustering analysis to divide the insula into three subregions: the dorsal anterior insula (dAI), ventral anterior insula (vAI) and posterior insula (PI). Then, whole-brain functional connectivity analysis was conducted based on these subregions. The results showed that the right dAI and PI in patients exhibited altered functional connections with the primary sensorimotor area. In addition, the right PI of the patients exhibited increased functional correlations with the thalamus. More importantly, the altered functional properties of the right PI were significantly correlated with the severity of the delusion and poor insight in schizophrenia. The results suggested that the right PI might play an important role in self-experience processing in schizophrenia. Accordingly, the right PI should be considered very important in the pathological mechanism of schizophrenia.
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Affiliation(s)
- Xi Chen
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of Psychiatry, Chengdu Mental Health Center, Chengdu, China
| | - Hui He
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Mi Yang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of Psychiatry, Chengdu Mental Health Center, Chengdu, China
| | - Benjamin Klugah-Brown
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hao Xu
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yongxiu Lai
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
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Malt EA, Juhasz K, Malt UF, Naumann T. A Role for the Transcription Factor Nk2 Homeobox 1 in Schizophrenia: Convergent Evidence from Animal and Human Studies. Front Behav Neurosci 2016; 10:59. [PMID: 27064909 PMCID: PMC4811959 DOI: 10.3389/fnbeh.2016.00059] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Accepted: 03/11/2016] [Indexed: 12/22/2022] Open
Abstract
Schizophrenia is a highly heritable disorder with diverse mental and somatic symptoms. The molecular mechanisms leading from genes to disease pathology in schizophrenia remain largely unknown. Genome-wide association studies (GWASs) have shown that common single-nucleotide polymorphisms associated with specific diseases are enriched in the recognition sequences of transcription factors that regulate physiological processes relevant to the disease. We have used a “bottom-up” approach and tracked a developmental trajectory from embryology to physiological processes and behavior and recognized that the transcription factor NK2 homeobox 1 (NKX2-1) possesses properties of particular interest for schizophrenia. NKX2-1 is selectively expressed from prenatal development to adulthood in the brain, thyroid gland, parathyroid gland, lungs, skin, and enteric ganglia, and has key functions at the interface of the brain, the endocrine-, and the immune system. In the developing brain, NKX2-1-expressing progenitor cells differentiate into distinct subclasses of forebrain GABAergic and cholinergic neurons, astrocytes, and oligodendrocytes. The transcription factor is highly expressed in mature limbic circuits related to context-dependent goal-directed patterns of behavior, social interaction and reproduction, fear responses, responses to light, and other homeostatic processes. It is essential for development and mature function of the thyroid gland and the respiratory system, and is involved in calcium metabolism and immune responses. NKX2-1 interacts with a number of genes identified as susceptibility genes for schizophrenia. We suggest that NKX2-1 may lie at the core of several dose dependent pathways that are dysregulated in schizophrenia. We correlate the symptoms seen in schizophrenia with the temporal and spatial activities of NKX2-1 in order to highlight promising future research areas.
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Affiliation(s)
- Eva A Malt
- Department of Adult Habilitation, Akershus University HospitalLørenskog, Norway; Institute of Clinical Medicine, Ahus Campus University of OsloOslo, Norway
| | - Katalin Juhasz
- Department of Adult Habilitation, Akershus University Hospital Lørenskog, Norway
| | - Ulrik F Malt
- Institute of Clinical Medicine, University of OsloOslo, Norway; Department of Research and Education, Institution of Oslo University HospitalOslo, Norway
| | - Thomas Naumann
- Centre of Anatomy, Institute of Cell Biology and Neurobiology, Charite Universitätsmedizin Berlin Berlin, Germany
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