1
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Zheng Y, Wang L, Dong H, Lin X, Zhao L, Ye S, Dong GH. Similarities and differences in dynamic properties of brain networks between internet gaming disorder and tobacco use disorder. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111119. [PMID: 39159804 DOI: 10.1016/j.pnpbp.2024.111119] [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: 11/19/2023] [Revised: 08/14/2024] [Accepted: 08/15/2024] [Indexed: 08/21/2024]
Abstract
BACKGROUND Internet gaming disorder (IGD) and tobacco use disorder (TUD) are two major addiction disorders that result in substantial financial loss. Identifying the similarities and differences between these two disorders is important to understand substance addiction and behavioral addiction. The current study was designed to compare these two disorders utilizing dynamic analysis. METHOD Resting-state data were collected from 35 individuals with IGD, 35 individuals with TUD and 35 healthy controls (HCs). Dynamic coactivation pattern analysis was employed to decipher their dynamic patterns. RESULTS IGD participants showed decreased coactivation patterns within the default mode network (DMN) and between the DMN and the salience network (SN). The SN showed reduced coactivation patterns with the executive control network (ECN) and DMN, and the ECN showed decreased coactivation patterns with the DMN. In the TUD group, the DMN exhibited decreased coactivation patterns with the SN, the SN exhibited reduced coactivation patterns with the DMN and ECN, and the ECN showed decreased coactivation patterns with the DMN and within the ECN. Furthermore, the triple network model was fitted to the dynamic properties of the two addiction disorders. Decoding analysis results indicated that addiction-related memory and memory retrieval displayed similar dysfunctions in both addictions. CONCLUSION The dynamic characteristics of IGD and TUD suggest that there are similarities in the dynamic features between the SN and DMN and differences in the dynamic features between the DMN and ECN. Our results revealed that the two addiction disorders have dissociable brain mechanisms, indicating that future studies should consider these two addiction disorders as having two separate mechanisms to achieve precise treatment for their individualized targets.
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Affiliation(s)
- Yanbin Zheng
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province, PR China; Centre for Cognition and Brain disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China; Centre for Cognition and Brain disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China
| | - Lingxiao Wang
- Centre for Cognition and Brain disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China; Centre for Cognition and Brain disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China
| | - Haohao Dong
- Centre for Cognition and Brain disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China
| | - Xiao Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, Beijing, China; National Clinical Research Center for Mental Disorders of Peking University Sixth Hospital, Chinese Academy of Medical Sciences Research Unit, Peking University, Beijing, China
| | - Lei Zhao
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Shuer Ye
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Guang-Heng Dong
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province, PR China.
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2
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Johnson JF, Schwartze M, Belyk M, Pinheiro AP, Kotz SA. Variability in white matter structure relates to hallucination proneness. Neuroimage Clin 2024; 43:103643. [PMID: 39042953 PMCID: PMC11325372 DOI: 10.1016/j.nicl.2024.103643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Accepted: 07/15/2024] [Indexed: 07/25/2024]
Abstract
Hallucinations are a prominent transdiagnostic psychiatric symptom but are also prevalent in individuals who do not require clinical care. Moreover, persistent psychosis-like experience in otherwise healthy individuals may be related to an increased risk to transition to a psychotic disorder. This suggests a common etiology across clinical and non-clinical individuals along a multidimensional psychosis continuum that may be detectable in structural variations of the brain. The current diffusion tensor imaging study assessed 50 healthy individuals (35 females) to identify possible differences in white matter associated with hallucination proneness (HP). This approach circumvents potential confounds related to medication, hospitalization, and disease progression common in clinical individuals. We determined how HP relates to white matter structure in selected association, commissural, and projection fiber pathways putatively linked to psychosis. Increased HP was associated with enhanced fractional anisotropy (FA) in the right uncinate fasciculus, the right anterior and posterior arcuate fasciculus, and the corpus callosum. These findings support the notion of a psychosis continuum, providing first evidence of structural white matter variability associated with HP in healthy individuals. Furthermore, alterations in the targeted pathways likely indicate an association between HP-related structural variations and the putative salience and attention mechanisms that these pathways subserve.
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Affiliation(s)
- Joseph F Johnson
- Université Libre de Bruxelles, Center for Research in Cognition & Neurosciences, Bruxelles, Belgium; University of Maastricht, Department of Neuropsychology and Psychopharmacology, Maastricht, The Netherlands
| | - Michael Schwartze
- University of Maastricht, Department of Neuropsychology and Psychopharmacology, Maastricht, The Netherlands
| | - Michel Belyk
- Edge Hill University, Department of Psychology, Ormskirk, United Kingdom
| | - Ana P Pinheiro
- Faculdade de Psicologia, Universidade de Lisboa, Lisboa, Portugal
| | - Sonja A Kotz
- University of Maastricht, Department of Neuropsychology and Psychopharmacology, Maastricht, The Netherlands; Max Planck Institute for Human and Cognitive Sciences, Department of Neuropsychology, Leipzig, Germany.
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3
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Mana L, Schwartz-Pallejà M, Vila-Vidal M, Deco G. Overview on cognitive impairment in psychotic disorders: From impaired microcircuits to dysconnectivity. Schizophr Res 2024; 269:132-143. [PMID: 38788432 DOI: 10.1016/j.schres.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
Schizophrenia's cognitive deficits, often overshadowed by positive symptoms, significantly contribute to the disorder's morbidity. Increasing attention highlights these deficits as reflections of neural circuit dysfunction across various cortical regions. Numerous connectivity alterations linked to cognitive symptoms in psychotic disorders have been reported, both at the macroscopic and microscopic level, emphasizing the potential role of plasticity and microcircuits impairment during development and later stages. However, the heterogeneous clinical presentation of cognitive impairment and diverse connectivity findings pose challenges in summarizing them into a cohesive picture. This review aims to synthesize major cognitive alterations, recent insights into network structural and functional connectivity changes and proposed mechanisms and microcircuit alterations underpinning these symptoms, particularly focusing on neurodevelopmental impairment, E/I balance, and sleep disturbances. Finally, we will also comment on some of the most recent and promising therapeutic approaches that aim to target these mechanisms to address cognitive symptoms. Through this comprehensive exploration, we strive to provide an updated and nuanced overview of the multiscale connectivity impairment underlying cognitive impairment in psychotic disorders.
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Affiliation(s)
- L Mana
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain.
| | - M Schwartz-Pallejà
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Department of Experimental and Health Science, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Eurecat, Technology Center of Catalonia, Multimedia Technologies, Barcelona, Spain.
| | - M Vila-Vidal
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Computational Biology and Complex Systems Group, Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain.
| | - G Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.
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4
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Zheng D, Ruan Y, Cao X, Guo W, Zhang X, Qi W, Yuan Q, Liang X, Zhang D, Huang Q, Xue C. Directed Functional Connectivity Changes of Triple Networks for Stable and Progressive Mild Cognitive Impairment. Neuroscience 2024; 545:47-58. [PMID: 38490330 DOI: 10.1016/j.neuroscience.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/22/2024] [Accepted: 03/05/2024] [Indexed: 03/17/2024]
Abstract
Mild cognitive impairment includes two distinct subtypes, namely progressive mild cognitive impairment and stable mild cognitive impairment. While alterations in extensive functional connectivity have been observed in both subtypes, limited attention has been given to directed functional connectivity. A triple network, composed of the central executive network, default mode network, and salience network, is considered to be the core cognitive network. We evaluated the alterations in directed functional connectivity within and between the triple network in progressive and stable mild cognitive impairment groups and investigated its role in predicting disease conversion. Resting-state functional magnetic resonance imaging was used to analyze directed functional connectivity within the triple networks. A correlation analysis was performed to investigate potential associations between altered directed functional connectivity within the triple networks and the neurocognitive performance of the participants. Our study revealed significant differences in directed functional connectivity within and between the triple network in the progressive and stable mild cognitive impairment groups. Altered directed functional connectivity within the triple network was involved in episodic memory and executive function. Thus, the directed functional connectivity of the triple network may be used as an imaging marker of mild cognitive impairment.
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Affiliation(s)
- Darui Zheng
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yiming Ruan
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xuan Cao
- Division of Statistics and Data Science, Department of Mathematical Sciences, University of Cincinnati, Cincinnati, USA
| | - Wenxuan Guo
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xulian Zhang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Wenzhang Qi
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Qianqian Yuan
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xuhong Liang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Da Zhang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Qingling Huang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.
| | - Chen Xue
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.
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5
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Davies C, Martins D, Dipasquale O, McCutcheon RA, De Micheli A, Ramella-Cravaro V, Provenzani U, Rutigliano G, Cappucciati M, Oliver D, Williams S, Zelaya F, Allen P, Murguia S, Taylor D, Shergill S, Morrison P, McGuire P, Paloyelis Y, Fusar-Poli P. Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin. Mol Psychiatry 2024; 29:1241-1252. [PMID: 38243074 PMCID: PMC11189815 DOI: 10.1038/s41380-024-02406-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 01/21/2024]
Abstract
Abnormalities in functional brain networks (functional connectome) are increasingly implicated in people at Clinical High Risk for Psychosis (CHR-P). Intranasal oxytocin, a potential novel treatment for the CHR-P state, modulates network topology in healthy individuals. However, its connectomic effects in people at CHR-P remain unknown. Forty-seven men (30 CHR-P and 17 healthy controls) received acute challenges of both intranasal oxytocin 40 IU and placebo in two parallel randomised, double-blind, placebo-controlled cross-over studies which had similar but not identical designs. Multi-echo resting-state fMRI data was acquired at approximately 1 h post-dosing. Using a graph theoretical approach, the effects of group (CHR-P vs healthy control), treatment (oxytocin vs placebo) and respective interactions were tested on graph metrics describing the topology of the functional connectome. Group effects were observed in 12 regions (all pFDR < 0.05) most localised to the frontoparietal network. Treatment effects were found in 7 regions (all pFDR < 0.05) predominantly within the ventral attention network. Our major finding was that many effects of oxytocin on network topology differ across CHR-P and healthy individuals, with significant interaction effects observed in numerous subcortical regions strongly implicated in psychosis onset, such as the thalamus, pallidum and nucleus accumbens, and cortical regions which localised primarily to the default mode network (12 regions, all pFDR < 0.05). Collectively, our findings provide new insights on aberrant functional brain network organisation associated with psychosis risk and demonstrate, for the first time, that oxytocin modulates network topology in brain regions implicated in the pathophysiology of psychosis in a clinical status (CHR-P vs healthy control) specific manner.
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Affiliation(s)
- Cathy Davies
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre (BRC), South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychiatry, University Hospitals of Genève, Geneva, Switzerland
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Robert A McCutcheon
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Andrea De Micheli
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Outreach And Support in South London (OASIS) Service, South London and Maudsley NHS Foundation Trust, London, UK
| | - Valentina Ramella-Cravaro
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Umberto Provenzani
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Grazia Rutigliano
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Marco Cappucciati
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Dominic Oliver
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Steve Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Paul Allen
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Silvia Murguia
- Tower Hamlets Early Detection Service, East London NHS Foundation Trust, London, UK
| | - David Taylor
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Sukhi Shergill
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Kent and Medway Medical School, Canterbury, UK
| | - Paul Morrison
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Philip McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
- NIHR Oxford Health Biomedical Research Centre, Oxford, UK
- Oxford Health NHS Foundation Trust, Oxford, UK
| | - Yannis Paloyelis
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre (BRC), South London and Maudsley NHS Foundation Trust, London, UK
- Outreach And Support in South London (OASIS) Service, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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6
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Maximo JO, Briend F, Armstrong WP, Kraguljac NV, Lahti AC. Higher-order functional brain networks and anterior cingulate glutamate + glutamine (Glx) in antipsychotic-naïve first episode psychosis patients. Transl Psychiatry 2024; 14:183. [PMID: 38600117 PMCID: PMC11006887 DOI: 10.1038/s41398-024-02854-7] [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: 03/23/2022] [Revised: 02/07/2024] [Accepted: 02/26/2024] [Indexed: 04/12/2024] Open
Abstract
Human connectome studies have provided abundant data consistent with the hypothesis that functional dysconnectivity is predominant in psychosis spectrum disorders. Converging lines of evidence also suggest an interaction between dorsal anterior cingulate cortex (dACC) cortical glutamate with higher-order functional brain networks (FC) such as the default mode (DMN), dorsal attention (DAN), and executive control networks (ECN) in healthy controls (HC) and this mechanism may be impaired in psychosis. Data from 70 antipsychotic-medication naïve first-episode psychosis (FEP) and 52 HC were analyzed. 3T Proton magnetic resonance spectroscopy (1H-MRS) data were acquired from a voxel in the dACC and assessed correlations (positive FC) and anticorrelations (negative FC) of the DMN, DAN, and ECN. We then performed regressions to assess associations between glutamate + glutamine (Glx) with positive and negative FC of these same networks and compared them between groups. We found alterations in positive and negative FC in all networks (HC > FEP). A relationship between dACC Glx and positive and negative FC was found in both groups, but when comparing these relationships between groups, we found contrasting associations between these variables in FEP patients compared to HC. We demonstrated that both positive and negative FC in three higher-order resting state networks are already altered in antipsychotic-naïve FEP, underscoring the importance of also considering anticorrelations for optimal characterization of large-scale functional brain networks as these represent biological processes as well. Our data also adds to the growing body of evidence supporting the role of dACC cortical Glx as a mechanism underlying alterations in functional brain network connectivity. Overall, the implications for these findings are imperative as this particular mechanism may differ in untreated or chronic psychotic patients; therefore, understanding this mechanism prior to treatment could better inform clinicians.Clinical trial registration: Trajectories of Treatment Response as Window into the Heterogeneity of Psychosis: A Longitudinal Multimodal Imaging Study, NCT03442101 . Glutamate, Brain Connectivity and Duration of Untreated Psychosis (DUP), NCT02034253 .
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Affiliation(s)
- Jose O Maximo
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Frederic Briend
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
- UMR1253, iBrain, Université de Tours, Inserm, Tours, France
| | - William P Armstrong
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Nina V Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA.
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7
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Voineskos AN, Hawco C, Neufeld NH, Turner JA, Ameis SH, Anticevic A, Buchanan RW, Cadenhead K, Dazzan P, Dickie EW, Gallucci J, Lahti AC, Malhotra AK, Öngür D, Lencz T, Sarpal DK, Oliver LD. Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions. World Psychiatry 2024; 23:26-51. [PMID: 38214624 PMCID: PMC10786022 DOI: 10.1002/wps.21159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2024] Open
Abstract
Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.
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Affiliation(s)
- Aristotle N Voineskos
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Nicholas H Neufeld
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH, USA
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Cundill Centre for Child and Youth Depression and McCain Centre for Child, Youth and Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Alan Anticevic
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kristin Cadenhead
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anil K Malhotra
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Dost Öngür
- McLean Hospital/Harvard Medical School, Belmont, MA, USA
| | - Todd Lencz
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Deepak K Sarpal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
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8
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Onofrj M, Russo M, Delli Pizzi S, De Gregorio D, Inserra A, Gobbi G, Sensi SL. The central role of the Thalamus in psychosis, lessons from neurodegenerative diseases and psychedelics. Transl Psychiatry 2023; 13:384. [PMID: 38092757 PMCID: PMC10719401 DOI: 10.1038/s41398-023-02691-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/06/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023] Open
Abstract
The PD-DLB psychosis complex found in Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB) includes hallucinations, Somatic Symptom/Functional Disorders, and delusions. These disorders exhibit similar presentation patterns and progression. Mechanisms at the root of these symptoms also share similarities with processes promoting altered states of consciousness found in Rapid Eye Movement sleep, psychiatric disorders, or the intake of psychedelic compounds. We propose that these mechanisms find a crucial driver and trigger in the dysregulated activity of high-order thalamic nuclei set in motion by ThalamoCortical Dysrhythmia (TCD). TCD generates the loss of finely tuned cortico-cortical modulations promoted by the thalamus and unleashes the aberrant activity of the Default Mode Network (DMN). TCD moves in parallel with altered thalamic filtering of external and internal information. The process produces an input overload to the cortex, thereby exacerbating DMN decoupling from task-positive networks. These phenomena alter the brain metastability, creating dreamlike, dissociative, or altered states of consciousness. In support of this hypothesis, mind-altering psychedelic drugs also modulate thalamic-cortical pathways. Understanding the pathophysiological background of these conditions provides a conceptual bridge between neurology and psychiatry, thereby helping to generate a promising and converging area of investigation and therapeutic efforts.
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Affiliation(s)
- Marco Onofrj
- Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, Institute for Advanced Biomedical Technology-ITAB University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
- Department of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
| | - Mirella Russo
- Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, Institute for Advanced Biomedical Technology-ITAB University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
- Department of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Stefano Delli Pizzi
- Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, Institute for Advanced Biomedical Technology-ITAB University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
- Department of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Danilo De Gregorio
- Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy
| | - Antonio Inserra
- Neurobiological Psychiatry Unit, McGill University, Montreal, QC, Canada
| | - Gabriella Gobbi
- Neurobiological Psychiatry Unit, McGill University, Montreal, QC, Canada
| | - Stefano L Sensi
- Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, Institute for Advanced Biomedical Technology-ITAB University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
- Department of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
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9
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Zhu T, Wang Z, Wu W, Ling Y, Wang Z, Zhou C, Fang X, Huang C, Xie C, Chen J, Zhang X. Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis. Front Hum Neurosci 2023; 17:1204632. [PMID: 37954938 PMCID: PMC10637389 DOI: 10.3389/fnhum.2023.1204632] [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: 04/12/2023] [Accepted: 10/10/2023] [Indexed: 11/14/2023] Open
Abstract
Objective To investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients. Methods We performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls. Results Seventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear. Conclusion This meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).
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Affiliation(s)
- Tingting Zhu
- Department of Psychiatry, The Third People’s Hospital of Huai’an, Huaian, Jiangsu, China
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zengxiu Wang
- Department of Hepatology, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China
| | - Weifeng Wu
- Department of Hepatology, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China
| | - Yuru Ling
- 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 Psychiatry, The Third People’s Hospital of Huai’an, Huaian, Jiangsu, China
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine Southeast University, Nanjing, China
| | - Jiu Chen
- 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, Jiangsu, China
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10
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Xie Y, Guan M, Wang Z, Ma Z, Wang H, Fang P. Alterations in brain connectivity patterns in schizophrenia patients with auditory verbal hallucinations during low frequency repetitive transcranial magnetic stimulation. Psychiatry Res 2023; 328:115457. [PMID: 37716322 DOI: 10.1016/j.psychres.2023.115457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 08/28/2023] [Accepted: 08/31/2023] [Indexed: 09/18/2023]
Abstract
OBJECTIVE Auditory verbal hallucinations (AVH) are a characteristic symptom of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has been demonstrated to alleviate the severity of AVH, its exact neurophysiological mechanisms remain unclear. This study aimed to elucidate the alterations in brain connectivity patterns in schizophrenia patients with AVH after low frequency rTMS. Furthermore, the relationship between these alterations and clinical outcomes was examined, thereby identifying potential biomarkers for rTMS treatment efficacy. METHODS A total of 30 schizophrenia patients with AVH and 33 healthy controls were recruited. The patients received 1 Hz rTMS applied to the left temporoparietal junction region over 15 days. Resting-state functional magnetic resonance imaging scans were conducted for all participants. Subsequently, degree centrality (DC) and seed-based functional connectivity (FC) analyses were employed to identify specific alterations in brain connectivity patterns after rTMS treatment. RESULTS At baseline, patients exhibited divergent DC patterns in the frontal, occipital, and limbic lobes compared to healthy controls. In addition, prior to treatment, patients demonstrated altered FC from the superior frontal gyrus seeds that linked to the frontal, temporal, and somatosensory regions. Following rTMS treatment, these abnormalities were notably reversed, correlating with improved clinical outcomes. CONCLUSIONS These findings demonstrate that schizophrenia patients with AVH exhibited atypical interactions within the frontal and temporal lobes. These alterations might be crucial biomarkers for predicting the efficacy of low frequency rTMS.
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Affiliation(s)
- Yuanjun Xie
- Military Medical Psychology School , Fourth Military Medical University, Xi'an, China; Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Muzhen Guan
- Department of Mental Health, Xi'an Medical College, Xi'an, China
| | - Zhongheng Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhujing Ma
- Military Medical Psychology School , Fourth Military Medical University, Xi'an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Peng Fang
- Military Medical Psychology School , Fourth Military Medical University, Xi'an, China; Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Xi'an, China.
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11
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Ramsay IS, Mueller B, Ma Y, Shen C, Sponheim SR. Thalamocortical connectivity and its relationship with symptoms and cognition across the psychosis continuum. Psychol Med 2023; 53:5582-5591. [PMID: 36047043 DOI: 10.1017/s0033291722002793] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Coordination between the thalamus and cortex is necessary for efficient processing of sensory information and appears disrupted in schizophrenia. The significance of this disrupted coordination (i.e. thalamocortical dysconnectivity) to the symptoms and cognitive deficits of schizophrenia is unclear. It is also unknown whether similar dysconnectivity is observed in other forms of psychotic psychopathology and associated with familial risk for psychosis. Here we examine the relevance of thalamocortical connectivity to the clinical symptoms and cognition of patients with psychotic psychopathology, their first-degree biological relatives, and a group of healthy controls. METHOD Patients with a schizophrenia-spectrum diagnosis (N = 100) or bipolar disorder with a history of psychosis (N = 33), their first-degree relatives (N = 73), and a group of healthy controls (N = 43) underwent resting functional MRI in addition to clinical and cognitive assessments as part of the Psychosis Human Connectome Project. A bilateral mediodorsal thalamus seed-based analysis was used to measure thalamocortical connectivity and test for group differences, as well as associations with symptomatology and cognition. RESULTS Reduced connectivity from mediodorsal thalamus to insular, orbitofrontal, and cerebellar regions was seen in schizophrenia. Across groups, greater symptomatology was related to less thalamocortical connectivity to the left middle frontal gyrus, anterior cingulate, right insula, and cerebellum. Poorer cognition was related to less thalamocortical connectivity to bilateral insula. Analyses revealed similar patterns of dysconnectivity across patient groups and their relatives. CONCLUSIONS Reduced thalamo-prefrontal-cerebellar and thalamo-insular connectivity may contribute to clinical symptomatology and cognitive deficits in patients with psychosis as well as individuals with familial risk for psychotic psychopathology.
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Affiliation(s)
- Ian S Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Bryon Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Yizhou Ma
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA
| | - Chen Shen
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Scott R Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota School of Medicine, Minneapolis, MN, USA
- Minneapolis Veterans Affairs Healthcare System, Minneapolis, MN, USA
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12
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Ha M, Park SH, Park I, Kim T, Lee J, Kim M, Kwon JS. Aberrant cortico-thalamo-cerebellar network interactions and their association with impaired cognitive functioning in patients with schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:50. [PMID: 37573437 PMCID: PMC10423253 DOI: 10.1038/s41537-023-00375-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 07/04/2023] [Indexed: 08/14/2023]
Abstract
Evidence indicating abnormal functional connectivity (FC) among the cortex, thalamus, and cerebellum in schizophrenia patients has increased. However, the role of the thalamus and cerebellum when integrated into intrinsic networks and how those integrated networks interact in schizophrenia patients are largely unknown. We generated an integrative network map by merging thalamic and cerebellar network maps, which were parcellated using a winner-take-all approach, onto a cortical network map. Using cognitive networks, the default mode network (DMN), the dorsal attention network (DAN), the salience network (SAL), and the central executive network (CEN) as regions of interest, the FC of 48 schizophrenia patients was compared with that of 57 healthy controls (HCs). The association between abnormal FC and cognitive impairment was also investigated in patients. FC was lower between the SAL-CEN, SAL-DMN, and DMN-CEN and within-CEN in schizophrenia patients than in HCs. Hypoconnectivity between the DMN-CEN was correlated with impaired cognition in schizophrenia patients. Our findings broadly suggest the plausible role of the thalamus and cerebellum in integrative intrinsic networks in patients, which may contribute to the disrupted triple network and cognitive dysmetria in schizophrenia.
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Affiliation(s)
- Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Soo Hwan Park
- Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Inkyung Park
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Taekwan Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Jungha Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea.
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea.
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13
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Gunasekera B, Wilson R, O'Neill A, Blest-Hopley G, O'Daly O, Bhattacharyya S. Cannabidiol attenuates insular activity during motivational salience processing in patients with early psychosis. Psychol Med 2023; 53:4732-4741. [PMID: 35775365 DOI: 10.1017/s0033291722001672] [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] [Indexed: 11/07/2022]
Abstract
BACKGROUND The mechanisms underlying the antipsychotic potential of cannabidiol (CBD) remain unclear but growing evidence indicates that dysfunction in the insula, a key brain region involved in the processing of motivationally salient stimuli, may have a role in the pathophysiology of psychosis. Here, we investigate whether the antipsychotic mechanisms of CBD are underpinned by their effects on insular activation, known to be involved in salience processing. METHODS A within-subject, crossover, double-blind, placebo-controlled investigation of 19 healthy controls and 15 participants with early psychosis was conducted. Administration of a single dose of CBD was compared with placebo in psychosis participants while performing the monetary incentive delay task, an fMRI paradigm. Anticipation of reward and loss were used to contrast motivationally salient stimuli against a neutral control condition. RESULTS No group differences in brain activation between psychosis patients compared with healthy controls were observed. Attenuation of insula activation was observed following CBD, compared to placebo. Sensitivity analyses controlling for current cannabis use history did not affect the main results. CONCLUSION Our findings are in accordance with existing evidence suggesting that CBD modulates brain regions involved in salience processing. Whether such effects underlie the putative antipsychotic effects of CBD remains to be investigated.
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Affiliation(s)
- Brandon Gunasekera
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Robin Wilson
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Aisling O'Neill
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Grace Blest-Hopley
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Centre for Neuroimaging Sciences, King's College London, UK
| | - Sagnik Bhattacharyya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
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14
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Chen X, Song X, Öngür D, Du F. Association of default-mode network neurotransmitters and inter-network functional connectivity in first episode psychosis. Neuropsychopharmacology 2023; 48:781-788. [PMID: 36788375 PMCID: PMC10066209 DOI: 10.1038/s41386-023-01546-y] [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: 10/25/2022] [Revised: 01/31/2023] [Accepted: 02/02/2023] [Indexed: 02/16/2023]
Abstract
Multiple psychiatric disorders are characterized by a failure to suppress default-mode network (DMN) activity during tasks and by weaker anti-correlations between DMN and other brain networks at rest. However, the cellular and molecular mechanisms underlying this phenomenon are poorly understood. At the cellular level, neuronal activity is regulated by multiple neurochemical processes including cycling of glutamate and GABA, the major excitatory and inhibitory neurotransmitters in brain. By combining functional MRI and magnetic resonance spectroscopy techniques, it has been shown that the neurotransmitter concentrations in DMN modulate not only functional activity during cognitive tasks, but also the functional connectivity between DMN and other brain networks such as frontoparietal executive control network (CN) at rest in the healthy brain. In the current study, we extend previous research to first episode psychosis (FEP) patients and their relatives. We detected higher glutamate (Glu) levels in the medial prefrontal cortex (MPFC) in FEP compared to healthy controls without a significant difference in GABA. We also observed a significantly lower functional anti-correlated connectivity between critical nodes within the DMN (MPFC) and CN (DLPFC) in FEP. Furthermore, the relationship between MPFC Glu and GABA concentrations and the functional anti-correlation that is seen in healthy people was absent in FEP patients. These findings imply that both the DMN Glu level and the interaction between DMN and CN are affected by the illness, as is the association between neurochemistry and functional connectivity. A better understanding of this observation could provide opportunities for developing novel treatment strategies for psychosis.
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Affiliation(s)
- Xi Chen
- Psychotic Disorders Division, McLean Hospital, Belmont, CA, 02478, USA
- McLean Imaging Center, McLean Hospital, Belmont, CA, 02478, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Xiaopeng Song
- Psychotic Disorders Division, McLean Hospital, Belmont, CA, 02478, USA
- McLean Imaging Center, McLean Hospital, Belmont, CA, 02478, USA
- Harvard Medical School, Boston, MA, 02115, USA
- Wuhan Zhongke Industrial Research Institute of Medical Science, Wuhan, Hubei, 430075, China
| | - Dost Öngür
- Psychotic Disorders Division, McLean Hospital, Belmont, CA, 02478, USA.
- Harvard Medical School, Boston, MA, 02115, USA.
| | - Fei Du
- Psychotic Disorders Division, McLean Hospital, Belmont, CA, 02478, USA
- McLean Imaging Center, McLean Hospital, Belmont, CA, 02478, USA
- Harvard Medical School, Boston, MA, 02115, USA
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15
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Kim M, Kim T, Ha M, Oh H, Moon SY, Kwon JS. Large-Scale Thalamocortical Triple Network Dysconnectivities in Patients With First-Episode Psychosis and Individuals at Risk for Psychosis. Schizophr Bull 2023; 49:375-384. [PMID: 36453986 PMCID: PMC10016393 DOI: 10.1093/schbul/sbac174] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
BACKGROUND AND HYPOTHESIS Aberrant thalamocortical connectivity and large-scale network interactions among the default mode network (DMN), salience network (SN), and executive control network (ECN) (ie, triple networks) have been regarded as critical in schizophrenia pathophysiology. Despite the importance of network properties and the role of the thalamus as an integrative hub, large-scale thalamocortical triple network functional connectivities (FCs) in different stages of the psychotic disorder have not yet been reported. STUDY DESIGN Thirty-nine first-episode psychosis (FEP) patients, 75 individuals at clinical high risk (CHR) for psychosis, 46 unaffected relatives (URs) of schizophrenia patients with high genetic loading, and 110 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Modular community detection was used to identify cortical and thalamic resting-state networks, and thalamocortical network interactions were compared across the groups. STUDY RESULTS Thalamic triple networks included higher-order thalamic nuclei. Thalamic SN-cortical ECN FC was greater in the FEP group than in the CHR, UR, and HC groups. Thalamic DMN-cortical DMN and thalamic SN-cortical DMN FCs were greater in FEP and CHR participants. Thalamic ECN-cortical DMN and thalamic ECN-cortical SN FCs were greater in FEP patients and URs. CONCLUSIONS These results highlight critical modulatory functions of thalamic triple networks and the shared and distinct patterns of thalamocortical triple network dysconnectivities across different stages of psychotic disorders. The current study findings suggest that large-scale thalamocortical triple network dysconnectivities may be used as an integrative biomarker for extending our understanding of the psychosis pathophysiology and for targeting network-based neuromodulation therapeutics.
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Affiliation(s)
- Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Taekwan Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Harin Oh
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Sun-Young Moon
- Department of Psychiatry, Hallym University Kangnam Sacred Heart Hospital, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea
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16
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Kim A, Ha M, Kim T, Park S, Lho SK, Moon SY, Kim M, Kwon JS. Triple-Network Dysconnectivity in Patients With First-Episode Psychosis and Individuals at Clinical High Risk for Psychosis. Psychiatry Investig 2022; 19:1037-1045. [PMID: 36588438 PMCID: PMC9806514 DOI: 10.30773/pi.2022.0091] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 10/06/2022] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE In the triple-network model, the salience network (SN) plays a crucial role in switching between the default-mode network (DMN) and the central executive network (CEN). Aberrant patterns of triple-network connectivity have been reported in schizophrenia patients, while findings have been less consistent for patients in the early stages of psychotic disorders. Thus, the present study examined the connectivity among the SN, DMN, and CEN in first-episode psychosis (FEP) patients and individuals at clinical high risk (CHR) for psychosis. METHODS Thirty-nine patients with FEP, 78 patients with CHR for psychosis, and 110 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. We compared the SN, DMN, and CEN connectivity patterns of the three groups. The role of the SN in networks with significant connectivity differences was examined by mediation analysis. RESULTS FEP patients showed lower SN-DMN and SN-CEN (cluster-level F=5.83, false discovery rate [FDR] corrected-p=0.001) connectivity than HCs. There was lower SN-DMN connectivity (cluster-level F=3.06, FDR corrected-p=0.053) at a trend level in CHR subjects compared to HCs. Between HCs and FEP patients, mediation analysis showed that SN-DMN connectivity was a mediator between group and SN-CEN connectivity. Additionally, SN-CEN connectivity functioned as a mediator between group and SN-DMN connectivity. CONCLUSION Aberrant connectivity between the SN and DMN/CEN suggests disrupted network switching in FEP patients, although CHR subjects showed trend-level SN-DMN dysconnectivity. Our findings suggest that dysfunctional triple-network dynamics centered on the SN can appear in patients in the early stages of psychotic disorders.
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Affiliation(s)
- Ahra Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Taekwan Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Sunghyun Park
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Silvia Kyungjin Lho
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sun-Young Moon
- Department of Psychiatry, Hallym University Kangnam Sacred Heart Hospital, Seoul, Republic of Korea
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea.,Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.,Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea
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17
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The stress-vulnerability model on the path to schizophrenia: Interaction between BDNF methylation and schizotypy on the resting-state brain network. SCHIZOPHRENIA 2022; 8:49. [PMID: 35853898 PMCID: PMC9261098 DOI: 10.1038/s41537-022-00258-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 04/25/2022] [Indexed: 11/08/2022]
Abstract
The interplay between schizophrenia liability and environmental influences has been considered to be responsible for the development of schizophrenia. Recent neuroimaging studies have linked aberrant functional connectivity (FC) between the default-mode network (DMN) and the frontoparietal network (FPN) in the resting-state to the underlying neural mechanism of schizophrenia. By using schizotypy as the proxy for genetic-based liability to schizophrenia and methylation of brain-derived neurotrophic factor (BDNF) to represent environmental exposure, this study investigated the impact of the interaction between vulnerability and the environment on the neurobiological substrates of schizophrenia. Participants in this study included 101 healthy adults (HC) and 46 individuals with ultra-high risk for psychosis (UHR). All participants were tested at resting-state by functional magnetic resonance imaging, and group-independent component analysis was used to identify the DMN and the FPN. The Perceptual Aberration Scale (PAS) was used to evaluate the schizotypy level. The methylation status of BDNF was measured by pyrosequencing. For moderation analysis, the final sample consisted of 83 HC and 32 UHR individuals. UHR individuals showed reduced DMN-FPN network FC compared to healthy controls. PAS scores significantly moderated the relationship between the percentage of BDNF methylation and DMN-FPN network FC. The strength of the positive relationship between BDNF methylation and the network FC was reduced when the schizotypy level increased. These findings support the moderating role of schizotypy on the neurobiological mechanism of schizophrenia in conjunction with epigenetic changes.
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18
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Sánchez C, Moskalewicz M. Kinesthesia and Temporal Experience: On the 'Knitting and Unknitting' Process of Bodily Subjectivity in Schizophrenia. Diagnostics (Basel) 2022; 12:2720. [PMID: 36359562 PMCID: PMC9689052 DOI: 10.3390/diagnostics12112720] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/30/2022] [Accepted: 10/30/2022] [Indexed: 01/03/2024] Open
Abstract
This paper proposes a phenomenological hypothesis that psychosis entails a disturbance of the two-fold process of the indication function of kinesthesia and the presentification function of touch that affects the constitution of bodily subjectivity. Recent functional connectivity studies showed that the increased synchrony between the right anterior insula and the default mode network are associated with psychosis. This association is proposed to be correlated with the disrupted dynamics between the pre-reflective and reflective temporal experience in psychotic patients. The paper first examines the dynamic nature of kinesthesia and the influence touch and vision exert on it, and then the reciprocal influence with temporal experience focusing on the body's cyclic sense of temporality and its impact on physiology and phenomenology. Affectivity and self-affection are considered in their basic bodily expressions mainly through the concepts of responsivity and receptivity. The overall constitutive processes referred to throughout the article are proposed as a roadmap to develop body-based therapeutic work.
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Affiliation(s)
- Camilo Sánchez
- Philosophy of Mental Health Unit, Department of Social Sciences and the Humanities, Poznan University of Medical Sciences, 61-701 Poznan, Poland
| | - Marcin Moskalewicz
- Philosophy of Mental Health Unit, Department of Social Sciences and the Humanities, Poznan University of Medical Sciences, 61-701 Poznan, Poland
- Institute of Philosophy, Marie Sklodowska-Curie University, 20-400 Lublin, Poland
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19
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Sonnenschein SF, Mayeli A, Yushmanov VE, Blazer A, Calabro FJ, Perica M, Foran W, Luna B, Hetherington HP, Ferrarelli F, Sarpal DK. A longitudinal investigation of GABA, glutamate, and glutamine across the insula during antipsychotic treatment of first-episode schizophrenia. Schizophr Res 2022; 248:98-106. [PMID: 36029656 PMCID: PMC10018530 DOI: 10.1016/j.schres.2022.08.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/29/2022] [Accepted: 08/20/2022] [Indexed: 11/23/2022]
Abstract
Individuals with first-episode schizophrenia (FES) typically present with acute psychotic symptoms. Though antipsychotic drugs are the mainstay for treatment, the neurobiology underlying successful treatment remains largely elusive. Recent evidence from functional connectivity studies highlights the insula as a key structure in the neural mechanism of response. However, molecular contributions to response across insular regions remain largely unknown. We used 7-Tesla magnetic resonance spectroscopic imaging (MRSI) to measure glutamate (Glu), Glutamine (Gln), and GABA from anterior and posterior regions of the insula across antipsychotic treatment. A total of 36 participants were examined, including 15 individuals with FES and moderate to severe psychosis who were scanned at two time points, while starting and after 6 weeks of antipsychotic treatment. Symptoms were carefully monitored across the study period to characterize treatment response. GABA, Glu, and Gln levels were calculated relative to creatine in anterior and posterior insular regions, bilaterally. In relation to psychotic symptom reduction, we observed a significant increase in Glu across all insular regions with (p < 0.001), but no corresponding changes in Gln or GABA. In group analyses, the FES cohort showed lower levels of Glu (p < 0.001) and GABA (p = 0.02) at baseline. Finally, in exploratory analyses, treatment remitters demonstrated a normalization of lower insular Glu levels across treatment, unlike non-remitters. Overall, these findings contribute to our understating of molecular changes associated with antipsychotic response and demonstrate abnormalities specific to the insula in FES.
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Affiliation(s)
| | - Ahmad Mayeli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Annie Blazer
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Finnegan J Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Perica
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Deepak K Sarpal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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20
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Interactions between the cortical midline structures and sensorimotor network track maladaptive self-beliefs in clinical high risk for psychosis. SCHIZOPHRENIA 2022; 8:74. [PMID: 36114173 PMCID: PMC9481626 DOI: 10.1038/s41537-022-00279-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 08/17/2022] [Indexed: 12/02/2022]
Abstract
Individuals at clinical high risk for psychosis (CHR) report a maladaptive self-concept—with more negative and less positive self-beliefs—linked to clinical symptoms and functional impairment. Alterations have also been reported in brain networks associated with intrinsic (cortical midline structures, CMS) and extrinsic (sensorimotor network, SMN) self-processing. Theoretical accounts of multiple levels of self-experience in schizophrenia suggest that interactions between these networks would be relevant for self-beliefs. This study tested whether self-beliefs related to resting-state functional connectivity within and between the CMS and SMN. Participants were 56 individuals meeting CHR criteria and 59 matched healthy community participants (HC). Pearson correlations examined potential mediators and outcomes. The CHR group reported more negative and less positive self-beliefs. Greater resting-state functional connectivity between the posterior CMS (posterior cingulate cortex) and the SMN was associated with less positive self-beliefs in CHR, but more positive self-beliefs in HC. Attenuated negative symptoms and poorer social functioning were associated with CMS-SMN connectivity (trend level after FDR-correction) and self-beliefs. Reduced connectivity between the left and right PCC was associated with lower positive self-beliefs in CHR, although this effect was specific to very low levels of positive self-beliefs. Left-right PCC connectivity did not correlate with outcomes. Dynamic interactions between intrinsic and extrinsic self-processing supported positive self-beliefs in typically developing youth while undermining positive self-beliefs in CHR youth. Implications are discussed for basic self-fragmentation, narrative self-related metacognition, and global belief updating. Interventions for self-processing may be beneficial in the CHR syndrome.
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21
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Structural and functional connectivity abnormalities of the default mode network in patients with Alzheimer's disease and mild cognitive impairment within two independent datasets. Methods 2022; 205:29-38. [PMID: 35671900 DOI: 10.1016/j.ymeth.2022.06.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/29/2022] [Accepted: 06/03/2022] [Indexed: 12/14/2022] Open
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive dementia, and amnestic mild cognitive impairment (aMCI) has been defined as a transitional stage between normal aging and AD. Accumulating evidence has shown that altered functional connectivity (FC) and structural connectivity (SC) in the default mode network (DMN) is the prominent hallmarks of AD. However, the relationship between the changes in SC and FC of the DMN is not yet clear. In the present study, we derived the FC and SC matrices of the DMN with functional magnetic resonance imaging (fMRI) and diffusion-weighted imaging (DWI) data and further assessed FC and SC abnormalities within a discovery dataset of 120 participants (39 normal controls, 34 patients with aMCI and 47 patients with AD), as well as a replication dataset of 122 participants (43 normal controls, 37 patients with aMCI and 42 patients with AD). Disrupted SC and FC were found among DMN components (e.g., the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), and hippocampus) in patients in the aMCI and AD groups in the discovery dataset; most of the disrupted connections were also identified in the replication dataset. More importantly, some SC and FC elements were significantly correlated with the cognitive ability of patients with aMCI and AD. In addition, we found structural-functional decoupling between the PCC and the right hippocampus in patients in the aMCI and AD groups. These findings of the alteration of DMN connectivity in neurodegenerative cohorts deepen our understanding of the pathophysiological mechanisms of AD.
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22
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Smigielski L, Stämpfli P, Wotruba D, Buechler R, Sommer S, Gerstenberg M, Theodoridou A, Walitza S, Rössler W, Heekeren K. White matter microstructure and the clinical risk for psychosis: A diffusion tensor imaging study of individuals with basic symptoms and at ultra-high risk. Neuroimage Clin 2022; 35:103067. [PMID: 35679786 PMCID: PMC9178487 DOI: 10.1016/j.nicl.2022.103067] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/19/2022] [Accepted: 05/28/2022] [Indexed: 12/29/2022]
Abstract
This DTI cross-sectional study compared UHR, basic symptom & control groups (n = 112). The splenium of UHR individuals exhibited differences in fractional anisotropy (FA). Basic symptoms alone were not associated with white matter microstructure changes. Large differences in FA & radial diffusivity were found in converters to psychosis. Regional FA was inversely correlated with the general psychopathology domain.
Background Widespread white matter abnormalities are a frequent finding in chronic schizophrenia patients. More inconsistent results have been provided by the sparser literature on at-risk states for psychosis, i.e., emerging subclinical symptoms. However, considering risk as a homogenous construct, an approach of earlier studies, may impede our understanding of neuro-progression into psychosis. Methods An analysis was conducted of 3-Tesla MRI diffusion and symptom data from 112 individuals (mean age, 21.97 ± 4.19) within two at-risk paradigm subtypes, only basic symptoms (n = 43) and ultra-high risk (n = 37), and controls (n = 32). Between-group comparisons (involving three study groups and further split based on the subsequent transition to schizophrenia) of four diffusion-tensor-imaging-derived scalars were performed using voxelwise tract-based spatial statistics, followed by correlational analyses with Structured Interview for Prodromal Syndromes responses. Results Relative to controls, fractional anisotropy was lower in the splenium of the corpus callosum of ultra-high-risk individuals, but only before stringent multiple-testing correction, and negatively correlated with General Symptom severity among at-risk individuals. At-risk participants who transitioned to schizophrenia within 3 years, compared to those that did not transition, had more severe WM differences in fractional anisotropy and radial diffusivity (particularly in the corpus callosum, anterior corona radiata, and motor/sensory tracts), which were even more extensive compared to healthy controls. Conclusions These findings align with the subclinical symptom presentation and more extensive disruptions in converters, suggestive of severity-related demyelination or axonal pathology. Fine-grained but detectable differences among ultra-high-risk subjects (i.e., with brief limited intermittent and/or attenuated psychotic symptoms) point to the splenium as a discrete site of emerging psychopathology, while basic symptoms alone were not associated with altered fractional anisotropy.
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Affiliation(s)
- Lukasz Smigielski
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Philipp Stämpfli
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Diana Wotruba
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Roman Buechler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich, Zurich, Switzerland
| | - Stefan Sommer
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Miriam Gerstenberg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Anastasia Theodoridou
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Wulf Rössler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Campus Charité Mitte, Berlin, Germany; Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, Universidade de São Paulo, São Paulo, Brazil
| | - Karsten Heekeren
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy I, LVR-Hospital, Cologne, Germany
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23
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Yankouskaya A, Denholm-Smith T, Yi D, Greenshaw AJ, Cao B, Sui J. Neural Connectivity Underlying Reward and Emotion-Related Processing: Evidence From a Large-Scale Network Analysis. Front Syst Neurosci 2022; 16:833625. [PMID: 35465191 PMCID: PMC9033203 DOI: 10.3389/fnsys.2022.833625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 03/18/2022] [Indexed: 12/23/2022] Open
Abstract
Neuroimaging techniques have advanced our knowledge about neurobiological mechanisms of reward and emotion processing. It remains unclear whether reward and emotion-related processing share the same neural connection topology and how intrinsic brain functional connectivity organization changes to support emotion- and reward-related prioritized effects in decision-making. The present study addressed these challenges using a large-scale neural network analysis approach. We applied this approach to two independent functional magnetic resonance imaging datasets, where participants performed a reward value or emotion associative matching task with tight control over experimental conditions. The results revealed that interaction between the Default Mode Network, Frontoparietal, Dorsal Attention, and Salience networks engaged distinct topological structures to support the effects of reward, positive and negative emotion processing. Detailed insights into the properties of these connections are important for understanding in detail how the brain responds in the presence of emotion and reward related stimuli. We discuss the linking of reward- and emotion-related processing to emotional regulation, an important aspect of regulation of human behavior in relation to mental health.
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Affiliation(s)
- Ala Yankouskaya
- Department of Psychology, Bournemouth University, Bournemouth, United Kingdom
- *Correspondence: Ala Yankouskaya
| | - Toby Denholm-Smith
- Department of Psychology, Bournemouth University, Bournemouth, United Kingdom
| | - Dewei Yi
- School of Natural and Computing Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | | | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry, Edmonton, AB, Canada
| | - Jie Sui
- School of Psychology, University of Aberdeen, Aberdeen, United Kingdom
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24
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Bulbul O, Kurt E, Ulasoglu-Yildiz C, Demiralp T, Ucok A. Altered Resting State Functional Connectivity and Its Correlation with Cognitive Functions at Ultra High Risk for Psychosis. Psychiatry Res Neuroimaging 2022; 321:111444. [PMID: 35093807 DOI: 10.1016/j.pscychresns.2022.111444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 01/06/2022] [Accepted: 01/17/2022] [Indexed: 01/10/2023]
Abstract
The aim of this study is to identify robust resting state-functional connectivity (rs-FC) alterations and their correlations with the neuropsychological characteristics of Ultra-High Risk (UHR) for psychosis subjects compared to healthy controls (HCs). Twenty individuals with UHR and sixteen HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) and a cognitive battery evaluating attention, episodic memory and executive functions. Compared to HCs, UHR individuals showed working memory and set-shifting impairments. In functional connectivity (FC) analyses, the Default Mode Network (DMN) of the UHR subjects displayed increased FC with the visual areas and decreased FC with the Dorsal Attention Network (DAN). Additionally, the salience network (SN) of the UHR subjects displayed increased connectivity with wide posterior cortical areas in the temporal, parietal and occipital lobes, corresponding to posterior nodes of the SN itself, the Somato-Motor Network (SMN) and the DAN. The SN connectivity with the left SMN and DAN was positively correlated with the Trail Making Test - B scores of the UHR subjects. These findings show that the SN and DMN, which mostly show abnormal connectivity patterns in psychosis, are also affected in UHR subjects, while the SN plays a more central role with its hyperconnectivity to the DAN and SMN.
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Affiliation(s)
- Oznur Bulbul
- Department of Psychiatry, Erenkoy Training and Research Hospital for Psychiatric and Neurological Diseases, Istanbul, Turkey.
| | - Elif Kurt
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Çapa, Istanbul 34093, Turkey
| | - Cigdem Ulasoglu-Yildiz
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Psychology, Faculty of Humanities and Social Sciences, Istinye University, Istanbul, Turkey
| | - Tamer Demiralp
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, Çapa, Istanbul 34093, Turkey
| | - Alp Ucok
- Department of Psychiatry, Faculty of Medicine, Istanbul University, Istanbul, Turkey
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25
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Carruzzo F, Kaiser S, Tobler PN, Kirschner M, Simon JJ. Increased ventral striatal functional connectivity in patients with schizophrenia during reward anticipation. Neuroimage Clin 2022; 33:102944. [PMID: 35078045 PMCID: PMC8789684 DOI: 10.1016/j.nicl.2022.102944] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 12/23/2021] [Accepted: 01/13/2022] [Indexed: 11/29/2022]
Abstract
Background Growing evidence points towards dysfunction of the ventral striatum as a neural substrate of motivational impairments in schizophrenia. Ventral striatal activity during reward anticipation is generally reduced in patients with schizophrenia and specifically correlates with apathy. However, little is known about the cortico-striatal functional connectivity in patients with schizophrenia during reward anticipation and its relation to negative symptoms. Objectives The aim of this study was to identify categorical group differences in ventral striatal functional connectivity during reward anticipation between patients with schizophrenia and healthy controls, and dimensional associations between cortico-striatal functional connectivity and negative symptom severity. Method A total of 40 patients with schizophrenia (10 females) and 33 healthy controls (8 females) were included from two previously published studies. All participants performed a variant of the Monetary Incentive Delay Task while undergoing event-related fMRI. Functional connectivity was assessed using psychophysical interactions (PPI) with the left and right ventral striatum as seeds and the contrast [High Reward Anticipation – No Reward Anticipation]. Negative symptoms were assessed using the Brief Negative Symptom Scale. Results Compared to controls, patients with schizophrenia showed increased functional connectivity between the left ventral striatum and the left precuneus and right parahippocampal gyrus, two hubs of the default mode network (cluster-level threshold: FWE, p < .05). In addition, we found a negative association between apathy scores on the BNSS and increased functional connectivity between the left ventral striatum and the left ventral anterior insula / putamen and the left inferior frontal gyrus / dorsal anterior insula (cluster-level threshold: FWE, p < .05). Conclusions Our results indicate that the patterns of increased functional connectivity between the ventral striatum and the dorsal default mode network during reward anticipation could act as a compensatory mechanism to regulate the activity of the ventral striatum. Our results also showed that functional connectivity patterns from the ventral striatum, much like its local activity, is specifically related to apathy, and not diminished expression.
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Affiliation(s)
- Fabien Carruzzo
- Clinical and Experimental Psychopathology Laboratory, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| | - Stefan Kaiser
- Clinical and Experimental Psychopathology Laboratory, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| | - Philippe N Tobler
- Laboratory for Social and Neural Systems Research, Department of Economics, Zurich Center for Neuroeconomics, University of Zurich, Zurich, Switzerland.
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.
| | - Joe J Simon
- Department of General Internal Medicine and Psychosomatics, University Hospital Heidelberg, Heidelberg, Germany.
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26
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Bruder J. The Algorithms of Mindfulness. SCIENCE, TECHNOLOGY & HUMAN VALUES 2022; 47:291-313. [PMID: 35103028 PMCID: PMC8796153 DOI: 10.1177/01622439211025632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
This paper analyzes notions and models of optimized cognition emerging at the intersections of psychology, neuroscience, and computing. What I somewhat polemically call the algorithms of mindfulness describes an ideal that determines algorithmic techniques of the self, geared at emotional resilience and creative cognition. A reframing of rest, exemplified in corporate mindfulness programs and the design of experimental artificial neural networks sits at the heart of this process. Mindfulness trainings provide cues as to this reframing, for they detail each in their own way how intermittent periods of rest are to be recruited to augment our cognitive capacities and combat the effects of stress and information overload. They typically rely on and co-opt neuroscience knowledge about what the brains of North Americans and Europeans do when we rest. Current designs for artificial neural networks draw on the same neuroscience research and incorporate coarse principles of cognition in brains to make machine learning systems more resilient and creative. These algorithmic techniques are primarily conceived to prevent psychopathologies where stress is considered the driving force of success. Against this backdrop, I ask how machine learning systems could be employed to unsettle the concept of pathological cognition itself.
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Affiliation(s)
- Johannes Bruder
- Institute of Experimental Design and Media Cultures/Critical Media Lab, FHNW Academy of Art and Design, Basel, Switzerland
- Milieux - Institute for Arts, Culture, Technology, Concordia University, Montreal, Quebec, Canada
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27
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Yuan L, Ma X, Li D, Li Z, Ouyang L, Fan L, Yang Z, Zhang Z, Li C, He Y, Chen X. Abnormal Brain Network Interaction Associated With Positive Symptoms in Drug-Naive Patients With First-Episode Schizophrenia. Front Psychiatry 2022; 13:870709. [PMID: 35656348 PMCID: PMC9152123 DOI: 10.3389/fpsyt.2022.870709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 04/14/2022] [Indexed: 11/23/2022] Open
Abstract
Positive symptoms are marked features of schizophrenia, and emerging evidence has suggested that abnormalities of the brain network underlying these symptoms may play a crucial role in the pathophysiology of the disease. We constructed two brain functional networks based on the positive and negative correlations between positive symptom scores and brain connectivity in drug-naive patients with first-episode schizophrenia (FES, n = 45) by using a machine-learning approach (connectome-based predictive modeling, CPM). The accuracy of the model was r = 0.47 (p = 0.002). The positively and negatively associated network strengths were then compared among FES subjects, individuals at genetic high risk (GHR, n = 41) for schizophrenia, and healthy controls (HCs, n = 48). The results indicated that the positively associated network contained more cross-subnetwork connections (96.02% of 176 edges), with a focus on the default-mode network (DMN)-salience network (SN) and the DMN-frontoparietal task control (FPT) network. The negatively associated network had fewer cross-subnetwork connections (71.79% of 117 edges) and focused on the sensory/somatomotor hand (SMH)-Cingulo opercular task control (COTC) network, the DMN, and the visual network with significantly decreased connectivity in the COTC-SMH network in FES (FES < GHR, p = 0.01; FES < HC, p = 0.01). Additionally, the connectivity strengths of the right supplementary motor area (SMA) (p < 0.001) and the right precentral gyrus (p < 0.0001) were reduced in FES. To the best of our knowledge, this is the first study to generate two brain networks associated with positive symptoms by utilizing CPM in FES. Abnormal segregation, interactions of brain subnetworks, and impaired SMA might lead to salience attribution abnormalities and, thus, as a result, induce positive symptoms in schizophrenia.
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Affiliation(s)
- Liu Yuan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Xiaoqian Ma
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - David Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zongchang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Lijun Ouyang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Lejia Fan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zihao Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zhenmei Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Chunwang Li
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Ying He
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Xiaogang Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
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28
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Yang B, Zhang W, Lencer R, Tao B, Tang B, Yang J, Li S, Zeng J, Cao H, Sweeney JA, Gong Q, Lui S. Grey matter connectome abnormalities and age-related effects in antipsychotic-naive schizophrenia. EBioMedicine 2021; 74:103749. [PMID: 34906839 PMCID: PMC8671864 DOI: 10.1016/j.ebiom.2021.103749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/12/2021] [Accepted: 11/29/2021] [Indexed: 02/05/2023] Open
Abstract
Background Convergent evidence is increasing to indicate progressive brain abnormalities in schizophrenia. Knowing the brain network features over the illness course in schizophrenia, independent of effects of antipsychotic medications, would extend our sight on this question. Methods We recruited 237 antipsychotic-naive patients with schizophrenia range from 16 to 73 years old, and 254 healthy controls. High-resolution T1 weighted images were obtained with a 3.0T MR scanner. Grey matter networks were constructed individually based on the similarities of regional grey matter measurements. Network metrics were compared between patient groups and healthy controls, and regression analyses with age were conducted to determine potential differential rate of age-related changes between them. Findings Nodal centrality abnormalities were observed in patients with untreated schizophrenia, particularly in the central executive, default mode and salience networks. Accelerated age-related declines and illness duration-related declines were observed in global assortativity, and in nodal metrics of left superior temporal pole in schizophrenia patients. Although no significant intergroup differences in age-related regression were observed, the pattern of network metric alternation of left thalamus indicated higher nodal properties in early course patients, which decreased in long-term ill patients. Interpretations Global and nodal alterations in the grey matter connectome related to age and duration of illness in antipsychotic-naive patients, indicating potentially progressive network organizations mainly involving temporal regions and thalamus in schizophrenia independent from medication effects. Funding The National Natural Science Foundation of China, Sichuan Science and Technology Program, the Fundamental Research Funds for the Central Universities, Post-Doctor Research Project, West China Hospital, Sichuan University , the Science and Technology Project of the Health Planning Committee of Sichuan, Postdoctoral Interdisciplinary Research Project of Sichuan University and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.
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Affiliation(s)
- Beisheng Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Muenster, Germany
| | - Bo Tao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Biqiu Tang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jing Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Siyi Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jiaxin Zeng
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Hengyi Cao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, United States
| | - John A Sweeney
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
| | - Su Lui
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
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Smigielski L, Papiol S, Theodoridou A, Heekeren K, Gerstenberg M, Wotruba D, Buechler R, Hoffmann P, Herms S, Adorjan K, Anderson-Schmidt H, Budde M, Comes AL, Gade K, Heilbronner M, Heilbronner U, Kalman JL, Klöhn-Saghatolislam F, Reich-Erkelenz D, Schaupp SK, Schulte EC, Senner F, Anghelescu IG, Arolt V, Baune BT, Dannlowski U, Dietrich DE, Fallgatter AJ, Figge C, Jäger M, Juckel G, Konrad C, Nieratschker V, Reimer J, Reininghaus E, Schmauß M, Spitzer C, von Hagen M, Wiltfang J, Zimmermann J, Gryaznova A, Flatau-Nagel L, Reitt M, Meyers M, Emons B, Haußleiter IS, Lang FU, Becker T, Wigand ME, Witt SH, Degenhardt F, Forstner AJ, Rietschel M, Nöthen MM, Andlauer TFM, Rössler W, Walitza S, Falkai P, Schulze TG, Grünblatt E. Polygenic risk scores across the extended psychosis spectrum. Transl Psychiatry 2021; 11:600. [PMID: 34836939 PMCID: PMC8626446 DOI: 10.1038/s41398-021-01720-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/24/2021] [Accepted: 10/29/2021] [Indexed: 12/23/2022] Open
Abstract
As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke's pseudo-R2: 1.3-7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.
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Affiliation(s)
- Lukasz Smigielski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland.
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Anastasia Theodoridou
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Karsten Heekeren
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy I, LVR-Hospital, Cologne, Germany
| | - Miriam Gerstenberg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Diana Wotruba
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Roman Buechler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
| | - Per Hoffmann
- Department of Biomedicine, Human Genomics Research Group, University Hospital and University of Basel, Basel, Switzerland
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Stefan Herms
- Department of Biomedicine, Human Genomics Research Group, University Hospital and University of Basel, Basel, Switzerland
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Kristina Adorjan
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Heike Anderson-Schmidt
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Ashley L Comes
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Katrin Gade
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Maria Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Janos L Kalman
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | | | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Sabrina K Schaupp
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Eva C Schulte
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Ion-George Anghelescu
- Department of Psychiatry and Psychotherapy, Mental Health Institute, Berlin, Germany
| | - Volker Arolt
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Detlef E Dietrich
- AMEOS Clinical Center Hildesheim, Hildesheim, Germany
- Center for Systems Neuroscience (ZSN), Hannover, Germany
| | - Andreas J Fallgatter
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, Tübingen, Germany
| | - Christian Figge
- Karl-Jaspers Clinic, European Medical School Oldenburg-Groningen, Oldenburg, Germany
| | - Markus Jäger
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Georg Juckel
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, Germany
| | - Vanessa Nieratschker
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, Tübingen, Germany
| | - Jens Reimer
- Department of Psychiatry, Klinikum Bremen-Ost, Bremen, Germany
- Department of Psychiatry, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | - Max Schmauß
- Clinic for Psychiatry, Psychotherapy and Psychosomatics, Augsburg University, Medical Faculty, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - Carsten Spitzer
- Department of Psychosomatic Medicine and Psychotherapy, University Medical Center Rostock, Rostock, Germany
| | - Martin von Hagen
- Clinic for Psychiatry and Psychotherapy, Clinical Center Werra-Meißner, Eschwege, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Jörg Zimmermann
- Psychiatrieverbund Oldenburger Land gGmbH, Karl-Jaspers-Klinik, Bad Zwischenahn, Germany
| | - Anna Gryaznova
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Laura Flatau-Nagel
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Markus Reitt
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Milena Meyers
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Barbara Emons
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Ida Sybille Haußleiter
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Fabian U Lang
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Thomas Becker
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Moritz E Wigand
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Wulf Rössler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
- Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, Universidade de São Paulo, São Paulo, Brazil
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Edna Grünblatt
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
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Kandilarova S, Stoyanov DS, Paunova R, Todeva-Radneva A, Aryutova K, Maes M. Effective Connectivity between Major Nodes of the Limbic System, Salience and Frontoparietal Networks Differentiates Schizophrenia and Mood Disorders from Healthy Controls. J Pers Med 2021; 11:1110. [PMID: 34834462 PMCID: PMC8623155 DOI: 10.3390/jpm11111110] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 10/24/2021] [Accepted: 10/26/2021] [Indexed: 12/18/2022] Open
Abstract
This study was conducted to examine whether there are quantitative or qualitative differences in the connectome between psychiatric patients and healthy controls and to delineate the connectome features of major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BD), as well as the severity of these disorders. Toward this end, we performed an effective connectivity analysis of resting state functional MRI data in these three patient groups and healthy controls. We used spectral Dynamic Causal Modeling (spDCM), and the derived connectome features were further subjected to machine learning. The results outlined a model of five connections, which discriminated patients from controls, comprising major nodes of the limbic system (amygdala (AMY), hippocampus (HPC) and anterior cingulate cortex (ACC)), the salience network (anterior insula (AI), and the frontoparietal and dorsal attention network (middle frontal gyrus (MFG), corresponding to the dorsolateral prefrontal cortex, and frontal eye field (FEF)). Notably, the alterations in the self-inhibitory connection of the anterior insula emerged as a feature of both mood disorders and SCZ. Moreover, four out of the five connectome features that discriminate mental illness from controls are features of mood disorders (both MDD and BD), namely the MFG→FEF, HPC→FEF, AI→AMY, and MFG→AMY connections, whereas one connection is a feature of SCZ, namely the AMY→SPL connectivity. A large part of the variance in the severity of depression (31.6%) and SCZ (40.6%) was explained by connectivity features. In conclusion, dysfunctions in the self-regulation of the salience network may underpin major mental disorders, while other key connectome features shape differences between mood disorders and SCZ, and can be used as potential imaging biomarkers.
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Affiliation(s)
- Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology and Research Institute, Medical University of Plovdiv, 4002 Plovdiv, Bulgaria; (D.S.S.); (R.P.); (A.T.-R.); (K.A.); (M.M.)
| | - Drozdstoy St. Stoyanov
- Department of Psychiatry and Medical Psychology and Research Institute, Medical University of Plovdiv, 4002 Plovdiv, Bulgaria; (D.S.S.); (R.P.); (A.T.-R.); (K.A.); (M.M.)
| | - Rositsa Paunova
- Department of Psychiatry and Medical Psychology and Research Institute, Medical University of Plovdiv, 4002 Plovdiv, Bulgaria; (D.S.S.); (R.P.); (A.T.-R.); (K.A.); (M.M.)
| | - Anna Todeva-Radneva
- Department of Psychiatry and Medical Psychology and Research Institute, Medical University of Plovdiv, 4002 Plovdiv, Bulgaria; (D.S.S.); (R.P.); (A.T.-R.); (K.A.); (M.M.)
| | - Katrin Aryutova
- Department of Psychiatry and Medical Psychology and Research Institute, Medical University of Plovdiv, 4002 Plovdiv, Bulgaria; (D.S.S.); (R.P.); (A.T.-R.); (K.A.); (M.M.)
| | - Michael Maes
- Department of Psychiatry and Medical Psychology and Research Institute, Medical University of Plovdiv, 4002 Plovdiv, Bulgaria; (D.S.S.); (R.P.); (A.T.-R.); (K.A.); (M.M.)
- Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
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31
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Palaniyappan L, Park MTM, Jeon P, Limongi R, Yang K, Sawa A, Théberge J. Is There a Glutathione Centered Redox Dysregulation Subtype of Schizophrenia? Antioxidants (Basel) 2021; 10:1703. [PMID: 34829575 PMCID: PMC8615159 DOI: 10.3390/antiox10111703] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 10/22/2021] [Accepted: 10/23/2021] [Indexed: 12/23/2022] Open
Abstract
Schizophrenia continues to be an illness with poor outcome. Most mechanistic changes occur many years before the first episode of schizophrenia; these are not reversible after the illness onset. A developmental mechanism that is still modifiable in adult life may center on intracortical glutathione (GSH). A large body of pre-clinical data has suggested the possibility of notable GSH-deficit in a subgroup of patients with schizophrenia. Nevertheless, studies of intracortical GSH are not conclusive in this regard. In this review, we highlight the recent ultra-high field magnetic resonance spectroscopic studies linking GSH to critical outcome measures across various stages of schizophrenia. We discuss the methodological steps required to conclusively establish or refute the persistence of GSH-deficit subtype and clarify the role of the central antioxidant system in disrupting the brain structure and connectivity in the early stages of schizophrenia. We propose in-vivo GSH quantification for patient selection in forthcoming antioxidant trials in psychosis. This review offers directions for a promising non-dopaminergic early intervention approach in schizophrenia.
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Affiliation(s)
- Lena Palaniyappan
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada; (M.T.M.P.); (J.T.)
- Department of Medical Biophysics, Western University, London, ON N6A 5C1, Canada;
- Robarts Research Institute, Western University, London, ON N6A 5C1, Canada;
- Lawson Health Research Institute, London, ON N6C 2R5, Canada
| | - Min Tae M. Park
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada; (M.T.M.P.); (J.T.)
| | - Peter Jeon
- Department of Medical Biophysics, Western University, London, ON N6A 5C1, Canada;
- Robarts Research Institute, Western University, London, ON N6A 5C1, Canada;
- Lawson Health Research Institute, London, ON N6C 2R5, Canada
| | - Roberto Limongi
- Robarts Research Institute, Western University, London, ON N6A 5C1, Canada;
| | - Kun Yang
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; (K.Y.); (A.S.)
| | - Akira Sawa
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; (K.Y.); (A.S.)
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Jean Théberge
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada; (M.T.M.P.); (J.T.)
- Department of Medical Biophysics, Western University, London, ON N6A 5C1, Canada;
- Lawson Health Research Institute, London, ON N6C 2R5, Canada
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N-methyl-d-aspartate receptor antagonism modulates P300 event-related potentials and associated activity in salience and central executive networks. Pharmacol Biochem Behav 2021; 211:173287. [PMID: 34653398 DOI: 10.1016/j.pbb.2021.173287] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/05/2021] [Accepted: 10/06/2021] [Indexed: 11/21/2022]
Abstract
Impairments in auditory information processing in schizophrenia as indexed electrophysiologically by P300 deficits during novelty (P3a) and target (P3b) processing are linked to N -methyl- D -aspartate receptor (NMDAR) dysfunction. This study in 14 healthy volunteers examined the effects of a subanesthetic dose of the NMDAR antagonist ketamine on P300 and their relationship to psychomimetic symptoms and cortical source activity (with eLORETA). Ketamine reduced early (e- P3a) and late (l-P3a) novelty P300 at sensor (scalp)-level and at source-level in the salience network. Increases in dissociation symptoms were negatively correlated with ketamine-induced P3b changes, at sensor-level and source-level, in both salience and central executive networks. These P3a alterations during novelty processing, and the symptom-related P3b changes during target processing support a model of NMDAR hypofunction underlying disrupted auditory attention in schizophrenia.
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Xue C, Qi W, Yuan Q, Hu G, Ge H, Rao J, Xiao C, Chen J. Disrupted Dynamic Functional Connectivity in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment Based on the Triple-Network Model. Front Aging Neurosci 2021; 13:711009. [PMID: 34603006 PMCID: PMC8484524 DOI: 10.3389/fnagi.2021.711009] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 08/16/2021] [Indexed: 12/20/2022] Open
Abstract
Background: Subjective cognitive decline and amnestic mild cognitive impairment (aMCI) were widely thought to be preclinical AD spectrum disorders, characterized by aberrant functional connectivity (FC) within the triple networks of the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture temporal fluctuations in brain FC during the scan, which static FC analysis cannot. The purpose of the current study was to explore the changes in dynamic FC within the triple networks of the preclinical AD spectrum and further reveal their potential diagnostic value in diagnosing preclinical AD spectrum disorders. Methods: We collected resting-state functional magnetic resonance imaging data from 44 patients with subjective cognitive decline (SCD), 49 with aMCI, and 58 healthy controls (HCs). DFC analysis based on the sliding time-window correlation method was used to analyze DFC variability within the triple networks in the three groups. Then, correlation analysis was conducted to reveal the relationship between altered DFC variability within the triple networks and a decline in cognitive function. Furthermore, logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in patients with SCD and aMCI. Results: Compared with the HC group, the groups with SCD and aMCI both showed altered DFC variability within the triple networks. DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within the ECN were significantly different between patients with SCD and aMCI. Moreover, the altered DFC variability in the left IFG within the ECN was obviously associated with a decline in episodic memory and executive function. The logistic regression analysis showed that multivariable analysis had high sensitivity and specificity for diagnosing SCD and aMCI. Conclusions: Subjective cognitive decline and aMCI showed varying degrees of change in DFC variability within the triple networks and altered DFC variability within the ECN involved episodic memory and executive function. More importantly, altered DFC variability and the triple-network model proved to be important biomarkers for diagnosing and identifying patients with preclinical AD spectrum disorders.
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Affiliation(s)
- Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Wenzhang Qi
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Qianqian Yuan
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Guanjie Hu
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Honglin Ge
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Jiang Rao
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chaoyong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Jiu Chen
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China.,Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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Wang Y, Jiang Y, Collin G, Liu D, Su W, Xu L, Wei Y, Tang Y, Zhang T, Tang X, Hu Y, Zhang J, Cui H, Wang J, Yao D, Luo C, Wang J. The effects of antipsychotics on interactions of dynamic functional connectivity in the triple-network in first episode schizophrenia. Schizophr Res 2021; 236:29-37. [PMID: 34365083 DOI: 10.1016/j.schres.2021.07.038] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 05/08/2021] [Accepted: 07/28/2021] [Indexed: 11/15/2022]
Abstract
BACKGROUND Brain dynamics abnormalities in the triple-network, which involves the salience network (SN), the default mode network (DMN) and the central executive network (CEN), have been reported in schizophrenia. However, it remains to be clarified how antipsychotics affect dynamic functional connectivity (DFC) within the triple-network and whether differences in clinical outcomes are associated with varying levels of network model dysfunction. METHODS Resting-state functional magnetic resonance imaging scans were obtained from 64 first-episode schizophrenia patients (SZ) and 67 healthy controls (HC). All patients were scanned before and after 12-week antipsychotic treatment and the HC were scanned only at baseline. RESULTS At baseline, SZ participants showed significantly reduced dynamic functional interactions across the triple-network compared to HC. The SZ group displayed a pattern of reduction in resting-state DFC among the triple-network compared with HC. After medication, the mean dynamic network interaction index (dNII) value was improved. A significant quadratic relation was observed between longitudinal change of mean dNII and the reduction ratio of PANSS total score within the SZ group. The DFC within inter-network (between DMN and SN, and between DMN and CEN) and intra-network connections of DMN were significantly higher relative to baseline. Intra-SN DFC, intra-DMN DFC and DFC between SN and DMN were found to be predictive of clinical features at baseline. Intra-CEN DFC and DFC between DMN and CEN were predictive of treatment response. CONCLUSIONS Aberrant brain dynamics in the triple-network could be regulated with medication. DFC organization in the triple network was found to predict the clinical outcome.
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Affiliation(s)
- Yingchan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
| | - Guusje Collin
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Dengtang Liu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Wenjun Su
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yanyan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Xiaochen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yegang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Jianye Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Huiru Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Jinhong Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai 200031, PR China; Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, PR China.
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35
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Metzak PD, Addington J, Hassel S, Goldstein BI, MacIntosh BJ, Lebel C, Wang JL, Kennedy SH, MacQueen GM, Bray S. Functional imaging in youth at risk for transdiagnostic serious mental illness: Initial results from the PROCAN study. Early Interv Psychiatry 2021; 15:1276-1291. [PMID: 33295151 DOI: 10.1111/eip.13078] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 09/29/2020] [Accepted: 11/13/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND In their early stages, serious mental illnesses (SMIs) are often indistinguishable from one another, suggesting that studying alterations in brain activity in a transdiagnostic fashion could help to understand the neurophysiological origins of different SMI. The purpose of this study was to examine brain activity in youth at varying stages of risk for SMI using functional magnetic resonance imaging tasks (fMRI) that engage brain systems believed to be affected. METHODS Two hundred and forty three participants at different stages of risk for SMI were recruited to the Canadian Psychiatric Risk and Outcome (PROCAN) study, however only 179 were scanned. Stages included asymptomatic participants at no elevated risk, asymptomatic participants at elevated risk due to family history, participants with undifferentiated general symptoms of mental illness, and those experiencing attenuated versions of diagnosable psychiatric illnesses. The fMRI tasks included: (1) a monetary incentive delay task; (2) an emotional Go-NoGo and (3) an n-back working memory task. RESULTS Strong main effects with each of the tasks were found in brain regions previously described in the literature. However, there were no significant differences in brain activity between any of the stages of risk for SMI for any of the task contrasts, after accounting for site, sex and age. Furthermore, results indicated no significant differences even when participants were dichotomized as asymptomatic or symptomatic. CONCLUSIONS These results suggest that univariate BOLD responses during typical fMRI tasks are not sensitive markers of SMI risk and that further study, particularly longitudinal designs, will be necessary to understand brain changes underlying the early stages of SMI.
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Affiliation(s)
- Paul D Metzak
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Jean Addington
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Benjamin I Goldstein
- Center for Youth Bipolar Disorder, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Pharmacology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Bradley J MacIntosh
- Hurvitz Brain Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Catherine Lebel
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada.,Child & Adolescent Imaging Research (CAIR) Program, Calgary, Alberta, Canada
| | - Jian Li Wang
- Work & Mental Health Research Unit, Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada.,School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University Health Network, Toronto, Ontario, Canada.,Department of Psychiatry, St. Michael's Hospital, Toronto, Ontario, Canada.,Arthur Somner Rotenberg Chair in Suicide and Depression Studies, St. Michael's Hospital, Toronto, Ontario, Canada.,Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Signe Bray
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada.,Child & Adolescent Imaging Research (CAIR) Program, Calgary, Alberta, Canada
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36
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Rajasilta O, Häkkinen S, Björnsdotter M, Scheinin NM, Lehtola SJ, Saunavaara J, Parkkola R, Lähdesmäki T, Karlsson L, Karlsson H, Tuulari JJ. Maternal pre-pregnancy BMI associates with neonate local and distal functional connectivity of the left superior frontal gyrus. Sci Rep 2021; 11:19182. [PMID: 34584134 PMCID: PMC8478954 DOI: 10.1038/s41598-021-98574-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 09/06/2021] [Indexed: 11/09/2022] Open
Abstract
Maternal obesity/overweight during pregnancy has reached epidemic proportions and has been linked with adverse outcomes for the offspring, including cognitive impairment and increased risk for neuropsychiatric disorders. Prior neuroimaging investigations have reported widespread aberrant functional connectivity and white matter tract abnormalities in neonates born to obese mothers. Here we explored whether maternal pre-pregnancy adiposity is associated with alterations in local neuronal synchrony and distal connectivity in the neonate brain. 21 healthy mother-neonate dyads from uncomplicated pregnancies were included in this study (age at scanning 26.14 ± 6.28 days, 12 male). The neonates were scanned with a 6-min resting-state functional magnetic resonance imaging (rs-fMRI) during natural sleep. Regional homogeneity (ReHo) maps were computed from obtained rs-fMRI data. Multiple regression analysis was performed to assess the association of pre-pregnancy maternal body-mass-index (BMI) and ReHo. Seed-based connectivity analysis with multiple regression was subsequently performed with seed-ROI derived from ReHo analysis. Maternal adiposity measured by pre-pregnancy BMI was positively associated with neonate ReHo values within the left superior frontal gyrus (SFG) (FWE-corrected p < 0.005). Additionally, we found both positive and negative associations (p < 0.05, FWE-corrected) for maternal pre-pregnancy BMI and seed-based connectivity between left SFG and prefrontal, amygdalae, basal ganglia and insular regions. Our results imply that maternal pre-pregnancy BMI associates with local and distal functional connectivity within the neonate left superior frontal gyrus. These findings add to the evidence that increased maternal pre-pregnancy BMI has a programming influence on the developing neonate brain functional networks.
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Affiliation(s)
- Olli Rajasilta
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.
| | - Suvi Häkkinen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Malin Björnsdotter
- Department of Psychiatry for Affective Disorders, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Noora M Scheinin
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
| | - Satu J Lehtola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, University of Turku and Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- Department of Pediatric Neurology, Turku University Hospital and University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Center for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland.,Center for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland.,Department of Psychiatry, University of Oxford, UK (Sigrid Juselius Fellowship), Oxford, UK.,Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
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37
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Neural Correlates of Aberrant Salience and Source Monitoring in Schizophrenia and At-Risk Mental States-A Systematic Review of fMRI Studies. J Clin Med 2021; 10:jcm10184126. [PMID: 34575237 PMCID: PMC8468329 DOI: 10.3390/jcm10184126] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 08/22/2021] [Accepted: 09/07/2021] [Indexed: 01/03/2023] Open
Abstract
Cognitive biases are an important factor contributing to the development and symptom severity of psychosis. Despite the fact that various cognitive biases are contributing to psychosis, they are rarely investigated together. In the current systematic review, we aimed at investigating specific and shared functional neural correlates of two important cognitive biases: aberrant salience and source monitoring. We conducted a systematic search of fMRI studies of said cognitive biases. Eight studies on aberrant salience and eleven studies on source monitoring were included in the review. We critically discussed behavioural and neuroimaging findings concerning cognitive biases. Various brain regions are associated with aberrant salience and source monitoring in individuals with schizophrenia and the risk of psychosis. The ventral striatum and insula contribute to aberrant salience. The medial prefrontal cortex, superior and middle temporal gyrus contribute to source monitoring. The anterior cingulate cortex and hippocampus contribute to both cognitive biases, constituting a neural overlap. Our review indicates that aberrant salience and source monitoring may share neural mechanisms, suggesting their joint role in producing disrupted external attributions of perceptual and cognitive experiences, thus elucidating their role in positive symptoms of psychosis. Account bridging mechanisms of these two biases is discussed. Further studies are warranted.
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38
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Liang S, Wang Q, Greenshaw AJ, Li X, Deng W, Ren H, Zhang C, Yu H, Wei W, Zhang Y, Li M, Zhao L, Du X, Meng Y, Ma X, Yan CG, Li T. Aberrant triple-network connectivity patterns discriminate biotypes of first-episode medication-naive schizophrenia in two large independent cohorts. Neuropsychopharmacology 2021; 46:1502-1509. [PMID: 33408329 PMCID: PMC8208970 DOI: 10.1038/s41386-020-00926-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 11/07/2020] [Accepted: 11/12/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a complex disorder associated with aberrant brain functional connectivity. This study aims to demonstrate the relation of heterogeneous symptomatology in this disorder to distinct brain connectivity patterns within the triple-network model. The study sample comprised 300 first-episode antipsychotic-naive patients with schizophrenia (FES) and 301 healthy controls (HCs). At baseline, resting-state functional magnetic resonance imaging data were captured for each participant, and concomitant neurocognitive functions were evaluated outside the scanner. Clinical information of 49 FES in the discovery dataset were reevaluated at a 6-week follow-up. Differential features between FES and HCs were selected from triple-network connectivity profiles. Cutting-edge unsupervised machine learning algorithms were used to define patient subtypes. Clinical and cognitive variables were compared between patient subgroups. Two FES subgroups with differing triple-network connectivity profiles were identified in the discovery dataset and confirmed in an independent hold-out cohort. One patient subgroup appearing to have more severe clinical symptoms was distinguished by salience network (SN)-centered hypoconnectivity, which was associated with greater impairments in sustained attention. The other subgroup exhibited hyperconnectivity and manifested greater deficits in cognitive flexibility. The SN-centered hypoconnectivity subgroup had more persistent negative symptoms at the 6-week follow-up than the hyperconnectivity subgroup. The present study illustrates that clinically relevant cognitive subtypes of schizophrenia may be associated with distinct differences in connectivity in the triple-network model. This categorization may foster further analysis of the effects of therapy on these network connectivity patterns, which may help to guide therapeutic choices to effectively reach personalized treatment goals.
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Affiliation(s)
- Sugai Liang
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China ,grid.13291.380000 0001 0807 1581West China Brain Research Centre, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Qiang Wang
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Andrew J. Greenshaw
- grid.17089.37Department of Psychiatry, University of Alberta, Edmonton, AB T6G 2B7 Canada
| | - Xiaojing Li
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Wei Deng
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China ,grid.13291.380000 0001 0807 1581West China Brain Research Centre, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Hongyan Ren
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Chengcheng Zhang
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Hua Yu
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Wei Wei
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Yamin Zhang
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Mingli Li
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Liansheng Zhao
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Xiangdong Du
- grid.263761.70000 0001 0198 0694Suzhou Psychiatry Hospital, Affiliated Guangji Hospital of Soochow University, 215137 Suzhou, Jiangsu China
| | - Yajing Meng
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Xiaohong Ma
- grid.13291.380000 0001 0807 1581Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Chao-Gan Yan
- grid.454868.30000 0004 1797 8574CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419Department of Psychology, University of Chinese Academy of Sciences, 100101 Beijing, China
| | - Tao Li
- Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, 610041, Chengdu, Sichuan, China. .,West China Brain Research Centre, West China Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
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39
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Functional brain network dysfunctions in subjects at high-risk for psychosis: A meta-analysis of resting-state functional connectivity. Neurosci Biobehav Rev 2021; 128:90-101. [PMID: 34119524 DOI: 10.1016/j.neubiorev.2021.06.020] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 06/08/2021] [Indexed: 01/10/2023]
Abstract
Although emerging evidence suggests that altered functional connectivity (FC) of large-scale neural networks is associated with disturbances in individuals at high-risk for psychosis, the findings are still far to be conclusive. We conducted a meta-analysis of seed-based resting-state functional magnetic resonance imaging studies that compared individuals at clinical high-risk for psychosis (CHR), first-degree relatives of patients with schizophrenia, or subjects who reported psychotic-like experiences with healthy controls. Twenty-nine studies met the inclusion criteria. The MetaNSUE method was used to analyze connectivity comparisons and symptom correlations. Our results showed a significant hypo-connectivity within the salience network (p = 0.012, uncorrected) in the sample of CHR individuals (n = 810). Additionally, we found a positive correlation between negative symptom severity and FC between the default mode network and both the salience network (p < 0.001, r = 0.298) and the central executive network (p = 0.003, r = 0.23) in the CHR group. This meta-analysis lends support for the hypothesis that large-scale network dysfunctions represent a core neural deficit underlying psychosis development.
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40
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Song X, Chen X, Yuksel C, Yuan J, Pizzagalli DA, Forester B, Öngür D, Du F. Bioenergetics and abnormal functional connectivity in psychotic disorders. Mol Psychiatry 2021; 26:2483-2492. [PMID: 33398087 PMCID: PMC8254819 DOI: 10.1038/s41380-020-00993-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 11/25/2020] [Accepted: 12/08/2020] [Indexed: 12/22/2022]
Abstract
Psychotic Disorders such as schizophrenia (SZ) and bipolar disorder (BD) are characterized by abnormal functional connectivity (FC) within neural networks such as the default mode network (DMN), as well as attenuated anticorrelation between DMN and task-positive networks (TPN). Bioenergetic processes are critical for synaptic connectivity and are also abnormal in psychotic disorders. We therefore examined the association between brain energy metabolism and FC in psychotic disorders. 31P magnetization transfer spectroscopy from medial prefrontal cortex (MPFC) and whole-brain fMRI data were collected from demographically matched groups of SZ, BD, and healthy control (HC) subjects. The creatine kinase (CK) reaction flux calculated from spectroscopy was used as an index of regional energy production rate. FC maps were generated with MPFC as the seed region. Compared to HC, SZ showed significantly lower CK flux, while both BD and SZ patients showed decreased anticorrelation between MPFC and TPN. CK flux was significantly correlated with FC between MPFC and other DMN nodes in HC. This positive correlation was reduced modestly in BD and strongly in SZ. CK flux was negatively correlated with the anticorrelation between MPFC and TPN in HC, but this relationship was not observed in BD or SZ. These results indicate that MPFC energy metabolism rates are associated with stronger FC within networks and stronger anticorrelation between networks in HC. However, this association is decreased in SZ and BD, where bioenergetic and FC abnormalities are evident. This pattern may suggest that impairment in energy production in psychotic disorders underlies the impaired neural connectivity.
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Affiliation(s)
- Xiaopeng Song
- Psychotic Disorders Division, McLean Hospital, 02478, USA,McLean Imaging Center, McLean Hospital, 02478, USA,Harvard Medical School, Boston, Massachusetts, 02115, USA,These authors contributed equally to this work
| | - Xi Chen
- Psychotic Disorders Division, McLean Hospital, 02478, USA,McLean Imaging Center, McLean Hospital, 02478, USA,Harvard Medical School, Boston, Massachusetts, 02115, USA,These authors contributed equally to this work
| | - Cagri Yuksel
- Psychotic Disorders Division, McLean Hospital, 02478, USA,Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Junliang Yuan
- McLean Imaging Center, McLean Hospital, 02478, USA,National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China
| | - Diego A. Pizzagalli
- McLean Imaging Center, McLean Hospital, 02478, USA,Harvard Medical School, Boston, Massachusetts, 02115, USA,Center for Depression, Anxiety and Stress Research, McLean Hospital, 02478, USA
| | - Brent Forester
- Harvard Medical School, Boston, Massachusetts, 02115, USA,Division of Geriatric Psychiatry, McLean Hospital, 02478, USA
| | - Dost Öngür
- Psychotic Disorders Division, McLean Hospital, 02478, USA,McLean Imaging Center, McLean Hospital, 02478, USA,Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Fei Du
- Psychotic Disorders Division, McLean Hospital, Belmont, MA, 02478, USA. .,McLean Imaging Center, McLean Hospital, Belmont, MA, 02478, USA. .,Harvard Medical School, Boston, MA, 02115, USA.
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41
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Xue C, Sun H, Yue Y, Wang S, Qi W, Hu G, Ge H, Yuan Q, Rao J, Tian L, Xiao C, Chen J. Structural and Functional Disruption of Salience Network in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment. ACS Chem Neurosci 2021; 12:1384-1394. [PMID: 33825444 DOI: 10.1021/acschemneuro.1c00051] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Salience network (SN), playing a vital role in advanced cognitive function, is regarded to be impaired in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The purpose of the study was to explore the importance of structural and functional features of SN in the diagnosis of SCD and aMCI. Structural and resting-state functional magnetic resonance imaging were collected from SCD, aMCI, and healthy control (HC). Cortex thickness, gray matter (GM) volume, spontaneous brain activity, functional connectivity (FC) within SN, and its relationship with cognitive function were analyzed. Moreover, the receiver operating characteristic analysis was performed to assess diagnostic efficacy of altered indictors for SCD and aMCI. Compared to HC, both SCD and aMCI showed decreased GM volume, decreased spontaneous brain activity, and increased FC within SN, while aMCI showed additional decreased cortex thickness. Furthermore, the altered FC in SCD and aMCI was significantly correlated with cognitive function. Particularly, the best-fitting classification models of SCD and aMCI were based on the combined multiple indicators. In conclusion, structure and function of SN were disrupted in SCD and aMCI, which involved in cognitive decline. The combined multiple indicators of SN provided powerful biomarkers for the diagnosis of SCD and aMCI.
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Affiliation(s)
- Chen Xue
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Haiting Sun
- Department of Pediatrics, Xijing Hospital, the Fourth Milit ary Medical University (Air Force Medical University), Xi’an, Shaanxi 710032, China
| | - Yingying Yue
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Siyu Wang
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Wenzhang Qi
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Guanjie Hu
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Honglin Ge
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Qianqian Yuan
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Jiang Rao
- Department of Rehabilitation, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Lei Tian
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Chaoyong Xiao
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Jiu Chen
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
- Institute of Neuropsychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
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42
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Antoniades M, Haas SS, Modabbernia A, Bykowsky O, Frangou S, Borgwardt S, Schmidt A. Personalized Estimates of Brain Structural Variability in Individuals With Early Psychosis. Schizophr Bull 2021; 47:1029-1038. [PMID: 33547470 PMCID: PMC8266574 DOI: 10.1093/schbul/sbab005] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Early psychosis in first-episode psychosis (FEP) and clinical high-risk (CHR) individuals has been associated with alterations in mean regional measures of brain morphology. Examination of variability in brain morphology could assist in quantifying the degree of brain structural heterogeneity in clinical relative to healthy control (HC) samples. METHODS Structural magnetic resonance imaging data were obtained from CHR (n = 71), FEP (n = 72), and HC individuals (n = 55). Regional brain variability in cortical thickness (CT), surface area (SA), and subcortical volume (SV) was assessed with the coefficient of variation (CV). Furthermore, the person-based similarity index (PBSI) was employed to quantify the similarity of CT, SA, and SV profile of each individual to others within the same diagnostic group. Normative modeling of the PBSI-CT, PBSI-SA, and PBSI-SV was used to identify CHR and FEP individuals whose scores deviated markedly from those of the healthy individuals. RESULTS There was no effect of diagnosis on the CV for any regional measure (P > .38). CHR and FEP individuals differed significantly from the HC group in terms of PBSI-CT (P < .0001), PBSI-SA (P < .0001), and PBSI-SV (P = .01). In the clinical groups, normative modeling identified 32 (22%) individuals with deviant PBSI-CT, 12 (8.4%) with deviant PBSI-SA, and 21 (15%) with deviant PBSI-SV; differences of small effect size indicated that individuals with deviant PBSI scores had lower IQ and higher psychopathology. CONCLUSIONS Examination of brain structural variability in early psychosis indicated heterogeneity at the level of individual profiles and encourages further large-scale examination to identify individuals that deviate markedly from normative reference data.
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Affiliation(s)
- Mathilde Antoniades
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Oleg Bykowsky
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
- Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Stefan Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - André Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
- To whom correspondence should be addressed; Wilhelm Klein-Strasse 27, 4002 Basel, Switzerland; tel: +41 0(61) 325 59 29, fax: +41 (0)61 325 55 82, e-mail:
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43
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Uhlmann L, Pazen M, van Kemenade BM, Kircher T, Straube B. Neural Correlates of Self-other Distinction in Patients with Schizophrenia Spectrum Disorders: The Roles of Agency and Hand Identity. Schizophr Bull 2021; 47:1399-1408. [PMID: 33433625 PMCID: PMC8379550 DOI: 10.1093/schbul/sbaa186] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Schizophrenia spectrum disorders (SSD) are characterized by disturbed self-other distinction. While previous studies associate abnormalities in the sense of agency (ie, the feeling that an action and the resulting sensory consequences are produced by oneself) with disturbed processing in the angular gyrus, passive movement conditions to isolate contributions of motor predictions are lacking. Furthermore, the role of body identity (ie, visual features determining whether a seen body part belongs to oneself) in self-other distinction is unclear. In the current study, fMRI was used to assess the roles of agency and hand identity in self-other distinction. Patients with SSD and healthy controls (HC) performed active and passive hand movements (agency manipulation) while seeing their own or someone else's hand moving in accordance with their action (hand identity manipulation). Variable delays (0-417 ms) between movement and feedback had to be detected. Our results showed overall lower delay detection performances during active than passive conditions; however, these differences were reduced in patients when the own hand was displayed. On a neural level, we found that in HC, activation in the right angular gyrus was modulated by agency and hand identity. In contrast, agency and hand identity revealed no overlapping activation in patients, due to reduced effects of agency. Importantly, HC and SSD patients shared similar effects of hand identity in the angular gyrus. Our results suggest that disturbances of self-other distinction in SSD are particularly driven by agency, while self-other distinction based on hand identity might be spared.
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Affiliation(s)
- Lukas Uhlmann
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind, Brain and Behavior (CMBB), Marburg, Germany,To whom correspondence should be addressed; Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany; tel: +49-6421-58-66883; e-mail:
| | - Mareike Pazen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Bianca M van Kemenade
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
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44
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de la Salle S, Choueiry J, Shah D, Bowers H, McIntosh J, Ilivitsky V, Carroll B, Knott V. Resting-state functional EEG connectivity in salience and default mode networks and their relationship to dissociative symptoms during NMDA receptor antagonism. Pharmacol Biochem Behav 2020; 201:173092. [PMID: 33385439 DOI: 10.1016/j.pbb.2020.173092] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 01/28/2023]
Abstract
N-methyl-d-aspartate receptor (NMDAR) antagonists administered to healthy humans results in schizophrenia-like symptoms, which are thought in part to be related to glutamatergically altered electrophysiological connectivity in large-scale intrinsic functional brain networks. Here, we examine resting-state source electroencephalographic (EEG) connectivity within and between the default mode (DMN: for self-related cognitive activity) and salience networks (SN: for detection of salient stimuli in internal and external environments) in 21 healthy volunteers administered a subanesthetic dose of the dissociative anesthetic and NMDAR antagonist, ketamine. In addition to provoking symptoms of dissociation, which are thought to originate from an altered sense of self that is common to schizophrenia, ketamine induces frequency-dependent increases and decreases in connectivity within and between DMN and SN. These altered interactive network couplings together with emergent dissociative symptoms tentatively support an NMDAR-hypofunction hypothesis of disturbed electrophysiologic connectivity in schizophrenia.
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Affiliation(s)
| | - Joelle Choueiry
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Dhrasti Shah
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
| | - Hayley Bowers
- Department of Psychology, University of Guelph, Guelph, ON, Canada
| | - Judy McIntosh
- University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
| | - Vadim Ilivitsky
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada; Royal Ottawa Mental Health Centre, Ottawa, ON, Canada
| | - Brooke Carroll
- University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
| | - Verner Knott
- School of Psychology, University of Ottawa, Ottawa, ON, Canada; Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada; University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada; Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada.
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45
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Roes MM, Yin J, Taylor L, Metzak PD, Lavigne KM, Chinchani A, Tipper CM, Woodward TS. Hallucination-Specific structure-function associations in schizophrenia. Psychiatry Res Neuroimaging 2020; 305:111171. [PMID: 32916453 DOI: 10.1016/j.pscychresns.2020.111171] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 08/15/2020] [Accepted: 08/19/2020] [Indexed: 01/13/2023]
Abstract
Combining structural (sMRI) and functional magnetic resonance imaging (fMRI) data in schizophrenia patients with and without auditory hallucinations (9 SZ_AVH, 12 SZ_nAVH), 18 patients with bipolar disorder, and 22 healthy controls, we examined whether cortical thinning was associated with abnormal activity in functional brain networks associated with auditory hallucinations. Language-task fMRI data were combined with mean cortical thickness values from 148 brain regions in a constrained principal component analysis (CPCA) to identify brain structure-function associations predictable from group differences. Two components emerged from the multimodal analysis. The "AVH component" highlighted an association of frontotemporal and cingulate thinning with altered brain activity characteristic of hallucinations among patients with AVH. In contrast, the "Bipolar component" distinguished bipolar patients from healthy controls and linked increased activity in the language network with cortical thinning in the left occipital-temporal lobe. Our findings add to a body of evidence of the biological underpinnings of hallucinations and illustrate a method for multimodal data analysis of structure-function associations in psychiatric illness.
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Affiliation(s)
- Meighen M Roes
- Department of Psychology, University of British Columbia, Vancouver, BC, Canada; BC Mental Health and Substance Use Services Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
| | - John Yin
- BC Mental Health and Substance Use Services Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Laura Taylor
- BC Mental Health and Substance Use Services Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Paul D Metzak
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Katie M Lavigne
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Abhijit Chinchani
- BC Mental Health and Substance Use Services Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Christine M Tipper
- BC Mental Health and Substance Use Services Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Todd S Woodward
- BC Mental Health and Substance Use Services Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.
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46
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Identifying neural signatures mediating behavioral symptoms and psychosis onset: High-dimensional whole brain functional mediation analysis. Neuroimage 2020; 226:117508. [PMID: 33157263 PMCID: PMC7836235 DOI: 10.1016/j.neuroimage.2020.117508] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/19/2020] [Accepted: 10/22/2020] [Indexed: 11/26/2022] Open
Abstract
Along the pathway from behavioral symptoms to the development of psychotic disorders sits the multivariate mediating brain. The functional organization and structural topography of large-scale multivariate neural mediators among patients with brain disorders, however, are not well understood. Here, we design a high-dimensional brain-wide functional mediation framework to investigate brain regions that intermediate between baseline behavioral symptoms and future conversion to full psychosis among individuals at clinical high risk (CHR). Using resting-state functional magnetic resonance imaging (fMRI) data from 263 CHR subjects, we extract an α brain atlas and a β brain atlas: the former underlines brain areas associated with prodromal symptoms and the latter highlights brain areas associated with disease onset. In parallel, we identify and separate mediators that potentially positively and negatively mediate symptoms and psychosis, respectively, and quantify the effect of each neural mediator on disease development. Taken together, these results paint a brain-wide picture of neural markers that are potentially mediating behavioral symptoms and the development of psychotic disorders; additionally, they underscore a statistical framework that is useful to uncover large-scale intermediating variables in a regulatory biological system.
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47
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Andreou C, Borgwardt S. Structural and functional imaging markers for susceptibility to psychosis. Mol Psychiatry 2020; 25:2773-2785. [PMID: 32066828 PMCID: PMC7577836 DOI: 10.1038/s41380-020-0679-7] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 01/15/2020] [Accepted: 01/31/2020] [Indexed: 12/21/2022]
Abstract
The introduction of clinical criteria for the operationalization of psychosis high risk provided a basis for early detection and treatment of vulnerable individuals. However, about two-thirds of people meeting clinical high-risk (CHR) criteria will never develop a psychotic disorder. In the effort to increase prognostic precision, structural and functional neuroimaging have received growing attention as a potentially useful resource in the prediction of psychotic transition in CHR patients. The present review summarizes current research on neuroimaging biomarkers in the CHR state, with a particular focus on their prognostic utility and limitations. Large, multimodal/multicenter studies are warranted to address issues important for clinical applicability such as generalizability and replicability, standardization of clinical definitions and neuroimaging methods, and consideration of contextual factors (e.g., age, comorbidity).
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Affiliation(s)
- Christina Andreou
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany.
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland.
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48
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Patients on the psychosis spectrum employ an alternate brain network to engage in complex decision-making. PLoS One 2020; 15:e0238774. [PMID: 32915832 PMCID: PMC7485831 DOI: 10.1371/journal.pone.0238774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 08/24/2020] [Indexed: 11/19/2022] Open
Abstract
Brain reward processing mechanisms that underlie complex decision-making are compromised in psychosis. The goal of this research was to advance our understanding of the underlying (1) neural mechanisms and (2) discrete neuro-economic/motivational processes that may be altered in complex decision-making in euthymic patients on the psychosis spectrum (PPS). Utilizing a functional magnetic resonance neuroimaging (fmri) paradigm of a well-validated laboratory measure of complex decision-making (Iowa Gambling Task-IGT), the brain activation patterns of a target group of PPS were compared to a demographically matched healthy comparison group (HMC). These two groups were also evaluated on real-life decision outcomes on day of scan. PPS primarily activate the Dorsal Attentional Network (DAN) in real-life decision outcomes and in achieving similar levels of performance on the IGT as the HMC, in-spite of dysregulated dopamine-based brain-reward circuit and salience network fmri activation patterns. However, PPS report more significant negative outcomes of their decision-making in real-life, compared to HMC. The differential engagement of brain networks by PPS on the IGT appear to be moderated by antipsychotic, dopamine antagonist, medication lifetime/daily dose levels. These findings may also be mediated by extent of dysregulation in brain reward circuitry and salience network associated with psychosis severity in the target PPS group. This is also evident in case studies of unmedicated PPS. We conclude by suggesting that the brain may adapt to this dysregulation by co-opting the DAN network, which is implicated in the related function of problem-solving, towards complex decision-making. The extent of utilization of the DAN network in complex decision-making may be moderated by psychosis severity.
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49
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Luo Q, Pan B, Gu H, Simmonite M, Francis S, Liddle PF, Palaniyappan L. Effective connectivity of the right anterior insula in schizophrenia: The salience network and task-negative to task-positive transition. Neuroimage Clin 2020; 28:102377. [PMID: 32805679 PMCID: PMC7451428 DOI: 10.1016/j.nicl.2020.102377] [Citation(s) in RCA: 18] [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: 01/03/2020] [Revised: 07/20/2020] [Accepted: 08/05/2020] [Indexed: 12/30/2022]
Abstract
Triple network dysfunction theory of schizophrenia postulates that the interaction between the default-mode and the fronto-parietal executive network is disrupted by aberrant salience signals from the right anterior insula (rAI). To date, it is not clear how the proposed resting-state disruption translates to task-processing inefficiency in subjects with schizophrenia. Using a contiguous resting and 2-back task performance fMRI paradigm, we quantified the change in effective connectivity that accompanies rest-to-task state transition in 29 clinically stable patients with schizophrenia and 31 matched healthy controls. We found an aberrant task-evoked increase in the influence of the rAI to both executive (Cohen's d = 1.35, p = 2.8 × 10-6) and default-mode (Cohen's d = 1.22, p = 1.5 × 10-5) network regions occur in patients when compared to controls. In addition, the effective connectivity from middle occipital gyrus (dorsal visual cortex) to insula is also increased in patients as compared with healthy controls. Aberrant insula to executive network influence is pronounced in patients with more severe negative symptom burden. These findings suggest that control signals from rAI are abnormally elevated and directed towards both task-positive and task-negative brain regions, when task-related demands arise in schizophrenia. This aberrant, undiscriminating surge in salience signalling may disrupt contextually appropriate allocation of resources in the neuronal workspace in patients with schizophrenia.
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Affiliation(s)
- Qiang Luo
- Institute of Science and Technology for Brain-Inspired Intelligence, MOE-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Fudan University, Shanghai 200433, China
| | - Baobao Pan
- School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, China
| | - Huaguang Gu
- School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, China
| | - Molly Simmonite
- Translational Neuroimaging for Mental Health, Division of Psychiatry and Applied Psychology, University of Nottingham, Nottingham, UK
| | - Susan Francis
- Sir Peter Mansfield Imaging Centre (SPMIC), School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Peter F Liddle
- Translational Neuroimaging for Mental Health, Division of Psychiatry and Applied Psychology, University of Nottingham, Nottingham, UK
| | - Lena Palaniyappan
- Robarts Research Institute & The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada; Department of Psychiatry, University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada.
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50
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Wang L, Li X, Zhu Y, Lin B, Bo Q, Li F, Wang C. Discriminative Analysis of Symptom Severity and Ultra-High Risk of Schizophrenia Using Intrinsic Functional Connectivity. Int J Neural Syst 2020; 30:2050047. [PMID: 32689843 DOI: 10.1142/s0129065720500471] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Past studies have consistently shown functional dysconnectivity of large-scale brain networks in schizophrenia. In this study, we aimed to further assess whether multivariate pattern analysis (MVPA) could yield a sensitive predictor of patient symptoms, as well as identify ultra-high risk (UHR) stage of schizophrenia from intrinsic functional connectivity of whole-brain networks. We first combined rank-based feature selection and support vector machine methods to distinguish between 43 schizophrenia patients and 52 healthy controls. The constructed classifier was then applied to examine functional connectivity profiles of 18 UHR individuals. The classifier indicated reliable relationship between MVPA measures and symptom severity, with higher classification accuracy in more severely affected schizophrenia patients. The UHR subjects had classification scores falling between those of healthy controls and patients, suggesting an intermediate level of functional brain abnormalities. Moreover, UHR individuals with schizophrenia-like connectivity profiles at baseline presented higher rate of conversion to full-blown illness in the follow-up visits. Spatial maps of discriminative brain regions implicated increases of functional connectivity in the default mode network, whereas decreases of functional connectivity in the cerebellum, thalamus and visual areas in schizophrenia. The findings may have potential utility in the early diagnosis and intervention of schizophrenia.
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Affiliation(s)
- Lubin Wang
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, P. R. China
| | - Xianbin Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, P. R. China
| | - Yuyang Zhu
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, P. R. China
| | - Bei Lin
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, P. R. China
| | - Qijing Bo
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, P. R. China
| | - Feng Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, P. R. China
| | - Chuanyue Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, P. R. China
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