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Moussa-Tooks AB, Beermann A, Manzanarez Felix K, Coleman M, Bouix S, Holt D, Lewandowski KE, Öngür D, Breier A, Shenton ME, Heckers S, Walther S, Brady RO, Ward HB. Isolation of Distinct Networks Driving Action and Cognition in Psychomotor Processes. Biol Psychiatry 2024; 96:390-400. [PMID: 38452884 DOI: 10.1016/j.biopsych.2024.02.1013] [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: 08/30/2023] [Revised: 02/02/2024] [Accepted: 02/23/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Psychomotor disturbances are observed across psychiatric disorders and often manifest as psychomotor slowing, agitation, disorganized behavior, or catatonia. Psychomotor function includes both cognitive and motor components, but the neural circuits driving these subprocesses and how they relate to symptoms have remained elusive for centuries. METHODS We analyzed data from the HCP-EP (Human Connectome Project for Early Psychosis), a multisite study of 125 participants with early psychosis and 58 healthy participants with resting-state functional magnetic resonance imaging and clinical characterization. Psychomotor function was assessed using the 9-hole pegboard task, a timed motor task that engages mechanical and psychomotor components of action, and tasks assessing processing speed and task switching. We used multivariate pattern analysis of whole-connectome data to identify brain correlates of psychomotor function. RESULTS We identified discrete brain circuits driving the cognitive and motor components of psychomotor function. In our combined sample of participants with psychosis (n = 89) and healthy control participants (n = 52), the strongest correlates of psychomotor function (pegboard performance) (p < .005) were between a midline cerebellar region and left frontal region and presupplementary motor area. Psychomotor function was correlated with both cerebellar-frontal connectivity (r = 0.33) and cerebellar-presupplementary motor area connectivity (r = 0.27). However, the cognitive component of psychomotor performance (task switching) was correlated only with cerebellar-frontal connectivity (r = 0.19), whereas the motor component (processing speed) was correlated only with cerebellar-presupplementary motor area connectivity (r = 0.15), suggesting distinct circuits driving unique subprocesses of psychomotor function. CONCLUSIONS We identified cerebellar-cortical circuits that drive distinct subprocesses of psychomotor function. Future studies should probe relationships between cerebellar connectivity and psychomotor performance using neuromodulation.
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Affiliation(s)
- Alexandra B Moussa-Tooks
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Department of Psychological and Brain Sciences and Program in Neuroscience, Indiana University Bloomington, Bloomington, Indiana
| | - Adam Beermann
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Michael Coleman
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Brigham & Women's Hospital, Boston, Massachusetts
| | - Sylvain Bouix
- Department of Software Engineering and Information Technology, École de technologie supérieure, Montréal, Québec, Canada
| | - Daphne Holt
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Kathryn E Lewandowski
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; McLean Hospital, Belmont, Massachusetts
| | - Dost Öngür
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; McLean Hospital, Belmont, Massachusetts
| | - Alan Breier
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana
| | - Martha E Shenton
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Brigham & Women's Hospital, Boston, Massachusetts; Department of Radiology, Harvard Medical School and Brigham & Women's Hospital, Boston, Massachusetts
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Roscoe O Brady
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; McLean Hospital, Belmont, Massachusetts
| | - Heather Burrell Ward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee.
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Lapenta OM, Rêgo GG, Boggio PS. Transcranial electrical stimulation for procedural learning and rehabilitation. Neurobiol Learn Mem 2024; 213:107958. [PMID: 38971460 DOI: 10.1016/j.nlm.2024.107958] [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: 01/16/2024] [Revised: 06/26/2024] [Accepted: 07/01/2024] [Indexed: 07/08/2024]
Abstract
Procedural learning is the acquisition of motor and non-motor skills through a gradual process that increases with practice. Impairments in procedural learning have been consistently demonstrated in neurodevelopmental, neurodegenerative, and neuropsychiatric disorders. Considering that noninvasive brain stimulation modulates brain activity and boosts neuroplastic mechanisms, we reviewed the effects of coupling transcranial direct current stimulation (tDCS) with training methods for motor and non-motor procedural learning to explore tDCS potential use as a tool for enhancing implicit learning in healthy and clinical populations. The review covers tDCS effects over i. motor procedural learning, from basic to complex activities; ii. non-motor procedural learning; iii. procedural rehabilitation in several clinical populations. We conclude that targeting the primary motor cortex and prefrontal areas seems the most promising for motor and non-motor procedural learning, respectively. For procedural rehabilitation, the use of tDCS is yet at an early stage but some effectiveness has been reported for implicit motor and memory learning. Still, systematic comparisons of stimulation parameters and target areas are recommended for maximising the effectiveness of tDCS and its robustness for procedural rehabilitation.
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Affiliation(s)
- Olivia Morgan Lapenta
- Psychological Neuroscience Laboratory, Psychology Research Center, School of Psychology, University of Minho - Rua da Universidade, 4710-057 Braga, Portugal.
| | - Gabriel Gaudencio Rêgo
- Social and Cognitive Neuroscience Laboratory, Mackenzie Presbyterian University - Rua Piauí, 181, 01241-001 São Paulo, Brazil; National Institute of Science and Technology on Social and Affective Neuroscience (INCT-SANI), São Paulo, Brazil
| | - Paulo Sérgio Boggio
- Social and Cognitive Neuroscience Laboratory, Mackenzie Presbyterian University - Rua Piauí, 181, 01241-001 São Paulo, Brazil; National Institute of Science and Technology on Social and Affective Neuroscience (INCT-SANI), São Paulo, Brazil
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3
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Ciricugno A, Oldrati V, Cattaneo Z, Leggio M, Urgesi C, Olivito G. Cerebellar Neurostimulation for Boosting Social and Affective Functions: Implications for the Rehabilitation of Hereditary Ataxia Patients. CEREBELLUM (LONDON, ENGLAND) 2024; 23:1651-1677. [PMID: 38270782 PMCID: PMC11269351 DOI: 10.1007/s12311-023-01652-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/15/2023] [Indexed: 01/26/2024]
Abstract
Beyond motor deficits, spinocerebellar ataxia (SCA) patients also suffer cognitive decline and show socio-affective difficulties, negatively impacting on their social functioning. The possibility to modulate cerebello-cerebral networks involved in social cognition through cerebellar neurostimulation has opened up potential therapeutic applications for ameliorating social and affective difficulties. The present review offers an overview of the research on cerebellar neurostimulation for the modulation of socio-affective functions in both healthy individuals and different clinical populations, published in the time period 2000-2022. A total of 25 records reporting either transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) studies were found. The investigated clinical populations comprised different pathological conditions, including but not limited to SCA syndromes. The reviewed evidence supports that cerebellar neurostimulation is effective in improving social abilities in healthy individuals and reducing social and affective symptoms in different neurological and psychiatric populations associated with cerebellar damage or with impairments in functions that involve the cerebellum. These findings encourage to further explore the rehabilitative effects of cerebellar neurostimulation on socio-affective deficits experienced by patients with cerebellar abnormalities, as SCA patients. Nevertheless, conclusions remain tentative at this stage due to the heterogeneity characterizing stimulation protocols, study methodologies and patients' samples.
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Affiliation(s)
- Andrea Ciricugno
- IRCCS Mondino Foundation, 27100, Pavia, Italy.
- Department of Brain and Behavioral Science, University of Pavia, 27100, Pavia, Italy.
| | - Viola Oldrati
- Scientific Institute, IRCCS Eugenio Medea, 23842, Bosisio Parini, Italy
| | - Zaira Cattaneo
- IRCCS Mondino Foundation, 27100, Pavia, Italy
- Department of Human and Social Sciences, University of Bergamo, 24129, Bergamo, Italy
| | - Maria Leggio
- Department of Psychology, Sapienza University of Rome, 00185, Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179, Rome, Italy
| | - Cosimo Urgesi
- Scientific Institute, IRCCS Eugenio Medea, 23842, Bosisio Parini, Italy
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, 33100, Udine, Italy
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, 00185, Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179, Rome, Italy
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4
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Du Y, Niu J, Xing Y, Li B, Calhoun VD. Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade. Schizophr Bull 2024:sbae110. [PMID: 38982882 DOI: 10.1093/schbul/sbae110] [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: 07/11/2024]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years. STUDY DESIGN The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade. STUDY RESULTS Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders. CONCLUSIONS We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.
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Affiliation(s)
- Yuhui Du
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Ju Niu
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Ying Xing
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Bang Li
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Vince D Calhoun
- The Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, 30303, GA, USA
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Pei H, Jiang S, Liu M, Ye G, Qin Y, Liu Y, Duan M, Yao D, Luo C. Simultaneous EEG-fMRI Investigation of Rhythm-Dependent Thalamo-Cortical Circuits Alteration in Schizophrenia. Int J Neural Syst 2024; 34:2450031. [PMID: 38623649 DOI: 10.1142/s012906572450031x] [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] [Indexed: 04/17/2024]
Abstract
Schizophrenia is accompanied by aberrant interactions of intrinsic brain networks. However, the modulatory effect of electroencephalography (EEG) rhythms on the functional connectivity (FC) in schizophrenia remains unclear. This study aims to provide new insight into network communication in schizophrenia by integrating FC and EEG rhythm information. After collecting simultaneous resting-state EEG-functional magnetic resonance imaging data, the effect of rhythm modulations on FC was explored using what we term "dynamic rhythm information." We also investigated the synergistic relationships among three networks under rhythm modulation conditions, where this relationship presents the coupling between two brain networks with other networks as the center by the rhythm modulation. This study found FC between the thalamus and cortical network regions was rhythm-specific. Further, the effects of the thalamus on the default mode network (DMN) and salience network (SN) were less similar under alpha rhythm modulation in schizophrenia patients than in controls ([Formula: see text]). However, the similarity between the effects of the central executive network (CEN) on the DMN and SN under gamma modulation was greater ([Formula: see text]), and the degree of coupling was negatively correlated with the duration of disease ([Formula: see text], [Formula: see text]). Moreover, schizophrenia patients exhibited less coupling with the thalamus as the center and greater coupling with the CEN as the center. These results indicate that modulations in dynamic rhythms might contribute to the disordered functional interactions seen in schizophrenia.
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Affiliation(s)
- Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mei Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Guofeng Ye
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yun Qin
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yayun Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mingjun Duan
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation Chinese, Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation Chinese, Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
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6
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Faris P, Pischedda D, Palesi F, D’Angelo E. New clues for the role of cerebellum in schizophrenia and the associated cognitive impairment. Front Cell Neurosci 2024; 18:1386583. [PMID: 38799988 PMCID: PMC11116653 DOI: 10.3389/fncel.2024.1386583] [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: 02/15/2024] [Accepted: 04/26/2024] [Indexed: 05/29/2024] Open
Abstract
Schizophrenia (SZ) is a complex neuropsychiatric disorder associated with severe cognitive dysfunction. Although research has mainly focused on forebrain abnormalities, emerging results support the involvement of the cerebellum in SZ physiopathology, particularly in Cognitive Impairment Associated with SZ (CIAS). Besides its role in motor learning and control, the cerebellum is implicated in cognition and emotion. Recent research suggests that structural and functional changes in the cerebellum are linked to deficits in various cognitive domains including attention, working memory, and decision-making. Moreover, cerebellar dysfunction is related to altered cerebellar circuit activities and connectivity with brain regions associated with cognitive processing. This review delves into the role of the cerebellum in CIAS. We initially consider the major forebrain alterations in CIAS, addressing impairments in neurotransmitter systems, synaptic plasticity, and connectivity. We then focus on recent findings showing that several mechanisms are also altered in the cerebellum and that cerebellar communication with the forebrain is impaired. This evidence implicates the cerebellum as a key component of circuits underpinning CIAS physiopathology. Further studies addressing cerebellar involvement in SZ and CIAS are warranted and might open new perspectives toward understanding the physiopathology and effective treatment of these disorders.
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Affiliation(s)
- Pawan Faris
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Doris Pischedda
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Egidio D’Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Digital Neuroscience Center, IRCCS Mondino Foundation, Pavia, Italy
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7
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Sefik E, Guest RM, Aberizk K, Espana R, Goines K, Novacek DM, Murphy MM, Goldman-Yassen AE, Cubells JF, Ousley O, Li L, Shultz S, Walker EF, Mulle JG. Psychosis spectrum symptoms among individuals with schizophrenia-associated copy number variants and evidence of cerebellar correlates of symptom severity. Psychiatry Res 2024; 335:115867. [PMID: 38537595 DOI: 10.1016/j.psychres.2024.115867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 03/14/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024]
Abstract
The 3q29 deletion (3q29Del) is a copy number variant (CNV) with one of the highest effect sizes for psychosis-risk (>40-fold). Systematic research offers avenues for elucidating mechanism; however, compared to CNVs like 22q11.2Del, 3q29Del remains understudied. Emerging findings indicate that posterior fossa abnormalities are common among carriers, but their clinical relevance is unclear. We report the first in-depth evaluation of psychotic symptoms in participants with 3q29Del (N=23), using the Structured Interview for Psychosis-Risk Syndromes, and compare this profile to 22q11.2Del (N=31) and healthy controls (N=279). We also explore correlations between psychotic symptoms and posterior fossa abnormalities. Cumulatively, 48% of the 3q29Del sample exhibited a psychotic disorder or attenuated positive symptoms, with a subset meeting criteria for clinical high-risk. 3q29Del had more severe ratings than controls on all domains and only exhibited less severe ratings than 22q11.2Del in negative symptoms; ratings demonstrated select sex differences but no domain-wise correlations with IQ. An inverse relationship was identified between positive symptoms and cerebellar cortex volume in 3q29Del, documenting the first clinically-relevant neuroanatomical connection in this syndrome. Our findings characterize the profile of psychotic symptoms in the largest 3q29Del sample reported to date, contrast with another high-impact CNV, and highlight cerebellar involvement in psychosis-risk.
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Affiliation(s)
- Esra Sefik
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA; Department of Psychology, Emory University, Atlanta, GA, USA
| | - Ryan M Guest
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Katrina Aberizk
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Roberto Espana
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Katrina Goines
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Derek M Novacek
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA; Desert Pacific Mental Illness, Research, Education, and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Melissa M Murphy
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Adam E Goldman-Yassen
- Department of Radiology, Children's Healthcare of Atlanta, Atlanta, GA, USA; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Joseph F Cubells
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA; Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Opal Ousley
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Longchuan Li
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Sarah Shultz
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Jennifer G Mulle
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, USA; Center for Advanced Biotechnology and Medicine, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, USA.
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8
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Zhang C, Liang J, Yan H, Li X, Li X, Jing H, Liang W, Li R, Ou Y, Wu W, Guo H, Deng W, Xie G, Guo W. Fractional amplitude of low-frequency fluctuations in sensory-motor networks and limbic system as a potential predictor of treatment response in patients with schizophrenia. Schizophr Res 2024; 267:519-527. [PMID: 38704344 DOI: 10.1016/j.schres.2024.04.020] [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: 08/14/2023] [Revised: 03/21/2024] [Accepted: 04/26/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Previous investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. METHODS In this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. RESULTS In this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. CONCLUSION Our findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.
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Affiliation(s)
- Chunguo Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xiaoling Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Xuesong Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Huan Jing
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Wenting Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Rongwei Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Weibin Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Huagui Guo
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Wen Deng
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China.
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
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9
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Chen J, Iraji A, Fu Z, Andrés-Camazón P, Thapaliya B, Liu J, Calhoun VD. Dynamic fusion of genomics and functional network connectivity in UK biobank reveals static and time-varying SNP manifolds. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.09.24301013. [PMID: 38260328 PMCID: PMC10802663 DOI: 10.1101/2024.01.09.24301013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Many psychiatric and neurological disorders show significant heritability, indicating strong genetic influence. In parallel, dynamic functional network connectivity (dFNC) measures functional temporal coupling between brain networks in a time-varying manner and has proven to identify disease-related changes in the brain. However, it remains largely unclear how genetic risk contributes to brain dysconnectivity that further manifests into clinical symptoms. The current work aimed to address this gap by proposing a novel joint ICA (jICA)-based "dynamic fusion" framework to identify dynamically tuned SNP manifolds by linking static SNPs to dynamic functional information of the brain. The sliding window approach was utilized to estimate four dFNC states and compute subject-level state-specific dFNC features. Each state of dFNC features were then combined with 12946 SZ risk SNPs for jICA decomposition, resulting in four parallel fusions in 32861 European ancestry individuals within the UK Biobank cohort. The identified joint SNP-dFNC components were further validated for SZ relevance in an aggregated SZ cohort, and compared for across-state similarity to indicate level of dynamism. The results supported that dynamic fusion yielded "static" and "dynamic" components (i.e., high and low across-state similarity, respectively) for SNP and dFNC modalities. As expected, the SNP components presented a mixture of static and dynamic manifolds, with the latter largely driven by fusion with dFNC. We also showed that some of the dynamic SNP manifolds uniquely elicited by fusion with state-specific dFNC features complemented each other in terms of biological interpretation. This dynamic fusion framework thus allows expanding the SNP modality to manifolds in the time dimension, which provides a unique lens to elicit unique SNP correlates of dFNC otherwise unseen, promising additional insights on how genetic risk links to disease-related dysconnectivity.
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Affiliation(s)
- Jiayu Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Armin Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA
| | - Pablo Andrés-Camazón
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - Bishal Thapaliya
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
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10
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Wang C, Wang C, Ren Y, Zhang R, Ai L, Wu Y, Ran X, Wang M, Hu H, Shen J, Zhao Z, Yang Y, Ren W, Yu Y. Multi feature fusion network for schizophrenia classification and abnormal brain network recognition. Brain Res Bull 2024; 206:110848. [PMID: 38104673 DOI: 10.1016/j.brainresbull.2023.110848] [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: 10/19/2023] [Revised: 12/06/2023] [Accepted: 12/13/2023] [Indexed: 12/19/2023]
Abstract
Schizophrenia classification and abnormal brain network recognition have an important research significance. Researchers have proposed many classification methods based on machine learning and deep learning. However, fewer studies utilized the advantages of complementary information from multi feature to learn the best representation of schizophrenia. In this study, we proposed a multi-feature fusion network (MFFN) using functional network connectivity (FNC) and time courses (TC) to distinguish schizophrenia patients from healthy controls. DNN backbone was adopted to learn the feature map of functional network connectivity, C-RNNAM backbone was designed to learn the feature map of time courses, and Deep SHAP was applied to obtain the most discriminative brain networks. We proved the effectiveness of this proposed model using the combining two public datasets and evaluated this model quantitatively using the evaluation indexes. The results showed that the functional network connectivity generated by independent component analysis has advantage in schizophrenia classification by comparing static and dynamic functional connections. This method obtained the best classification accuracy (ACC=87.30%, SPE=89.28%, SEN=85.71%, F1 =88.23%, and AUC=0.9081), and it demonstrated the superiority of this proposed model by comparing state-of-the-art methods. Ablation experiment also demonstrated that multi feature fusion and attention module can improve classification accuracy. The most discriminative brain networks showed that default mode network and visual network of schizophrenia patients have aberrant connections in brain networks. In conclusion, this method can identify schizophrenia effectively and visualize the abnormal brain network, and it has important clinical application value.
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Affiliation(s)
- Chang Wang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China; Xinxiang Engineering Technology Research Center of Intelligent Medical Imaging Diagnosis, Xinxiang, China
| | - Chen Wang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China; Xinxiang Engineering Technology Research Center of Intelligent Medical Imaging Diagnosis, Xinxiang, China
| | - Yaning Ren
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China; Xinxiang Engineering Technology Research Center of Intelligent Medical Imaging Diagnosis, Xinxiang, China
| | - Rui Zhang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China; Xinxiang Engineering Technology Research Center of Intelligent Medical Imaging Diagnosis, Xinxiang, China
| | - Lunpu Ai
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Yang Wu
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China; Xinxiang Engineering Technology Research Center of Intelligent Medical Imaging Diagnosis, Xinxiang, China
| | - Xiangying Ran
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Mengke Wang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Heshun Hu
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Jiefen Shen
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China; Xinxiang Engineering Technology Research Center of Intelligent Medical Imaging Diagnosis, Xinxiang, China
| | - Zongya Zhao
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Yongfeng Yang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China
| | - Wenjie Ren
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Yi Yu
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Laboratory of Biological Psychiatry, Xinxiang, China; School of Medical Engineering, Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China.
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11
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Chen J, Jiang S, Lu B, Liao J, Yang Z, Li H, Pei H, Li J, Iturria-Medina Y, Yao D, Luo C. The role of the primary sensorimotor system in generalized epilepsy: Evidence from the cerebello-cerebral functional integration. Hum Brain Mapp 2024; 45:e26551. [PMID: 38063289 PMCID: PMC10789200 DOI: 10.1002/hbm.26551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 11/12/2023] [Accepted: 11/16/2023] [Indexed: 01/16/2024] Open
Abstract
The interaction between cerebellum and cerebrum participates widely in function from motor processing to high-level cognitive and affective processing. Because of the motor symptom, idiopathic generalized epilepsy (IGE) patients with generalized tonic-clonic seizure have been recognized to associate with motor abnormalities, but the functional interaction in the cerebello-cerebral circuit is still poorly understood. Resting-state functional magnetic resonance imaging data were collected for 101 IGE patients and 106 healthy controls. The voxel-based functional connectivity (FC) between cerebral cortex and the cerebellum was contacted. The functional gradient and independent components analysis were applied to evaluate cerebello-cerebral functional integration on the voxel-based FC. Cerebellar motor components were further linked to cerebellar gradient. Results revealed cerebellar motor functional modules were closely related to cerebral motor components. The altered mapping of cerebral motor components to cerebellum was observed in motor module in patients with IGE. In addition, patients also showed compression in cerebello-cerebral functional gradient between motor and cognition modules. Interestingly, the contribution of the motor components to the gradient was unbalanced between bilateral primary sensorimotor components in patients: the increase was observed in cerebellar cognitive module for the dominant hemisphere primary sensorimotor, but the decrease was found in the cerebellar cognitive module for the nondominant hemisphere primary sensorimotor. The present findings suggest that the cerebral primary motor system affects the hierarchical architecture of cerebellum, and substantially contributes to the functional integration evidence to understand the motor functional abnormality in IGE patients.
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Affiliation(s)
- Junxia Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Bao Lu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Jiangyan Liao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Zhihuan Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yasser Iturria-Medina
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, P. R. China
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12
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Cattarinussi G, Di Giorgio A, Moretti F, Bondi E, Sambataro F. Dynamic functional connectivity in schizophrenia and bipolar disorder: A review of the evidence and associations with psychopathological features. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110827. [PMID: 37473954 DOI: 10.1016/j.pnpbp.2023.110827] [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: 01/10/2023] [Revised: 06/05/2023] [Accepted: 07/10/2023] [Indexed: 07/22/2023]
Abstract
Alterations of functional network connectivity have been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). Recent studies also suggest that the temporal dynamics of functional connectivity (dFC) can be altered in these disorders. Here, we summarized the existing literature on dFC in SCZ and BD, and their association with psychopathological and cognitive features. We systematically searched PubMed, Web of Science, and Scopus for studies investigating dFC in SCZ and BD and identified 77 studies. Our findings support a general model of dysconnectivity of dFC in SCZ, whereas a heterogeneous picture arose in BD. Although dFC alterations are more severe and widespread in SCZ compared to BD, dysfunctions of a triple network system underlying goal-directed behavior and sensory-motor networks were present in both disorders. Furthermore, in SCZ, positive and negative symptoms were associated with abnormal dFC. Implications for understanding the pathophysiology of disorders, the role of neurotransmitters, and treatments on dFC are discussed. The lack of standards for dFC metrics, replication studies, and the use of small samples represent major limitations for the field.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy
| | - Annabella Di Giorgio
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Federica Moretti
- Department of Medicine and Surgery, University of Milan Bicocca, Milan, Italy
| | - Emi Bondi
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy.
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13
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Lan H, Suo X, Zuo C, Ni W, Wang S, Kemp GJ, Gong Q. Shared and distinct abnormalities of brain magnetization transfer ratio in schizophrenia and major depressive disorder: a comparative voxel-based meta-analysis. Chin Med J (Engl) 2023; 136:2824-2833. [PMID: 37697951 PMCID: PMC10686600 DOI: 10.1097/cm9.0000000000002538] [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: 02/19/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Patients with schizophrenia (SCZ) and major depressive disorder (MDD) share significant clinical overlap, although it remains unknown to what extent this overlap reflects shared neural profiles. To identify the shared and specific abnormalities in SCZ and MDD, we performed a whole-brain voxel-based meta-analysis using magnetization transfer imaging, a technique that characterizes the macromolecular structural integrity of brain tissue in terms of the magnetization transfer ratio (MTR). METHODS A systematic search based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted in PubMed, EMBASE, International Scientific Index (ISI) Web of Science, and MEDLINE for relevant studies up to March 2022. Two researchers independently screened the articles. Rigorous scrutiny and data extraction were performed for the studies that met the inclusion criteria. Voxel-wise meta-analyses were conducted using anisotropic effect size-signed differential mapping with a unified template. Meta-regression was used to explore the potential effects of demographic and clinical characteristics. RESULTS A total of 15 studies with 17 datasets describing 365 SCZ patients, 224 MDD patients, and 550 healthy controls (HCs) were identified. The conjunction analysis showed that both disorders shared higher MTR than HC in the left cerebellum ( P =0.0006) and left fusiform gyrus ( P =0.0004). Additionally, SCZ patients showed disorder-specific lower MTR in the anterior cingulate/paracingulate gyrus, right superior temporal gyrus, and right superior frontal gyrus, and higher MTR in the left thalamus, precuneus/cuneus, posterior cingulate gyrus, and paracentral lobule; and MDD patients showed higher MTR in the left middle occipital region. Meta-regression showed no statistical significance in either group. CONCLUSIONS The results revealed a structural neural basis shared between SCZ and MDD patients, emphasizing the importance of shared neural substrates across psychopathology. Meanwhile, distinct disease-specific characteristics could have implications for future differential diagnosis and targeted treatment.
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Affiliation(s)
- Huan Lan
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Xueling Suo
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian 361000, China
| | - Chao Zuo
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
| | - Weishi Ni
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Song Wang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Graham J. Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L693BX, United Kingdom
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian 361000, China
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14
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Luo L, Li Q, Wang Y, He N, Wang Y, You W, Zhang Q, Long F, Chen L, Zhao Y, Yao L, Sweeney JA, Gong Q, Li F. Shared and Disorder-Specific Alterations of Brain Temporal Dynamics in Obsessive-Compulsive Disorder and Schizophrenia. Schizophr Bull 2023; 49:1387-1398. [PMID: 37030006 PMCID: PMC10483459 DOI: 10.1093/schbul/sbad042] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/10/2023]
Abstract
BACKGROUND Obsessive-compulsive disorder (OCD) and schizophrenia have distinct but also overlapping symptoms. Few studies have examined the shared and disorder-specific disturbances in dynamic brain function in the 2 disorders. STUDY DESIGN Resting-state functional magnetic resonance imaging data of 31 patients with OCD and 49 patients with schizophrenia, all untreated, and 45 healthy controls (HCs) were analyzed using spatial group independent component (IC) analysis. Time-varying degree centrality patterns across the whole brain were clustered into 3 reoccurring states, and state transition metrics were obtained. We further explored regional temporal variability of degree centrality for each IC across all time windows. STUDY RESULTS Patients with OCD and patients with schizophrenia both showed decreased occurrence of a state having the highest centrality in the sensorimotor and auditory networks. Additionally, patients with OCD and patients with schizophrenia both exhibited reduced dynamics of degree centrality in the superior frontal gyrus than controls, while dynamic degree centrality of the cerebellum was lower in patients with schizophrenia than with OCD and HCs. Altered dynamics of degree centrality nominally correlated with symptom severity in both patient groups. CONCLUSIONS Our study provides evidence of transdiagnostic and clinically relevant functional brain abnormalities across OCD and schizophrenia in neocortex, as well as functional dynamic alterations in the cerebellum specific to schizophrenia. These findings add to the recognition of overlap in neocortical alterations in the 2 disorders, and indicate that cerebellar alterations in schizophrenia may be specifically important in schizophrenia pathophysiology via impact on cerebellar thalamocortical circuitry.
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Affiliation(s)
- Lekai Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
- Department of Radiology, West China Second Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Qian Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Yaxuan Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Ning He
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Yuxia Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Wanfang You
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Qian Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Fenghua Long
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Lizhou Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Youjin Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Li Yao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Fei Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
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15
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Ng B, Tasaki S, Greathouse KM, Walker CK, Zhang A, Covitz S, Cieslak M, Adamson AB, Andrade JP, Poovey EH, Curtis KA, Muhammad HM, Seidlitz J, Satterthwaite T, Bennett DA, Seyfried NT, Vogel J, Gaiteri C, Herskowitz JH. A Molecular Basis of Human Brain Connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.20.549895. [PMID: 37546752 PMCID: PMC10401931 DOI: 10.1101/2023.07.20.549895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Neuroimaging is commonly used to infer human brain connectivity, but those measurements are far-removed from the molecular underpinnings at synapses. To uncover the molecular basis of human brain connectivity, we analyzed a unique cohort of 98 individuals who provided neuroimaging and genetic data contemporaneous with dendritic spine morphometric, proteomic, and gene expression data from the superior frontal and inferior temporal gyri. Through cellular contextualization of the molecular data with dendritic spine morphology, we identified hundreds of proteins related to synapses, energy metabolism, and RNA processing that explain between-individual differences in functional connectivity and structural covariation. By integrating data at the genetic, molecular, subcellular, and tissue levels, we bridged the divergent fields of molecular biology and neuroimaging to identify a molecular basis of brain connectivity. One-Sentence Summary Dendritic spine morphometry and synaptic proteins unite the divergent fields of molecular biology and neuroimaging.
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16
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Li Y, Zhao M, Cao Y, Gao Y, Wang Y, Yun B, Luo L, Liu W, Zheng C. Static and dynamic resting-state brain activity patterns of table tennis players in 7-Tesla MRI. Front Neurosci 2023; 17:1202932. [PMID: 37521699 PMCID: PMC10375049 DOI: 10.3389/fnins.2023.1202932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 06/27/2023] [Indexed: 08/01/2023] Open
Abstract
Table tennis involves quick and accurate motor responses during training and competition. Multiple studies have reported considerably faster visuomotor responses and expertise-related intrinsic brain activity changes among table tennis players compared with matched controls. However, the underlying neural mechanisms remain unclear. Herein, we performed static and dynamic resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 20 table tennis players and 21 control subjects using 7T ultra-high field imaging. We calculated the static and dynamic amplitude of low-frequency fluctuations (ALFF) of the two groups. The results revealed that table tennis players exhibited decreased static ALFF in the left inferior temporal gyrus (lITG) compared with the control group. Voxel-wised static functional connectivity (sFC) and dynamic functional connectivity (dFC) analyses using lITG as the seed region afforded complementary and overlapping results. The table tennis players exhibited decreased sFC in the right middle temporal gyrus and left inferior parietal gyrus. Conversely, they displayed increased dFC from the lITG to prefrontal cortex, particularly the left middle frontal gyrus, left superior frontal gyrus-medial, and left superior frontal gyrus-dorsolateral. These findings suggest that table tennis players demonstrate altered visuomotor transformation and executive function pathways. Both pathways involve the lITG, which is a vital node in the ventral visual stream. These static and dynamic analyses provide complementary and overlapping results, which may help us better understand the neural mechanisms underlying the changes in intrinsic brain activity and network organization induced by long-term table tennis skill training.
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Affiliation(s)
- Yuyang Li
- Key Laboratory of Medical Neurobiology of Zhejiang Province, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Mengqi Zhao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Yuting Cao
- Key Laboratory of Medical Neurobiology of Zhejiang Province, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yanyan Gao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Yadan Wang
- College of Information and Electronic Technology, Jiamusi University, Jiamusi, China
| | - Bing Yun
- Department of Public Physical and Art Education, Zhejiang University, Hangzhou, China
| | - Le Luo
- Hangzhou Wuyunshan Hospital, Hangzhou, China
| | - Wenming Liu
- Department of Sport Science, College of Education, Zhejiang University, Hangzhou, China
| | - Chanying Zheng
- Key Laboratory of Medical Neurobiology of Zhejiang Province, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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17
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Duda M, Faghiri A, Belger A, Bustillo JR, Ford JM, Mathalon DH, Mueller BA, Pearlson GD, Potkin SG, Preda A, Sui J, Van Erp TGM, Calhoun VD. Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.05.547840. [PMID: 37461731 PMCID: PMC10350020 DOI: 10.1101/2023.07.05.547840] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Schizophrenia (SZ) is a complex psychiatric disorder that is currently defined by symptomatic and behavioral, rather than biological, criteria. Neuroimaging is an appealing avenue for SZ biomarker development, as several neuroimaging-based studies comparing individuals with SZ to healthy controls (HC) have shown measurable group differences in brain structure, as well as functional brain alterations in both static and dynamic functional network connectivity (sFNC and dFNC, respectively). The recently proposed filter-banked connectivity (FBC) method extends the standard dFNC sliding-window approach to estimate FNC within an arbitrary number of distinct frequency bands. The initial implementation used a set of filters spanning the full connectivity spectral range, providing a unified approach to examine both sFNC and dFNC in a single analysis. Initial FBC results found that individuals with SZ spend more time in a less structured, more disconnected low-frequency (i.e., static) FNC state than HC, as well as preferential SZ occupancy in high-frequency connectivity states, suggesting a frequency-specific component underpinning the functional dysconnectivity observed in SZ. Building on these findings, we sought to link such frequency-specific patterns of FNC to covarying data-driven structural brain networks in the context of SZ. Specifically, we employ a multi-set canonical correlation analysis + joint independent components analysis (mCCA + jICA) data fusion framework to study the connection between grey matter volume (GMV) maps and FBC states across the full connectivity frequency spectrum. Our multimodal analysis identified two joint sources that captured co-varying patterns of frequency-specific functional connectivity and alterations in GMV with significant group differences in loading parameters between the SZ group and HC. The first joint source linked frequency-modulated connections between the subcortical and sensorimotor networks and GMV alterations in the frontal and temporal lobes, while the second joint source identified a relationship between low-frequency cerebellar-sensorimotor connectivity and structural changes in both the cerebellum and motor cortex. Together, these results show a strong connection between cortico-subcortical functional connectivity at both high and low frequencies and alterations in cortical GMV that may be relevant to the pathogenesis and pathophysiology of SZ.
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Affiliation(s)
- Marlena Duda
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Ashkan Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Juan R Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Judith M Ford
- Mental Health Service, San Francisco Veterans Affairs Healthcare System, San Francisco, California, USA
- Department of Psychiatry and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
| | - Daniel H Mathalon
- Mental Health Service, San Francisco Veterans Affairs Healthcare System, San Francisco, California, USA
- Department of Psychiatry and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
| | - Bryon A Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Steven G Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Theo G M Van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
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18
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Zhao J, Huang CC, Zhang Y, Liu Y, Tsai SJ, Lin CP, Lo CYZ. Structure-function coupling in white matter uncovers the abnormal brain connectivity in Schizophrenia. Transl Psychiatry 2023; 13:214. [PMID: 37339983 DOI: 10.1038/s41398-023-02520-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 06/09/2023] [Accepted: 06/12/2023] [Indexed: 06/22/2023] Open
Abstract
Schizophrenia is characterized by dysconnectivity syndrome. Evidence of widespread impairment of structural and functional integration has been demonstrated in schizophrenia. Although white matter (WM) microstructural abnormalities have been commonly reported in schizophrenia, the dysfunction of WM as well as the relationship between structure and function in WM remains uncertain. In this study, we proposed a novel structure-function coupling measurement to reflect neuronal information transfer, which combined spatial-temporal correlations of functional signals with diffusion tensor orientations in the WM circuit from functional and diffusion magnetic resonance images (MRI). By analyzing MRI data from 75 individuals with schizophrenia (SZ) and 89 healthy volunteers (HV), the associations between structure and function in WM regions in schizophrenia were examined. Randomized validation of the measurement was performed in the HV group to confirm the capacity of the neural signal transferring along the WM tracts, referring to quantifying the association between structure and function. Compared to HV, SZ showed a widespread decrease in the structure-function coupling within WM regions, involving the corticospinal tract and the superior longitudinal fasciculus. Additionally, the structure-function coupling in the WM tracts was found to be significantly correlated with psychotic symptoms and illness duration in schizophrenia, suggesting that abnormal signal transfer of neuronal fiber pathways could be a potential mechanism of the neuropathology of schizophrenia. This work supports the dysconnectivity hypothesis of schizophrenia from the aspect of circuit function, and highlights the critical role of WM networks in the pathophysiology of schizophrenia.
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Affiliation(s)
- Jiajia Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China.
- Shanghai Changning Mental Health Center, Shanghai, China.
| | - Yajuan Zhang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Yuchen Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
| | - Chun-Yi Zac Lo
- Department of Biomedical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan.
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19
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Ceylan MF, Tural Hesapcioglu S, Kanoğlu Yüksekkaya S, Erçin G, Yavas CP, Neşelіoğlu S, Erel O. Changes in neurofilament light chain protein (NEFL) in children and adolescents with Schizophrenia and Bipolar Disorder: Early period neurodegeneration. J Psychiatr Res 2023; 161:342-347. [PMID: 37003244 DOI: 10.1016/j.jpsychires.2023.03.027] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/08/2022] [Accepted: 03/16/2023] [Indexed: 04/03/2023]
Abstract
AIM Neurofilament light chain protein (NEFL), is defined as a structural protein which exists particularly in axones of neurons and is released to the cerum in consequence of neuroaxonal damage. The aim of this study is to investigate the peripheral cerumNEFLlevels of children and adolescents with early onset schizophrenia and bipolar disorder. METHOD In this study, we evaluated serum levels of NEFL in children and adolescents (13-17 years) with schizophrenia, bipolar disorder and healthy control group. The study is conducted with 35 schizophrenia, 38 bipolar disorder manic episode patients and 40 healthy controls. RESULTS The median age of the patient and control groups was 16 (IQR- Interquartile Range: 2). There was no statistical difference in median age (p = 0.52) and gender distribution(p = 0.53) between groups. NEFL levels of the patients with schizophrenia were significantly higher than the controls. NEFL levels of the patients with bipolar disorder were significantly higher than the controls. Serum levels of NEFL of the schizophrenia were higher than the bipolar disorder; however, the difference was not statistically significant. CONCLUSION In conclusion, serum NEFL level, as a confidential marker of neural damage, is increased in the children and adolescents with bipolar disorder and schizophrenia. This result may indicatea degenerative period in neurons of children and adolescents with schizophrenia or bipolar disorder and may play a role in the pathophisiology of these disorders. This result shows that there is neuronal damage in both diseases, but neuronal damage may be more in schizophrenia.
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Affiliation(s)
- Mehmet Fatih Ceylan
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey.
| | - Selma Tural Hesapcioglu
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Seda Kanoğlu Yüksekkaya
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Görkem Erçin
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Cansu Pınar Yavas
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Salim Neşelіoğlu
- Ankara Yildirim Beyazit University, Faculty of Medicine, Clinical Biochemistry Department, Ankara, Turkey
| | - Ozcan Erel
- Ankara Yildirim Beyazit University, Faculty of Medicine, Clinical Biochemistry Department, Ankara, Turkey
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20
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Zhou J, Guo X, Liu X, Luo Y, Chang X, He H, Duan M, Li S, Li Q, Tan Y, Yao G, Yao D, Luo C. Intrinsic Therapeutic Link between Recuperative Cerebellar Con-Nectivity and Psychiatry Symptom in Schizophrenia Patients with Comorbidity of Metabolic Syndrome. LIFE (BASEL, SWITZERLAND) 2023; 13:life13010144. [PMID: 36676092 PMCID: PMC9863013 DOI: 10.3390/life13010144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 12/23/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023]
Abstract
Components of metabolic syndrome might be predictors of the therapeutic outcome of psychiatric symptom in schizophrenia, whereas clinical results are inconsistent and an intrinsic therapeutic link between weaker psychiatric symptoms and emergent metabolic syndrome remains unclear. This study aims to reveal the relationship and illustrate potential mechanism by exploring the alteration of cerebellar functional connectivity (FC) in schizophrenia patients with comorbidity metabolic syndrome. Thirty-six schizophrenia patients with comorbidity of metabolic syndrome (SCZ-MetS), 45 schizophrenia patients without metabolic syndrome (SCZ-nMetS) and 39 healthy controls (HC) were recruited in this study. We constructed FC map of cerebello-cortical circuit and used moderation effect analysis to reveal complicated relationship among FC, psychiatric symptom and metabolic disturbance. Components of metabolic syndrome were significantly correlated with positive symptom score and negative symptom score. Importantly, the dysconnectivity between cognitive module of cerebellum and left middle frontal gyrus in SCZ-nMetS was recuperative increased in SCZ-MetS, and was significantly correlated with general symptom score. Finally, we observed significant moderation effect of body mass index on this correlation. The present findings further supported the potential relationship between emergence of metabolic syndrome and weaker psychiatric symptom, and provided neuroimaging evidence. The mechanism of intrinsic therapeutic link involved functional change of cerebello-cortical circuit.
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Affiliation(s)
- Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xiao Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xiaoli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Shicai Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Qifu Li
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
| | - Ying Tan
- The Key Laboratory for Computer Systems of State Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610093, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
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21
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Schmitt JE, DeBevits JJ, Roalf DR, Ruparel K, Gallagher RS, Gur RC, Alexander-Bloch A, Eom TY, Alam S, Steinberg J, Akers W, Khairy K, Crowley TB, Emanuel B, Zakharenko SS, McDonald-McGinn DM, Gur RE. A Comprehensive Analysis of Cerebellar Volumes in the 22q11.2 Deletion Syndrome. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:79-90. [PMID: 34848384 PMCID: PMC9162086 DOI: 10.1016/j.bpsc.2021.11.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 10/12/2021] [Accepted: 11/08/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND The presence of a 22q11.2 microdeletion (22q11.2 deletion syndrome [22q11DS]) ranks among the greatest known genetic risk factors for the development of psychotic disorders. There is emerging evidence that the cerebellum is important in the pathophysiology of psychosis. However, there is currently limited information on cerebellar neuroanatomy in 22q11DS specifically. METHODS High-resolution 3T magnetic resonance imaging was acquired in 79 individuals with 22q11DS and 70 typically developing control subjects (N = 149). Lobar and lobule-level cerebellar volumes were estimated using validated automated segmentation algorithms, and subsequently group differences were compared. Hierarchical clustering, principal component analysis, and graph theoretical models were used to explore intercerebellar relationships. Cerebrocerebellar structural connectivity with cortical thickness was examined via linear regression models. RESULTS Individuals with 22q11DS had, on average, 17.3% smaller total cerebellar volumes relative to typically developing subjects (p < .0001). The lobules of the superior posterior cerebellum (e.g., VII and VIII) were particularly affected in 22q11DS. However, all cerebellar lobules were significantly smaller, even after adjusting for total brain volumes (all cerebellar lobules p < .0002). The superior posterior lobule was disproportionately associated with cortical thickness in the frontal lobes and cingulate cortex, brain regions known be affected in 22q11DS. Exploratory analyses suggested that the superior posterior lobule, particularly Crus I, may be associated with psychotic symptoms in 22q11DS. CONCLUSIONS The cerebellum is a critical but understudied component of the 22q11DS neuroendophenotype.
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Affiliation(s)
- J Eric Schmitt
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania; Division of Neuroradiology, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
| | - John J DeBevits
- Division of Neuroradiology, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
| | - David R Roalf
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Kosha Ruparel
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - R Sean Gallagher
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Ruben C Gur
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Aaron Alexander-Bloch
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Tae-Yeon Eom
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Shahinur Alam
- Center for Bioimage Informatics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Jeffrey Steinberg
- Center for Bioimage Informatics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Walter Akers
- Center for Bioimage Informatics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Khaled Khairy
- Center for In Vivo Imaging and Therapeutics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - T Blaine Crowley
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Beverly Emanuel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Stanislav S Zakharenko
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Donna M McDonald-McGinn
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Raquel E Gur
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania; Division of Neuroradiology, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
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22
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Frosch IR, Damme KSF, Bernard JA, Mittal VA. Cerebellar correlates of social dysfunction among individuals at clinical high risk for psychosis. Front Psychiatry 2022; 13:1027470. [PMID: 36532176 PMCID: PMC9752902 DOI: 10.3389/fpsyt.2022.1027470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 11/01/2022] [Indexed: 12/03/2022] Open
Abstract
Introduction Social deficits are a significant feature among both individuals with psychosis and those at clinical high-risk (CHR) for developing psychosis. Critically, the psychosis risk syndrome emerges in adolescence and young adulthood, when social skill development is being fine-tuned. Yet, the underlying pathophysiology of social deficits in individuals at CHR for psychosis remains unclear. Literature suggests the cerebellum plays a critical role in social functioning. Cerebellar dysfunction in psychosis and CHR individuals is well-established, yet limited research has examined links between the cerebellum and social functioning deficits in this critical population. Method In the current study, 68 individuals at CHR for developing psychosis and 66 healthy controls (HCs) completed social processing measures (examining social interaction, social cognition, and global social functioning) and resting-state MRI scans. Seed-to-voxel resting-state connectivity analyses were employed to examine the relationship between social deficits and lobular cerebellar network connectivity. Results Analyses indicated that within the CHR group, each social domain variable was linked to reduced connectivity between social cerebellar subregions (e.g., Crus II, lobules VIIIa and VIIIb) and cortical regions (e.g., frontal pole and frontal gyrus), but a control cerebellar subregion (e.g., lobule X) and was unrelated to these social variables. Discussion These results indicate an association between several cerebellar lobules and specific deficits in social processing. The cerebellum, therefore, may be particularly salient to the social domain and future research is need to examine the role of the cerebellum in psychosis.
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Affiliation(s)
- Isabelle R. Frosch
- Department of Psychology, Northwestern University, Evanston, IL, United States
| | - Katherine S. F. Damme
- Department of Psychology, Northwestern University, Evanston, IL, United States
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston, IL, United States
| | - Jessica A. Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX, United States
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, United States
| | - Vijay A. Mittal
- Department of Psychology, Northwestern University, Evanston, IL, United States
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston, IL, United States
- Department of Psychiatry, Northwestern University, Chicago, IL, United States
- Department of Medical Social Sciences, Northwestern University, Chicago, IL, United States
- Institute for Policy Research, Northwestern University, Chicago, IL, United States
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23
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Feng S, Zheng S, Zou H, Dong L, Zhu H, Liu S, Wang D, Ning Y, Jia H. Altered functional connectivity of cerebellar networks in first-episode schizophrenia. Front Cell Neurosci 2022; 16:1024192. [PMID: 36439199 PMCID: PMC9692071 DOI: 10.3389/fncel.2022.1024192] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction Abnormalities of the cerebellum have been displayed to be a manifestation of schizophrenia (SCH) which is a detrimental psychiatric disorder. It has been recognized that the cerebellum contributes to motor function, sensorimotor function, cognition, and other brain functions in association with cerebral functions. Multiple studies have observed that abnormal alterations in cerebro-cerebellar functional connectivity (FC) were shown in patients with SCH. However, the FC of cerebellar networks in SCH remains unclear. Methods In this study, we explored the FC of cerebellar networks of 45 patients with first-episode SCH and 45 healthy control (HC) subjects by using a defined Yeo 17 network parcellation system. Furthermore, we performed a correlation analysis between cerebellar networks’ FC and positive and negative symptoms in patients with first-episode SCH. Finally, we established the classification model to provide relatively suitable features for patients with first-episode SCH concerning the cerebellar networks. Results We found lower between-network FCs between 14 distinct cerebellar network pairs in patients with first-episode SCH, compared to the HCs. Significantly, the between-network FC in N2-N15 was positively associated with positive symptom severity; meanwhile, N4-N15 was negatively associated with negative symptom severity. Besides, our results revealed a satisfactory classification accuracy (79%) of these decreased between-network FCs of cerebellar networks for correctly identifying patients with first-episode SCH. Conclusion Conclusively, between-network abnormalities in the cerebellum are closely related to positive and negative symptoms of patients with first-episode SCH. In addition, the classification results suggest that the cerebellar networks can be a potential target for further elucidating the underlying mechanisms in first-episode SCH.
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Affiliation(s)
- Sitong Feng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Sisi Zheng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Haoming Zou
- Department of Electronic Engineering, Tsinghua University, Beijing, China
| | - Linrui Dong
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Hong Zhu
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Shanshan Liu
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Dan Wang
- Inner Mongolia Autonomous Region Mental Health Center, Hohhot, China
| | - Yanzhe Ning
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- *Correspondence: Yanzhe Ning,
| | - Hongxiao Jia
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- Hongxiao Jia,
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24
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Moussa-Tooks AB, Rogers BP, Huang AS, Sheffield JM, Heckers S, Woodward ND. Cerebellar Structure and Cognitive Ability in Psychosis. Biol Psychiatry 2022; 92:385-395. [PMID: 35680432 PMCID: PMC9378489 DOI: 10.1016/j.biopsych.2022.03.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/15/2022] [Accepted: 03/17/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND Dysconnectivity theories, combined with advances in fundamental cognitive neuroscience, have led to increased interest in characterizing cerebellar abnormalities in psychosis. Smaller cerebellar gray matter volume has been found in schizophrenia spectrum disorders. However, the course of these deficits across illness stage, specificity to schizophrenia (vs. psychosis more broadly), and relationship to clinical phenotypes, primarily cognitive impairment, remain unclear. METHODS The Spatially Unbiased Infratentorial toolbox, a gold standard for analyzing human neuroimaging data of the cerebellum, was used to quantify cerebellar volumes and conduct voxel-based morphometry on structural magnetic resonance images obtained from 574 individuals (249 schizophrenia spectrum, 108 bipolar with psychotic features, 217 nonpsychiatric control). Analyses examining diagnosis (schizophrenia spectrum, bipolar disorder), illness stage (early, chronic), and cognitive effects on cerebellum structure in psychosis were performed. RESULTS Cerebellar structure in psychosis did not differ significantly from healthy participants, regardless of diagnosis and illness stage (effect size = 0.01-0.14). In contrast, low premorbid cognitive functioning was associated with smaller whole and regional cerebellum volumes, including cognitive (lobules VI and VII, Crus I, frontoparietal and attention networks) and motor (lobules I-IV, V, and X; somatomotor network) regions in psychosis (effect size = 0.36-0.60). These effects were not present in psychosis cohorts with average estimated premorbid cognition. CONCLUSIONS Cerebellar structural abnormalities in psychosis are related to lower premorbid cognitive functioning implicating early antecedents, atypical neurodevelopment, or both in cerebellar dysfunction. Future research focused on identifying the impact of early-life risk factors for psychosis on the development of the cerebellum and cognition is warranted.
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Affiliation(s)
- Alexandra B Moussa-Tooks
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee.
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Science, Nashville, Tennessee
| | - Anna S Huang
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Julia M Sheffield
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee
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Gao Y, Sun J, Cheng L, Yang Q, Li J, Hao Z, Zhan L, Shi Y, Li M, Jia X, Li H. Altered resting state dynamic functional connectivity of amygdala subregions in patients with autism spectrum disorder: A multi-site fMRI study. J Affect Disord 2022; 312:69-77. [PMID: 35710036 DOI: 10.1016/j.jad.2022.06.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/31/2022] [Accepted: 06/08/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is associated with altered brain connectivity. Previous studies have focused on the static functional connectivity pattern from amygdala subregions in ASD while ignoring its dynamics. Considering that dynamic functional connectivity (dFC) can provide different perspectives, the present study aims to investigate the dFC pattern of the amygdala subregions in ASD patients. METHODS Data of 618 ASD patients and 836 typical controls (TCs) of 30 sites were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. The sliding window approach was applied to conduct seed-based dFC analysis. The seed regions were bilateral basolateral (BLA) and centromedial-superficial amygdala (CSA). A two-sample t-test was done at each site. Image-based meta-analysis (IBMA) based on the results from all sites was performed. Correlation analysis was conducted between the dFC values and the clinical scores. RESULTS The ASD patients showed lower dFC between the left BLA and the bilateral inferior temporal (ITG)/left superior frontal gyrus, between the right BLA and right ITG/right thalamus/left superior temporal gyrus, and between the right CSA and middle temporal gyrus. The ASD patients showed higher dFC between the left BLA and temporal lobe/right supramarginal gyrus, between the right BLA and left calcarine gyrus, and between the left CSA and left calcarine gyrus. Correlation analysis revealed that the symptom severity was positively correlated with the dFC between the bilateral BLA and ITG in ASD. CONCLUSIONS Abnormal dFC of the specific amygdala subregions may provide new insights into the pathological mechanisms of ASD.
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Affiliation(s)
- Yanyan Gao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Lulu Cheng
- School of Foreign Studies, China University of Petroleum, Qingdao, China; Shanghai Center for Research in English Language Education, Shanghai International Studies University, Shanghai, China
| | - Qihang Yang
- College of Foreign Language, Zhejiang Normal University, Jinhua, China
| | - Jing Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Zeqi Hao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- Faculty of Western Languages, Heilongjiang University, Harbin, China
| | - Yuyu Shi
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Mengting Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Xize Jia
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China.
| | - Huayun Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China.
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Song P, Wang Y, Yuan X, Wang S, Song X. Exploring Brain Structural and Functional Biomarkers in Schizophrenia via Brain-Network-Constrained Multi-View SCCA. Front Neurosci 2022; 16:879703. [PMID: 35794950 PMCID: PMC9252525 DOI: 10.3389/fnins.2022.879703] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 04/04/2022] [Indexed: 11/17/2022] Open
Abstract
Recent studies have proved that dynamic regional measures extracted from the resting-state functional magnetic resonance imaging, such as the dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), could provide a great insight into brain dynamic characteristics of the schizophrenia. However, the unimodal feature is limited for delineating the complex patterns of brain deficits. Thus, functional and structural imaging data are usually analyzed together for uncovering the neural mechanism of schizophrenia. Investigation of neural function-structure coupling enables to find the potential biomarkers and further helps to understand the biological basis of schizophrenia. Here, a brain-network-constrained multi-view sparse canonical correlation analysis (BN-MSCCA) was proposed to explore the intrinsic associations between brain structure and dynamic brain function. Specifically, the d-fALFF was first acquired based on the sliding window method, whereas the gray matter map was computed based on voxel-based morphometry analysis. Then, the region-of-interest (ROI)-based features were extracted and further selected by performing the multi-view sparse canonical correlation analysis jointly with the diagnosis information. Moreover, the brain-network-based structural constraint was introduced to prompt the detected biomarkers more interpretable. The experiments were conducted on 191 patients with schizophrenia and 191 matched healthy controls. Results showed that the BN-MSCCA could identify the critical ROIs with more sparse canonical weight patterns, which are corresponding to the specific brain networks. These are biologically meaningful findings and could be treated as the potential biomarkers. The proposed method also obtained a higher canonical correlation coefficient for the testing data, which is more consistent with the results on training data, demonstrating its promising capability for the association identification. To demonstrate the effectiveness of the potential clinical applications, the detected biomarkers were further analyzed on a schizophrenia-control classification task and a correlation analysis task. The experimental results showed that our method had a superior performance with a 5–8% increment in accuracy and 6–10% improvement in area under the curve. Furthermore, two of the top-ranked biomarkers were significantly negatively correlated with the positive symptom score of Positive and Negative Syndrome Scale (PANSS). Overall, the proposed method could find the association between brain structure and dynamic brain function, and also help to identify the biological meaningful biomarkers of schizophrenia. The findings enable our further understanding of this disease.
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Affiliation(s)
- Peilun Song
- School of Information Engineering, Zhengzhou University, Zhengzhou, China
| | - Yaping Wang
- School of Information Engineering, Zhengzhou University, Zhengzhou, China
- *Correspondence: Yaping Wang
| | - Xiuxia Yuan
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Biological Psychiatry International Joint Laboratory of Henan/Zhengzhou University, Zhengzhou, China
| | - Shuying Wang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Biological Psychiatry International Joint Laboratory of Henan/Zhengzhou University, Zhengzhou, China
| | - Xueqin Song
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Biological Psychiatry International Joint Laboratory of Henan/Zhengzhou University, Zhengzhou, China
- Xueqin Song
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Jiang Y, Duan M, He H, Yao D, Luo C. Structural and Functional MRI Brain Changes in Patients with Schizophrenia Following Electroconvulsive Therapy: A Systematic Review. Curr Neuropharmacol 2022; 20:1241-1252. [PMID: 34370638 PMCID: PMC9886826 DOI: 10.2174/1570159x19666210809101248] [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: 03/23/2021] [Revised: 07/17/2021] [Accepted: 07/31/2021] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Schizophrenia (SZ) is a severe psychiatric disorder typically characterized by multidimensional psychotic syndromes. Electroconvulsive therapy (ECT) is a treatment option for medication-resistant patients with SZ or treating acute symptoms. Although the efficacy of ECT has been demonstrated in clinical use, its therapeutic mechanisms in the brain remain elusive. OBJECTIVE This study aimed to summarize brain changes on structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) after ECT. METHODS According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was carried out. The PubMed and Medline databases were systematically searched using the following medical subject headings (MeSH): (electroconvulsive therapy OR ECT) AND (schizophrenia) AND (MRI OR fMRI OR DTI OR DWI). RESULTS This review yielded 12 MRI studies, including 4 with sMRI, 5 with fMRI and 3 with multimodal MRI. Increases in volumes of the hippocampus and its adjacent regions (parahippocampal gyrus and amygdala), as well as the insula and frontotemporal regions, were noted after ECT. fMRI studies found ECT-induced changes in different brain regions/networks, including the hippocampus, amygdala, default model network, salience network and other regions/networks that are thought to highly correlate with the pathophysiologic characteristics of SZ. The results of the correlation between brain changes and symptom remissions are inconsistent. CONCLUSION Our review provides evidence supporting ECT-induced brain changes on sMRI and fMRI in SZ and explores the relationship between these changes and symptom remission.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China; ,High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P.R. China;
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China; ,Address correspondence to these authors at the The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu 610054, China; Tel: 86-28-83201018; Fax: 86-28-83208238; E-mails: (C. Luo) and (M. Duan)
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China; ,High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P.R. China;
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China; ,High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P.R. China; ,Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, P.R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China; ,High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P.R. China; ,Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, P.R. China,Address correspondence to these authors at the The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu 610054, China; Tel: 86-28-83201018; Fax: 86-28-83208238; E-mails: (C. Luo) and (M. Duan)
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Chen J, Xue K, Yang M, Wang K, Xu Y, Wen B, Cheng J, Han S, Wei Y. Altered Coupling of Cerebral Blood Flow and Functional Connectivity Strength in First-Episode Schizophrenia Patients With Auditory Verbal Hallucinations. Front Neurosci 2022; 16:821078. [PMID: 35546878 PMCID: PMC9083321 DOI: 10.3389/fnins.2022.821078] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 02/09/2022] [Indexed: 11/13/2022] Open
Abstract
Objective Auditory verbal hallucinations (AVHs) are a major symptom of schizophrenia and are connected with impairments in auditory and speech-related networks. In schizophrenia with AVHs, alterations in resting-state cerebral blood flow (CBF) and functional connectivity have been described. However, the neurovascular coupling alterations specific to first-episode drug-naïve schizophrenia (FES) patients with AVHs remain unknown. Methods Resting-state functional MRI and arterial spin labeling (ASL) was performed on 46 first-episode drug-naïve schizophrenia (FES) patients with AVHs (AVH), 39 FES drug-naïve schizophrenia patients without AVHs (NAVH), and 48 healthy controls (HC). Then we compared the correlation between the CBF and functional connection strength (FCS) of the entire gray matter between the three groups, as well as the CBF/FCS ratio of each voxel. Correlation analyses were performed on significant results between schizophrenia patients and clinical measures scale. Results The CBF/FCS ratio was reduced in the cognitive and emotional brain regions in both the AVH and NAVH groups, primarily in the crus I/II, vermis VI/VII, and cerebellum VI. In the AVH group compared with the HC group, the CBF/FCS ratio was higher in auditory perception and language-processing areas, primarily the left superior and middle temporal gyrus (STG/MTG). The CBF/FCS ratio in the left STG and left MTG positively correlates with the score of the Auditory Hallucination Rating Scale in AVH patients. Conclusion These findings point to the difference in neurovascular coupling failure between AVH and NAVH patients. The dysfunction of the forward model based on the predictive and computing role of the cerebellum may increase the excitability in the auditory cortex, which may help to understand the neuropathological mechanism of AVHs.
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Affiliation(s)
- Jingli Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kangkang Xue
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meng Yang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kefan Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yinhuan Xu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Baohong Wen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Xie Y, He Y, Guan M, Zhou G, Wang Z, Ma Z, Wang H, Yin H. Impact of low-frequency rTMS on functional connectivity of the dentate nucleus subdomains in schizophrenia patients with auditory verbal hallucination. J Psychiatr Res 2022; 149:87-96. [PMID: 35259665 DOI: 10.1016/j.jpsychires.2022.02.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 02/07/2022] [Accepted: 02/28/2022] [Indexed: 01/10/2023]
Abstract
Despite low-frequency repetitive transcranial magnetic stimulation (rTMS) is effective in treating schizophrenia patients with auditory verbal hallucinations (AVH), the underlying neural mechanisms of the effect still need to be clarified. Using the cerebellar dentate nucleus (DN) subdomain (dorsal and versal DN) as seeds, the present study investigated resting state functional connectivity (FC) alternations of the seeds with the whole brain and their associations with clinical responses in schizophrenia patients with AVH receiving 1 Hz rTMS treatment. The results showed that the rTMS treatment improved the psychiatric symptoms (e.g., AVH and positive symptoms) and certain neurocognitive functions (e.g., visual learning and verbal learning) in the patients. In addition, the patients at baseline showed increased FC between the DN subdomains and temporal lobes (e.g., right superior temporal gyrus and right middle temporal gyrus) and decreased FC between the DN subdomains and the left superior frontal gyrus, right postcentral gyrus, left supramarginal gyrus and regional cerebellum (e.g., lobule 4-5) compared to controls. Furthermore, these abnormal DN subdomain connectivity patterns did not persist and decreased FC of DN subdomains with cerebellum lobule 4-5 were reversed in patients after rTMS treatment. Linear regression analysis showed that the FC difference values of DN subdomains with the temporal lobes, supramarginal gyrus and cerebellum 4-5 between the patients at baseline and posttreatment were associated with clinical improvements (e.g., AVH and verbal learning) after rTMS treatment. The results suggested that rTMS treatment may modulate the neural circuits of the DN subdomains and hint to underlying neural mechanisms for low-frequency rTMS treating schizophrenia with AVH.
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Affiliation(s)
- Yuanjun Xie
- School of Education, Xinyang College, Xinyang, China; Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Ying He
- Department of Psychiatry, Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Muzhen Guan
- Department of Mental Health, Xi'an Medical University, Xi'an, China
| | | | - Zhongheng Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhujing Ma
- Department of Military Psychology, School of Psychology, Fourth Military Medical University, Xi'an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
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Badaly D, Beers SR, Ceschin R, Lee VK, Sulaiman S, Zahner A, Wallace J, Berdaa-Sahel A, Burns C, Lo CW, Panigrahy A. Cerebellar and Prefrontal Structures Associated With Executive Functioning in Pediatric Patients With Congenital Heart Defects. Front Neurol 2022; 13:827780. [PMID: 35356449 PMCID: PMC8959311 DOI: 10.3389/fneur.2022.827780] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 01/31/2022] [Indexed: 11/17/2022] Open
Abstract
Objective Children, adolescents, and young adults with congenital heart defects (CHD) often display executive dysfunction. We consider the prefrontal and cerebellar brain structures as mechanisms for executive dysfunction among those with CHD. Methods 55 participants with CHD (M age = 13.93) and 95 healthy controls (M age = 13.13) completed magnetic resonance imaging (MRI) of the brain, from which we extracted volumetric data on prefrontal and cerebellar regions. Participants also completed neuropsychological tests of executive functioning; their parents completed ratings of their executive functions. Results Compared to healthy controls, those with CHD had smaller cerebellums and lateral, medial, and orbital prefrontal regions, they performed more poorly on tests of working memory, inhibitory control, and mental flexibility, and their parents rated them as having poorer executive functions across several indices. Across both groups, there were significant correlations for cerebellar and/or prefrontal volumes with cognitive assessments of working memory, mental flexibility, and inhibitory control and with parent-completed ratings of task initiation, working memory, and planning/organization. Greater prefrontal volumes were associated with better working memory, among those with larger cerebellums (with group differences based on the measure and the prefrontal region). Greater prefrontal volumes were related to better emotional regulation only among participants with CHD with smaller cerebellar volumes, and with poorer inhibition and emotional regulation only among healthy controls with larger cerebellar volumes. Conclusion The cerebellum not only contributes to executive functioning among young individuals with CHD but may also modulate the relationships between prefrontal regions and executive functioning differently for pediatric patients with CHD vs. health controls.
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Affiliation(s)
- Daryaneh Badaly
- Learning and Development Center, Child Mind Institute, New York, NY, United States
- *Correspondence: Daryaneh Badaly
| | - Sue R. Beers
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Rafael Ceschin
- Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Vincent K. Lee
- Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Shahida Sulaiman
- Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Alexandria Zahner
- Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Julia Wallace
- Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Aurélia Berdaa-Sahel
- Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Cheryl Burns
- Traumatic Brain Injury Program, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
| | - Cecilia W. Lo
- Department of Developmental Biology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Ashok Panigrahy
- Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
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31
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Li X, Liu N, Yang C, Zhang W, Lui S. Cerebellar gray matter volume changes in patients with schizophrenia: A voxel-based meta-analysis. Front Psychiatry 2022; 13:1083480. [PMID: 36620665 PMCID: PMC9814486 DOI: 10.3389/fpsyt.2022.1083480] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND In schizophrenia, the structural changes in the cerebellum are associated with patients' cognition and motor deficits. However, the findings are inconsistent owing to the heterogeneity in sample size, magnetic resonance imaging (MRI) scanners, and other factors among them. In this study, we conducted a meta-analysis to characterize the anatomical changes in cerebellar subfields in patients with schizophrenia. METHODS Systematic research was conducted to identify studies that compare the gray matter volume (GMV) differences in the cerebellum between patients with schizophrenia and healthy controls with a voxel-based morphometry (VBM) method. A coordinate-based meta-analysis was adopted based on seed-based d mapping (SDM) software. An exploratory meta-regression analysis was conducted to associate clinical and demographic features with cerebellar changes. RESULTS Of note, 25 studies comprising 996 patients with schizophrenia and 1,109 healthy controls were included in the present meta-analysis. In patients with schizophrenia, decreased GMVs were demonstrated in the left Crus II, right lobule VI, and right lobule VIII, while no increased GMV was identified. In the meta-regression analysis, the mean age and illness duration were negatively associated with the GMV in the left Crus II in patients with schizophrenia. CONCLUSION The most significant structural changes in the cerebellum are mainly located in the posterior cerebellar hemisphere in patients with schizophrenia. The decreased GMVs of these regions might partly explain the cognitive deficits and motor symptoms in patients with schizophrenia.
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Affiliation(s)
- Xing Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
| | - Naici Liu
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
| | - Chengmin Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
| | - Su Lui
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
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Wang Y, Jiang Y, Liu D, Zhang J, Yao D, Luo C, Wang J. Atypical Antipsychotics Mediate Dynamics of Intrinsic Brain Activity in Early-Stage Schizophrenia? A Preliminary Study. Psychiatry Investig 2021; 18:1205-1212. [PMID: 34965706 PMCID: PMC8721296 DOI: 10.30773/pi.2020.0418] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 09/24/2021] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE Abnormalities of static brain activity have been reported in schizophrenia, but it remains to be clarified the temporal variability of intrinsic brain activities in schizophrenia and how atypical antipsychotics affect it. METHODS We employed a resting-state functional magnetic resonance imaging (rs-fMRI) and a sliding-window analysis of dynamic amplitude of low-frequency fluctuation (dALFF) to evaluate the dynamic brain activities in schizophrenia (SZ) patients before and after 8-week antipsychotic treatment. Twenty-six schizophrenia individuals and 26 matched healthy controls (HC) were included in this study. RESULTS Compared with HC, SZ showed stronger dALFF in the right inferior temporal gyrus (ITG.R) at baseline. After medication, the SZ group exhibited reduced dALFF in the right middle occipital gyrus (MOG.R) and increased dALFF in the left superior frontal gyrus (SFG.L), right middle frontal gyrus (MFG.R), and right inferior parietal lobule (IPL.R). Dynamic ALFF in IPL.R was found to significant negative correlate with the Scale for the Assessment of Negative Symptoms (SANS) scores at baseline. CONCLUSION Our results showed dynamic intrinsic brain activities altered in schizophrenia after short term antipsychotic treatment. The findings of this study support and expand the application of dALFF method in the study of the pathological mechanism in psychosis in the future.
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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, 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, China
| | - Dengtang Liu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianye Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 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, 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, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
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Thalamic connectivity system across psychiatric disorders: Current status and clinical implications. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 2:332-340. [PMID: 36324665 PMCID: PMC9616255 DOI: 10.1016/j.bpsgos.2021.09.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 09/23/2021] [Accepted: 09/25/2021] [Indexed: 12/20/2022] Open
Abstract
The thalamic connectivity system, with the thalamus as the central node, enables transmission of the brain’s neural computations via extensive connections to cortical, subcortical, and cerebellar regions. Emerging reports suggest deficits in this system across multiple psychiatric disorders, making it a unique network of high translational and transdiagnostic utility in mapping neural alterations that potentially contribute to symptoms and disturbances in psychiatric patients. However, despite considerable research effort, it is still debated how this system contributes to psychiatric disorders. This review characterizes current knowledge regarding thalamic connectivity system deficits in psychiatric disorders, including schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder, across multiple levels of the system. We identify the presence of common and distinct patterns of deficits in the thalamic connectivity system in major psychiatric disorders and assess their nature and characteristics. Specifically, this review assembles evidence for the hypotheses of 1) thalamic microstructure, particularly in the mediodorsal nucleus, as a state marker of psychosis; 2) thalamo-prefrontal connectivity as a trait marker of psychosis; and 3) thalamo-somatosensory/parietal connectivity as a possible marker of general psychiatric illness. Furthermore, possible mechanisms contributing to thalamocortical dysconnectivity are explored. We discuss current views on the contributions of cerebellar-thalamic connectivity to the thalamic connectivity system and propose future studies to examine its effects at multiple levels, from the molecular (e.g., glutamatergic) to the behavioral (e.g., cognition), to gain a deeper understanding of the mechanisms that underlie the disturbances observed in psychiatric disorders.
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Li X, Jiang Y, Li W, Qin Y, Li Z, Chen Y, Tong X, Xiao F, Zuo X, Gong Q, Zhou D, Yao D, An D, Luo C. Disrupted functional connectivity in white matter resting-state networks in unilateral temporal lobe epilepsy. Brain Imaging Behav 2021; 16:324-335. [PMID: 34478055 DOI: 10.1007/s11682-021-00506-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/14/2021] [Indexed: 02/08/2023]
Abstract
Unilateral temporal lobe epilepsy (TLE) is the most common type of focal epilepsy characterized by foci in the unilateral temporal lobe grey matters of regions such as the hippocampus. However, it remains unclear how the functional features of white matter are altered in TLE. In the current study, resting-state functional magnetic resonance imaging (fMRI) was performed on 71 left TLE (LTLE) patients, 79 right TLE (RTLE) patients and 47 healthy controls (HC). Clustering analysis was used to identify fourteen white matter networks (WMN). The functional connectivity (FC) was calculated among WMNs and between WMNs and grey matter. Furthermore, the FC laterality of hemispheric WMNs was assessed. First, both patient groups showed decreased FCs among WMNs. Specifically, cerebellar white matter illustrated decreased FCs with the cerebral superficial WMNs, implying a dysfunctional interaction between the cerebellum and the cerebral cortex in TLE. Second, the FCs between WMNs and the ipsilateral hippocampus (grey matter foci) were also reduced in patient groups, which may suggest insufficient functional integration in unilateral TLE. Interestingly, RTLE showed more severe abnormalities of white matter FCs, including links to the bilateral hippocampi and temporal white matter, than LTLE. Taken together, these findings provide functional evidence of white matter abnormalities, extending the understanding of the pathological mechanism of white matter impairments in unilateral TLE.
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Affiliation(s)
- Xuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu, 610054, People's Republic of 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, Second North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610054, People's Republic of China
| | - Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610054, People's Republic of China
| | - Zhiliang Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Xin Tong
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610054, People's Republic of China
| | - Fenglai Xiao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610054, People's Republic of China
| | - Xiaojun Zuo
- 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, Second North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610054, People's Republic of China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610054, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610054, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu, 610054, People's Republic of China.
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35
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Mastrandrea R, Piras F, Gabrielli A, Banaj N, Caldarelli G, Spalletta G, Gili T. The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia. Sci Rep 2021; 11:15400. [PMID: 34321538 PMCID: PMC8319172 DOI: 10.1038/s41598-021-94825-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 07/08/2021] [Indexed: 01/10/2023] Open
Abstract
Network neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization's basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions.
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Affiliation(s)
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, 00179, Rome, Italy
| | - Andrea Gabrielli
- Dipartimento di Ingegneria, Università Roma Tre, 00146, Rome, Italy.,Istituto dei Sistemi Complessi (ISC)-CNR, UoS Sapienza, Dipartimento di Fisica, Università "Sapienza", 00185, Rome, Italy
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, 00179, Rome, Italy
| | - Guido Caldarelli
- Networks Unit, IMT School for Advanced Studies, 55100, Lucca, Italy.,Istituto dei Sistemi Complessi (ISC)-CNR, UoS Sapienza, Dipartimento di Fisica, Università "Sapienza", 00185, Rome, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, 00179, Rome, Italy. .,Division of Neuropsychiatry, Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA.
| | - Tommaso Gili
- Networks Unit, IMT School for Advanced Studies, 55100, Lucca, Italy
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Dynamic functional connectivity and its anatomical substrate reveal treatment outcome in first-episode drug-naïve schizophrenia. Transl Psychiatry 2021; 11:282. [PMID: 33980821 PMCID: PMC8115129 DOI: 10.1038/s41398-021-01398-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/09/2021] [Accepted: 04/20/2021] [Indexed: 02/06/2023] Open
Abstract
Convergent evidence has suggested a significant effect of antipsychotic exposure on brain structure and function in patients with schizophrenia, yet the characteristics of favorable treatment outcome remains largely unknown. In this work, we aimed to examine how large-scale brain networks are modulated by antipsychotic treatment, and whether the longitudinal changes could track the improvements of psychopathologic scores. Thirty-four patients with first-episode drug-naïve schizophrenia and 28 matched healthy controls were recruited at baseline from Shanghai Mental Health Center. After 8 weeks of antipsychotic treatment, 24 patients were re-scanned. Through a systematical dynamic functional connectivity (dFC) analysis, we investigated the schizophrenia-related intrinsic alterations of dFC at baseline, followed by a longitudinal study to examine the influence of antipsychotic treatment on these abnormalities by comparing patients at baseline and follow-up. A structural connectivity (SC) association analysis was further carried out to investigate longitudinal anatomical changes that underpin the alterations of dFC. We found a significant symptomatic improvement-related increase in the occurrence of a dFC state characterized by stronger inter-network integration. Furthermore, symptom reduction was correlated with increased FC variability in a unique connectomic signature, particularly in the connections within the default mode network and between the auditory, cognitive control, and cerebellar network to other networks. Additionally, we observed that the SC between the superior frontal gyrus and medial prefrontal cortex was decreased after treatment, suggesting a relaxation of normal constraints on dFC. Taken together, these findings provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network. Moreover, our identified neuroimaging markers tied to the neurobiology of schizophrenia could be used as potential indicators in predicting the treatment outcome of antipsychotics.
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Zhang Y, Yang R, Cai X. Frequency-specific alternations in the moment-to-moment BOLD signals variability in schizophrenia. Brain Imaging Behav 2021; 15:68-75. [PMID: 31900893 DOI: 10.1007/s11682-019-00233-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Variability of neuronal activity is considered as the fundamental mechanism for the flexible and optimal brain function. Moreover, different frequency neuro signal is related to specific function. While little is currently known regarding changes in spontaneous BOLD variability of schizophrenia. The current study used resting-state fMRI data from 53 chronic schizophrenic subjects and 67 healthy subjects to investigate this issue. The data-driven method was used to measure the BOLD variability (MSSD: mean square successive difference) in two different frequency bands respectively (slow-5: 0.01-0.027 Hz; slow-4:0.027-0.073 Hz). Schizophrenic subjects exhibited decreased BOLD variability in thalamus region, sensorimotor and visual networks, and increased BOLD variability in salience network compared to matched healthy controls. Moreover, the interaction effects between frequency and group were observed in thalamus and right dorsolateral prefrontal cortex (DLPFC). These findings identified that altered BOLD variability is frequency dependent in schizophrenia. Importantly, the severity of patients' negative symptom was related to the increased BOLD variability of DLPFC within slow-4 frequency band, highlighting the evidence that abnormal BOLD variability of frontal cortex is likely to have effects on the pathophysiology of negative symptom in schizophrenia.
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Affiliation(s)
- Youxue Zhang
- School of Psychology, Chengdu Normal University, No.99, East section, Haike Road, Chengdu, People's Republic of China, 611130.
| | - Rui Yang
- Psychological Research and Counseling Center, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China
| | - Xueli Cai
- Psychological Research and Counseling Center, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China
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Yang Y, Chattun MR, Yan R, Zhao K, Chen Y, Zhu R, Shi J, Wang X, Lu Q, Yao Z. Atrophy of right inferior frontal orbital gyrus and frontoparietal functional connectivity abnormality in depressed suicide attempters. Brain Imaging Behav 2021; 14:2542-2552. [PMID: 32157476 DOI: 10.1007/s11682-019-00206-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Although structural and functional brain abnormalities have been observed in depressed suicide attempters (DS), structural deficits and functional impairments together with their relationship in DS remain unclear. To clarify this issue, we aimed to examine the differences in gray matter (GM) alteration, corresponding functional connectivity (FC) change, and their relationship between DS and depressed non-suicide attempters (NDS). Sixty-eight DS, 119 NDS and 103 healthy controls were enrolled and subjected to magnetic resonance imaging scans. The patients were evaluated using the 17-item Hamilton Rating Scale for Depression (HRSD) and Nurses' Global Assessment of Suicide Risk (NGASR) scale. Both voxel-based morphometry and resting-state FC analyses were performed based on functional and structural imaging data. Compared with NDS, the DS group showed reduced GM volume in the right inferior frontal orbital gyrus (IFOG) and left caudate (CAU) but increased GM volume in the left calcarine fissure, weaker negative right IFOG-left rectus gyrus (REG) FC, and weaker positive right IFOG-left inferior parietal lobule (IPL) FC. In DS, the GM volume of the right IFOG and left CAU was negatively correlated with NGASR and HRSD scores, respectively; the right IFOG-left IPL FC was negatively correlated with cognitive factor scores; and the GM volume of the right IFOG was positively correlated with IFOG-REG and IFOG-IPL FC. Our findings indicate that structural deficit with its related functional alterations in brain circuits converged in right IFOG centralized pathways and may play a central role in suicidal behaviors in depression.
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Affiliation(s)
- Yuyin Yang
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Mohammad Ridwan Chattun
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Rui Yan
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China
| | - Ke Zhao
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325000, China
| | - Yu Chen
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Rongxin Zhu
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Jiabo Shi
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Xinyi Wang
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, 210096, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China
| | - Qing Lu
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, 210096, China. .,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China.
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China. .,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China.
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Variants in regulatory elements of PDE4D associate with major mental illness in the Finnish population. Mol Psychiatry 2021; 26:816-824. [PMID: 31138891 DOI: 10.1038/s41380-019-0429-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 04/04/2019] [Accepted: 04/11/2019] [Indexed: 01/29/2023]
Abstract
We have previously reported a replicable association between variants at the PDE4D gene and familial schizophrenia in a Finnish cohort. In order to identify the potential functional mutations underlying these previous findings, we sequenced 1.5 Mb of the PDE4D genomic locus in 20 families (consisting of 96 individuals and 79 independent chromosomes), followed by two stages of genotyping across 6668 individuals from multiple Finnish cohorts for major mental illnesses. We identified 4570 SNPs across the PDE4D gene, with 380 associated to schizophrenia (p ≤ 0.05). Importantly, two of these variants, rs35278 and rs165940, are located at transcription factor-binding sites, and displayed replicable association in the two-stage enlargement of the familial schizophrenia cohort (combined statistics for rs35278 p = 0.0012; OR = 1.18, 95% CI: 1.06-1.32; and rs165940 p = 0.0016; OR = 1.27, 95% CI: 1.13-1.41). Further analysis using additional cohorts and endophenotypes revealed that rs165940 principally associates within the psychosis (p = 0.025, OR = 1.18, 95% CI: 1.07-1.30) and cognitive domains of major mental illnesses (g-score p = 0.044, β = -0.033). Specifically, the cognitive domains represented verbal learning and memory (p = 0.0091, β = -0.044) and verbal working memory (p = 0.0062, β = -0.036). Moreover, expression data from the GTEx database demonstrated that rs165940 significantly correlates with the mRNA expression levels of PDE4D in the cerebellum (p-value = 0.04; m-value = 0.9), demonstrating a potential functional consequence for this variant. Thus, rs165940 represents the most likely functional variant for major mental illness at the PDE4D locus in the Finnish population, increasing risk broadly to psychotic disorders.
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Hertzberg L, Zohar AH, Yitzhaky A. Gene Expression Meta-Analysis of Cerebellum Samples Supports the FKBP5 Gene-Environment Interaction Model for Schizophrenia. Life (Basel) 2021; 11:190. [PMID: 33673722 PMCID: PMC7997256 DOI: 10.3390/life11030190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 02/19/2021] [Accepted: 02/22/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND One of the most studied molecular models of gene-environment interactions is that of FKBP5, which has been shown to interact with childhood adversity to increase the risk of psychiatric disorders, and has been implicated in schizophrenia. While the model predicts up-regulation of FKBP5, previous brain samples gene expression studies yielded inconsistent results. METHODS We performed a systematic gene expression meta-analysis of FKBP5 and NR3C1, a glucocorticoid receptor inhibited by FKBP5, in cerebellum samples of patients with schizophrenia. The gene expression databases GEO, SMRI and those of NIMH were searched, and out of six screened datasets, three were eligible for the meta-analysis (overall 69 with schizophrenia and 78 controls). RESULTS We detected up-regulation of FKBP5 and down-regulation of NR3C1 in schizophrenia, and a negative correlation between their expression patterns. Correlation analysis suggested that the detected differential expression did not result from potential confounding factors. CONCLUSIONS Our results give significant support to the FKBP5 gene-environment interaction model for schizophrenia, which provides a molecular mechanism by which childhood adversity is involved in the development of the disorder. To explore FKBP5's potential as a therapeutic target, a mapping of its differential expression patterns in different brain regions of schizophrenia patients is needed.
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Affiliation(s)
- Libi Hertzberg
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel;
- Shalvata Mental Health Center, Affiliated with the Sackler School of Medicine, Tel-Aviv University, Tel Aviv 69978, Israel
| | - Ada H. Zohar
- Department of Behavioral Sciences, Ruppin Academic Center, Hefer Valley 40250, Israel;
| | - Assif Yitzhaky
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel;
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41
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He H, Cao H, Huang B, He M, Ma C, Yao D, Luo C, Yao G, Duan M. Functional abnormalities of striatum are related to the season-specific effect on schizophrenia. Brain Imaging Behav 2021; 15:2347-2355. [PMID: 33398777 DOI: 10.1007/s11682-020-00430-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2020] [Indexed: 11/29/2022]
Abstract
Schizophrenia is a syndrome that is typically accompanied by delusions, hallucinations and cognitive impairments. Specifically, abundant evidences support the notion that more people diagnosed with schizophrenia are born during fall-winter than spring-summer. Although pathophysiological of schizophrenia might be associated with abnormal brain functional network, little is currently known the relationship between season and deficient brain functional network of schizophrenia. To investigate this issue, in this study 51 schizophrenic subjects and 72 healthy controls underwent MRI scanning to detect the brain functional mapping, each at spring-summer and fall-winter season throughout the year. The data-driven method was used to measure the blood oxygen metabolism variability (BOMV). Decreased BOMV in spring-summer while increased in fall-winter were observed within dopaminergic network of schizophrenic subjects, including striatum, thalamus, and hippocampus. The post hoc analysis exploring the coupling among changed BOMV regions, confirmed that a positive relationship, between pallidum and hippocampus existed in fall-winter healthy controls, but not in fall-winter schizophrenic subjects. These findings identified that seasonal effect on striatum might be associated with modulation of striatum-hippocampus. Our results provide a new insight into the role of season in understanding the pathophysiological of schizophrenia.
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Affiliation(s)
- Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Huan Cao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Binxin Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Manxi He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Chi Ma
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China. .,High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China.
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China.
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He H, Luo C, He C, He M, Du J, Biswal BB, Yao D, Yao G, Duan M. Altered Spatial Organization of Dynamic Functional Network Associates With Deficient Sensory and Perceptual Network in Schizophrenia. Front Psychiatry 2021; 12:687580. [PMID: 34421674 PMCID: PMC8374440 DOI: 10.3389/fpsyt.2021.687580] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/08/2021] [Indexed: 12/31/2022] Open
Abstract
Schizophrenia is currently thought as a disorder with dysfunctional communication within and between sensory and cognitive processes. It has been hypothesized that these deficits mediate heterogeneous and comprehensive schizophrenia symptomatology. In this study, we investigated as to how the abnormal dynamic functional architecture of sensory and cognitive networks may contribute to these symptoms in schizophrenia. We calculated a sliding-window-based dynamic functional connectivity strength (FCS) and amplitude of low-frequency fluctuation (ALFF) maps. Then, using group-independent component analysis, we characterized spatial organization of dynamic functional network (sDFN) across various time windows. The spatial architectures of FCS/ALFF-sDFN were similar with traditional resting-state functional networks and cannot be accounted by length of the sliding window. Moreover, schizophrenic subjects demonstrated reduced dynamic functional connectivity (dFC) within sensory and perceptual sDFNs, as well as decreased connectivity between these sDFNs and high-order frontal sDFNs. The severity of patients' positive and total symptoms was related to these abnormal dFCs. Our findings revealed that the sDFN during rest might form the intrinsic functional architecture and functional changes associated with psychotic symptom deficit. Our results support the hypothesis that the dynamic functional network may influence the aberrant sensory and cognitive function in schizophrenia, further highlighting that targeting perceptual deficits could extend our understanding of the pathophysiology of schizophrenia.
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Affiliation(s)
- Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, China
| | - Chuan He
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, China
| | - Manxi He
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, China
| | - Jing Du
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, China
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, Ministry of Education (MOE) Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
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Jiang S, Pei H, Huang Y, Chen Y, Liu L, Li J, He H, Yao D, Luo C. Dynamic Temporospatial Patterns of Functional Connectivity and Alterations in Idiopathic Generalized Epilepsy. Int J Neural Syst 2020; 30:2050065. [PMID: 33161788 DOI: 10.1142/s0129065720500653] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The dynamic profile of brain function has received much attention in recent years and is also a focus in the study of epilepsy. The present study aims to integrate the dynamics of temporal and spatial characteristics to provide comprehensive and novel understanding of epileptic dynamics. Resting state fMRI data were collected from eighty-three patients with idiopathic generalized epilepsy (IGE) and 87 healthy controls (HC). Specifically, we explored the temporal and spatial variation of functional connectivity density (tvFCD and svFCD) in the whole brain. Using a sliding-window approach, for a given region, the standard variation of the FCD series was calculated as the tvFCD and the variation of voxel-wise spatial distribution was calculated as the svFCD. We found primary, high-level, and sub-cortical networks demonstrated distinct tvFCD and svFCD patterns in HC. In general, the high-level networks showed the highest variation, the subcortical and primary networks showed moderate variation, and the limbic system showed the lowest variation. Relative to HC, the patients with IGE showed weaken temporal and enhanced spatial variation in the default mode network and weaken temporospatial variation in the subcortical network. Besides, enhanced temporospatial variation in sensorimotor and high-level networks was also observed in patients. The hyper-synchronization of specific brain networks was inferred to be associated with the phenomenon responsible for the intrinsic propensity of generation and propagation of epileptic activities. The disrupted dynamic characteristics of sensorimotor and high-level networks might potentially contribute to the driven motion and cognition phenotypes in patients. In all, presently provided evidence from the temporospatial variation of functional interaction shed light on the dynamics underlying neuropathological profiles of epilepsy.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Haonan Pei
- 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 611731, P. R. China
| | - Yang Huang
- 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 611731, P. R. China
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Linli Liu
- 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 611731, P. R. China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Hui He
- 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 611731, P. R. 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 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu P. R. China
| | - 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 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu P. R. China
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Kolenič M, Španiel F, Hlinka J, Matějka M, Knytl P, Šebela A, Renka J, Hajek T. Higher Body-Mass Index and Lower Gray Matter Volumes in First Episode of Psychosis. Front Psychiatry 2020; 11:556759. [PMID: 33173508 PMCID: PMC7538831 DOI: 10.3389/fpsyt.2020.556759] [Citation(s) in RCA: 6] [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: 04/28/2020] [Accepted: 09/02/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Neurostructural alterations are often reported in first episode of psychosis (FEP), but there is heterogeneity in the direction and location of findings between individual studies. The reasons for this heterogeneity remain unknown. Obesity is disproportionately frequent already early in the course of psychosis and is associated with smaller brain volumes. Thus, we hypothesized that obesity may contribute to brain changes in FEP. METHOD We analyzed MRI scans from 120 participants with FEP and 114 healthy participants. In primary analyses, we performed voxel-based morphometry (VBM) with small volume corrections to regions associated with FEP or obesity in previous meta-analyses. In secondary analyses, we performed whole-brain VBM analyses. RESULTS In primary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in a) left fronto-temporal region (pTFCE = 0.008) and b) left postcentral gyrus (pTFCE = 0.043). When controlling for FEP, BMI was associated with lower GM volume in left cerebellum (pTFCE < 0.001). In secondary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in the a) cerebellum (pTFCE = 0.004), b) left frontal (pTFCE = 0.024), and c) right temporal cortex (pTFCE = 0.031). When controlling for FEP, BMI was associated with lower GM volume in cerebellum (pTFCE = 0.004). Levels of C-reactive protein, HDL and LDL-cholesterol correlated with obesity related neurostructural alterations. CONCLUSIONS This study suggests that higher BMI, which is frequent in FEP, may contribute to cerebellar alterations in schizophrenia. As previous studies showed that obesity-related brain alterations may be reversible, our findings raise the possibility that improving the screening for and treatment of obesity and associated metabolic changes could preserve brain structure in FEP.
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Affiliation(s)
- Marián Kolenič
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Filip Španiel
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
| | - Jaroslav Hlinka
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
- Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences, Prague, Czechia
| | - Martin Matějka
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Pavel Knytl
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Antonín Šebela
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
| | - Jiří Renka
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Tomas Hajek
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
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Efficacy of Intensive Cerebellar Intermittent Theta Burst Stimulation (iCiTBS) in Treatment-Resistant Schizophrenia: a Randomized Placebo-Controlled Study. THE CEREBELLUM 2020; 20:116-123. [PMID: 32964381 PMCID: PMC7508243 DOI: 10.1007/s12311-020-01193-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 09/13/2020] [Indexed: 12/21/2022]
Abstract
Trans-cranial magnetic stimulation (TMS) can noninvasively modulate specific brain regions to dissipate symptoms in treatment-resistant schizophrenia (TRS). Citing impaired resting state connectivity between cerebellum and prefrontal cortex in schizophrenia, we aimed to study the effect of intermittent theta burst stimulation (iTBS) targeting midline cerebellum in TRS subjects on a randomized rater blinded placebo control study design. In this study, 36 patients were randomly allocated (using block randomization method) to active and sham iTBS groups. They were scheduled to receive ten iTBS sessions, two per day (total of 1200 pulses) for 5 days in a week. The Positive and Negative Syndrome Scale (PANSS), Brief Psychiatric Rating Scale (BPRS), Schizophrenia Cognition Rating Scale (SCoRS), Simpson-Angus Extrapyramidal Side Effects Scale (SAS), and Clinical Global Impression (CGI) were assessed at baseline, after last session, and at 2 weeks post-rTMS. Thirty patients (16 and 14 in active and sham groups) completed the study. Intention to treat analysis (ITT) using mixed (growth curve) model analysis was conducted. No significant group (active vs sham) × time (pretreatment–end of 10th session–end of 2 weeks post iTBS) interaction was found for any of the variable. No major side effects were reported. Our study fails to show a significant effect of intensive cerebellar iTBS (iCiTBS) on schizophrenia psychopathology, cognitive functions, and global improvement, compared with sham stimulation, in treatment resistant cases. However, we conclude that it is safe and well tolerated. Trials using better localization technique with large sample, longer duration, and better dosing protocols are needed.
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Dong D, Luo C, Guell X, Wang Y, He H, Duan M, Eickhoff SB, Yao D. Compression of Cerebellar Functional Gradients in Schizophrenia. Schizophr Bull 2020; 46:1282-1295. [PMID: 32144421 PMCID: PMC7505192 DOI: 10.1093/schbul/sbaa016] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Our understanding of cerebellar involvement in brain disorders has evolved from motor processing to high-level cognitive and affective processing. Recent neuroscience progress has highlighted hierarchy as a fundamental principle for the brain organization. Despite substantial research on cerebellar dysfunction in schizophrenia, there is a need to establish a neurobiological framework to better understand the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellum in schizophrenia. To help to establish such a framework, we investigated the abnormalities in the distribution of sensorimotor-supramodal hierarchical processing topography in the cerebellum and cerebellar-cerebral circuits in schizophrenia using a novel gradient-based resting-state functional connectivity (FC) analysis (96 patients with schizophrenia vs 120 healthy controls). We found schizophrenia patients showed a compression of the principal motor-to-supramodal gradient. Specifically, there were increased gradient values in sensorimotor regions and decreased gradient values in supramodal regions, resulting in a shorter distance (compression) between the sensorimotor and supramodal poles of this gradient. This pattern was observed in intra-cerebellar, cerebellar-cerebral, and cerebral-cerebellar FC. Further investigation revealed hyper-connectivity between sensorimotor and cognition areas within cerebellum, between cerebellar sensorimotor and cerebral cognition areas, and between cerebellar cognition and cerebral sensorimotor areas, possibly contributing to the observed compressed pattern. These findings present a novel mechanism that may underlie the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellar and cerebro-cerebellar circuits in schizophrenia. Within this framework of abnormal motor-to-supramodal organization, a cascade of impairments stemming from disrupted low-level sensorimotor system may in part account for high-level cognitive cerebellar dysfunction in schizophrenia.
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Affiliation(s)
- Debo Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Department of Psychiatry, The Fourth People’s Hospital of Chengdu, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Xavier Guell
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
- Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Yulin Wang
- Faculty of Psychological and Educational Sciences, Department of Experimental and Applied Psychology, Vrije Universiteit Brussel, Brussels, Belgium
- Faculty of Psychology and Educational Sciences, Department of Data Analysis, Ghent University, Ghent, Belgium
| | - Hui He
- Department of Psychiatry, The Fourth People’s Hospital of Chengdu, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- Department of Psychiatry, The Fourth People’s Hospital of Chengdu, Chengdu, China
| | - Simon B Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - 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, China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, China
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Yao Y, He H, Duan M, Li S, Li C, Chen X, Yao G, Chang X, Shu H, Wang H, Luo C. The Effects of Music Intervention on Pallidum-DMN Circuit of Schizophrenia. BIOMED RESEARCH INTERNATIONAL 2020; 2020:4107065. [PMID: 33015164 PMCID: PMC7525302 DOI: 10.1155/2020/4107065] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Revised: 11/04/2019] [Accepted: 12/03/2019] [Indexed: 11/20/2022]
Abstract
Music intervention has been applied to improve symptoms of schizophrenic subjects as a complementary treatment in medicine. Although the psychiatric symptoms, especially for motivation and emotion, could be increased in schizophrenia, the underlying neural mechanisms remain poorly understood. We employed a longitudinal study to measure the alteration of striatum functional networks in schizophrenic subjects undergoing Mozart music listening using resting-state functional magnetic resonance imaging (fMRI). Forty-five schizophrenic inpatients were recruited and randomly assigned to two groups. Under the standard care with antipsychotic medication, one group received music intervention for 1 month and the other group is set as control. Both schizophrenic groups were compared to healthy subjects. Resting-state fMRI was acquired from schizophrenic subjects at baseline and after one-month music intervention and from healthy subjects at baseline. Striatum network was assessed through seed-based static and dynamic functional connectivity (FC) analyses. After music intervention, increased static FC was observed between pallidum and ventral hippocampus in schizophrenic subjects. Increased dynamic FCs were also found between pallidus and subregions of default mode network (DMN), including cerebellum crus and posterior cingulate cortex. Moreover, static pallidus-hippocampus FC increment was positively correlated with the improvement of negative symptoms in schizophrenic subjects. Together, these findings provided evidence that music intervention might have an effect on the FC of the striatum-DMN circuit and might be related to the remission of symptoms of schizophrenia.
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Affiliation(s)
- Yutong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Shicai Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Cheng Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xi Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Haifeng Shu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hongming Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
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Qin Y, Zhang N, Chen Y, Zuo X, Jiang S, Zhao X, Dong L, Li J, Zhang T, Yao D, Luo C. Rhythmic Network Modulation to Thalamocortical Couplings in Epilepsy. Int J Neural Syst 2020; 30:2050014. [PMID: 32308081 DOI: 10.1142/s0129065720500148] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Thalamus interacts with cortical areas, generating oscillations characterized by their rhythm and levels of synchrony. However, little is known of what function the rhythmic dynamic may serve in thalamocortical couplings. This work introduced a general approach to investigate the modulatory contribution of rhythmic scalp network to the thalamo-frontal couplings in juvenile myoclonic epilepsy (JME) and frontal lobe epilepsy (FLE). Here, time-varying rhythmic network was constructed using the adapted directed transfer function between EEG electrodes, and then was applied as a modulator in fMRI-based thalamocortical functional couplings. Furthermore, the relationship between corticocortical connectivity and rhythm-dependent thalamocortical coupling was examined. The results revealed thalamocortical couplings modulated by EEG scalp network have frequency-dependent characteristics. Increased thalamus- sensorimotor network (SMN) and thalamus-default mode network (DMN) couplings in JME were strongly modulated by alpha band. These thalamus-SMN couplings demonstrated enhanced association with SMN-related corticocortical connectivity. In addition, altered theta-dependent and beta-dependent thalamus-frontoparietal network (FPN) couplings were found in FLE. The reduced theta-dependent thalamus-FPN couplings were associated with the decreased FPN-related corticocortical connectivity. This study proposed interactive links between the rhythmic modulation and thalamocortical coupling. The crucial role of SMN and FPN in subcortical-cortical circuit may have implications for intervention in generalized and focal epilepsy.
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Affiliation(s)
- Yun Qin
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Nan Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Xiaojun Zuo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Xiaole Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Tao Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
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Cerebello-cerebral connectivity in idiopathic generalized epilepsy. Eur Radiol 2020; 30:3924-3933. [DOI: 10.1007/s00330-020-06674-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Revised: 12/17/2019] [Accepted: 01/24/2020] [Indexed: 12/24/2022]
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Luo Y, He H, Duan M, Huang H, Hu Z, Wang H, Yao G, Yao D, Li J, Luo C. Dynamic Functional Connectivity Strength Within Different Frequency-Band in Schizophrenia. Front Psychiatry 2020; 10:995. [PMID: 32116820 PMCID: PMC7029741 DOI: 10.3389/fpsyt.2019.00995] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 12/17/2019] [Indexed: 12/18/2022] Open
Abstract
As a complex psychiatric disorder, schizophrenia is interpreted as a "dysconnection" syndrome, which is linked to abnormal integrations in between distal brain regions. Recently, neuroimaging has been widely adopted to investigate how schizophrenia affects brain networks. Furthermore, some studies reported frequency dependence of the abnormalities of functional network in schizophrenia, however, dynamic functional connectivity with frequency dependence is rarely used to explore changes in the whole brain of patients with schizophrenia (SZ). Therefore, in the current study, dynamic functional connectivity strength (dFCS) was performed on resting-state functional magnetic resonance data from 96 SZ patients and 121 healthy controls (HCs) at slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz), and slow-2 (0.198-0.25 Hz) frequency bands and further assessed whether the altered dFCS was correlated to clinical symptoms in SZ patients. Results revealed that decreased dFCS of schizophrenia were found in salience, auditory, sensorimotor, visual networks, while increased dFCS in cerebellum, basal ganglia, and prefrontal networks were observed across different frequency bands. Specifically, the thalamus subregion of schizophrenic patients exhibited enhanced dynamic FCS in slow-5 and slow-4, while reduced in slow-3. Moreover, in slow-5 and slow-4, significant interaction effects between frequency and group were observed in the left calcarine cortex, the bilateral inferior orbitofrontal gyrus, and anterior cingulum cortex (ACC). Furthermore, the altered dFCS of insula, thalamus (THA), calcarine cortex, orbitofrontal gyrus, and paracentral lobule were partial correlated with clinical symptoms of SZ patients in slow-5 and slow-4 bands. These results demonstrate the abnormalities of dFCS in schizophrenia patients is rely on different frequency bands and may provide potential implications for exploring the neuropathological mechanism of schizophrenia.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
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