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Yang KC, Yang BH, Liu MN, Liou YJ, Chou YH. Cognitive impairment in schizophrenia is associated with prefrontal-striatal functional hypoconnectivity and striatal dopaminergic abnormalities. J Psychopharmacol 2024; 38:515-525. [PMID: 38853592 DOI: 10.1177/02698811241257877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
BACKGROUND A better understanding of the mechanisms underlying cognitive impairment in schizophrenia is imperative, as it causes poor functional outcomes and a lack of effective treatments. AIMS This study aimed to investigate the relationships of two proposed main pathophysiology of schizophrenia, altered prefrontal-striatal connectivity and the dopamine system, with cognitive impairment and their interactions. METHODS Thirty-three patients with schizophrenia and 27 healthy controls (HCs) who are right-handed and matched for age and sex were recruited. We evaluated their cognition, functional connectivity (FC) between the dorsolateral prefrontal cortex (DLPFC)/middle frontal gyrus (MiFG) and striatum, and the availability of striatal dopamine transporter (DAT) using a cognitive battery investigating attention, memory, and executive function, resting-state functional magnetic resonance imaging with group independent component analysis and single-photon emission computed tomography with 99mTc-TRODAT. RESULTS Patients with schizophrenia exhibited poorer cognitive performance, reduced FC between DLPFC/MiFG and the caudate nucleus (CN) or putamen, decreased DAT availability in the left CN, and decreased right-left DAT asymmetry in the CN compared to HCs. In patients with schizophrenia, altered imaging markers are associated with cognitive impairments, especially the relationship between DLPFC/MiFG-putamen FC and attention and between DAT asymmetry in the CN and executive function. CONCLUSIONS This study is the first to demonstrate how prefrontal-striatal hypoconnectivity and altered striatal DAT markers are associated with different domains of cognitive impairment in schizophrenia. More research is needed to evaluate their complex relationships and potential therapeutic implications.
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Affiliation(s)
- Kai-Chun Yang
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Bang-Hung Yang
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Mu-N Liu
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ying-Jay Liou
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yuan-Hwa Chou
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Psychiatry, Taichung Veterans General Hospital, Taichung, Taiwan
- The Human Brain Research Center, Taichung Veterans General Hospital, Taichung, Taiwan
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Kobayashi H, Sasabayashi D, Takahashi T, Furuichi A, Kido M, Takayanagi Y, Noguchi K, Suzuki M. The relationship between gray/white matter contrast and cognitive performance in first-episode schizophrenia. Cereb Cortex 2024; 34:bhae009. [PMID: 38265871 DOI: 10.1093/cercor/bhae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 01/04/2024] [Accepted: 01/04/2024] [Indexed: 01/26/2024] Open
Abstract
Previous postmortem brain studies have revealed disturbed myelination in the intracortical regions in patients with schizophrenia, possibly reflecting anomalous brain maturational processes. However, it currently remains unclear whether this anomalous myelination is already present in early illness stages and/or progresses during the course of the illness. In this magnetic resonance imaging study, we examined gray/white matter contrast (GWC) as a potential marker of intracortical myelination in 63 first-episode schizophrenia (FESz) patients and 77 healthy controls (HC). Furthermore, we investigated the relationships between GWC findings and clinical/cognitive variables in FESz patients. GWC in the bilateral temporal, parietal, occipital, and insular regions was significantly higher in FESz patients than in HC, which was partly associated with the durations of illness and medication, the onset age, and lower executive and verbal learning performances. Because higher GWC implicates lower myelin in the deeper layers of the cortex, these results suggest that schizophrenia patients have less intracortical myelin at the time of their first psychotic episode, which underlies lower cognitive performance in early illness stages.
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Affiliation(s)
- Haruko Kobayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Mikio Kido
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Kido Clinic, 244 Honoki, Imizu City, Toyama, 934-0053, Japan
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Arisawabashi Hospital, 5-5 Hane-Shin, Fuchu-Machi, Toyama, 939-2704, Japan
| | - Kyo Noguchi
- Department of Radiology, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
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Shao T, Huang J, Zhao Y, Wang W, Tian X, Hei G, Kang D, Gao Y, Liu F, Zhao J, Liu B, Yuan TF, Wu R. Metformin improves cognitive impairment in patients with schizophrenia: associated with enhanced functional connectivity of dorsolateral prefrontal cortex. Transl Psychiatry 2023; 13:315. [PMID: 37821461 PMCID: PMC10567690 DOI: 10.1038/s41398-023-02616-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/21/2023] [Accepted: 09/26/2023] [Indexed: 10/13/2023] Open
Abstract
Cognitive impairment is a core feature of schizophrenia, which is aggravated by antipsychotics-induced metabolic disturbance and lacks effective pharmacologic treatments in clinical practice. Our previous study demonstrated the efficiency of metformin in alleviating metabolic disturbance following antipsychotic administration. Here we report that metformin could ameliorate cognitive impairment and improve functional connectivity (FC) in prefrontal regions. This is an open-labeled, evaluator-blinded study. Clinically stable patients with schizophrenia were randomly assigned to receive antipsychotics plus metformin (N = 48) or antipsychotics alone (N = 24) for 24 weeks. The improvement in cognition was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Its association with metabolic measurements, and voxel-wise whole-brain FC with dorsolateral prefrontal cortex (DLPFC) subregions as seeds were evaluated. When compared to the antipsychotics alone group, the addition of metformin resulted in significantly greater improvements in the MCCB composite score, speed of processing, working memory, verbal learning, and visual learning. A significant time × group interaction effect of increased FC between DLPFC and the anterior cingulate cortex (ACC)/middle cingulate cortex (MCC), and between DLPFC subregions were observed after metformin treatment, which was positively correlated with MCCB cognitive performance. Furthermore, the FC between left DLPFC A9/46d to right ACC/MCC significantly mediated metformin-induced speed of processing improvement; the FC between left A46 to right ACC significantly mediated metformin-induced verbal learning improvement. Collectively, these findings demonstrate that metformin can improve cognitive impairments in schizophrenia patients and is partly related to the FC changes in the DLPFC. Trial Registration: The trial was registered with ClinicalTrials.gov (NCT03271866). The full trial protocol is provided in Supplementary Material.
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Affiliation(s)
- Tiannan Shao
- 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, PR China
| | - Jing Huang
- 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, PR China
| | - Yuxin Zhao
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, PR China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, PR China
| | - Weiyan Wang
- 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, PR China
| | - Xiaohan Tian
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, PR China
| | - Gangrui Hei
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
| | - Dongyu Kang
- 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, PR China
| | - Yong Gao
- Department of Orthopedics, The First People's Hospital of Changde, Changde Hospital Affiliated to Xiangya Medical College of Central South University, Changde, 415900, PR China
| | - Fangkun Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, PR China
| | - Jingping Zhao
- 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, PR China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, PR China
| | - Ti-Fei Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
- Co-innovation Center of Neuroregeneration, Nantong University, Nantong, 226001, PR China
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, 200434, PR China
| | - Renrong Wu
- 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, PR China.
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Xue K, Chen J, Wei Y, Chen Y, Han S, Wang C, Zhang Y, Song X, Cheng J. Impaired large-scale cortico-hippocampal network connectivity, including the anterior temporal and posterior medial systems, and its associations with cognition in patients with first-episode schizophrenia. Front Neurosci 2023; 17:1167942. [PMID: 37342466 PMCID: PMC10277613 DOI: 10.3389/fnins.2023.1167942] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 05/08/2023] [Indexed: 06/23/2023] Open
Abstract
Background and objective The cortico-hippocampal network is an emerging neural framework with striking evidence that it supports cognition in humans, especially memory; this network includes the anterior temporal (AT) system, the posterior medial (PM) system, the anterior hippocampus (aHIPPO), and the posterior hippocampus (pHIPPO). This study aimed to detect aberrant patterns of functional connectivity within and between large-scale cortico-hippocampal networks in first-episode schizophrenia patients compared with a healthy control group via resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the correlations of these aberrant patterns with cognition. Methods A total of 86 first-episode, drug-naïve schizophrenia patients and 102 healthy controls (HC) were recruited to undergo rs-fMRI examinations and clinical evaluations. We conducted large-scale edge-based network analysis to characterize the functional architecture of the cortico-hippocampus network and investigate between-group differences in within/between-network functional connectivity. Additionally, we explored the associations of functional connectivity (FC) abnormalities with clinical characteristics, including scores on the Positive and Negative Syndrome Scale (PANSS) and cognitive scores. Results Compared with the HC group, schizophrenia patients exhibited widespread alterations to within-network FC of the cortico-hippocampal network, with decreases in FC involving the precuneus (PREC), amygdala (AMYG), parahippocampal cortex (PHC), orbitofrontal cortex (OFC), perirhinal cortex (PRC), retrosplenial cortex (RSC), posterior cingulate cortex (PCC), angular gyrus (ANG), aHIPPO, and pHIPPO. Schizophrenia patients also showed abnormalities in large-scale between-network FC of the cortico-hippocampal network, in the form of significantly decreased FC between the AT and the PM, the AT and the aHIPPO, the PM and the aHIPPO, and the aHIPPO and the pHIPPO. A number of these signatures of aberrant FC were correlated with PANSS score (positive, negative, and total score) and with scores on cognitive test battery items, including attention/vigilance (AV), working memory (WM), verbal learning and memory (Verb_Lrng), visual learning and memory (Vis_Lrng), reasoning and problem-solving (RPS), and social cognition (SC). Conclusion Schizophrenia patients show distinct patterns of functional integration and separation both within and between large-scale cortico-hippocampal networks, reflecting a network imbalance of the hippocampal long axis with the AT and PM systems, which regulate cognitive domains (mainly Vis_Lrng, Verb_Lrng, WM, and RPS), and particularly involving alterations to FC of the AT system and the aHIPPO. These findings provide new insights into the neurofunctional markers of schizophrenia.
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Affiliation(s)
- Kangkang Xue
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Jingli Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Xueqin Song
- Department of Psychiatry, 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
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
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Impact of low-frequency repetitive transcranial magnetic stimulation on functional network connectivity in schizophrenia patients with auditory verbal hallucinations. Psychiatry Res 2023; 320:114974. [PMID: 36587467 DOI: 10.1016/j.psychres.2022.114974] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/10/2022] [Accepted: 11/19/2022] [Indexed: 11/22/2022]
Abstract
Auditory verbal hallucinations (AVH) are a key symptom of schizophrenia. Low-frequency repetitive transcranial magnetic stimulation (rTMS) has shown potential in the treatment of AVH. However, the underlying neural mechanismof rTMS in the treatment of AVH remains largely unknown. In this study, we used a static and dynamic functional network connectivity approach to investigate the connectivity changes among the brain functional networks in schizophrenia patients with AVH receiving 1 Hz rTMS treatment. The static functional network connectivity (sFNC) analysis revealed that patients at baseline had significantly decreased connectivity between the default mode network (DMN) and language network (LAN), and within the executive control network (ECN) as well as within the auditory network (AUD) compared to controls. However, the abnormal network connectivity patterns were normalized or restored after rTMS treatment in patients, instead of increased connectivity between the ECN and LAN, as well as within the AUD. Moreover, the dynamic functional network connectivity (dFNC) analysis showed that the patients at baseline spent more time in this state that was characterized by strongly negative connectivity between the ENC and AUD, as well as within the AUD relative to controls. While after rTMS treatment, the patients showed a higher occurrence rate in this state that was characterized by strongly positive connectivity among the LAN, DMN, and ENC, as well as within the ECN. In addition, the altered static and dynamic connectivity properties were associated with reduced severity of clinical symptoms. Both sFNC and dFNC analyses provided complementary information and suggested that low-frequency rTMS treatment could induce intrinsic functional network alternations and contribute to improvements in clinical symptoms in patients with AVH.
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Huang H, Zhang B, Mi L, Liu M, Chang X, Luo Y, Li C, He H, Zhou J, Yang R, Li H, Jiang S, Yao D, Li Q, Duan M, Luo C. Reconfiguration of Functional Dynamics in Cortico-Thalamo-Cerebellar Circuit in Schizophrenia Following High-Frequency Repeated Transcranial Magnetic Stimulation. Front Hum Neurosci 2022; 16:928315. [PMID: 35959244 PMCID: PMC9359206 DOI: 10.3389/fnhum.2022.928315] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/22/2022] [Indexed: 11/20/2022] Open
Abstract
Schizophrenia is a serious mental illness characterized by a disconnection between brain regions. Transcranial magnetic stimulation is a non-invasive brain intervention technique that can be used as a new and safe treatment option for patients with schizophrenia with drug-refractory symptoms, such as negative symptoms and cognitive impairment. However, the therapeutic effects of transcranial magnetic stimulation remain unclear and would be investigated using non-invasive tools, such as functional connectivity (FC). A longitudinal design was adopted to investigate the alteration in FC dynamics using a dynamic functional connectivity (dFC) approach in patients with schizophrenia following high-frequency repeated transcranial magnetic stimulation (rTMS) with the target at the left dorsolateral prefrontal cortex (DLPFC). Two groups of schizophrenia inpatients were recruited. One group received a 4-week high-frequency rTMS together with antipsychotic drugs (TSZ, n = 27), while the other group only received antipsychotic drugs (DSZ, n = 26). Resting-state functional magnetic resonance imaging (fMRI) and psychiatric symptoms were obtained from the patients with schizophrenia twice at baseline (t1) and after 4-week treatment (t2). The dynamics was evaluated using voxel- and region-wise FC temporal variability resulting from fMRI data. The pattern classification technique was used to verify the clinical application value of FC temporal variability. For the voxel-wise FC temporary variability, the repeated measures ANCOVA analysis showed significant treatment × time interaction effects on the FC temporary variability between the left DLPFC and several regions, including the thalamus, cerebellum, precuneus, and precentral gyrus, which are mainly located within the cortico-thalamo-cerebellar circuit (CTCC). For the ROI-wise FC temporary variability, our results found a significant interaction effect on the FC among CTCC. rTMS intervention led to a reduced FC temporary variability. In addition, higher alteration in FC temporal variability between left DLPFC and right posterior parietal thalamus predicted a higher remission ratio of negative symptom scores, indicating that the decrease of FC temporal variability between the brain regions was associated with the remission of schizophrenia severity. The support vector regression (SVR) results suggested that the baseline pattern of FC temporary variability between the regions in CTCC could predict the efficacy of high-frequency rTMS intervention on negative symptoms in schizophrenia. These findings confirm the potential relationship between the reduction in whole-brain functional dynamics induced by high-frequency rTMS and the improvement in psychiatric scores, suggesting that high-frequency rTMS affects psychiatric symptoms by coordinating the heterogeneity of activity between the brain regions. Future studies would examine the clinical utility of using functional dynamics patterns between specific brain regions as a biomarker to predict the treatment response of high-frequency rTMS.
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Affiliation(s)
- Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bei Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Mi
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Meiqing Liu
- Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Li
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ruikun Yang
- University of Science and Technology Beijing, Beijing, China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, China
- Research Unit of Neuroinformation, Chinese Academy of Medical Sciences, Chengdu, China
| | - Qifu Li
- Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, China
- *Correspondence: Qifu Li,
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of Neuroinformation, Chinese Academy of Medical Sciences, Chengdu, China
- Mingjun Duan,
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of Neuroinformation, Chinese Academy of Medical Sciences, Chengdu, China
- Cheng Luo,
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7
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Reardon AM, Li K, Hu XP. Improving Between-Group Effect Size for Multi-Site Functional Connectivity Data via Site-Wise De-Meaning. Front Comput Neurosci 2021; 15:762781. [PMID: 34924984 PMCID: PMC8674307 DOI: 10.3389/fncom.2021.762781] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 11/04/2021] [Indexed: 11/18/2022] Open
Abstract
Background: Multi-site functional MRI (fMRI) databases are becoming increasingly prevalent in the study of neurodevelopmental and psychiatric disorders. However, multi-site databases are known to introduce site effects that may confound neurobiological and measures such as functional connectivity (FC). Although studies have been conducted to mitigate site effects, these methods often result in reduced effect size in FC comparisons between controls and patients. Methods: We present a site-wise de-meaning (SWD) strategy in multi-site FC analysis and compare its performance with two common site-effect mitigation methods, i.e., generalized linear model (GLM) and Combining Batches (ComBat) Harmonization. For SWD, after FC was calculated and Fisher z-transformed, the site-wise FC mean was removed from each subject before group-level statistical analysis. The above methods were tested on two multi-site psychiatric consortiums [Autism Brain Imaging Data Exchange (ABIDE) and Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP)]. Preservation of consistent FC alterations in patients were evaluated for each method through the effect sizes (Hedge’s g) of patients vs. controls. Results: For the B-SNIP dataset, SWD improved the effect size between schizophrenic and control subjects by 4.5–7.9%, while GLM and ComBat decreased the effect size by 22.5–42.6%. For the ABIDE dataset, SWD improved the effect size between autistic and control subjects by 2.9–5.3%, while GLM and ComBat decreased the effect size by up to 11.4%. Conclusion: Compared to the original data and commonly used methods, the SWD method demonstrated superior performance in preserving the effect size in FC features associated with disorders.
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Affiliation(s)
- Alexandra M Reardon
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States
| | - Kaiming Li
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States
| | - Xiaoping P Hu
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States.,Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States
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Gao J, Tang X, Wang C, Yu M, Sha W, Wang X, Zhang H, Zhang X, Zhang X. Aberrant cerebellar neural activity and cerebro-cerebellar functional connectivity involving executive dysfunction in schizophrenia with primary negative symptoms. Brain Imaging Behav 2021; 14:869-880. [PMID: 30612342 DOI: 10.1007/s11682-018-0032-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Deficit schizophrenia (DS) is a distinct subtype of schizophrenia characterized by primary and enduring negative symptoms. More severe executive dysfunctions were observed in DS patients, however, the associated neuroimaging characteristics, especially cerebellar functional anomalies in DS, remain largely unknown. We employed resting-state functional and structural MRI data of 106 male participants, including data from 29 DS patients, 39 non-deficit schizophrenia (NDS) patients and 38 healthy controls (HCs). Z-standardized fractional amplitude of low-frequency fluctuation (zfALFF) values were calculated in order to examine spontaneous regional brain activity. Cerebro-cerebellar functional connectivity and changes in the volume of gray matter in the cerebellum were also examined. Relative to the HCs, both DS and NDS patients exhibited decreased zfALFF in the bilateral cerebellar lobules VIII and IX. The zfALFF in the left Crus II was lower in DS patients compared to NDS patients. No significant difference was observed in the volume of cerebellar gray matter among the three groups. Compared with NDS patients, cerebro-cerebellar functional connectivity analysis revealed increased connectivity in the left orbital medial frontal cortex and right putamen regions in DS patients. Reduced zfALFF in the left Crus II in the DS group was significantly positively correlated with Stroop Color and Word scores, while negatively correlated with Trail-Making Test part B scores. The increased functional connectivity in the right putamen in DS patients was significantly positively correlated with Animal Naming Test and semantic Verbal Fluency Test scores. These results highlight cerebellar functional abnormality in DS patients and provide insight into the pathophysiological mechanism of executive dysfunction.
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Affiliation(s)
- Ju Gao
- Department of Geriatric Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, 210029, Jiangsu, China.,Department I of Geriatric Psychiatry, Shanghai Changning Mental Health Center, Shanghai, 200335, China
| | - Xiaowei Tang
- Department of Geriatric Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, 210029, Jiangsu, China.,Department of Psychiatry, Wutaishan Hospital of Yangzhou, Yangzhou, 225003, Jiangsu Province, China
| | - Congjie Wang
- Department of Psychiatry, Huai'an No. 3 People's Hospital, Huai'an, 223001, Jiangsu, China
| | - Miao Yu
- Department of Geriatric Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Weiwei Sha
- Department of Psychiatry, Wutaishan Hospital of Yangzhou, Yangzhou, 225003, Jiangsu Province, China
| | - Xiang Wang
- Medical Psychological Institute of the Second Xiangya Hospital, Changsha, 410011, Hunan, China
| | - Hongying Zhang
- Department of Radiology, Subei People's Hospital of Jiangsu province, Yangzhou, 225001, Jiangsu, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
| | - Xiaobin Zhang
- Department of Psychiatry, Wutaishan Hospital of Yangzhou, Yangzhou, 225003, Jiangsu Province, China.
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9
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Wang Y, Wei Y, Edmiston EK, Womer FY, Zhang X, Duan J, Zhu Y, Zhang R, Yin Z, Zhang Y, Jiang X, Wei S, Liu Z, Zhang Y, Tang Y, Wang F. Altered structural connectivity and cytokine levels in Schizophrenia and Genetic high-risk individuals: Associations with disease states and vulnerability. Schizophr Res 2020; 223:158-165. [PMID: 32684357 DOI: 10.1016/j.schres.2020.05.044] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 03/26/2020] [Accepted: 05/17/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Alterations of white matter (WM) integrity have been observed in both schizophrenia (SZ) and individuals at genetic high risk for SZ (GHR-SZ); however, the molecular mechanisms underlying WM disruption remain unclear. Cytokines are chemical messengers of the immune system that are closely related to inflammation and neurogenesis in the brain. This study aimed to identify abnormalities in WM integrity, cytokine levels, and their association in SZ and GHR-SZ. METHODS A total of 355 participants (126 with SZ, 99 GHR-SZ, and 130 healthy controls [HCs]) were recruited. All participants underwent diffusion tensor imaging and blood samples were obtained from 113 participants within 24 h of imaging. RESULTS In SZ, there was decreased fractional anisotropy(FA) in the genu and body of the corpus callosum (GCC/BCC), anterior corona radiata, anterior and posterior limbs of the internal capsule (ALIC/PLIC), superior fronto-occipital fasciculus, external capsule, and fornix, and elevated IL-6 levels. In both SZ and GHR-SZ, decreased FA in the splenium of the corpus callosum (SCC), posterior corona radiate (PCR), and posterior thalamic radiation (PTR) was observed, and elevated leptin levels were present. Additionally, the IL-6 levels were negatively correlated with FA in the GCC and ALIC in SZ, and leptin levels were negatively correlated with the SCC, PCR, and PTR in SZ and GHR-SZ. CONCLUSIONS Abnormal WM integrity in SZ may reflect the state of disease and is associated with increased IL-6 levels. In addition, these leptin-associated WM integrity abnormalities in both SZ and GHR-SZ may reflect a genetic vulnerability to SZ.
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Affiliation(s)
- Yang Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Yange Wei
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - E Kale Edmiston
- Department of Psychiatry, University of Pittsburgh Medical Center, USA
| | - Fay Y Womer
- Department of Psychiatry, Washington University School of Medicine, St. Louis, USA
| | - Xizhe Zhang
- School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, PR China
| | - Jia Duan
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Yue Zhu
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Ran Zhang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Zhiyang Yin
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Yifan Zhang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Xiaowei Jiang
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Shengnan Wei
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Zhuang Liu
- School of Public Health, China Medical University, Shenyang, Liaoning, PR China
| | - Yanbo Zhang
- Department of Psychiatry, College of Medicine, University of Saskatchewan, Canada
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
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Liu S, Li A, Liu Y, Li J, Wang M, Sun Y, Qin W, Yu C, Jiang T, Liu B. MIR137 polygenic risk is associated with schizophrenia and affects functional connectivity of the dorsolateral prefrontal cortex. Psychol Med 2020; 50:1510-1518. [PMID: 31239006 DOI: 10.1017/s0033291719001442] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Genome-wide association studies (GWAS) have consistently revealed that a variant of microRNA 137 (MIR137) shows a quite significant association with schizophrenia. Identifying the network of genes regulated by MIR137 could provide insights into the biological processes underlying schizophrenia. In addition, DLPFC functional connectivity, a robust correlate of MIR137, may provide plausible endophenotypes. However, the regulatory role of the MIR137 gene network in the disrupted functional connectivity remains unclear. Here, we tested the effects of the MIR137 regulated genes on the risk for schizophrenia and DLPFC functional connectivity. METHODS To evaluate the additive effects of the MIR137 regulated genes (N = 1274), we calculated a MIR137 polygenic risk score (PRS) for schizophrenia and tested its association with the risk for schizophrenia in the genomic data of a Han Chinese population that included schizophrenia patients (N = 589) and normal controls (N = 575). We then investigated the association between MIR137 PRS and DLPFC functional connectivity in two independent young healthy cohorts (N = 356 and N = 314). RESULTS We found that the MIR137 PRS successfully captured the differences in genetic structure between the patients and controls, but the single gene MIR137 did not. We then consistently found that a higher MIR137 PRS was correlated with lower functional connectivities between the DLPFC and both the superior parietal cortex and the inferior temporal cortex in two independent cohorts. CONCLUSION The findings suggested that these two functional connectivities of the DLPFC could be important endophenotypes linking the MIR137-regulated genetic structure to schizophrenia.
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Affiliation(s)
- Shu Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Ang Li
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Yong Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
| | - Jin Li
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Meng Wang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Yuqing Sun
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Wen Qin
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin300052, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin300052, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu610054, China
- Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
| | - Bing Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China
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11
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Weiss F, Zamoscik V, Schmidt SN, Halli P, Kirsch P, Gerchen MF. Just a very expensive breathing training? Risk of respiratory artefacts in functional connectivity-based real-time fMRI neurofeedback. Neuroimage 2020; 210:116580. [DOI: 10.1016/j.neuroimage.2020.116580] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/15/2020] [Accepted: 01/20/2020] [Indexed: 10/25/2022] Open
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12
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Altered neural processing of negative stimuli in people with internet gaming disorder: fMRI evidence from the comparison with recreational game users. J Affect Disord 2020; 264:324-332. [PMID: 32056768 DOI: 10.1016/j.jad.2020.01.008] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 12/19/2019] [Accepted: 01/03/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Abundant clinical studies have suggested that emotion dysregulation seems to be the essential pathogenesis for Internet gaming disorder (IGD). However, the neural mechanism of emotion regulation for IGD is still unclear. METHODS Subjective evaluation and fMRI data were collected from 50 subjects (IGD: 24; recreational game user (RGU): 26) while they were performing an emotion reappraisal task. We collected and compared their brain features during emotion processing of different visual stimuli. RESULTS Higher activation in the left dorsal anterior cingulate cortex (dACC), right ventral ACC, left claustrum and bilateral insula was observed in participants with IGD during emotion reappraisal relative to that of the RGU participants. In addition, generalized psychophysiological interaction analysis also showed that IGD participants had stronger functional connectivity between the right insula and bilateral dorsolateral prefrontal cortex (DLPFC) than the RGU participants. CONCLUSIONS The results suggest that IGD participants could not down-regulate their negative emotional experiences as efficiently as the RGU participants, although they engaged more cognitive resources. These results reveal the special neural circuits of emotion dysregulation in IGD individuals and provide new neural perspective for the intervention of IGD.
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Yan W, Calhoun V, Song M, Cui Y, Yan H, Liu S, Fan L, Zuo N, Yang Z, Xu K, Yan J, Lv L, Chen J, Chen Y, Guo H, Li P, Lu L, Wan P, Wang H, Wang H, Yang Y, Zhang H, Zhang D, Jiang T, Sui J. Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data. EBioMedicine 2019; 47:543-552. [PMID: 31420302 PMCID: PMC6796503 DOI: 10.1016/j.ebiom.2019.08.023] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 08/09/2019] [Accepted: 08/09/2019] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage the full temporal information. METHODS Motivated by the ability of recurrent neural networks (RNN) in capturing dynamic information of time sequences, we propose a multi-scale RNN model, which enables classification between 558 schizophrenia and 542 healthy controls by using time courses of fMRI independent components (ICs) directly. To increase interpretability, we also propose a leave-one-IC-out looping strategy for estimating the top contributing ICs. FINDINGS Accuracies of 83·2% and 80·2% were obtained respectively for the multi-site pooling and leave-one-site-out transfer classification. Subsequently, dorsal striatum and cerebellum components contribute the top two group-discriminative time courses, which is true even when adopting different brain atlases to extract time series. INTERPRETATION This is the first attempt to apply a multi-scale RNN model directly on fMRI time courses for classification of mental disorders, and shows the potential for multi-scale RNN-based neuroimaging classifications. FUND: Natural Science Foundation of China, the Strategic Priority Research Program of the Chinese Academy of Sciences, National Institutes of Health Grants, National Science Foundation.
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Affiliation(s)
- Weizheng Yan
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Vince Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Center, Atlanta 30303, GA, USA
| | - Ming Song
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yue Cui
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hao Yan
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Shengfeng Liu
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lingzhong Fan
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nianming Zuo
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhengyi Yang
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kaibin Xu
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jun Yan
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, Henan, China
| | - Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
| | - Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an 710032, Shaanxi, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, Zhumadian 463000, Henan, China
| | - Peng Li
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Lin Lu
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Ping Wan
- Zhumadian Psychiatric Hospital, Zhumadian 463000, Henan, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an 710032, Shaanxi, China
| | - Huiling Wang
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, Henan, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, Henan, China; Department of Psychology, Xinxiang Medical University, Xinxiang 453002, Henan, China
| | - Dai Zhang
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China; Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Tianzi Jiang
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China; Queensland Brain Institute, University of Queensland, Brisbane 4072, QLD, Australia; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
| | - Jing Sui
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
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Abnormal Neural Activity in Children With Diffuse Intrinsic Pontine Glioma Had Manifested Deficit in Behavioral Inhibition: A Resting-State Functional MRI Study. J Comput Assist Tomogr 2019; 43:547-552. [PMID: 31162235 DOI: 10.1097/rct.0000000000000881] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE The purpose of this study was to investigate whether alterations of regional neural function in children with diffuse intrinsic pontine glioma (DIPG) had manifested deficit in behavioral inhibition using resting-state functional MRI (rs-fMRI). METHODS There were 17 participants with DIPG who took part in the study. Eight children were with deficit in behavioral inhibition, whereas the other 9 children did not obtain deficit in behavioral inhibition. Five healthy children with age, sex, and education matched to the study group also participated as the control group. These 3 groups underwent rs-fMRI, and the results were then converted to amplitude of low-frequency fluctuation (ALFF) data. Amplitude of low-frequency fluctuation data were further analyzed by single-factor analysis of variance comparing among 3 groups based on the whole brain levels. Amplitude of low-frequency fluctuation results were subjected to t test of voxel-wised comparison to derive the rs-fMRI brain function differences between the 2 DIPG groups. The Pearson correlation between ALFF values of abnormal regions found in 3 groups and the scores obtained according to the Child Behavior Checklist were analyzed. RESULTS The 3 groups had shown significant differences in terms of the ALFF results, with the ALFF increased in several brain regions (P < 0.05, corrected with AlphaSim, clusters >59 voxels), which include left supramarginal gyrus, left dorsolateral superior frontal gyrus, right precentral gyrus, and right middle frontal gyrus. Participants with deficit in behavioral inhibition had shown significant differences (ALFF decreased) in several brain regions, including left dorsolateral superior frontal gyrus and right fusiform gyrus (P < 0.05, corrected with AlphaSim, clusters >123 voxels), whereas other brain regions had shown ALFF increased, including left supramarginal gyrus, left middle frontal gyrus, and right medial superior frontal gyrus (P < 0.05, corrected with AlphaSim, clusters >123 voxels). There was no significant correlation between ALFF values and Child Behavior Checklist scores (P > 0.05). CONCLUSIONS These findings of focal spontaneous hyperfunction and hypofunction, which correlate with deficit in behavioral inhibition processing, and the abnormal brain regions are considered to be inefficient (in regions of the brain that may relate to compensatory brain and behavioral functioning, and it may be that the brain region needs to exert extra energy to perform a task to the same degree as the control group) or inability (inability in a certain region, or underpowered), pointing to a pathophysiologic process in executive dysfunction.
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De Simoni S, Jenkins PO, Bourke NJ, Fleminger JJ, Hellyer PJ, Jolly AE, Patel MC, Cole JH, Leech R, Sharp DJ. Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury. Brain 2019; 141:148-164. [PMID: 29186356 PMCID: PMC5837394 DOI: 10.1093/brain/awx309] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2017] [Accepted: 09/25/2017] [Indexed: 11/15/2022] Open
Abstract
Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with measures of executive dysfunction. We show for the first time that altered subcortical connectivity is associated with large-scale network disruption in traumatic brain injury and that this disruption is related to the cognitive impairments seen in these patients.
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Affiliation(s)
- Sara De Simoni
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
| | - Peter O Jenkins
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
| | - Niall J Bourke
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
| | - Jessica J Fleminger
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
| | - Peter J Hellyer
- Department of Bioengineering, Imperial College London, London, UK
| | - Amy E Jolly
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
| | | | - James H Cole
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
| | - Robert Leech
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
| | - David J Sharp
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Division of Brain Sciences, Hammersmith Hospital, London, UK
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16
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Li S, Hu N, Zhang W, Tao B, Dai J, Gong Y, Tan Y, Cai D, Lui S. Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity. Front Psychiatry 2019; 10:482. [PMID: 31354545 PMCID: PMC6639431 DOI: 10.3389/fpsyt.2019.00482] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 06/19/2019] [Indexed: 02/05/2023] Open
Abstract
Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.
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Affiliation(s)
- Siyi Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Na Hu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Dai
- Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, China
| | - Yao Gong
- Department of Geriatric Psychiatry, The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Youguo Tan
- Department of Psychiatry, Zigong Mental Health Center, Zigong, China
| | - Duanfang Cai
- Department of Psychiatry, Zigong Mental Health Center, Zigong, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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17
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Köhler S, Wagner G, Bär KJ. Activation of brainstem and midbrain nuclei during cognitive control in medicated patients with schizophrenia. Hum Brain Mapp 2018; 40:202-213. [PMID: 30184301 DOI: 10.1002/hbm.24365] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 07/27/2018] [Accepted: 08/07/2018] [Indexed: 12/12/2022] Open
Abstract
Evidence suggests that cognitive control functions as well as the underlying brain network, anchored by the prefrontal cortex (PFC) and the dorsal anterior cingulate cortex (dACC), are dysfunctional in schizophrenia. Catecholamine producing midbrain and brainstem nuclei are densely connected with the PFC and dACC and exert profound contributions to cognitive control processes. Dysfunctions within the underlying neurotransmitter systems are considered to play a central role in the occurrence of various symptoms of schizophrenia. We sought to investigate the putatively abnormal activation pattern of the dopaminergic midbrain nuclei, that is, ventral tegmental area (VTA) and substantia nigra as well as that of the noradrenergic locus coeruleus (LC) in patients with schizophrenia during cognitive control. A total of 28 medicated patients and 27 healthy controls were investigated with the manual version of the Stroop task using event-related fMRI. The main finding was a reduced BOLD activation in the VTA during both Stroop task conditions in patients in comparison to controls, which correlated significantly with the degree of negative symptoms. We further detected a comparable LC activation in in patients and healthy controls. However, in controls LC activation was significantly correlated with the Stroop interference time, which was not observed in patients. The finding of reduced VTA activation in schizophrenia patients lends further support to the assumed dysfunction of the DA system in schizophrenia. In addition, despite comparable LC activation, the nonsignificant correlation with the Stroop interference time might indicate altered LC functioning in schizophrenia and, thus, needs further investigations.
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Affiliation(s)
- Stefanie Köhler
- Psychiatric Brain and Body Research Group Jena, Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
| | - Gerd Wagner
- Psychiatric Brain and Body Research Group Jena, Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
| | - Karl-Jürgen Bär
- Psychiatric Brain and Body Research Group Jena, Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
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18
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Dong D, Wang Y, Chang X, Luo C, Yao D. Dysfunction of Large-Scale Brain Networks in Schizophrenia: A Meta-analysis of Resting-State Functional Connectivity. Schizophr Bull 2018; 44:168-181. [PMID: 28338943 PMCID: PMC5767956 DOI: 10.1093/schbul/sbx034] [Citation(s) in RCA: 289] [Impact Index Per Article: 48.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Schizophrenia is a complex mental disorder with disorganized communication among large-scale brain networks, as demonstrated by impaired resting-state functional connectivity (rsFC). Individual rsFC studies, however, vary greatly in their methods and findings. We searched for consistent patterns of network dysfunction in schizophrenia by using a coordinate-based meta-analysis. Fifty-six seed-based voxel-wise rsFC datasets from 52 publications (2115 patients and 2297 healthy controls) were included in this meta-analysis. Then, coordinates of seed regions of interest (ROI) and between-group effects were extracted and coded. Seed ROIs were categorized into seed networks by their location within an a priori template. Multilevel kernel density analysis was used to identify brain networks in which schizophrenia was linked to hyper-connectivity or hypo-connectivity with each a priori network. Our results showed that schizophrenia was characterized by hypo-connectivity within the default network (DN, self-related thought), affective network (AN, emotion processing), ventral attention network (VAN, processing of salience), thalamus network (TN, gating information) and somatosensory network (SS, involved in sensory and auditory perception). Additionally, hypo-connectivity between the VAN and TN, VAN and DN, VAN and frontoparietal network (FN, external goal-directed regulation), FN and TN, and FN and DN were found in schizophrenia. Finally, the only instance of hyper-connectivity in schizophrenia was observed between the AN and VAN. Our meta-analysis motivates an empirical foundation for a disconnected large-scale brain networks model of schizophrenia in which the salience processing network (VAN) plays the core role, and its imbalanced communication with other functional networks may underlie the core difficulty of patients to differentiate self-representation (inner world) and environmental salience processing (outside world).
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Affiliation(s)
- Debo Dong
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yulin Wang
- Faculty of Psychological and Educational Sciences, Department of Experimental and Applied Psychology, Research Group of Biological Psychology, Vrije Universiteit Brussel, Brussels, Belgium
- Faculty of Psychology and Educational Sciences, Department of Data Analysis, Ghent University, Ghent, Belgium
| | - Xuebin Chang
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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19
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Cui LB, Wang LX, Tian P, Wang HN, Cai M, Guo F, Li C, Wu YJ, Qiao PG, Xu ZL, Liu L, He H, Wu WJ, Xi YB, Yin H. Aberrant perfusion and its connectivity within default mode network of first-episode drug-naïve schizophrenia patients and their unaffected first-degree relatives. Sci Rep 2017; 7:16201. [PMID: 29170485 PMCID: PMC5700958 DOI: 10.1038/s41598-017-14343-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Accepted: 10/06/2017] [Indexed: 02/03/2023] Open
Abstract
Neural substrates behind schizophrenia (SZ) and its heritability mediated by brain function are largely unknown. Cerebral blood flow (CBF), as a biomarker of activation in the brain, reflects the neuronal metabolism, and is promisingly used to detect cerebral alteration thereby shedding light on the features of individuals at high genetic risk. We performed a cross-sectional functional magnetic resonance imaging (MRI) study enrolling 45 first-episode drug-naïve patients with SZ, 32 unaffected first-degree relatives of these patients, and 51 healthy controls (HCs). We examined CBF, CBF connectivity, and CBF topological properties. SZ patients showed increased CBF in the left medial superior frontal gyrus and right precuneus compared with HCs, and decreased CBF in the left middle temporal gyrus compared with their relatives. Furthermore, unaffected relatives revealed higher level of CBF pronounced in regions within default mode network (DMN). Both SZ patients and their relatives exhibited dysconnectivity patterns. Notably, as for the network properties, unaffected relatives were with an intermediate level between SZ patients and HCs in the local efficiency and global efficiency. Our findings demonstrate the aberrant CBF of areas within DMN and the CBF connectivity pattern might be a familial feature in the brain of first-episode SZ patients and their relatives.
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Affiliation(s)
- Long-Biao Cui
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
- School of Medical Psychology, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Liu-Xian Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Ping Tian
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Min Cai
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Yu-Jing Wu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Peng-Gang Qiao
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
- Department of Radiology, Affiliated Hospital of the Academy of Military Medical Sciences, Beijing, China
| | - Zi-Liang Xu
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Lin Liu
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Hong He
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
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20
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Chen X, Liu C, He H, Chang X, Jiang Y, Li Y, Duan M, Li J, Luo C, Yao D. Transdiagnostic differences in the resting-state functional connectivity of the prefrontal cortex in depression and schizophrenia. J Affect Disord 2017; 217:118-124. [PMID: 28407554 DOI: 10.1016/j.jad.2017.04.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 02/22/2017] [Accepted: 04/02/2017] [Indexed: 01/06/2023]
Abstract
BACKGROUND Depression and schizophrenia are two of the most serious psychiatric disorders. They share similar symptoms but the pathology-specific commonalities and differences remain unknown. This study was conducted to acquire a full picture of the functional alterations in schizophrenia and depression patients. METHODS The resting-state fMRI data from 20 patients with schizophrenia, 20 patients with depression and 20 healthy control subjects were collected. A data-driven approach that included local functional connectivity density (FCD) analysis combined with multivariate pattern analysis (MVPA) was used to compare the three groups. RESULTS Based on the results of the MVPA, the local FCD value in the orbitofrontal cortex (OFC) can differentiate depression patients from schizophrenia patients. The patients with depression had a higher local FCD value in the medial and anterior parts of the OFC than the subjects in the other two groups, which suggested altered abstract and reward reinforces processing in depression patients. Subsequent functional connectivity analysis indicated that the connection in the prefrontal cortex was significantly lower in people with schizophrenia compared to people with depression and healthy controls. LIMITATION The systematically different medications for schizophrenia and depression may have different effects on functional connectivity. CONCLUSIONS These results suggested that the resting-state functional connectivity pattern in the prefrontal cortex may be a transdiagnostic difference between depression and schizophrenia patients.
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Affiliation(s)
- Xi Chen
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chang Liu
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; College of Information Science and Engineering, Chengdu University, Chengdu 610106, China
| | - Hui He
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xin Chang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuchao Jiang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yingjia Li
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of psychiatry, Chengdu Mental Health Center, Chengdu, China
| | - Jianfu Li
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
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21
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Xu Y, Qin W, Zhuo C, Xu L, Zhu J, Liu X, Yu C. Selective functional disconnection of the orbitofrontal subregions in schizophrenia. Psychol Med 2017; 47:1637-1646. [PMID: 28183367 DOI: 10.1017/s0033291717000101] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND As a disconnection syndrome, schizophrenia has shown impaired resting-state functional connectivity (rsFC) in the orbitofrontal cortex (OFC); however, the OFC is a rather heterogeneous region and the rsFC changes in the OFC subregions remain unknown. METHOD A total of 98 schizophrenia patients and 102 healthy controls underwent resting-state functional MRI using a sensitivity-encoded spiral-in imaging sequence (SENSE-SPIRAL) to reduce susceptibility-induced signal loss and distortion. The OFC subregions were defined according to a previous parcellation study that divided the OFC into the anterior (OFCa), medial (OFCm), posterior (OFCp), intermediate (OFCi), and lateral (OFCl) subregions. The rsFC was compared using two-way repeated-measures ANOVA. RESULTS Whether or not global signal regression, compared with healthy controls, schizophrenia patients consistently exhibited decreased rsFC between the left OFCi and the left middle temporal gyrus and the right middle frontal gyrus (MFG), between the right OFCi and the right MFG and the left inferior frontal gyrus, between the right OFCm and the middle cingulate cortex and the left Rolandic operculum. These rsFC changes still remained significant even after cortical atrophy correction. CONCLUSIONS These findings suggest a selective functional disconnection of the OFC subregions in schizophrenia, and provide more precise information about the functional disconnections of the OFC in this disorder.
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Affiliation(s)
- Y Xu
- Department of Radiology,Tianjin Key Laboratory of Functional Imaging,Tianjin Medical University General Hospital,Tianjin,China
| | - W Qin
- Department of Radiology,Tianjin Key Laboratory of Functional Imaging,Tianjin Medical University General Hospital,Tianjin,China
| | - C Zhuo
- Tianjin Anning Hospital,Tianjin,China
| | - L Xu
- Department of Radiology,Tianjin Key Laboratory of Functional Imaging,Tianjin Medical University General Hospital,Tianjin,China
| | - J Zhu
- Department of Radiology,Tianjin Key Laboratory of Functional Imaging,Tianjin Medical University General Hospital,Tianjin,China
| | - X Liu
- Department of Radiology,Tianjin Key Laboratory of Functional Imaging,Tianjin Medical University General Hospital,Tianjin,China
| | - C Yu
- Department of Radiology,Tianjin Key Laboratory of Functional Imaging,Tianjin Medical University General Hospital,Tianjin,China
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22
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Peeters SCT, Gronenschild EHBM, van Amelsvoort T, van Os J, Marcelis M, Kahn R, Wiersma D, Bruggeman R, Cahn W, de Haan L, Meijer C, Myin-Germeys I. Reduced specialized processing in psychotic disorder: a graph theoretical analysis of cerebral functional connectivity. Brain Behav 2016; 6:e00508. [PMID: 27688938 PMCID: PMC5036431 DOI: 10.1002/brb3.508] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2015] [Revised: 04/24/2016] [Accepted: 04/29/2016] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Previous research has shown that the human brain can be represented as a complex functional network that is characterized by specific topological properties, such as clustering coefficient, characteristic path length, and global/local efficiency. Patients with psychotic disorder may have alterations in these properties with respect to controls, indicating altered efficiency of network organization. This study examined graph theoretical changes in relation to differential genetic risk for the disorder and aimed to identify clinical correlates. METHODS Anatomical and resting-state MRI brain scans were obtained from 73 patients with psychotic disorder, 83 unaffected siblings, and 72 controls. Topological measures (i.e., clustering coefficient, characteristic path length, and small-worldness) were used as dependent variables in a multilevel random regression analysis to investigate group differences. In addition, associations with (subclinical) psychotic/cognitive symptoms were examined. RESULTS Patients had a significantly lower clustering coefficient compared to siblings and controls, with no difference between the latter groups. No group differences were observed for characteristic path length and small-worldness. None of the topological properties were associated with (sub)clinical psychotic and cognitive symptoms. CONCLUSIONS The reduced ability for specialized processing (reflected by a lower clustering coefficient) within highly interconnected brain regions observed in the patient group may indicate state-related network alterations. There was no evidence for an intermediate phenotype and no evidence for psychopathology-related alterations.
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Affiliation(s)
- Sanne C T Peeters
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands; Faculty of Psychology and Educational Sciences Open University of the Netherlands Heerlen The Netherlands
| | - Ed H B M Gronenschild
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Therese van Amelsvoort
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Jim van Os
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands; Department of Psychosis Studies Institute of Psychiatry King's Health Partners King's College London London UK
| | - Machteld Marcelis
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands; Institute for Mental Health Care Eindhoven (GGzE) Eindhoven The Netherlands
| | | | - Rene Kahn
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Durk Wiersma
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Richard Bruggeman
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Lieuwe de Haan
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Carin Meijer
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
| | - Inez Myin-Germeys
- Department of Psychiatry & Neuropsychology School for Mental Health and Neuroscience EURON Maastricht University Medical Center PO Box 616 6200 MD Maastricht The Netherlands
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23
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Xi YB, Li C, Cui LB, Liu J, Guo F, Li L, Liu TT, Liu K, Chen G, Xi M, Wang HN, Yin H. Anterior Cingulate Cortico-Hippocampal Dysconnectivity in Unaffected Relatives of Schizophrenia Patients: A Stochastic Dynamic Causal Modeling Study. Front Hum Neurosci 2016; 10:383. [PMID: 27512370 PMCID: PMC4961710 DOI: 10.3389/fnhum.2016.00383] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2016] [Accepted: 07/14/2016] [Indexed: 11/13/2022] Open
Abstract
Familial risk plays a significant role in the etiology of schizophrenia (SZ). Many studies using neuroimaging have demonstrated structural and functional alterations in relatives of SZ patients, with significant results found in diverse brain regions involving the anterior cingulate cortex (ACC), caudate, dorsolateral prefrontal cortex (DLPFC), and hippocampus. This study investigated whether unaffected relatives of first episode SZ differ from healthy controls (HCs) in effective connectivity measures among these regions. Forty-six unaffected first-degree relatives of first episode SZ patients-according to the DSM-IV-were studied. Fifty HCs were included for comparison. All subjects underwent resting state functional magnetic resonance imaging (fMRI). We used stochastic dynamic causal modeling (sDCM) to estimate the directed connections between the left ACC, right ACC, left caudate, right caudate, left DLPFC, left hippocampus, and right hippocampus. We used Bayesian parameter averaging (BPA) to characterize the differences. The BPA results showed hyperconnectivity from the left ACC to right hippocampus and hypoconnectivity from the right ACC to right hippocampus in SZ relatives compared to HCs. The pattern of anterior cingulate cortico-hippocampal connectivity in SZ relatives may be a familial feature of SZ risk, appearing to reflect familial susceptibility for SZ.
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Affiliation(s)
- Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Long-Biao Cui
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Jian Liu
- Network Center, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Liang Li
- School of Biomedical Engineering, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Ting-Ting Liu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Kang Liu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Gang Chen
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Min Xi
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University Xi'an, Shaanxi, China
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Sasabayashi D, Takayanagi Y, Nishiyama S, Takahashi T, Furuichi A, Kido M, Nishikawa Y, Nakamura M, Noguchi K, Suzuki M. Increased Frontal Gyrification Negatively Correlates with Executive Function in Patients with First-Episode Schizophrenia. Cereb Cortex 2016; 27:2686-2694. [DOI: 10.1093/cercor/bhw101] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
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25
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Functional connectivity measures as schizophrenia intermediate phenotypes: advances, limitations, and future directions. Curr Opin Neurobiol 2016; 36:7-14. [DOI: 10.1016/j.conb.2015.07.008] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Revised: 07/09/2015] [Accepted: 07/25/2015] [Indexed: 01/08/2023]
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Eack SM, Newhill CE, Keshavan MS. Cognitive Enhancement Therapy Improves Resting-State Functional Connectivity in Early Course Schizophrenia. JOURNAL OF THE SOCIETY FOR SOCIAL WORK AND RESEARCH 2016; 7:211-230. [PMID: 27713804 PMCID: PMC5047289 DOI: 10.1086/686538] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
OBJECTIVE Cognitive remediation is emerging as an effective psychosocial intervention for addressing untreated cognitive and functional impairments in persons with schizophrenia, and might achieve its benefits through neuroplastic changes in brain connectivity. This study seeks to examine the effects of cognitive enhancement therapy (CET) on fronto-temporal brain connectivity in a randomized controlled trial with individuals in the early course of schizophrenia. METHOD Stabilized, early course outpatients with schizophrenia or schizoaffective disorder (N = 41) were randomly assigned to CET (n = 25) or an active enriched supportive therapy (EST) control (n = 16) and treated for 2 years. Functional MRI data were collected annually, and pseudo resting-state functional connectivity analysis was used to examine differential changes in fronto-temporal connectivity between those treated with CET compared with EST. RESULTS Individuals receiving CET evidenced significantly less functional connectivity loss between the resting-state network and the left dorsolateral prefrontal cortex as well as significantly increased connectivity with the right insular cortex compared to EST (all corrected p < .01). These neural networks are involved in emotion processing and problem-solving. Increased connectivity with the right insula significantly mediated CET effects on improved emotion perception (z' = -1.96, p = .021), and increased connectivity with the left dorsolateral prefrontal cortex mediated CET-related improvements in emotion regulation (z' = -1.71, p = .052). CONCLUSIONS These findings provide preliminary evidence that CET, a psychosocial cognitive remediation intervention, may enhance connectivity between frontal and temporal brain regions implicated in problem-solving and emotion processing in service of cognitive enhancement in schizophrenia.
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Affiliation(s)
- Shaun M Eack
- David E. Epperson Associate Professor of Social Work and an associate professor of psychiatry at the University of Pittsburgh
| | - Christina E Newhill
- professor of social work with a joint appointment to the Clinical and Translational Science Institute at the University of Pittsburgh
| | - Matcheri S Keshavan
- Stanley Cobb Professor of Psychiatry at Harvard Medical School in Boston, MA
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Sheffield JM, Barch DM. Cognition and resting-state functional connectivity in schizophrenia. Neurosci Biobehav Rev 2015; 61:108-20. [PMID: 26698018 DOI: 10.1016/j.neubiorev.2015.12.007] [Citation(s) in RCA: 231] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Revised: 10/09/2015] [Accepted: 12/10/2015] [Indexed: 01/10/2023]
Abstract
Individuals with schizophrenia consistently display deficits in a multitude of cognitive domains, but the neurobiological source of these cognitive impairments remains unclear. By analyzing the functional connectivity of resting-state functional magnetic resonance imaging (rs-fcMRI) data in clinical populations like schizophrenia, research groups have begun elucidating abnormalities in the intrinsic communication between specific brain regions, and assessing relationships between these abnormalities and cognitive performance in schizophrenia. Here we review studies that have reported analysis of these brain-behavior relationships. Through this systematic review we found that patients with schizophrenia display abnormalities within and between regions comprising (1) the cortico-cerebellar-striatal-thalamic loop and (2) task-positive and task-negative cortical networks. Importantly, we did not observe unique relationships between specific functional connectivity abnormalities and distinct cognitive domains, suggesting that the observed functional systems may underlie mechanisms that are shared across cognitive abilities, the disturbance of which could contribute to the "generalized" cognitive deficit found in schizophrenia. We also note several areas of methodological change that we believe will strengthen this literature.
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Affiliation(s)
- Julia M Sheffield
- Washington University in St Louis, Department of Psychology, 1 Brookings Drive, St Louis, MO 63130, USA.
| | - Deanna M Barch
- Washington University in St Louis, Department of Psychology, 1 Brookings Drive, St Louis, MO 63130, USA; Washington University in St Louis, Department of Psychiatry, 4940 Childrens Place, St Louis, MO 63110, USA; Washington University in St Louis, Department of Radiology, 224 Euclid Ave, St Louis, MO 63110, USA
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Su TW, Hsu TW, Lin YC, Lin CP. Schizophrenia symptoms and brain network efficiency: A resting-state fMRI study. Psychiatry Res 2015; 234:208-18. [PMID: 26409574 DOI: 10.1016/j.pscychresns.2015.09.013] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2014] [Revised: 08/10/2015] [Accepted: 09/02/2015] [Indexed: 12/18/2022]
Abstract
Schizophrenia is a condition marked by a disrupted brain functional network. In schizophrenia, the brain network is characterized by reduced distributed information processing efficiency; however, the correlation between information processing efficiency and the symptomatology of schizophrenia remains unclear. Few studies have examined path length efficiencies in schizophrenia. In this study, we examined small-world network metrics computed from resting state functional magnetic resonance imaging data collected from 49 patients with schizophrenia and 28 healthy people. We calculated brain network efficiency using graph theoretical analysis of the networks of brain areas, as defined by the Automated Anatomical Labeling parcellation scheme, and investigated efficiency correlations by using the 5-factor model of psychopathology, which considers the various domains of schizophrenic symptoms and might also consider discrete pathogenetic processes. The global efficiency of the resting schizophrenic brains was lower than that of the healthy controls, but local efficiency did not differ between the groups. The severity of psychopathology, negative symptoms, and depression and anxiety symptoms were correlated with global efficiency in schizophrenic brains. The severity of psychopathology was correlated with increased network efficiency from short-range connections, but not networks from long-range connections. Our findings indicate that schizophrenic psychopathology is correlated with brain network information processing efficiency.
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Affiliation(s)
- Tsung-Wei Su
- Brain Connectivity Lab., Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, No. 155, Section 2, Linong Street, Taipei 112, Taiwan; Department of Psychiatry, Losheng Sanatorium and Hospital, Ministry of Health and Welfare, No. 2, Lane 50, Section 1, Wanshou Rd., Guishan Shiang, Taoyuan County, Taiwan
| | - Tun-Wei Hsu
- Brain Connectivity Lab., Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, No. 155, Section 2, Linong Street, Taipei 112, Taiwan
| | - Yi-Ching Lin
- Department of Psychiatry, Losheng Sanatorium and Hospital, Ministry of Health and Welfare, No. 2, Lane 50, Section 1, Wanshou Rd., Guishan Shiang, Taoyuan County, Taiwan
| | - Ching-Po Lin
- Brain Connectivity Lab., Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, No. 155, Section 2, Linong Street, Taipei 112, Taiwan.
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Kraguljac NV, White DM, Hadley JA, Visscher K, Knight D, ver Hoef L, Falola B, Lahti AC. Abnormalities in large scale functional networks in unmedicated patients with schizophrenia and effects of risperidone. NEUROIMAGE-CLINICAL 2015; 10:146-58. [PMID: 26793436 PMCID: PMC4683457 DOI: 10.1016/j.nicl.2015.11.015] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Revised: 10/30/2015] [Accepted: 11/20/2015] [Indexed: 12/25/2022]
Abstract
Objective To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks. Material and methods 34 unmedicated patients with schizophrenia and 34 matched healthy controls were enrolled in this longitudinal study. We collected resting state functional MRI data with a 3T scanner at baseline and six weeks after they were started on risperidone. In addition, a group of 19 healthy controls were scanned twice six weeks apart. Four large scale networks, the dorsal attention network, executive control network, salience network, and default mode network were identified with seed based functional connectivity analyses. Group differences in connectivity, as well as changes in connectivity over time, were assessed on the group's participant level functional connectivity maps. Results In unmedicated patients with schizophrenia we found resting state connectivity to be increased in the dorsal attention network, executive control network, and salience network relative to control participants, but not the default mode network. Dysconnectivity was attenuated after six weeks of treatment only in the dorsal attention network. Baseline connectivity in this network was also related to clinical response at six weeks of treatment with risperidone. Conclusions Our results demonstrate abnormalities in large scale functional networks in patients with schizophrenia that are modulated by risperidone only to a certain extent, underscoring the dire need for development of novel antipsychotic medications that have the ability to alleviate symptoms through attenuation of dysconnectivity. We found widespread functional dysconnectivity in unmedicated patients with schizophrenia. Large scale functional networks appear differentially affected in the disorder. Attenuation of dysconnectivity with risperidone is seen only to a limited extent.
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Key Words
- ALFF, amplitude of low frequency fluctuations
- Antipsychotic medication
- BOLD, blood oxygen level dependent signal
- BPRS, Brief Psychiatric Rating Scale
- DAN, dorsal attention network
- DARTEL, diffeomorphic anatomical registration using exponentiated lie algebra algorithm
- DMN, default mode network
- Default mode network
- Dorsal attention network
- ECN, executive control network
- Executive control network
- FD, framewise displacement
- FDR, false discovery rate
- HC, healthy control
- KE, cluster extent
- MNI, Montreal Neurological Institute
- RBANS, Repeatable Battery for the Assessment of Neuropsychological Status
- SZ, patient with schizophrenia
- Salience network
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Affiliation(s)
- Nina Vanessa Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - David Matthew White
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Jennifer Ann Hadley
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Kristina Visscher
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - David Knight
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Lawrence ver Hoef
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Blessing Falola
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Adrienne Carol Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
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Cognitive correlates of frontoparietal network connectivity 'at rest' in individuals with differential risk for psychotic disorder. Eur Neuropsychopharmacol 2015; 25:1922-32. [PMID: 26411531 DOI: 10.1016/j.euroneuro.2015.08.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2015] [Revised: 06/14/2015] [Accepted: 08/13/2015] [Indexed: 11/23/2022]
Abstract
Altered frontoparietal network functional connectivity (FPN-fc) has been associated with neurocognitive dysfunction in individuals with (risk for) psychotic disorder. Cannabis use is associated with cognitive and FPN-fc alterations in healthy individuals, but it is not known whether cannabis exposure moderates the FPN-fc-cognition association. We studied FPN-fc in relation to psychosis risk, as well as the moderating effects of psychosis risk and cannabis use on the association between FPN-fc and (social) cognition. This was done by collecting resting-state fMRI scans and (social) cognitive test results from 63 patients with psychotic disorder, 73 unaffected siblings and 59 controls. Dorsolateral prefrontal cortex (DLPFC) seed-based correlation analyses were used to estimate FPN-fc group differences. Additionally, group×FPN-fc and cannabis×FPN-fc interactions in models of cognition were assessed with regression models. Results showed that DLPFC-fc with the left precuneus, right inferior parietal lobule, right middle temporal gyrus (MTG), inferior frontal gyrus (IFG) regions and right insula was decreased in patients compared to controls. Siblings had reduced DLPFC-fc with the right MTG, left middle frontal gyrus, right superior frontal gyrus, IFG regions, and right insula compared to controls, with an intermediate position between patients and controls for DLPFC-IFG/MTG and insula-fc. There were no significant FPN-fc×group or FPN-fc×cannabis interactions in models of cognition. Reduced DLPFC-insula-fc was associated with worse social cognition in the total sample. In conclusion, besides patient- and sibling-specific FPN-fc alterations, there was evidence for trait-related alterations. FPN-fc-cognition associations were not conditional on familial liability or cannabis use. Lower FPN-fc was associated with lower emotion processing in the total group.
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Peeters S, Simas T, Suckling J, Gronenschild E, Patel A, Habets P, van Os J, Marcelis M. Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder. NEUROIMAGE-CLINICAL 2015; 9:607-16. [PMID: 26740914 PMCID: PMC4644247 DOI: 10.1016/j.nicl.2015.10.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Revised: 09/21/2015] [Accepted: 10/02/2015] [Indexed: 12/26/2022]
Abstract
Background Dysconnectivity in schizophrenia can be understood in terms of dysfunctional integration of a distributed network of brain regions. Here we propose a new methodology to analyze complex networks based on semi-metric behavior, whereby higher levels of semi-metricity may represent a higher level of redundancy and dispersed communication. It was hypothesized that individuals with (increased risk for) psychotic disorder would have more semi-metric paths compared to controls and that this would be associated with symptoms. Methods Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 unaffected siblings and 72 controls. Semi-metric percentages (SMP) at the whole brain, hemispheric and lobar level were the dependent variables in a multilevel random regression analysis to investigate group differences. SMP was further examined in relation to symptomatology (i.e., psychotic/cognitive symptoms). Results At the whole brain and hemispheric level, patients had a significantly higher SMP compared to siblings and controls, with no difference between the latter. In the combined sibling and control group, individuals with high schizotypy had intermediate SMP values in the left hemisphere with respect to patients and individuals with low schizotypy. Exploratory analyses in patients revealed higher SMP in 12 out of 42 lobar divisions compared to controls, of which some were associated with worse PANSS symptomatology (i.e., positive symptoms, excitement and emotional distress) and worse cognitive performance on attention and emotion processing tasks. In the combined group of patients and controls, working memory, attention and social cognition were associated with higher SMP. Discussion The results are suggestive of more dispersed network communication in patients with psychotic disorder, with some evidence for trait-based network alterations in high-schizotypy individuals. Dispersed communication may contribute to the clinical phenotype in psychotic disorder. In addition, higher SMP may contribute to neuro- and social cognition, independent of psychosis risk. Higher SMP was observed at whole brain and hemispheric level in psychotic disorder. In patients, lobar SMP was associated with psychotic and cognitive symptoms. Trait-based SMP alterations were observed in high schizotypy individuals.
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Affiliation(s)
- Sanne Peeters
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands; Faculty of Psychology and Educational Sciences, Open University of the Netherlands, Heerlen, The Netherlands
| | - Tiago Simas
- Behavioral and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, United Kingdom
| | - John Suckling
- Behavioral and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, United Kingdom; Cambridge and Peterborough Foundation NHS Trust. Cambridge, United Kingdom
| | - Ed Gronenschild
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands
| | - Ameera Patel
- Behavioral and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, United Kingdom
| | - Petra Habets
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands; King's College London, King's Health Partners, Department of Psychosis Studies Institute of Psychiatry, London, United Kingdom
| | - Machteld Marcelis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands; Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
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Neural correlates of executive dysfunction in schizophrenia: failure to modulate brain activity with task demands. Neuroreport 2015; 25:1308-15. [PMID: 25275638 DOI: 10.1097/wnr.0000000000000264] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
In schizophrenia, executive functions are impaired and are associated with altered activation of prefrontal areas. We used H2[15]O PET to examine patients with schizophrenia and matched controls on a random number generation (RNG) task and a control counting (COUNT) task. To assess the effects of increasing task demand, both tasks were performed at three different rates (intervals 1, 2 or 3 s). Both groups showed a significant increase in the nonrandomness of responses at faster rates of RNG. Despite similar performances, patients but not controls showed higher activation of the right dorsolateral prefrontal cortex (DLPFC) and atypically reduced activation of the right anterior cingulate gyrus and the right medial frontal gyrus in RNG compared with COUNT, whereas only for controls, activation of the left DLPFC was increased and activation of the right superior temporal gyrus and the right superior frontal gyrus was reduced in the same comparison. Whereas for the controls several cortical areas including the bilateral superior temporal gyrus and the bilateral DLPFC, together with the right cerebellum, showed significant changes in regional cerebral blood flow with faster or slower rates, patients with schizophrenia showed rate-dependent changes only in the left cerebellum. In conclusion, the patients' failure to modulate cortical activation with changing demands of rate, particularly in prefrontal areas and in the cerebellum, and even when performance is similar to that in healthy controls, is a characteristic of their abnormal pattern of executive processing.
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Chang X, Xi YB, Cui LB, Wang HN, Sun JB, Zhu YQ, Huang P, Collin G, Liu K, Xi M, Qi S, Tan QR, Miao DM, Yin H. Distinct inter-hemispheric dysconnectivity in schizophrenia patients with and without auditory verbal hallucinations. Sci Rep 2015; 5:11218. [PMID: 26053998 PMCID: PMC4459220 DOI: 10.1038/srep11218] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2014] [Accepted: 05/19/2015] [Indexed: 01/26/2023] Open
Abstract
Evidence from behavioral, electrophysiological and diffusion-weighted imaging studies suggest that schizophrenia patients suffer from deficiencies in bilateral brain communication, and this disruption may be related to the occurrence of auditory verbal hallucinations (AVH). To increase our understanding of aberrant inter-hemispheric communication in relation to AVH, we recruited two groups of first-episode schizophrenia patients: one group with AVH (N = 18 AVH patients) and one without hallucinations (N = 18 Non-AVH patients), and 20 healthy controls. All participants received T1 structural imaging and resting-state fMRI scanning. We adopted a newly developed index, voxel-mirrored homotopic connectivity (VMHC), to quantitatively describe bilateral functional connectivity. The whole-brain VMHC measure was compared among the three groups and correlation analyses were conducted between symptomology scores and neurological measures. Our findings suggest all patients shared abnormalities in parahippocampus and striatum. Aberrant bilateral connectivity of default mode network (DMN), inferior frontal gyrus and cerebellum only showed in AVH patients, whereas aberrances in superior temporal gyrus and precentral gyrus were specific to Non-AVH patients. Meanwhile, inter-hemispheric connectivity of DMN correlated with patients' symptomatology scores. This study corroborates that schizophrenia is characterized by inter-hemispheric dysconnectivity, and suggests the localization of such abnormalities may be crucial to whether auditory verbal hallucinations develop.
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Affiliation(s)
- Xiao Chang
- Department of Medical Psychology, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
| | - Yi-Bin Xi
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Long-Biao Cui
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Jin-Bo Sun
- Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi’an, Shaanxi Province, 710126, P.R. China
| | - Yuan-Qiang Zhu
- Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi’an, Shaanxi Province, 710126, P.R. China
| | - Peng Huang
- Department of Medical Psychology, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Guusje Collin
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
| | - Kang Liu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Min Xi
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Shun Qi
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Qing-Rong Tan
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Dan-Min Miao
- Department of Medical Psychology, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, P.R. China
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Shinn AK, Baker JT, Lewandowski KE, Öngür D, Cohen BM. Aberrant cerebellar connectivity in motor and association networks in schizophrenia. Front Hum Neurosci 2015; 9:134. [PMID: 25852520 PMCID: PMC4364170 DOI: 10.3389/fnhum.2015.00134] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Accepted: 02/26/2015] [Indexed: 11/16/2022] Open
Abstract
Schizophrenia is a devastating illness characterized by disturbances in multiple domains. The cerebellum is involved in both motor and non-motor functions, and the "cognitive dysmetria" and "dysmetria of thought" models propose that abnormalities of the cerebellum may contribute to schizophrenia signs and symptoms. The cerebellum and cerebral cortex are reciprocally connected via a modular, closed-loop network architecture, but few schizophrenia neuroimaging studies have taken into account the topographical and functional heterogeneity of the cerebellum. In this study, using a previously defined 17-network cerebral cortical parcellation system as the basis for our functional connectivity seeds, we systematically investigated connectivity abnormalities within the cerebellum of 44 schizophrenia patients and 28 healthy control participants. We found selective alterations in cerebro-cerebellar functional connectivity. Specifically, schizophrenia patients showed decreased cerebro-cerebellar functional connectivity in higher level association networks (ventral attention, salience, control, and default mode networks) relative to healthy control participants. Schizophrenia patients also showed increased cerebro-cerebellar connectivity in somatomotor and default mode networks, with the latter showing no overlap with the regions found to be hypoconnected within the same default mode network. Finally, we found evidence to suggest that somatomotor and default mode networks may be inappropriately linked in schizophrenia. The relationship of these dysconnectivities to schizophrenia symptoms, such as neurological soft signs and altered sense of agency, is discussed. We conclude that the cerebellum ought to be considered for analysis in all future studies of network abnormalities in SZ, and further suggest the cerebellum as a potential target for further elucidation, and possibly treatment, of the underlying mechanisms and network abnormalities producing symptoms of schizophrenia.
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Affiliation(s)
- Ann K. Shinn
- Schizophrenia and Bipolar Disorder Program, Psychotic Disorders Division, McLean HospitalBelmont, MA, USA
- Department of Psychiatry, Harvard Medical SchoolBoston, MA, USA
| | - Justin T. Baker
- Schizophrenia and Bipolar Disorder Program, Psychotic Disorders Division, McLean HospitalBelmont, MA, USA
- Department of Psychiatry, Harvard Medical SchoolBoston, MA, USA
| | - Kathryn E. Lewandowski
- Schizophrenia and Bipolar Disorder Program, Psychotic Disorders Division, McLean HospitalBelmont, MA, USA
- Department of Psychiatry, Harvard Medical SchoolBoston, MA, USA
| | - Dost Öngür
- Schizophrenia and Bipolar Disorder Program, Psychotic Disorders Division, McLean HospitalBelmont, MA, USA
- Department of Psychiatry, Harvard Medical SchoolBoston, MA, USA
| | - Bruce M. Cohen
- Schizophrenia and Bipolar Disorder Program, Psychotic Disorders Division, McLean HospitalBelmont, MA, USA
- Department of Psychiatry, Harvard Medical SchoolBoston, MA, USA
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Littow H, Huossa V, Karjalainen S, Jääskeläinen E, Haapea M, Miettunen J, Tervonen O, Isohanni M, Nikkinen J, Veijola J, Murray G, Kiviniemi VJ. Aberrant Functional Connectivity in the Default Mode and Central Executive Networks in Subjects with Schizophrenia - A Whole-Brain Resting-State ICA Study. Front Psychiatry 2015; 6:26. [PMID: 25767449 PMCID: PMC4341512 DOI: 10.3389/fpsyt.2015.00026] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2014] [Accepted: 02/09/2015] [Indexed: 01/04/2023] Open
Abstract
Neurophysiological changes of schizophrenia are currently linked to disturbances in connectivity between functional brain networks. Functional magnetic resonance imaging studies on schizophrenia have focused on a few selected networks. Also previously, it has not been possible to discern whether the functional alterations in schizophrenia originate from spatial shifting or amplitude alterations of functional connectivity. In this study, we aim to discern the differences in schizophrenia patients with respect to spatial shifting vs. signal amplitude changes in functional connectivity in the whole-brain connectome. We used high model order-independent component analysis to study some 40 resting-state networks (RSN) covering the whole cortex. Group differences were analyzed with dual regression coupled with y-concat correction for multiple comparisons. We investigated the RSNs with and without variance normalization in order to discern spatial shifting from signal amplitude changes in 43 schizophrenia patients and matched controls from the Northern Finland 1966 Birth Cohort. Voxel-level correction for multiple comparisons revealed 18 RSNs with altered functional connectivity, 6 of which had both spatial and signal amplitude changes. After adding the multiple comparison, y-concat correction to the analysis for including the 40 RSNs as well, we found that four RSNs showed still changes. These robust changes actually seem encompass parcellations of the default mode network and central executive networks. These networks both have spatially shifted connectivity and abnormal signal amplitudes. Interestingly the networks seem to mix their functional representations in areas like left caudate nucleus and dorsolateral prefrontal cortex. These changes overlapped with areas that have been related to dopaminergic alterations in patients with schizophrenia compared to controls.
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Affiliation(s)
- Harri Littow
- Department of Radiology, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Ville Huossa
- Department of Radiology, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Sami Karjalainen
- Department of Psychiatry, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Erika Jääskeläinen
- Department of Psychiatry, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Marianne Haapea
- Department of Psychiatry, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Jouko Miettunen
- Department of Psychiatry, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Osmo Tervonen
- Department of Radiology, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Matti Isohanni
- Department of Psychiatry, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Juha Nikkinen
- Department of Oncology, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Juha Veijola
- Department of Psychiatry, Medical Research Center, Oulu University Hospital , Oulu , Finland
| | - Graham Murray
- Department of Psychiatry, University of Cambridge , Cambridge , UK
| | - Vesa J Kiviniemi
- Department of Radiology, Medical Research Center, Oulu University Hospital , Oulu , Finland
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Jia X, Liang P, Shi L, Wang D, Li K. Prefrontal and parietal activity is modulated by the rule complexity of inductive reasoning and can be predicted by a cognitive model. Neuropsychologia 2014; 66:67-74. [PMID: 25447072 DOI: 10.1016/j.neuropsychologia.2014.10.015] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Revised: 09/11/2014] [Accepted: 10/13/2014] [Indexed: 11/26/2022]
Abstract
In neuroimaging studies, increased task complexity can lead to increased activation in task-specific regions or to activation of additional regions. How the brain adapts to increased rule complexity during inductive reasoning remains unclear. In the current study, three types of problems were created: simple rule induction (i.e., SI, with rule complexity of 1), complex rule induction (i.e., CI, with rule complexity of 2), and perceptual control. Our findings revealed that increased activations accompany increased rule complexity in the right dorsal lateral prefrontal cortex (DLPFC) and medial posterior parietal cortex (precuneus). A cognitive model predicted both the behavioral and brain imaging results. The current findings suggest that neural activity in frontal and parietal regions is modulated by rule complexity, which may shed light on the neural mechanisms of inductive reasoning.
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Affiliation(s)
- Xiuqin Jia
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China
| | - Peipeng Liang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Defeng Wang
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China.
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