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Miranda-Barrientos J, Adiraju S, Rehg JJ, Hallock HL, Li Y, Carr GV, Martinowich K. Patterns of neural activity in prelimbic cortex neurons correlate with attentional behavior in the rodent continuous performance test. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605300. [PMID: 39091763 PMCID: PMC11291163 DOI: 10.1101/2024.07.26.605300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Sustained attention, the ability to focus on a stimulus or task over extended periods, is crucial for higher level cognition, and is impaired in individuals diagnosed with neuropsychiatric and neurodevelopmental disorders, including attention-deficit/hyperactivity disorder, schizophrenia, and depression. Translational tasks like the rodent continuous performance test (rCPT) can be used to study the cellular mechanisms underlying sustained attention. Accumulating evidence points to a role for the prelimbic cortex (PrL) in sustained attention, as electrophysiological single unit and local field (LFPs) recordings reflect changes in neural activity in the PrL in mice performing sustained attention tasks. While the evidence correlating PrL electrical activity with sustained attention is compelling, limitations inherent to electrophysiological recording techniques, including low sampling in single unit recordings and source ambivalence for LFPs, impede the ability to fully resolve the cellular mechanisms in the PrL that contribute to sustained attention. In vivo endoscopic calcium imaging using genetically encoded calcium sensors in behaving animals can address these questions by simultaneously recording up to hundreds of neurons at single cell resolution. Here, we used in vivo endoscopic calcium imaging to record patterns of neuronal activity in PrL neurons using the genetically encoded calcium sensor GCaMP6f in mice performing the rCPT at three timepoints requiring differing levels of cognitive demand and task proficiency. A higher proportion of PrL neurons were recruited during correct responses in sessions requiring high cognitive demand and task proficiency, and mice intercalated non-responsive-disengaged periods with responsive-engaged periods that resemble attention lapses. During disengaged periods, the correlation of calcium activity between PrL neurons was higher compared to engaged periods, suggesting a neuronal network state change during attention lapses in the PrL. Overall, these findings illustrate that cognitive demand, task proficiency, and task engagement differentially recruit activity in a subset of PrL neurons during sustained attention.
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Affiliation(s)
| | - Suhaas Adiraju
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Jason J. Rehg
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | | | - Ye Li
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Gregory V. Carr
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- The Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21205, USA
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Zhang T, Wei Y, Tang X, Cui H, Hu Y, Xu L, Liu H, Wang Z, Chen T, Hu Q, Li C, Wang J. Cognitive Impairments in Drug-Naive Patients With First-Episode Negative Symptom-Dominant Psychosis. JAMA Netw Open 2024; 7:e2415110. [PMID: 38842809 PMCID: PMC11157355 DOI: 10.1001/jamanetworkopen.2024.15110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 04/04/2024] [Indexed: 06/07/2024] Open
Abstract
Importance Available antipsychotic medications are predominantly used to treat positive symptoms, such as hallucinations and delusions, in patients with first-episode psychosis (FEP). However, treating negative and cognitive symptoms, which are closely related to functional outcomes, remains a challenge. Objective To explore the cognitive characteristics of patients with negative symptom-dominant (NSD) psychosis. Design, Setting, and Participants This large-scale cross-sectional study of patients with FEP was led by the Shanghai Mental Health Center in China from 2016 to 2021, with participants recruited from 10 psychiatric tertiary hospitals. A comprehensive cognitive assessment was performed among 788 patients with FEP who were drug-naive. Symptom profiles were determined using the Positive and Negative Symptoms Scale (PANSS), and NSD was defined as a PANSS score for negative symptoms higher than that for positive and general symptoms. Positive symptom-dominant (PSD) and general symptom-dominant (GSD) psychosis were defined similarly. Data were analyzed in 2023. Exposure Psychotic symptoms were categorized into 3 groups: NSD, PSD, and GSD. Main Outcomes and Measures Neurocognitive performance, assessed using the Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery. Results This study included 788 individuals with FEP (median age, 22 [IQR, 17-28] years; 399 men [50.6%]). Patients with NSD exhibited more-pronounced cognitive impairment than did those with PSD or GSD. Specifically, cognitive differences between the NSD and PSD group, as well as between the NSD and GSD group, were most notable in the processing speed and attention domains (Trail Making [F = 4.410; P = .01], Symbol Coding [F = 4.957; P = .007], Verbal Learning [F = 3.198; P = .04], and Continuous Performance [F = 3.057; P = .05]). Patients with PSD and GSD showed no significant cognitive differences. Cognitive impairment was positively associated with the severity of negative symptoms. Most of the cognitive function tests used were able to differentiate patients with NSD from those with PSD and GSD, with significant differences observed across a range of tests, from Brief Visuospatial Memory Test-Revised (χ2 = 3.968; P = .05) to Brief Assessment of Cognition in Schizophrenia symbol coding (χ2 = 9.765; P = .002). Conclusions and Relevance The findings of this cross-sectional study of patients with FEP suggest the presence of a clinical subtype characterized by a predominance of negative symptoms and cognitive impairment.
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Affiliation(s)
- TianHong Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
| | - YanYan Wei
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
| | - XiaoChen Tang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
| | - HuiRu Cui
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
| | - YeGang Hu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
| | - LiHua Xu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
| | - HaiChun Liu
- Department of Automation, Shanghai Jiao Tong University, Shanghai, PR China
| | - ZiXuan Wang
- Shanghai Xinlianxin Psychological Counseling Center, Shanghai, PR China
| | - Tao Chen
- Big Data Research Lab, University of Waterloo, Waterloo, Ontario, Canada
- Labor and Worklife Program, Harvard University, Cambridge, Massachusetts
| | - Qiang Hu
- Department of Psychiatry, ZhenJiang Mental Health Center, Zhenjiang, PR China
| | - ChunBo Li
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
| | - JiJun Wang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, PR China
- Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, PR China
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, PR China
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Lin P, Zhu G, Xu X, Wang Z, Li X, Li B. Brain network analysis of working memory in schizophrenia based on multi graph attention network. Brain Res 2024; 1831:148816. [PMID: 38387716 DOI: 10.1016/j.brainres.2024.148816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/25/2024] [Accepted: 02/19/2024] [Indexed: 02/24/2024]
Abstract
The cognitive impairment in schizophrenia (SZ) is characterized by significant deficits in working memory task. In order to explore the brain changes of SZ during a working memory task, we performed time-domain and time-frequency analysis of event related potentials (ERP) of SZ during a 0-back task. The P3 wave amplitude was found to be significantly lower in SZ patients than in healthy controls (HC) (p < 0.05). The power in the θ and α bands was significantly enhanced in the SZ group 200 ms after stimulation, while the θ band was significantly enhanced and the β band was weakened in the HC group. Furthermore, phase lag index (PLI) based brain functional connectivity maps showed differences in the connections between parietal and frontotemporal lobes between SZ and HC (p < 0.05). Due to the natural similarity between brain networks and graph data, and the fact that graph attention network can aggregate the features of adjacent nodes, it has more advantages in learning the features of brain regions. We propose a multi graph attention network model combined with adaptive initial residual (AIR) for SZ classification, which achieves an accuracy of 90.90 % and 78.57 % on an open dataset (Zenodo) and our 0-back dataset, respectively. Overall, the proposed methodology offers promising potential for understanding the brain functional connections of schizophrenia.
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Affiliation(s)
- Ping Lin
- College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China; College of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Geng Zhu
- College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Xinyi Xu
- College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China; College of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Zhen Wang
- College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Xiaoou Li
- College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China; College of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; Shanghai Yangpu Mental Health Center, Shanghai 200093, China.
| | - Bin Li
- Shanghai Yangpu Mental Health Center, Shanghai 200093, China.
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Hallock HL, Adiraju SS, Miranda-Barrientos J, McInerney JM, Oh S, DeBrosse AC, Li Y, Carr GV, Martinowich K. Electrophysiological correlates of attention in the locus coeruleus-prelimbic cortex circuit during the rodent continuous performance test. Neuropsychopharmacology 2024; 49:521-531. [PMID: 37563281 PMCID: PMC10789747 DOI: 10.1038/s41386-023-01692-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 08/12/2023]
Abstract
Sustained attention, the ability to focus on an activity or stimulus over time, is significantly impaired in many psychiatric disorders, and there remains a major unmet need in treating impaired attention. Continuous performance tests (CPTs) were developed to measure sustained attention in humans, non-human primates, rats, and mice, and similar neural circuits are engaged across species during CPT performance, supporting their use in translational studies to identify novel therapeutics. Here, we identified electrophysiological correlates of attentional performance in a touchscreen-based rodent CPT (rCPT) in the locus coeruleus (LC) and prelimbic cortex (PrL), two inter-connected regions that are implicated in attentional processes. We used viral labeling and molecular techniques to demonstrate that neural activity is recruited in LC-PrL projections during the rCPT, and that this recruitment increases with cognitive demand. We implanted male mice with depth electrodes within the LC and PrL for local field potential (LFP) recordings during rCPT training, and identified an increase in PrL delta and theta power, and an increase in LC delta power during correct responses in the rCPT. We also found that the LC leads the PrL in theta frequencies during correct responses while the PrL leads the LC in gamma frequencies during incorrect responses. These findings may represent translational biomarkers that can be used to screen novel therapeutics for drug discovery in attention.
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Affiliation(s)
- Henry L Hallock
- Neuroscience Program, Lafayette College, Easton, PA, 18042, USA
| | - Suhaas S Adiraju
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | | | - Jessica M McInerney
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Seyun Oh
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Adrienne C DeBrosse
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Ye Li
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Gregory V Carr
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA.
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA.
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA.
- The Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21205, USA.
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Hallock HL, Adiraju S, Miranda-Barrientos J, McInerney JM, Oh S, DeBrosse AC, Li Y, Carr GV, Martinowich K. Electrophysiological correlates of attention in the locus coeruleus - anterior cingulate cortex circuit during the rodent continuous performance test. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.19.537406. [PMID: 37131757 PMCID: PMC10153204 DOI: 10.1101/2023.04.19.537406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Sustained attention, the ability to focus on an activity or stimulus over time, is significantly impaired in many psychiatric disorders, and there remains a major unmet need in treating impaired attention. Continuous performance tests (CPTs) were developed to measure sustained attention in humans, non-human primates, rats, and mice, and similar neural circuits are engaged across species during CPT performance, supporting their use in translational studies to identify novel therapeutics. Here, we identified electrophysiological correlates of attentional performance in a touchscreen-based rodent CPT (rCPT) in the locus coeruleus (LC) and anterior cingulate cortex (ACC), two inter-connected regions that are implicated in attentional processes. We used viral labeling and molecular techniques to demonstrate that neural activity is recruited in LC-ACC projections during the rCPT, and that this recruitment increases with cognitive demand. We implanted male mice with depth electrodes within the LC and ACC for local field potential (LFP) recordings during rCPT training, and identified an increase in ACC delta and theta power, and an increase in LC delta power during correct responses in the rCPT. We also found that the LC leads the ACC in theta frequencies during correct responses while the ACC leads the LC in gamma frequencies during incorrect responses. These findings may represent translational biomarkers that can be used to screen novel therapeutics for drug discovery in attention.
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Affiliation(s)
| | - Suhaas Adiraju
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | | | - Jessica M. McInerney
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Seyun Oh
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Adrienne C. DeBrosse
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Ye Li
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Gregory V. Carr
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- The Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21205, USA
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Song X, Li R, Wang K, Bai Y, Xiao Y, Wang YP. Joint Sparse Collaborative Regression on Imaging Genetics Study of Schizophrenia. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:1137-1146. [PMID: 35503837 PMCID: PMC10321021 DOI: 10.1109/tcbb.2022.3172289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The imaging genetics approach generates large amount of high dimensional and multi-modal data, providing complementary information for comprehensive study of Schizophrenia, a complex mental disease. However, at the same time, the variety of these data in structures, resolutions, and formats makes their integrative study a forbidding task. In this paper, we propose a novel model called Joint Sparse Collaborative Regression (JSCoReg), which can extract class-specific features from different health conditions/disease classes. We first evaluate the performance of feature selection in terms of Receiver operating characteristic curve and the area under the ROC curve in the simulation experiment. We demonstrate that the JSCoReg model can achieve higher accuracy compared with similar models including Joint Sparse Canonical Correlation Analysis and Sparse Collaborative Regression. We then applied the JSCoReg model to the analysis of schizophrenia dataset collected from the Mind Clinical Imaging Consortium. The JSCoReg enables us to better identify biomarkers associated with schizophrenia, which are verified to be both biologically and statistically significant.
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Affiliation(s)
- Xueli Song
- School of Sciences, Chang’an University, Xi’an, 710064, China
| | - Rongpeng Li
- School of Sciences, Chang’an University, Xi’an, 710064, China
| | - Kaiming Wang
- School of Sciences, Chang’an University, Xi’an, 710064, China
| | - Yuntong Bai
- Biomedical Engineering Department, Tulane University, New Orleans, LA 70118, USA
| | - Yuzhu Xiao
- School of Sciences, Chang’an University, Xi’an, 710064, China
| | - Yu-ping Wang
- Biomedical Engineering Department, Tulane University, New Orleans, LA 70118, USA
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Zhou J, Guo X, Liu X, Luo Y, Chang X, He H, Duan M, Li S, Li Q, Tan Y, Yao G, Yao D, Luo C. Intrinsic Therapeutic Link between Recuperative Cerebellar Con-Nectivity and Psychiatry Symptom in Schizophrenia Patients with Comorbidity of Metabolic Syndrome. LIFE (BASEL, SWITZERLAND) 2023; 13:life13010144. [PMID: 36676092 PMCID: PMC9863013 DOI: 10.3390/life13010144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 12/23/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023]
Abstract
Components of metabolic syndrome might be predictors of the therapeutic outcome of psychiatric symptom in schizophrenia, whereas clinical results are inconsistent and an intrinsic therapeutic link between weaker psychiatric symptoms and emergent metabolic syndrome remains unclear. This study aims to reveal the relationship and illustrate potential mechanism by exploring the alteration of cerebellar functional connectivity (FC) in schizophrenia patients with comorbidity metabolic syndrome. Thirty-six schizophrenia patients with comorbidity of metabolic syndrome (SCZ-MetS), 45 schizophrenia patients without metabolic syndrome (SCZ-nMetS) and 39 healthy controls (HC) were recruited in this study. We constructed FC map of cerebello-cortical circuit and used moderation effect analysis to reveal complicated relationship among FC, psychiatric symptom and metabolic disturbance. Components of metabolic syndrome were significantly correlated with positive symptom score and negative symptom score. Importantly, the dysconnectivity between cognitive module of cerebellum and left middle frontal gyrus in SCZ-nMetS was recuperative increased in SCZ-MetS, and was significantly correlated with general symptom score. Finally, we observed significant moderation effect of body mass index on this correlation. The present findings further supported the potential relationship between emergence of metabolic syndrome and weaker psychiatric symptom, and provided neuroimaging evidence. The mechanism of intrinsic therapeutic link involved functional change of cerebello-cortical circuit.
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Affiliation(s)
- Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xiao Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xiaoli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Shicai Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Qifu Li
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
| | - Ying Tan
- The Key Laboratory for Computer Systems of State Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610093, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 610056, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
- Research Unit of Neuroinformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu 610072, China
- Correspondence: (Y.T.); (G.Y.); (C.L.)
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Association of reduced local activities in the default mode and sensorimotor networks with clinical characteristics in first-diagnosed of schizophrenia. Neuroscience 2022; 495:47-57. [DOI: 10.1016/j.neuroscience.2022.05.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 01/10/2023]
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Basavaraju R, Ithal D, Thanki MV, Ramalingaiah AH, Thirthalli J, Reddy RP, Brady RO, Halko MA, Bolo NR, Keshavan MS, Pascual-Leone A, Mehta UM, Kesavan M. Intermittent theta burst stimulation of cerebellar vermis enhances fronto-cerebellar resting state functional connectivity in schizophrenia with predominant negative symptoms: A randomized controlled trial. Schizophr Res 2021; 238:108-120. [PMID: 34653740 PMCID: PMC8662658 DOI: 10.1016/j.schres.2021.10.005] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 10/01/2021] [Accepted: 10/03/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE Negative symptoms of schizophrenia are substantially disabling and treatment resistant. Novel treatments like repetitive transcranial magnetic stimulation (TMS) need to be examined for the same using the experimental medicine approach that incorporates tests of mechanism of action in addition to clinical efficacy in trials. METHODS Study was a double-blind, parallel, randomized, sham-controlled trial recruiting schizophrenia with at least a moderate severity of negative symptoms. Participants were randomized to real or sham intermittent theta burst stimulation (iTBS) under MRI-guided neuro-navigation, targeting the cerebellar vermis area VII-B, at a stimulus intensity of 100% active motor threshold, two sessions/day for five days (total = 6000 pulses). Assessments were conducted at baseline (T0), day-6 (T1) and week-6 (T2) after initiation of intervention. Main outcomes were, a) Scale for the Assessment of Negative Symptoms (SANS) score (T0, T1, T2), b) fronto-cerebellar resting state functional connectivity (RSFC) (T0, T1). RESULTS Thirty participants were recruited in each arm. Negative symptoms improved in both arms (p < 0.001) but was not significantly different between the two arms (p = 0.602). RSFC significantly increased between the cerebellar vermis and the right inferior frontal gyrus (pcluster-FWER = 0.033), right pallidum (pcluster-FWER = 0.042) and right frontal pole (pcluster-FWER = 0.047) in the real arm with no change in the sham arm. CONCLUSION Cerebellar vermal iTBS engaged a target belonging to the class of cerebello-subcortical-cortical networks, implicated in negative symptoms of schizophrenia. However, this did not translate to a superior clinical efficacy. Future trials should employ enhanced midline cerebellar TMS stimulation parameters for longer durations that can potentiate and translate biological changes into clinical effects.
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Affiliation(s)
- Rakshathi Basavaraju
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India
| | - Dhruva Ithal
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India
| | - Milind Vijay Thanki
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India
| | - Arvinda Hanumanthapura Ramalingaiah
- Department of Neuro Imaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India
| | - Jagadisha Thirthalli
- Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, Karnataka, India
| | - Rajakumari P. Reddy
- Department of Clinical Psychology, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, Karnataka, India
| | - Roscoe O. Brady
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Mark A. Halko
- Department of Psychiatry, McLean Hospital and Harvard Medical School, Belmont, MA, USA
| | - Nicolas R. Bolo
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Center for Memory Health, Hebrew Senior Life, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; Guttmann Brain Health Institut, Institut Guttmann, Universitat Autonoma Barcelona, Spain.
| | - Urvakhsh Meherwan Mehta
- Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore 560029, Karnataka, India.
| | - Muralidharan Kesavan
- Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore 560029, Karnataka, India.
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10
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Dilernia A, Quevedo K, Camchong J, Lim K, Pan W, Zhang L. Penalized model-based clustering of fMRI data. Biostatistics 2021; 23:825-843. [PMID: 33527998 DOI: 10.1093/biostatistics/kxaa061] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 12/21/2020] [Indexed: 11/14/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) data have become increasingly available and are useful for describing functional connectivity (FC), the relatedness of neuronal activity in regions of the brain. This FC of the brain provides insight into certain neurodegenerative diseases and psychiatric disorders, and thus is of clinical importance. To help inform physicians regarding patient diagnoses, unsupervised clustering of subjects based on FC is desired, allowing the data to inform us of groupings of patients based on shared features of connectivity. Since heterogeneity in FC is present even between patients within the same group, it is important to allow subject-level differences in connectivity, while still pooling information across patients within each group to describe group-level FC. To this end, we propose a random covariance clustering model (RCCM) to concurrently cluster subjects based on their FC networks, estimate the unique FC networks of each subject, and to infer shared network features. Although current methods exist for estimating FC or clustering subjects using fMRI data, our novel contribution is to cluster or group subjects based on similar FC of the brain while simultaneously providing group- and subject-level FC network estimates. The competitive performance of RCCM relative to other methods is demonstrated through simulations in various settings, achieving both improved clustering of subjects and estimation of FC networks. Utility of the proposed method is demonstrated with application to a resting-state fMRI data set collected on 43 healthy controls and 61 participants diagnosed with schizophrenia.
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Affiliation(s)
- Andrew Dilernia
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Karina Quevedo
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Jazmin Camchong
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Kelvin Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Lin Zhang
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
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11
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Sun X, Liu J, Ma Q, Duan J, Wang X, Xu Y, Xu Z, Xu K, Wang F, Tang Y, He Y, Xia M. Disrupted Intersubject Variability Architecture in Functional Connectomes in Schizophrenia. Schizophr Bull 2020; 47:837-848. [PMID: 33135075 PMCID: PMC8084432 DOI: 10.1093/schbul/sbaa155] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Schizophrenia (SCZ) is a highly heterogeneous disorder with remarkable intersubject variability in clinical presentations. Previous neuroimaging studies in SCZ have primarily focused on identifying group-averaged differences in the brain connectome between patients and healthy controls (HCs), largely neglecting the intersubject differences among patients. We acquired whole-brain resting-state functional MRI data from 121 SCZ patients and 183 HCs and examined the intersubject variability of the functional connectome (IVFC) in SCZ patients and HCs. Between-group differences were determined using permutation analysis. Then, we evaluated the relationship between IVFC and clinical variables in SCZ. Finally, we used datasets of patients with bipolar disorder (BD) and major depressive disorder (MDD) to assess the specificity of IVFC alteration in SCZ. The whole-brain IVFC pattern in the SCZ group was generally similar to that in HCs. Compared with the HC group, the SCZ group exhibited higher IVFC in the bilateral sensorimotor, visual, auditory, and subcortical regions. Moreover, altered IVFC was negatively correlated with age of onset, illness duration, and Brief Psychiatric Rating Scale scores and positively correlated with clinical heterogeneity. Although the SCZ shared altered IVFC in the visual cortex with BD and MDD, the alterations of IVFC in the sensorimotor, auditory, and subcortical cortices were specific to SCZ. The alterations of whole-brain IVFC in SCZ have potential implications for the understanding of the high clinical heterogeneity of SCZ and the future individualized clinical diagnosis and treatment of this disease.
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Affiliation(s)
- Xiaoyi Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jin Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qing Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jia Duan
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xindi Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ke Xu
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China,Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China,To whom correspondence should be addressed; National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Key Laboratory of Brain Imaging and Connectomics, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; tel: +86-10-58802036, fax: +86-10-58802036, e-mail:
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12
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Rürup L, Mathes B, Schmiedt-Fehr C, Wienke AS, Özerdem A, Brand A, Basar-Eroglu C. Altered gamma and theta oscillations during multistable perception in schizophrenia. Int J Psychophysiol 2020; 155:127-139. [DOI: 10.1016/j.ijpsycho.2020.06.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 06/01/2020] [Accepted: 06/05/2020] [Indexed: 12/24/2022]
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13
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Arjmand S, Kohlmeier KA, Behzadi M, Ilaghi M, Mazhari S, Shabani M. Looking into a Deluded Brain through a Neuroimaging Lens. Neuroscientist 2020; 27:73-87. [PMID: 32648532 DOI: 10.1177/1073858420936172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Delusions are irrational, tenacious, and incorrigible false beliefs that are the most common symptom of a range of brain disorders including schizophrenia, Alzheimer's, and Parkinson's disease. In the case of schizophrenia and other primary delusional disorders, their appearance is often how the disorder is first detected and can be sufficient for diagnosis. At this time, not much is known about the brain dysfunctions leading to delusions, and hindering our understanding is that the complexity of the nature of delusions, and their very unique relevance to the human experience has hampered elucidation of their underlying neurobiology using either patients or animal models. Advances in neuroimaging along with improved psychiatric and cognitive modeling offers us a new opportunity to look with more investigative power into the deluded brain. In this article, based on data obtained from neuroimaging studies, we have attempted to draw a picture of the neural networks involved when delusion is present and evaluate whether different manifestations of delusions engage different regions of the brain.
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Affiliation(s)
- Shokouh Arjmand
- Institute of Neuropharmacology, Kerman Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran
| | - Kristi A Kohlmeier
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mina Behzadi
- Institute of Neuropharmacology, Kerman Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran
| | - Mehran Ilaghi
- Institute of Neuropharmacology, Kerman Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran
| | - Shahrzad Mazhari
- Institute of Neuropharmacology, Kerman Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran.,Department of Psychiatry, School of Medicine, Kerman University of Medical Sciences, Kerman, Iran
| | - Mohammad Shabani
- Institute of Neuropharmacology, Kerman Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran
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14
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Osborne KJ, Walther S, Shankman SA, Mittal VA. Psychomotor Slowing in Schizophrenia: Implications for Endophenotype and Biomarker Development. Biomark Neuropsychiatry 2020; 2:100016. [PMID: 33738459 PMCID: PMC7963400 DOI: 10.1016/j.bionps.2020.100016] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Motor abnormalities (e.g., dyskinesia, psychomotor slowing, neurological soft signs) are core features of schizophrenia that occur independent of drug treatment and are associated with the genetic vulnerability and pathophysiology for the illness. Among this list, psychomotor slowing in particular is one of the most consistently observed and robust findings in the field. Critically, psychomotor slowing may serve as a uniquely promising endophenotype and/or biomarker for schizophrenia considering it is frequently observed in those with genetic vulnerability for the illness, predicts transition in subjects at high-risk for the disorder, and is associated with symptoms and recovery in patients. The purpose of the present review is to provide an overview of the history of psychomotor slowing in psychosis, discuss its possible neural underpinnings, and review the current literature supporting slowing as a putative endophenotype and/or biomarker for the illness. This review summarizes substantial evidence from a diverse array of methodologies and research designs that supports the notion that psychomotor slowing not only reflects genetic vulnerability, but is also sensitive to disease processes and the pathophysiology of the illness. Furthermore, there are unique deficits across the cognitive (prefix "psycho") and motor execution (root word "motor") aspects of slowing, with cognitive processes such as planning and response selection being particularly affected. These findings suggest that psychomotor slowing may serve as a promising endophenotype and biomarker for schizophrenia that may prove useful for identifying individuals at greatest risk and tracking the course of the illness and recovery.
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Affiliation(s)
- K. Juston Osborne
- Northwestern University, Department of Psychology, Evanston, IL, USA
| | - Sebastian Walther
- University of Bern, University Hospital of Psychiatry, Translational Research Center, Bern, Switzerland
| | - Stewart A. Shankman
- Northwestern University, Department of Psychology, Evanston, IL, USA
- Northwestern University, Department of Psychiatry, Chicago, IL, USA
| | - Vijay A. Mittal
- Northwestern University, Department of Psychology, Evanston, IL, USA
- Northwestern University, Department of Psychiatry, Chicago, IL, USA
- Northwestern University, Department of Psychiatry, Institute for Policy Research, Department of Medical Social Sciences, Institute for Innovations in Developmental Sciences (DevSci), Evanston, Chicago, IL, USA
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15
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Reis-de-Oliveira G, Zuccoli GS, Fioramonte M, Schimitt A, Falkai P, Almeida V, Martins-de-Souza D. Digging deeper in the proteome of different regions from schizophrenia brains. J Proteomics 2020; 223:103814. [PMID: 32389842 DOI: 10.1016/j.jprot.2020.103814] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 04/21/2020] [Accepted: 05/05/2020] [Indexed: 02/07/2023]
Abstract
Schizophrenia is a psychiatric disorder that affects 21 million people worldwide. Despite several studies having been shown that some brain regions may play a critical role in the pathophysiology of schizophrenia, the molecular basis to explain this diversity is still lacking. The cerebellum (CER), caudate nucleus (CAU), and posterior cingulate cortex (PCC) are areas associated with negative and cognitive symptoms in schizophrenia. In this study, we performed shotgun proteomics of the aforementioned brain regions, collected postmortem from patients with schizophrenia and compared with the mentally healthy group. In addition, we performed a proteomic analysis of nuclear and mitochondrial fractions of these same regions. Our results presented 106, 727 and 135 differentially regulated proteins in the CAU, PCC, and CER, respectively. Pathway enrichment analysis revealed dysfunctions associated with synaptic processes in the CAU, transport in the CER, and in energy metabolism in the PCC. In all brain areas, we found that proteins related to oligodendrocytes and the metabolic processes were dysregulated in schizophrenia. SIGNIFICANCE: Schizophrenia is a complex and heterogeneous psychiatric disorder. Despite much research having been done to increase the knowledge about the role of each region in the pathophysiology of this disorder, the molecular mechanisms underlying it are still lacking. We performed shotgun proteomics in the postmortem cerebellum (CER), caudate nucleus (CAU) and posterior cingulate cortex (PCC) from patients with schizophrenia and compared with healthy controls. Our findings suggest that each aforementioned region presents dysregulations in specific molecular pathways, such as energy metabolism in the PCC, transport in the CER, and synaptic process in the CAU. Additionally, these areas presented dysfunctions in oligodendrocytes and metabolic processes. Our results may highlight future directions for the development of novel clinical approaches for specific therapeutic targets.
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Affiliation(s)
- G Reis-de-Oliveira
- Lab of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - G S Zuccoli
- Lab of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - M Fioramonte
- Lab of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - A Schimitt
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University (LMU), Munich, Germany; Laboratory of Neurosciences (LIM-27), Institute of Psychiatry, University of São Paulo, São Paulo, Brazil
| | - P Falkai
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University (LMU), Munich, Germany
| | - V Almeida
- Lab of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - D Martins-de-Souza
- Lab of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil; Experimental Medicine Research Cluster (EMRC), University of Campinas, Campinas, Brazil; D'Or Institute for Research and Education (IDOR), São Paulo, Brazil; Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBION), Conselho Nacional de Desenvolvimento Científico e Tecnológico, São Paulo, Brazil.
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16
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Yang QX, Wang YX, Li FC, Zhang S, Luo YC, Li Y, Tang J, Li B, Chen YZ, Xue WW, Zhu F. Identification of the gene signature reflecting schizophrenia's etiology by constructing artificial intelligence-based method of enhanced reproducibility. CNS Neurosci Ther 2019; 25:1054-1063. [PMID: 31350824 PMCID: PMC6698965 DOI: 10.1111/cns.13196] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 06/27/2019] [Accepted: 07/03/2019] [Indexed: 12/15/2022] Open
Abstract
Aims As one of the most fundamental questions in modern science, “what causes schizophrenia (SZ)” remains a profound mystery due to the absence of objective gene markers. The reproducibility of the gene signatures identified by independent studies is found to be extremely low due to the incapability of available feature selection methods and the lack of measurement on validating signatures’ robustness. These irreproducible results have significantly limited our understanding of the etiology of SZ. Methods In this study, a new feature selection strategy was developed, and a comprehensive analysis was then conducted to ensure a reliable signature discovery. Particularly, the new strategy (a) combined multiple randomized sampling with consensus scoring and (b) assessed gene ranking consistency among different datasets, and a comprehensive analysis among nine independent studies was conducted. Results Based on a first‐ever evaluation of methods’ reproducibility that was cross‐validated by nine independent studies, the newly developed strategy was found to be superior to the traditional ones. As a result, 33 genes were consistently identified from multiple datasets by the new strategy as differentially expressed, which might facilitate our understanding of the mechanism underlying the etiology of SZ. Conclusion A new strategy capable of enhancing the reproducibility of feature selection in current SZ research was successfully constructed and validated. A group of candidate genes identified in this study should be considered as great potential for revealing the etiology of SZ.
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Affiliation(s)
- Qing-Xia Yang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.,School of Pharmaceutical Sciences, Chongqing University, Chongqing, China
| | - Yun-Xia Wang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Feng-Cheng Li
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Song Zhang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Yong-Chao Luo
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Yi Li
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Jing Tang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.,School of Pharmaceutical Sciences, Chongqing University, Chongqing, China
| | - Bo Li
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, China
| | - Yu-Zong Chen
- Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Singapore, Singapore
| | - Wei-Wei Xue
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.,School of Pharmaceutical Sciences, Chongqing University, Chongqing, China
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17
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Abstract
Episodic memory deficits are consistently documented as a core aspect of cognitive dysfunction in schizophrenia patients, present from the onset of the illness and strongly associated with functional disability. Over the past decade, research using approaches from experimental cognitive neuroscience revealed disproportionate episodic memory impairments in schizophrenia (Sz) under high cognitive demand relational encoding conditions and relatively unimpaired performance under item-specific encoding conditions. These specific deficits in component processes of episodic memory reflect impaired activation and connectivity within specific elements of frontal-medial temporal lobe circuits, with a central role for the dorsolateral prefrontal cortex (DLPFC), relatively intact function of ventrolateral prefrontal cortex and variable results in the hippocampus. We propose that memory deficits can be understood within the broader context of cognitive deficits in Sz, where impaired DLPFC-related cognitive control has a broad impact across multiple cognitive domains. The therapeutic implications of these findings are discussed.
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Affiliation(s)
- JY Guo
- Department of Psychiatry and Behavioral Sciences, Imaging Research Center, University of California at Davis, Sacramento, CA, United States,Department of Psychology, Center for Neuroscience, University of California at Davis, Davis, CA, United States
| | - JD Ragland
- Department of Psychiatry and Behavioral Sciences, Imaging Research Center, University of California at Davis, Sacramento, CA, United States
| | - CS Carter
- Department of Psychiatry and Behavioral Sciences, Imaging Research Center, University of California at Davis, Sacramento, CA, United States,Department of Psychology, Center for Neuroscience, University of California at Davis, Davis, CA, United States
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18
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Takayanagi Y, Sasabayashi D, Takahashi T, Komori Y, Furuichi A, Kido M, Nishikawa Y, Nakamura M, Noguchi K, Suzuki M. Altered brain gyrification in deficit and non-deficit schizophrenia. Psychol Med 2019; 49:573-580. [PMID: 29739476 DOI: 10.1017/s0033291718001228] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Patients with the deficit form of schizophrenia (D-SZ) are characterized by severe primary negative symptoms and differ from patients with the non-deficit form of schizophrenia (ND-SZ) in several aspects. No study has measured brain gyrification, which is a potential marker of neurodevelopment, in D-SZ and ND-SZ. METHODS We obtained magnetic resonance scans from 135 schizophrenia patients and 50 healthy controls. The proxy scale for deficit syndrome (PDS) was used for the classification of D-SZ and ND-SZ. The local gyrification index (LGI) of the entire cortex was measured using FreeSurfer. Thirty-seven D-SZ and 36 ND-SZ patients were included in the LGI analyses. We compared LGI across the groups. RESULTS SZ patients exhibited hyper-gyral patterns in the bilateral dorsal medial prefrontal and ventromedial prefrontal cortices, bilateral anterior cingulate gyri and right lateral parietal/occipital cortices as compared with HCs. Although patients with D-SZ or ND-SZ had higher LGI in similar regions compared with HC, the hyper-gyral patterns were broader in ND-SZ. ND-SZ patients exhibited a significantly higher LGI in the left inferior parietal lobule relative to D-SZ patients. Duration of illness inversely associated with LGI in broad regions only among ND-SZ patients. CONCLUSIONS The common hyper-gyral patterns among D-SZ and ND-SZ suggest that D-SZ and ND-SZ may share neurodevelopmental abnormalities. The different degrees of cortical gyrification seen in the left parietal regions, and the distinct correlation between illness chronicity and LGI observed in the prefrontal and insular cortices may be related to the differences in the clinical manifestations among D-SZ and ND-SZ.
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Affiliation(s)
- Yoichiro Takayanagi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Yuko Komori
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Mikio Kido
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Yumiko Nishikawa
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Mihoko Nakamura
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Kyo Noguchi
- Department of Radiology,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Michio Suzuki
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
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19
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Koike T, Sumiya M, Nakagawa E, Okazaki S, Sadato N. What Makes Eye Contact Special? Neural Substrates of On-Line Mutual Eye-Gaze: A Hyperscanning fMRI Study. eNeuro 2019; 6:ENEURO.0284-18.2019. [PMID: 30834300 PMCID: PMC6397949 DOI: 10.1523/eneuro.0284-18.2019] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 01/27/2019] [Accepted: 02/05/2019] [Indexed: 12/03/2022] Open
Abstract
Automatic mimicry is a critical element of social interaction. A salient type of automatic mimicry is eye contact characterized by sharing of affective and mental states among individuals. We conducted a hyperscanning functional magnetic resonance imaging study involving on-line (LIVE) and delayed off-line (REPLAY) conditions to test our hypothesis that recurrent interaction through eye contact activates the limbic mirror system, including the anterior cingulate cortex (ACC) and anterior insular cortex (AIC), both of which are critical for self-awareness. Sixteen pairs of human adults participated in the experiment. Given that an eye-blink represents an individual's attentional window toward the partner, we analyzed pairwise time-series data for eye-blinks. We used multivariate autoregression analysis to calculate the noise contribution ratio (NCR) as an index of how a participant's directional attention was influenced by that of their partner. NCR was greater in the LIVE than in the REPLAY condition, indicating mutual perceptual-motor interaction during real-time eye contact. Relative to the REPLAY condition, the LIVE condition was associated with greater activation in the left cerebellar hemisphere, vermis, and ACC, accompanied by enhanced functional connectivity between ACC and right AIC. Given the roles of the cerebellum in sensorimotor prediction and ACC in movement initiation, ACC-cerebellar activation may represent their involvement in modulating visual input related to the partner's movement, which may, in turn, involve the limbic mirror system. Our findings indicate that mutual interaction during eye contact is mediated by the cerebellum and limbic mirror system.
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Affiliation(s)
- Takahiko Koike
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi 444-8585, Japan
- Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies (SOKENDAI), Hayama 240-0193, Japan
| | - Motofumi Sumiya
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi 444-8585, Japan
- Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies (SOKENDAI), Hayama 240-0193, Japan
| | - Eri Nakagawa
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi 444-8585, Japan
| | - Shuntaro Okazaki
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi 444-8585, Japan
| | - Norihiro Sadato
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi 444-8585, Japan
- Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies (SOKENDAI), Hayama 240-0193, Japan
- Biomedical Imaging Research Center (BIRC), University of Fukui, Fukui 910-1193, Japan
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20
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Abstract
Objectives：Schizophrenia is a predominant product of pathological alterations distributed throughout interconnected neural systems. Functional connections (FCs) methodology is an effective lever to investigate macroscopic neural activity patterns underlying critical aspects of cognition and behaviour. However, region properties of brain architecture have been less investigated by special markers of dynamical graph in general mental disorders. Methods：Embracing the eigenvector centrality in holism significance, our important process is to uncover noticeable edges and regions with antagonistic stance between morbid and normal FCs of 67 healthy controls (HCs) and 53 chronic schizophrenia patients (SZs). Results: Results suggest that, there are 12 abnormal edges with significant p value of FCs weight, such as lingual gyrus L versus cuneus L, thalamus L versus middle frontal gyrus R, superior temporal gyrus R versus thalamus R. Importantly, SZs' superior temporal gyrus R, parahippocampal gyrus L and parahippocampal gyrus R are endowed with different eigenvector centrality scores. Conclusion: Consistent with SZs' positive symptoms of hallucinations, and negative symptoms of thinking impairment, it can be infer that the functional separation and integration are destroyed in schizophrenia. Thought the strict contrastive study, it is worth stressing that eigenvector centrality is a meaningful biological marker to excavating schizophrenic psychopathology.
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Affiliation(s)
- Bo Chen
- a School of Science , Hangzhou Dianzi University , Hangzhou , PR China
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21
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Reinertsen E, Shashikumar SP, Shah AJ, Nemati S, Clifford GD. Multiscale network dynamics between heart rate and locomotor activity are altered in schizophrenia. Physiol Meas 2018; 39:115001. [PMID: 30222594 DOI: 10.1088/1361-6579/aae1ed] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Changes in heart rate (HR) and locomotor activity reflect changes in autonomic physiology, behavior, and mood. These systems may involve interrelated neural circuits that are altered in psychiatric illness, yet their interactions are poorly understood. We hypothesized interactions between HR and locomotor activity could be used to discriminate patients with schizophrenia from controls, and would be less able to discriminate non-psychiatric patients from controls. APPROACH HR and locomotor activity were recorded via wearable patches in 16 patients with schizophrenia and 19 healthy controls. Measures of signal complexity and interactions were calculated over multiple time scales, including sample entropy, mutual information, and transfer entropy. A support vector machine was trained on these features to discriminate patients from controls. Additionally, time series were converted into a network with nodes comprised of HR and locomotor activity states, and edges representing state transitions. Graph properties were used as features. Leave-one-out cross validation was performed. To compare against non-psychiatric illness, the same approach was repeated in 41 patients with atrial fibrillation (AFib) and 53 controls. MAIN RESULTS Network features enabled perfect discrimination of schizophrenia patients from controls with an areas under the receiver operating characteristic curve (AUC) of 1.00 for training and test data. Other bivariate measures of interaction achieved lower AUCs (train 0.98, test 0.96), and univariate measures of complexity achieved the lowest performance. Conversely, interaction features did not improve discrimination of AFib patients from controls beyond univariate approaches. SIGNIFICANCE Interactions between HR and locomotor activity enabled perfect discrimination of subjects with schizophrenia from controls, but these features were less performant in a non-psychiatric illness. This is the first quantitative evaluation of interactions between physiology and behavior in patients with psychiatric illness.
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Affiliation(s)
- Erik Reinertsen
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
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22
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Zaytseva Y, Fajnerová I, Dvořáček B, Bourama E, Stamou I, Šulcová K, Motýl J, Horáček J, Rodriguez M, Španiel F. Theoretical Modeling of Cognitive Dysfunction in Schizophrenia by Means of Errors and Corresponding Brain Networks. Front Psychol 2018; 9:1027. [PMID: 30026711 PMCID: PMC6042473 DOI: 10.3389/fpsyg.2018.01027] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Accepted: 05/31/2018] [Indexed: 01/22/2023] Open
Abstract
The current evidence of cognitive disturbances and brain alterations in schizophrenia does not provide the plausible explanation of the underlying mechanisms. Neuropsychological studies outlined the cognitive profile of patients with schizophrenia, that embodied the substantial disturbances in perceptual and motor processes, spatial functions, verbal and non-verbal memory, processing speed and executive functioning. Standardized scoring in the majority of the neurocognitive tests renders the index scores or the achievement indicating the severity of the cognitive impairment rather than the actual performance by means of errors. At the same time, the quantitative evaluation may lead to the situation when two patients with the same index score of the particular cognitive test, demonstrate qualitatively different performances. This may support the view why test paradigms that habitually incorporate different cognitive variables associate weakly, reflecting an ambiguity in the interpretation of noted cognitive constructs. With minor exceptions, cognitive functions are not attributed to the localized activity but eventuate from the coordinated activity in the generally dispersed brain networks. Functional neuroimaging has progressively explored the connectivity in the brain networks in the absence of the specific task and during the task processing. The spatio-temporal fluctuations of the activity of the brain areas detected in the resting state and being highly reproducible in numerous studies, resemble the activation and communication patterns during the task performance. Relatedly, the activation in the specific brain regions oftentimes is attributed to a number of cognitive processes. Given the complex organization of the cognitive functions, it becomes crucial to designate the roles of the brain networks in relation to the specific cognitive functions. One possible approach is to identify the commonalities of the deficits across the number of cognitive tests or, common errors in the various tests and identify their common "denominators" in the brain networks. The qualitative characterization of cognitive performance might be beneficial in addressing diffuse cognitive alterations presumably caused by the dysconnectivity of the distributed brain networks. Therefore, in the review, we use this approach in the description of standardized tests in the scope of potential errors in patients with schizophrenia with a subsequent reference to the brain networks.
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Affiliation(s)
- Yuliya Zaytseva
- National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University in Prague, Prague, Czechia
| | | | | | - Eva Bourama
- 3rd Faculty of Medicine, Charles University in Prague, Prague, Czechia
| | - Ilektra Stamou
- 3rd Faculty of Medicine, Charles University in Prague, Prague, Czechia
| | - Kateřina Šulcová
- National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University in Prague, Prague, Czechia
| | - Jiří Motýl
- National Institute of Mental Health, Klecany, Czechia
| | - Jiří Horáček
- National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University in Prague, Prague, Czechia
| | | | - Filip Španiel
- National Institute of Mental Health, Klecany, Czechia
- 3rd Faculty of Medicine, Charles University in Prague, Prague, Czechia
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23
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Huang P, Cui LB, Li X, Lu ZL, Zhu X, Xi Y, Wang H, Li B, Hou F, Miao D, Yin H. Identifying first-episode drug naïve patients with schizophrenia with or without auditory verbal hallucinations using whole-brain functional connectivity: A pattern analysis study. Neuroimage Clin 2018; 19:351-359. [PMID: 30013918 PMCID: PMC6044229 DOI: 10.1016/j.nicl.2018.04.026] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Revised: 04/11/2018] [Accepted: 04/22/2018] [Indexed: 12/21/2022]
Abstract
Many studies have focused on patients with schizophrenia with or without auditory verbal hallucinations (AVHs), but due to the complexity of schizophrenia, biologically based diagnosis of patients with schizophrenia remains unsolved. The objectives of this study are to classify between first-episode drug-naïve patients with schizophrenia and healthy controls, and to classify between patients with and without AVHs. Resting state fMRI data from 41 patients with schizophrenia (22 with and 19 without AVHs) and 23 normal controls (NC) were included to compute functional connectivity between brain regions. Classifiers based on support vector machine (SVM) were developed to classify patients with schizophrenia from NC, as well as between the two subgroups of patients. The classification accuracy was evaluated with a leave-one-out cross-validation (LOOCV) strategy. The accuracy in discriminating both subgroups of patients from NC was 81.3%, with 92.0% (sensitivity) and 65.2% (specificity) for the patients and NC, respectively. The classification accuracy in discriminating patients with and without AVHs was 75.6%, with 77.3% (sensitivity) and 73.9% (specificity) for patients with and without AVHs, respectively. The results suggest that functional connectivity provided good discriminative power not only for identifying patients with schizophrenia among NC, but also in discriminating patients with schizophrenia with and without AVHs.
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Affiliation(s)
- Peng Huang
- Department of Medical Psychology, Fourth Military Medical University, Xi'an, Shaanxi 710032, China; Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China; The Center for Cognitive and Behavioral Brain Imaging (CCBBI), Department of Psychology, The Ohio State University, Columbus, OH 43210, USA
| | - Long-Biao Cui
- Department of Medical Psychology, Fourth Military Medical University, Xi'an, Shaanxi 710032, China; Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Xiangrui Li
- The Center for Cognitive and Behavioral Brain Imaging (CCBBI), Department of Psychology, The Ohio State University, Columbus, OH 43210, USA
| | - Zhong-Lin Lu
- The Center for Cognitive and Behavioral Brain Imaging (CCBBI), Department of Psychology, The Ohio State University, Columbus, OH 43210, USA
| | - Xia Zhu
- Department of Medical Psychology, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Yibin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Baojuan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, 710032, China
| | - Fang Hou
- The Center for Cognitive and Behavioral Brain Imaging (CCBBI), Department of Psychology, The Ohio State University, Columbus, OH 43210, USA
| | - Danmin Miao
- Department of Medical Psychology, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
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Hoonakker M, Doignon-Camus N, Bonnefond A. Sustaining attention to simple visual tasks: a central deficit in schizophrenia? A systematic review. Ann N Y Acad Sci 2017; 1408:32-45. [PMID: 29090832 DOI: 10.1111/nyas.13514] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Revised: 08/20/2017] [Accepted: 09/11/2017] [Indexed: 11/30/2022]
Abstract
Impairments in sustained attention, that is, the ability to achieve and maintain the focus of cognitive activity on a given stimulation source or task, have been described as central to schizophrenia. Today, sustained attention deficit is still considered as a hallmark of schizophrenia. Nevertheless, current findings on this topic are not consistent. To clarify these findings, we attempt to put these results into perspective according to the type of assessment (i.e., overall and over time assessment), the participants' characteristics (i.e., clinical and demographic characteristics), and the paradigms (i.e., traditionally formatted tasks, go/no-go tasks, and the sustained attention task) and measures used. Two types of assessment lead to opposite findings; they do not evaluate sustained attention the same way. Studies using overall assessments of sustained attention ability tend to reveal a deficit, whereas studies using over time assessments do not. Therefore, further research is needed to investigate the underlying cognitive control mechanisms of changes in sustained attention in schizophrenia.
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Affiliation(s)
- Marc Hoonakker
- INSERM U1114, Department of Psychiatry, University Hospital of Strasbourg, Strasbourg, France
| | - Nadège Doignon-Camus
- University of Strasbourg, University of Haute-Alsace, University of Lorraine, LISEC EA 2310, Strasbourg, France
| | - Anne Bonnefond
- INSERM U1114, Department of Psychiatry, University Hospital of Strasbourg, Strasbourg, France
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25
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Abboud R, Noronha C, Diwadkar VA. Motor system dysfunction in the schizophrenia diathesis: Neural systems to neurotransmitters. Eur Psychiatry 2017. [PMID: 28641214 DOI: 10.1016/j.eurpsy.2017.04.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Motor control is a ubiquitous aspect of human function, and from its earliest origins, abnormal motor control has been proposed as being central to schizophrenia. The neurobiological architecture of the motor system is well understood in primates and involves cortical and sub-cortical components including the primary motor cortex, supplementary motor area, dorsal anterior cingulate cortex, the prefrontal cortex, the basal ganglia, and cerebellum. Notably all of these regions are associated in some manner to the pathophysiology of schizophrenia. At the molecular scale, both dopamine and γ-Aminobutyric Acid (GABA) abnormalities have been associated with working memory dysfunction, but particularly relating to the basal ganglia and the prefrontal cortex respectively. As evidence from multiple scales (behavioral, regional and molecular) converges, here we provide a synthesis of the bio-behavioral relevance of motor dysfunction in schizophrenia, and its consistency across scales. We believe that the selective compendium we provide can supplement calls arguing for renewed interest in studying the motor system in schizophrenia. We believe that in addition to being a highly relevant target for the study of schizophrenia related pathways in the brain, such focus provides tractable behavioral probes for in vivo imaging studies in the illness. Our assessment is that the motor system is a highly valuable research domain for the study of schizophrenia.
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Affiliation(s)
- R Abboud
- College of Osteopathic Medicine, Michigan State University Lansing, MI, USA
| | - C Noronha
- School of Medicine, University of Michigan, Ann Arbor, MI, USA
| | - V A Diwadkar
- Department of Psychiatry and Behavioral Neuroscience, Wayne State University School of Medicine, Suite 5A, Tolan Park Medical Building, 3901 Chrysler Service Drive, 48201 Detroit, MI, USA.
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26
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Affiliation(s)
- Roy Salomon
- Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
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27
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Charles L, Gaillard R, Amado I, Krebs MO, Bendjemaa N, Dehaene S. Conscious and unconscious performance monitoring: Evidence from patients with schizophrenia. Neuroimage 2017; 144:153-163. [DOI: 10.1016/j.neuroimage.2016.09.056] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Revised: 09/20/2016] [Accepted: 09/21/2016] [Indexed: 12/21/2022] Open
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28
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Influencing connectivity and cross-frequency coupling by real-time source localized neurofeedback of the posterior cingulate cortex reduces tinnitus related distress. Neurobiol Stress 2016; 8:211-224. [PMID: 29888315 PMCID: PMC5991329 DOI: 10.1016/j.ynstr.2016.11.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 11/15/2016] [Accepted: 11/19/2016] [Indexed: 12/20/2022] Open
Abstract
Background In this study we are using source localized neurofeedback to moderate tinnitus related distress by influencing neural activity of the target region as well as the connectivity within the default network. Hypothesis We hypothesize that up-training alpha and down-training beta and gamma activity in the posterior cingulate cortex has a moderating effect on tinnitus related distress by influencing neural activity of the target region as well as the connectivity within the default network and other functionally connected brain areas. Methods Fifty-eight patients with chronic tinnitus were included in the study. Twenty-three tinnitus patients received neurofeedback training of the posterior cingulate cortex with the aim of up-training alpha and down-training beta and gamma activity, while 17 patients underwent training of the lingual gyrus as a control situation. A second control group consisted of 18 tinnitus patients on a waiting list for future tinnitus treatment. Results This study revealed that neurofeedback training of the posterior cingulate cortex results in a significant decrease of tinnitus related distress. No significant effect on neural activity of the target region could be obtained. However, functional and effectivity connectivity changes were demonstrated between remote brain regions or functional networks as well as by altering cross frequency coupling of the posterior cingulate cortex. Conclusion This suggests that neurofeedback could remove the information, processed in beta and gamma, from the carrier wave, alpha, which transports the high frequency information and influences the salience attributed to the tinnitus sound. Based on the observation that much pathology is the result of an abnormal functional connectivity within and between neural networks various pathologies should be considered eligible candidates for the application of source localized EEG based neurofeedback training.
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29
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Characterising brain network topologies: A dynamic analysis approach using heat kernels. Neuroimage 2016; 141:490-501. [DOI: 10.1016/j.neuroimage.2016.07.006] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 05/27/2016] [Accepted: 07/03/2016] [Indexed: 12/13/2022] Open
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30
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Rana M, Varan AQ, Davoudi A, Cohen RA, Sitaram R, Ebner NC. Real-Time fMRI in Neuroscience Research and Its Use in Studying the Aging Brain. Front Aging Neurosci 2016; 8:239. [PMID: 27803662 PMCID: PMC5067937 DOI: 10.3389/fnagi.2016.00239] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Accepted: 09/27/2016] [Indexed: 02/05/2023] Open
Abstract
Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age. An emerging literature on neurofeedback and Brain Computer Interface (BCI) reports exciting results supporting the benefits of volitional modulation of brain activity on cognition and behavior. Neurofeedback studies based on real-time functional magnetic resonance imaging (rtfMRI) have shown behavioral changes in schizophrenia and behavioral benefits in nicotine addiction. This article integrates research on cognitive and brain aging with evidence of brain and behavioral modification due to rtfMRI neurofeedback. We offer a state-of-the-art description of the rtfMRI technique with an eye towards its application in aging. We present preliminary results of a feasibility study exploring the possibility of using rtfMRI to train older adults to volitionally control brain activity. Based on these first findings, we discuss possible implementations of rtfMRI neurofeedback as a novel technique to study and alleviate cognitive decline in healthy and pathological aging.
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Affiliation(s)
- Mohit Rana
- Department of Psychiatry and Division of Neuroscience, School of Medicine, Pontificia Universidad Católica de ChileSantiago, Chile; Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de ChileSantiago, Chile
| | - Andrew Q Varan
- Department of Psychology, University of Florida Gainesville, FL, USA
| | - Anis Davoudi
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida Gainesville, FL, USA
| | - Ronald A Cohen
- Center for Cognitive Aging and Memory, Institute on Aging, University of FloridaGainesville, FL, USA; Department of Aging and Geriatric Research, College of Medicine, University of FloridaGainesville, FL, USA
| | - Ranganatha Sitaram
- Department of Psychiatry and Division of Neuroscience, School of Medicine, Pontificia Universidad Católica de ChileSantiago, Chile; Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de ChileSantiago, Chile; Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de ChileSantiago, Chile
| | - Natalie C Ebner
- Department of Psychology, University of FloridaGainesville, FL, USA; Center for Cognitive Aging and Memory, Institute on Aging, University of FloridaGainesville, FL, USA; Department of Aging and Geriatric Research, College of Medicine, University of FloridaGainesville, FL, USA
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31
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Wang C, Ji F, Hong Z, Poh JS, Krishnan R, Lee J, Rekhi G, Keefe RSE, Adcock RA, Wood SJ, Fornito A, Pasternak O, Chee MWL, Zhou J. Disrupted salience network functional connectivity and white-matter microstructure in persons at risk for psychosis: findings from the LYRIKS study. Psychol Med 2016; 46:2771-2783. [PMID: 27396386 PMCID: PMC5358474 DOI: 10.1017/s0033291716001410] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2016] [Revised: 05/12/2016] [Accepted: 05/16/2016] [Indexed: 11/30/2022]
Abstract
BACKGROUND Salience network (SN) dysconnectivity has been hypothesized to contribute to schizophrenia. Nevertheless, little is known about the functional and structural dysconnectivity of SN in subjects at risk for psychosis. We hypothesized that SN functional and structural connectivity would be disrupted in subjects with At-Risk Mental State (ARMS) and would be associated with symptom severity and disease progression. METHOD We examined 87 ARMS and 37 healthy participants using both resting-state functional magnetic resonance imaging and diffusion tensor imaging. Group differences in SN functional and structural connectivity were examined using a seed-based approach and tract-based spatial statistics. Subject-level functional connectivity measures and diffusion indices of disrupted regions were correlated with CAARMS scores and compared between ARMS with and without transition to psychosis. RESULTS ARMS subjects exhibited reduced functional connectivity between the left ventral anterior insula and other SN regions. Reduced fractional anisotropy (FA) and axial diffusivity were also found along white-matter tracts in close proximity to regions of disrupted functional connectivity, including frontal-striatal-thalamic circuits and the cingulum. FA measures extracted from these disrupted white-matter regions correlated with individual symptom severity in the ARMS group. Furthermore, functional connectivity between the bilateral insula and FA at the forceps minor were further reduced in subjects who transitioned to psychosis after 2 years. CONCLUSIONS Our findings support the insular dysconnectivity of the proximal SN hypothesis in the early stages of psychosis. Further developed, the combined structural and functional SN assays may inform the prognosis of persons at-risk for psychosis.
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Affiliation(s)
- C. Wang
- Center for Cognitive Neuroscience,
Neuroscience and Behavioral Disorder Program, Duke-NUS
Medical School, National University of Singapore,
Singapore
| | - F. Ji
- Center for Cognitive Neuroscience,
Neuroscience and Behavioral Disorder Program, Duke-NUS
Medical School, National University of Singapore,
Singapore
| | - Z. Hong
- Center for Cognitive Neuroscience,
Neuroscience and Behavioral Disorder Program, Duke-NUS
Medical School, National University of Singapore,
Singapore
| | - J. S. Poh
- Center for Cognitive Neuroscience,
Neuroscience and Behavioral Disorder Program, Duke-NUS
Medical School, National University of Singapore,
Singapore
| | - R. Krishnan
- Center for Cognitive Neuroscience,
Neuroscience and Behavioral Disorder Program, Duke-NUS
Medical School, National University of Singapore,
Singapore
| | - J. Lee
- Research Division,
Institute of Mental Health, Singapore
- Office of Clinical Sciences,
Duke-NUS Medical School, Singapore
| | - G. Rekhi
- Research Division,
Institute of Mental Health, Singapore
| | - R. S. E. Keefe
- Department of Psychiatry and Behavioral
Sciences, Duke University, Durham,
NC, USA
| | - R. A. Adcock
- Department of Psychiatry and Behavioral
Sciences, Duke University, Durham,
NC, USA
- Center for Cognitive Neuroscience,
Duke University, Durham, NC,
USA
| | - S. J. Wood
- School of Psychology,
University of Birmingham, Edgbaston,
UK
- Department of Psychiatry,
Melbourne Neuropsychiatry Centre, University of
Melbourne and Melbourne Health, Victoria,
Australia
| | - A. Fornito
- Monash Clinical and Imaging
Neuroscience, School of Psychology and Psychiatry & Monash
Biomedical Imaging, Monash University,
Australia
| | - O. Pasternak
- Departments of Psychiatry and Radiology,
Brigham and Women's Hospital, Harvard Medical
School, Boston, MA, USA
| | - M. W. L. Chee
- Center for Cognitive Neuroscience,
Neuroscience and Behavioral Disorder Program, Duke-NUS
Medical School, National University of Singapore,
Singapore
| | - J. Zhou
- Center for Cognitive Neuroscience,
Neuroscience and Behavioral Disorder Program, Duke-NUS
Medical School, National University of Singapore,
Singapore
- Clinical Imaging Research Centre, the Agency for
Science, Technology and Research and National University of
Singapore, Singapore
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32
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Cerebellar microstructural abnormalities in bipolar depression and unipolar depression: A diffusion kurtosis and perfusion imaging study. J Affect Disord 2016; 195:21-31. [PMID: 26852094 DOI: 10.1016/j.jad.2016.01.042] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Revised: 12/21/2015] [Accepted: 01/26/2016] [Indexed: 01/02/2023]
Abstract
BACKGROUND Depression in the context of bipolar disorder (BD) is often misdiagnosed as unipolar depression (UD), leading to mistreatment and poor clinical outcomes. However, little is known about the similarities and differences in cerebellum between BD and UD. METHODS Patients with BD (n=35) and UD (n=30) during a depressive episode as well as 40 healthy controls underwent diffusional kurtosis imaging (DKI) and three dimensional arterial spin labeling (3D ASL). The DKI parameters including mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr),fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da) and radial diffusivity (Dr) and 3D ASL parameters (i.e. cerebral blood flow) was measured by using regions-of-interest (ROIs) analysis in the superior cerebellar peduncles (SCP), middle cerebellar peduncles (MCP) and dentate nuclei (DN) of cerebellum. RESULTS Patients with UD exhibited significant differences from controls for DKI measures in bilateral SCP and MCP and cerebral blood flow (CBF) in bilateral SCP and left DN. Patients with BD exhibited significant differences from controls for DKI measures in the right MCP and left DN and CBF in the left DN. Patients with UD showed significantly lower MD values compared with patients with BD in the right SCP. Correlation analysis showed there were negative correlations between illness duration and MD and Dr values in the right SCP in UD. LIMITATIONS This study was cross-sectional and the sample size was not large. Parts of the patients included were under medication prior to MRI scanning. CONCLUSIONS Our findings provide new evidence of microstructural changes in cerebellum in BD and UD. The two disorders may have overlaps in microstructural abnormality in MCP and DN during the depressive period. Microstructural abnormality in SCP may be a key neurobiological feature of UD.
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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: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
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34
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Berman RA, Gotts SJ, McAdams HM, Greenstein D, Lalonde F, Clasen L, Watsky RE, Shora L, Ordonez AE, Raznahan A, Martin A, Gogtay N, Rapoport J. Disrupted sensorimotor and social-cognitive networks underlie symptoms in childhood-onset schizophrenia. Brain 2015; 139:276-91. [PMID: 26493637 DOI: 10.1093/brain/awv306] [Citation(s) in RCA: 81] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2015] [Accepted: 08/30/2015] [Indexed: 12/11/2022] Open
Abstract
Schizophrenia is increasingly recognized as a neurodevelopmental disorder with altered connectivity among brain networks. In the current study we examined large-scale network interactions in childhood-onset schizophrenia, a severe form of the disease with salient genetic and neurobiological abnormalities. Using a data-driven analysis of resting-state functional magnetic resonance imaging fluctuations, we characterized data from 19 patients with schizophrenia and 26 typically developing controls, group matched for age, sex, handedness, and magnitude of head motion during scanning. This approach identified 26 regions with decreased functional correlations in schizophrenia compared to controls. These regions were found to organize into two function-related networks, the first with regions associated with social and higher-level cognitive processing, and the second with regions involved in somatosensory and motor processing. Analyses of across- and within-network regional interactions revealed pronounced across-network decreases in functional connectivity in the schizophrenia group, as well as a set of across-network relationships with overall negative coupling indicating competitive or opponent network dynamics. Critically, across-network decreases in functional connectivity in schizophrenia predicted the severity of positive symptoms in the disorder, such as hallucinations and delusions. By contrast, decreases in functional connectivity within the social-cognitive network of regions predicted the severity of negative symptoms, such as impoverished speech and flattened affect. These results point toward the role that abnormal integration of sensorimotor and social-cognitive processing may play in the pathophysiology and symptomatology of schizophrenia.
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Affiliation(s)
- Rebecca A Berman
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Stephen J Gotts
- 2 Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Harrison M McAdams
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Dede Greenstein
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Francois Lalonde
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Liv Clasen
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Rebecca E Watsky
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Lorie Shora
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Anna E Ordonez
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Armin Raznahan
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Alex Martin
- 2 Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Nitin Gogtay
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
| | - Judith Rapoport
- 1 Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda MD 20892, USA
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35
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Internetwork dynamic connectivity effectively differentiates schizophrenic patients from healthy controls. Neuroreport 2015; 25:1344-9. [PMID: 25275678 DOI: 10.1097/wnr.0000000000000267] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Increasingly more neuroimaging studies have shown that the complex symptoms of schizophrenia are linked to disrupted neural circuits and dysconnectivity of intrinsic connectivity networks. Previous studies have assumed temporal stationarity of resting-state functional connectivity, whereas temporal dynamics have rarely been explored. Here, we utilized resting-state functional MRI with a sliding window approach to measure the amplitude of low-frequency fluctuations (ALFFs) in functional connectivity in 24 patients with schizophrenia and 25 healthy controls. We found that there were significant differences in the ALFFs of specific connections, the majority of which were located between the intrinsic connectivity networks. Importantly, the experimental results of a multivariate pattern analysis of these ALFF measures showed that 81.3% (P<0.0009) of the participants were correctly classified as either schizophrenic patients or healthy controls by leave-one-out cross-validation. Our results show significant abnormality in the dynamics of internetwork functional connectivity in schizophrenia, which contributes toward the characterization and differentiation of schizophrenic patients, and may be used as a potential biomarker.
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Mueller S, Wang D, Pan R, Holt DJ, Liu H. Abnormalities in hemispheric specialization of caudate nucleus connectivity in schizophrenia. JAMA Psychiatry 2015; 72:552-60. [PMID: 25830688 PMCID: PMC4630217 DOI: 10.1001/jamapsychiatry.2014.3176] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Hemispheric specialization of the human brain is a marker of successful neurodevelopment. Altered brain asymmetry that has been repeatedly reported in schizophrenia may represent consequences of disrupted neurodevelopment in the disorder. However, a complete picture of functional specialization in the schizophrenic brain and its connectional substrates is yet to be unveiled. OBJECTIVES To quantify intrinsic hemispheric specialization at cortical and subcortical levels and to reveal potential disease effects in schizophrenia. DESIGN, SETTING, AND PARTICIPANTS Resting-state functional connectivity magnetic resonance imaging has been previously used to quantitatively measure hemispheric specialization in healthy individuals in a reliable manner. We quantified the intrinsic hemispheric specialization at the whole brain level in 31 patients with schizophrenia and 37 demographically matched healthy controls from November 28, 2007, through June 29, 2010, using resting-state functional magnetic resonance imaging. RESULTS The caudate nucleus and cortical regions with connections to the caudate nucleus had markedly abnormal hemispheric specialization in schizophrenia. Compared with healthy controls, patients exhibited weaker specialization in the left, but the opposite pattern in the right, caudate nucleus (P < .001). Patients with schizophrenia also had a disruption of the interhemispheric coordination among the cortical regions with connections to the caudate nucleus. A linear classifier based on the specialization of the caudate nucleus distinguished patients from controls with a classification accuracy of 74% (with a sensitivity of 68% and a specificity of 78%). CONCLUSIONS AND RELEVANCE These data suggest that hemispheric specialization could serve as a potential imaging biomarker of schizophrenia that, compared with task-based functional magnetic resonance imaging measures, is less prone to the confounding effects of variation in task compliance, cognitive ability, and command of language.
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Affiliation(s)
- Sophia Mueller
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Charlestown, MA
- Ludwig Maximilians University Munich, Institute of Clinical Radiology, Munich, Germany
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Charlestown, MA
| | - Ruiqi Pan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Charlestown, MA
| | - Daphne J. Holt
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Charlestown, MA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Charlestown, MA
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Lee HJ, Preda A, Ford JM, Mathalon DH, Keator DB, van Erp TG, Turner JA, Potkin SG. Functional magnetic resonance imaging of motor cortex activation in schizophrenia. J Korean Med Sci 2015; 30:625-31. [PMID: 25931795 PMCID: PMC4414648 DOI: 10.3346/jkms.2015.30.5.625] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Accepted: 01/20/2015] [Indexed: 11/22/2022] Open
Abstract
Previous fMRI studies of sensorimotor activation in schizophrenia have found in some cases hypoactivity, no difference, or hyperactivity when comparing patients with controls; similar disagreement exists in studies of motor laterality. In this multi-site fMRI study of a sensorimotor task in individuals with chronic schizophrenia and matched healthy controls, subjects responded with a right-handed finger press to an irregularly flashing visual checker board. The analysis includes eighty-five subjects with schizophrenia diagnosed according to the DSM-IV criteria and eighty-six healthy volunteer subjects. Voxel-wise statistical parametric maps were generated for each subject and analyzed for group differences; the percent Blood Oxygenation Level Dependent (BOLD) signal changes were also calculated over predefined anatomical regions of the primary sensory, motor, and visual cortex. Both healthy controls and subjects with schizophrenia showed strongly lateralized activation in the precentral gyrus, inferior frontal gyrus, and inferior parietal lobule, and strong activations in the visual cortex. There were no significant differences between subjects with schizophrenia and controls in this multi-site fMRI study. Furthermore, there was no significant difference in laterality found between healthy controls and schizophrenic subjects. This study can serve as a baseline measurement of schizophrenic dysfunction in other cognitive processes.
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Affiliation(s)
- Hyo Jong Lee
- Division of Computer Science and Engineering, CAIIT, Chonbuk National University, Jeonju, Korea
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Judith M. Ford
- Department of Psychiatry, San Francisco VAMC and University of California, San Francisco, CA, USA
| | - Daniel H. Mathalon
- Department of Psychiatry, San Francisco VAMC and University of California, San Francisco, CA, USA
| | - David B. Keator
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Theo G.M. van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Jessica A. Turner
- Department of Psychology and Neuroscience, Georgia State University, Atlanta, GA, USA
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
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Hahamy A, Calhoun V, Pearlson G, Harel M, Stern N, Attar F, Malach R, Salomon R. Save the global: global signal connectivity as a tool for studying clinical populations with functional magnetic resonance imaging. Brain Connect 2015; 4:395-403. [PMID: 24923194 DOI: 10.1089/brain.2014.0244] [Citation(s) in RCA: 149] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
The global signal is commonly removed from resting-state data, as it was presumed to reflect physiological noise. However, removal of the global signal is now under debate, as this signal may reflect important neuronal components, and its removal may introduce artifacts into the data. Here, we show that the functional connectivity (FC) of the global signal is of functional relevance, as it differentiates between schizophrenia patients and healthy controls during rest. We also demonstrate that other reported findings related to various clinical populations may actually reflect alternations in global signal FC. The evidence of the clinical relevance of the global signal propose its usage as a research tool, and extend previously reported perils of global signal removal in resting-state data of clinical populations.
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Affiliation(s)
- Avital Hahamy
- 1 Department of Neurobiology, Weizmann Institute of Science , Rehovot, Israel
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Diwadkar VA, Burgess A, Hong E, Rix C, Arnold PD, Hanna GL, Rosenberg DR. Dysfunctional Activation and Brain Network Profiles in Youth with Obsessive-Compulsive Disorder: A Focus on the Dorsal Anterior Cingulate during Working Memory. Front Hum Neurosci 2015; 9:149. [PMID: 25852529 PMCID: PMC4362304 DOI: 10.3389/fnhum.2015.00149] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Accepted: 03/03/2015] [Indexed: 01/05/2023] Open
Abstract
Brain network dysfunction is emerging as a central biomarker of interest in psychiatry, in large part, because psychiatric conditions are increasingly seen as disconnection syndromes. Understanding dysfunctional brain network profiles in task-active states provides important information on network engagement in an experimental context. This in turn may be predictive of many of the cognitive and behavioral deficits associated with complex behavioral phenotypes. Here we investigated brain network profiles in youth with obsessive-compulsive disorder (OCD), contrasting them with a group of age-comparable controls. Network interactions were assessed during simple working memory: in particular, we focused on the modulation by the dorsal anterior cingulate cortex (dACC) of cortical, striatal, and thalamic regions. The focus on the dACC was motivated by its hypothesized role in the pathophysiology of OCD. However, its task-active network signatures have not been investigated before. Network interactions were modeled using psychophysiological interaction, a simple directional model of seed to target brain interactions. Our results indicate that OCD is characterized by significantly increased dACC modulation of cortical, striatal, and thalamic targets during working memory, and that this aberrant increase in OCD patients is maintained regardless of working memory demand. The results constitute compelling evidence of dysfunctional brain network interactions in OCD and suggest that these interactions may be related to a combination of network inefficiencies and dACC hyper-activity that has been associated with the phenotype.
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Affiliation(s)
- Vaibhav A Diwadkar
- Department of Psychiatry and Behavioral Neurosciences, Brain Imaging Research Division, Wayne State University School of Medicine , Detroit, MI , USA
| | - Ashley Burgess
- Department of Psychiatry and Behavioral Neurosciences, Brain Imaging Research Division, Wayne State University School of Medicine , Detroit, MI , USA
| | - Ella Hong
- Department of Psychiatry and Behavioral Neurosciences, Brain Imaging Research Division, Wayne State University School of Medicine , Detroit, MI , USA
| | - Carrie Rix
- Department of Psychiatry and Behavioral Neurosciences, Brain Imaging Research Division, Wayne State University School of Medicine , Detroit, MI , USA
| | - Paul D Arnold
- Department of Psychiatry, Hospital for Sick Children, University of Toronto , Toronto, ON , Canada
| | - Gregory L Hanna
- Department of Psychiatry, University of Michigan , Ann Arbor, MI , USA
| | - David R Rosenberg
- Department of Psychiatry and Behavioral Neurosciences, Brain Imaging Research Division, Wayne State University School of Medicine , Detroit, MI , USA
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Basar-Eroglu C, Mathes B, Khalaidovski K, Brand A, Schmiedt-Fehr C. Altered alpha brain oscillations during multistable perception in schizophrenia. Int J Psychophysiol 2015; 103:118-28. [PMID: 25746892 DOI: 10.1016/j.ijpsycho.2015.02.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Schizophrenia is a complex mental disorder with impairments in integrating sensory and cognitive functions, leading to severe problems in coherent perception. This impairment might be accelerated during multistable perception. Multistable perception is a phenomenon, where a visual pattern gives rise to at least two different perceptual representations. We addressed this issue by assessing event-related alpha oscillations during continuous viewing of an ambiguous and unambiguous control stimulus. Perceptual reversals were indicated by a manual response, allowing differentiation between phases of reversion and non-reversion (that is perceptual stability) in both tasks. During the ambiguous task, patients and controls showed a comparable number of perceptual reversals. Alpha amplitudes in patients were larger in non-reversion phases, accompanied by a stronger decrease of alpha activity preceding the perceptual reversal. This group difference was pronounced for lower alpha activity and not apparent during the unambiguous task. This indicates that ambiguous perception taps into the specific deficits that patients experience in maintaining coherent perception. Given that top-down influences in generating a meaningful percept seems to be low in patients, they appear more dependent on sensory information. Similar, bottom-up mechanisms might be more important in triggering perceptual reversals in patients than in controls.
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Affiliation(s)
- Canan Basar-Eroglu
- University of Bremen, Institute of Psychology and Cognition Research, Grazer Str.4, D-28359 Bremen, Germany; Centre for Cognitive Science, Bremen, Germany.
| | - Birgit Mathes
- University of Bremen, Institute of Psychology and Cognition Research, Grazer Str.4, D-28359 Bremen, Germany; Centre for Cognitive Science, Bremen, Germany
| | - Ksenia Khalaidovski
- University of Bremen, Institute of Psychology and Cognition Research, Grazer Str.4, D-28359 Bremen, Germany; Centre for Cognitive Science, Bremen, Germany
| | - Andreas Brand
- University of Bremen, Institute of Psychology and Cognition Research, Grazer Str.4, D-28359 Bremen, Germany; Centre for Cognitive Science, Bremen, Germany
| | - Christina Schmiedt-Fehr
- University of Bremen, Institute of Psychology and Cognition Research, Grazer Str.4, D-28359 Bremen, Germany; Centre for Cognitive Science, Bremen, Germany
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41
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Guo W, Liu F, Liu J, Yu L, Zhang J, Zhang Z, Xiao C, Zhai J, Zhao J. Abnormal causal connectivity by structural deficits in first-episode, drug-naive schizophrenia at rest. Schizophr Bull 2015; 41:57-65. [PMID: 25170032 PMCID: PMC4266300 DOI: 10.1093/schbul/sbu126] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Anatomical deficits and resting-state functional connectivity (FC) alterations in prefrontal-thalamic-cerebellar circuit have been implicated in the neurobiology of schizophrenia. However, the effect of structural deficits in schizophrenia on causal connectivity of this circuit remains unclear. This study was conducted to examine the causal connectivity biased by structural deficits in first-episode, drug-naive schizophrenia patients. Structural and resting-state functional magnetic resonance imaging (fMRI) data were obtained from 49 first-episode, drug-naive schizophrenia patients and 50 healthy controls. Data were analyzed by voxel-based morphometry and Granger causality analysis. The causal connectivity of the integrated prefrontal-thalamic (limbic)-cerebellar (sensorimotor) circuit was partly affected by structural deficits in first-episode, drug-naive schizophrenia as follows: (1) unilateral prefrontal-sensorimotor connectivity abnormalities (increased driving effect from the left medial prefrontal cortex [MPFC] to the sensorimotor regions); (2) bilateral limbic-sensorimotor connectivity abnormalities (increased driving effect from the right anterior cingulate cortex [ACC] to the sensorimotor regions and decreased feedback from the sensorimotor regions to the right ACC); and (3) bilateral increased and decreased causal connectivities among the sensorimotor regions. Some correlations between the gray matter volume of the seeds, along with their causal effects and clinical variables (duration of untreated psychosis and symptom severity), were also observed in the patients. The findings indicated the partial effects of structural deficits in first-episode, drug-naive schizophrenia on the prefrontal-thalamic (limbic)-cerebellar (sensorimotor) circuit. Schizophrenia may reinforce the driving connectivities from the left MPFC or right ACC to the sensorimotor regions and may disrupt bilateral causal connectivities among the sensorimotor regions.
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Affiliation(s)
- Wenbin Guo
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, China;
| | - Feng Liu
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Jianrong Liu
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, China
| | - Liuyu Yu
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, China
| | - Jian Zhang
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, China
| | - Zhikun Zhang
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, China
| | - Changqing Xiao
- Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, China
| | - Jinguo Zhai
- School of Mental Health, Jining Medical University, Jining, China
| | - Jingping Zhao
- Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, China
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42
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Wang L, Zou F, Shao Y, Ye E, Jin X, Tan S, Hu D, Yang Z. Disruptive changes of cerebellar functional connectivity with the default mode network in schizophrenia. Schizophr Res 2014; 160:67-72. [PMID: 25445623 DOI: 10.1016/j.schres.2014.09.034] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2014] [Revised: 08/31/2014] [Accepted: 09/16/2014] [Indexed: 11/15/2022]
Abstract
The default mode network (DMN) plays an important role in the physiopathology of schizophrenia. Previous studies have suggested that the cerebellum participates in higher-order cognitive networks such as the DMN. However, the specific contribution of the cerebellum to the DMN abnormalities in schizophrenia has yet to be established. In this study, we investigated cerebellar functional connectivity differences between 60 patients with schizophrenia and 60 healthy controls from a public resting-state fMRI database. Seed-based correlation analysis was performed by using seeds from the left Crus I, right Crus I and Lobule IX, which have previously been identified as being involved in the DMN. Our results revealed that, compared with the healthy controls, the patients showed significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions including the middle frontal gyrus, anterior cingulate cortex, and supplementary motor area. Moreover, the positive correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity observed in the healthy subjects were diminished in the patients. Our findings implicate disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, which may provide further evidence for the "cognitive dysmetria" concept of schizophrenia.
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Affiliation(s)
- Lubin Wang
- Beijing Institute of Basic Medical Sciences, Beijing, PR China; Cognitive and Mental Health Research Center, Beijing, PR China
| | - Feng Zou
- Beijing Institute of Basic Medical Sciences, Beijing, PR China; Cognitive and Mental Health Research Center, Beijing, PR China
| | - Yongcong Shao
- Beijing Institute of Basic Medical Sciences, Beijing, PR China; Cognitive and Mental Health Research Center, Beijing, PR China
| | - Enmao Ye
- Beijing Institute of Basic Medical Sciences, Beijing, PR China; Cognitive and Mental Health Research Center, Beijing, PR China
| | - Xiao Jin
- Beijing Institute of Basic Medical Sciences, Beijing, PR China; Cognitive and Mental Health Research Center, Beijing, PR China
| | - Shuwen Tan
- Beijing Institute of Basic Medical Sciences, Beijing, PR China; Cognitive and Mental Health Research Center, Beijing, PR China
| | - Dewen Hu
- College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, PR China.
| | - Zheng Yang
- Beijing Institute of Basic Medical Sciences, Beijing, PR China; Cognitive and Mental Health Research Center, Beijing, PR China.
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Rashid B, Damaraju E, Pearlson GD, Calhoun VD. Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects. Front Hum Neurosci 2014; 8:897. [PMID: 25426048 PMCID: PMC4224100 DOI: 10.3389/fnhum.2014.00897] [Citation(s) in RCA: 298] [Impact Index Per Article: 27.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2014] [Accepted: 10/20/2014] [Indexed: 12/11/2022] Open
Abstract
Schizophrenia (SZ) and bipolar disorder (BP) share significant overlap in clinical symptoms, brain characteristics, and risk genes, and both are associated with dysconnectivity among large-scale brain networks. Resting state functional magnetic resonance imaging (rsfMRI) data facilitates studying macroscopic connectivity among distant brain regions. Standard approaches to identifying such connectivity include seed-based correlation and data-driven clustering methods such as independent component analysis (ICA) but typically focus on average connectivity. In this study, we utilize ICA on rsfMRI data to obtain intrinsic connectivity networks (ICNs) in cohorts of healthy controls (HCs) and age matched SZ and BP patients. Subsequently, we investigated difference in functional network connectivity, defined as pairwise correlations among the timecourses of ICNs, between HCs and patients. We quantified differences in both static (average) and dynamic (windowed) connectivity during the entire scan duration. Disease-specific differences were identified in connectivity within different dynamic states. Notably, results suggest that patients make fewer transitions to some states (states 1, 2, and 4) compared to HCs, with most such differences confined to a single state. SZ patients showed more differences from healthy subjects than did bipolars, including both hyper and hypo connectivity in one common connectivity state (dynamic state 3). Also group differences between SZ and bipolar patients were identified in patterns (states) of connectivity involving the frontal (dynamic state 1) and frontal-parietal regions (dynamic state 3). Our results provide new information about these illnesses and strongly suggest that state-based analyses are critical to avoid averaging together important factors that can help distinguish these clinical groups.
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Affiliation(s)
- Barnaly Rashid
- The Mind Research Network, Albuquerque NM, USA ; Department of Electrical and Computer Engineering, University of New Mexico Albuquerque, NM, USA
| | - Eswar Damaraju
- The Mind Research Network, Albuquerque NM, USA ; Department of Electrical and Computer Engineering, University of New Mexico Albuquerque, NM, USA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center - Institute of Living, Hartford CT, USA ; Departments of Psychiatry, Yale University School of Medicine New Haven, CT, USA ; Departments of Neurobiology, Yale University School of Medicine New Haven, CT, USA
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque NM, USA ; Department of Electrical and Computer Engineering, University of New Mexico Albuquerque, NM, USA ; Olin Neuropsychiatry Research Center - Institute of Living, Hartford CT, USA ; Departments of Psychiatry, Yale University School of Medicine New Haven, CT, USA
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Barnes SA, Sawiak SJ, Caprioli D, Jupp B, Buonincontri G, Mar AC, Harte MK, Fletcher PC, Robbins TW, Neill JC, Dalley JW. Impaired limbic cortico-striatal structure and sustained visual attention in a rodent model of schizophrenia. Int J Neuropsychopharmacol 2014; 18:pyu010. [PMID: 25552430 PMCID: PMC4368881 DOI: 10.1093/ijnp/pyu010] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Accepted: 06/09/2014] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND N-methyl-d-aspartate receptor (NMDAR) dysfunction is thought to contribute to the pathophysiology of schizophrenia. Accordingly, NMDAR antagonists such as phencyclidine (PCP) are used widely in experimental animals to model cognitive impairment associated with this disorder. However, it is unclear whether PCP disrupts the structural integrity of brain areas relevant to the profile of cognitive impairment in schizophrenia. METHODS Here we used high-resolution magnetic resonance imaging and voxel-based morphometry to investigate structural alterations associated with sub-chronic PCP treatment in rats. RESULTS Sub-chronic exposure of rats to PCP (5mg/kg twice daily for 7 days) impaired sustained visual attention on a 5-choice serial reaction time task, notably when the attentional load was increased. In contrast, sub-chronic PCP had no significant effect on the attentional filtering of a pre-pulse auditory stimulus in an acoustic startle paradigm. Voxel-based morphometry revealed significantly reduced grey matter density bilaterally in the hippocampus, anterior cingulate cortex, ventral striatum, and amygdala. PCP-treated rats also exhibited reduced cortical thickness in the insular cortex. CONCLUSIONS These findings demonstrate that sub-chronic NMDA receptor antagonism is sufficient to produce highly-localized morphological abnormalities in brain areas implicated in the pathogenesis of schizophrenia. Furthermore, PCP exposure resulted in dissociable impairments in attentional function.
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Affiliation(s)
- Samuel A Barnes
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Stephen J Sawiak
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Daniele Caprioli
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Bianca Jupp
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Guido Buonincontri
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Adam C Mar
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Michael K Harte
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Paul C Fletcher
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Trevor W Robbins
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Jo C Neill
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill)
| | - Jeffrey W Dalley
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA (Dr Barnes); Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Downing St, Cambridge UK (Drs Sawiak, Caprioli, Jupp, Mar, Fletcher, Robbins, and Dalley); Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Sawiak and Buonincontri); Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (Drs Fletcher and Dalley); Manchester Pharmacy School, University of Manchester, UK (Drs Harte and Neill).
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Parker KL, Narayanan NS, Andreasen NC. The therapeutic potential of the cerebellum in schizophrenia. Front Syst Neurosci 2014; 8:163. [PMID: 25309350 PMCID: PMC4163988 DOI: 10.3389/fnsys.2014.00163] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2014] [Accepted: 08/22/2014] [Indexed: 12/19/2022] Open
Abstract
The cognitive role of the cerebellum is critically tied to its distributed connections throughout the brain. Accumulating evidence from anatomical, structural and functional imaging, and lesion studies advocate a cognitive network involving indirect connections between the cerebellum and non-motor areas in the prefrontal cortex. Cerebellar stimulation dynamically influences activity in several regions of the frontal cortex and effectively improves cognition in schizophrenia. In this manuscript, we summarize current literature on the cingulocerebellar circuit and we introduce a method to interrogate this circuit combining opotogenetics, neuropharmacology, and electrophysiology in awake-behaving animals while minimizing incidental stimulation of neighboring cerebellar nuclei. We propose the novel hypothesis that optogenetic cerebellar stimulation can restore aberrant frontal activity and rescue impaired cognition in schizophrenia. We focus on how a known cognitive region in the frontal cortex, the anterior cingulate, is influenced by the cerebellum. This circuit is of particular interest because it has been confirmed using tracing studies, neuroimaging reveals its role in cognitive tasks, it is conserved from rodents to humans, and diseases such as schizophrenia and autism appear in its aberrancy. Novel tract tracing results presented here provide support for how these two areas communicate. The primary pathway involves a disynaptic connection between the cerebellar dentate nuclei (DN) and the anterior cingulate cortex. Secondarily, the pathway from cerebellar fastigial nuclei (FN) to the ventral tegmental area, which supplies dopamine to the prefrontal cortex, may play a role as schizophrenia characteristically involves dopamine deficiencies. We hope that the hypothesis described here will inspire new therapeutic strategies targeting currently untreatable cognitive impairments in schizophrenia.
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Lin D, Cao H, Calhoun VD, Wang YP. Sparse models for correlative and integrative analysis of imaging and genetic data. J Neurosci Methods 2014; 237:69-78. [PMID: 25218561 DOI: 10.1016/j.jneumeth.2014.09.001] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2014] [Revised: 08/27/2014] [Accepted: 09/01/2014] [Indexed: 11/29/2022]
Abstract
The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis.
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Affiliation(s)
- Dongdong Lin
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, 70118, USA; Center of Genomics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA.
| | - Hongbao Cao
- Unit on Statistical Genomics, Intramural Program of Research, National Institute of Mental Health, NIH, Bethesda 20852, USA.
| | - Vince D Calhoun
- The Mind Research Network & LBERI, Albuquerque, NM 87106, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131, USA.
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, 70118, USA; Center of Genomics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA.
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Oflaz S, Akyuz F, Hamamci A, Firat Z, Keskinkılıç C, Kilickesmez O, Cihangiroglu M. Working memory dysfunction in delusional disorders: an fMRI investigation. J Psychiatr Res 2014; 56:43-9. [PMID: 24841112 DOI: 10.1016/j.jpsychires.2014.04.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2014] [Revised: 04/15/2014] [Accepted: 04/28/2014] [Indexed: 10/25/2022]
Abstract
BACKGROUND Delusional disorder (DD) is a rare and understudied psychiatric disorder. There is limited number of studies concerning cognitive characteristics in DD. Using an established working memory paradigm with variable levels of memory load, we investigated alterations in functional magnetic resonance imaging (fMRI) of brain regions in patients with DD. METHODS This case control study included 9 patients with DD and 9 healthy control subjects matched for age, sex, and education level. Diagnosis of DD was confirmed using the Structured Clinical Interview for DSM-IV Axis I. The severity of the symptoms was evaluated using the Positive and Negative Syndrome Scale. All patients were asked to perform 0-back and 2-back tasks during fMRI experiments. Functional imaging was performed using the 3.0 T Philips whole-body scanner using an 8-channel head coil. RESULTS Participants with DD had less neural activation of the left dorsolateral prefrontal cortex in fMRI scans obtained during performance tasks. On the other hand, neural activation of the left and right superior temporal gyrus, left middle and inferior temporal gyrus, right and left posterior cingulate gyrus, right amygdala, left and right fusiform gyrus was more prominent in patients with DD in comparison with the control group. DISCUSSION Patients with DD had dysfunction in the prefrontal, temporal and limbic regions of the brain in particular, during performance tasks of working memory. Our findings were in line with the findings of the early reports on deficient functioning in temporal or limbic regions of the brain. Further, patients with DD displayed prefrontal dysfunction as seen in patients with schizophrenia.
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Affiliation(s)
- Serap Oflaz
- Department of Psychiatry, Istanbul School of Medicine, Istanbul University, Istanbul Millet Street, Capa 34390 Istanbul, Turkey.
| | - Fatma Akyuz
- Department of Psychiatry, Bakirkoy Dr Sadi Konuk Education and Research Hospital, Istanbul, Turkey
| | - Andac Hamamci
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey
| | - Zeynep Firat
- Department of Radiology, Yeditepe University Hospital, Istanbul, Turkey
| | - Cahit Keskinkılıç
- Department of Neurology, Bakirkoy Research and Training Hospital for Psychiatry, Neurology and Neurosurgery, İstanbul, Turkey
| | - Ozgur Kilickesmez
- Department of Radiology, Istanbul Education and Research Hospital, Istanbul, Turkey
| | - Mutlu Cihangiroglu
- Department of Radiology, Medicalpark University, Göztepe Hospital, Istanbul, Turkey
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48
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Lin D, Calhoun VD, Wang YP. Correspondence between fMRI and SNP data by group sparse canonical correlation analysis. Med Image Anal 2014; 18:891-902. [PMID: 24247004 PMCID: PMC4007390 DOI: 10.1016/j.media.2013.10.010] [Citation(s) in RCA: 86] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2013] [Revised: 08/27/2013] [Accepted: 10/16/2013] [Indexed: 10/26/2022]
Abstract
Both genetic variants and brain region abnormalities are recognized as important factors for complex diseases (e.g., schizophrenia). In this paper, we investigated the correspondence between single nucleotide polymorphism (SNP) and brain activity measured by functional magnetic resonance imaging (fMRI) to understand how genetic variation influences the brain activity. A group sparse canonical correlation analysis method (group sparse CCA) was developed to explore the correlation between these two datasets which are high dimensional-the number of SNPs/voxels is far greater than the number of samples. Different from the existing sparse CCA methods (sCCA), our approach can exploit structural information in the correlation analysis by introducing group constraints. A simulation study demonstrates that it outperforms the existing sCCA. We applied this method to the real data analysis and identified two pairs of significant canonical variates with average correlations of 0.4527 and 0.4292 respectively, which were used to identify genes and voxels associated with schizophrenia. The selected genes are mostly from 5 schizophrenia (SZ)-related signalling pathways. The brain mappings of the selected voxles also indicate the abnormal brain regions susceptible to schizophrenia. A gene and brain region of interest (ROI) correlation analysis was further performed to confirm the significant correlations between genes and ROIs.
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Affiliation(s)
- Dongdong Lin
- Biomedical Engineering Department, Tulane University, New Orleans, LA 70118, USA; Center of Genomics and Bioinformatics, Tulane University, New Orleans, LA 70118, USA.
| | - Vince D Calhoun
- The Mind Research Network, Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131, USA.
| | - Yu-Ping Wang
- Biomedical Engineering Department, Tulane University, New Orleans, LA 70118, USA; Center of Genomics and Bioinformatics, Tulane University, New Orleans, LA 70118, USA; Center for Systems Biomedicine, Shanghai University for Science and Technology, Shanghai, China.
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Taurisano P, Romano R, Mancini M, Giorgio AD, Antonucci LA, Fazio L, Rampino A, Quarto T, Gelao B, Porcelli A, Papazacharias A, Ursini G, Caforio G, Masellis R, Niccoli-Asabella A, Todarello O, Popolizio T, Rubini G, Blasi G, Bertolino A. Prefronto-striatal physiology is associated with schizotypy and is modulated by a functional variant of DRD2. Front Behav Neurosci 2014; 8:235. [PMID: 25071490 PMCID: PMC4089730 DOI: 10.3389/fnbeh.2014.00235] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2014] [Accepted: 06/13/2014] [Indexed: 11/13/2022] Open
Abstract
“Schizotypy” is a latent organization of personality related to the genetic risk for schizophrenia. Some evidence suggests that schizophrenia and schizotypy share some biological features, including a link to dopaminergic D2 receptor signaling. A polymorphism in the D2 gene (DRD2 rs1076560, guanine > thymine (G > T)) has been associated with the D2 short/long isoform expression ratio, as well as striatal dopamine signaling and prefrontal cortical activity during different cognitive operations, which are measures that are altered in patients with schizophrenia. Our aim is to determine the association of schizotypy scores with the DRD2 rs1076560 genotype in healthy individuals and their interaction with prefrontal activity during attention and D2 striatal signaling. A total of 83 healthy subjects were genotyped for DRD2 rs1076560 and completed the Schizotypal Personality Questionnaire (SPQ). Twenty-six participants underwent SPECT with [123I]IBZM D2 receptor radiotracer, while 68 performed an attentional control task during fMRI. We found that rs1076560 GT subjects had greater SPQ scores than GG individuals. Moreover, the interaction between schizotypy and the GT genotype predicted prefrontal activity and related attentional behavior, as well as striatal binding of IBZM. No interaction was found in GG individuals. These results suggest that rs1076560 GT healthy individuals are prone to higher levels of schizotypy, and that the interaction between rs1076560 and schizotypy scores modulates phenotypes related to the pathophysiology of schizophrenia, such as prefrontal activity and striatal dopamine signaling. These results provide systems-level qualitative evidence for mapping the construct of schizotypy in healthy individuals onto the schizophrenia continuum.
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Affiliation(s)
- Paolo Taurisano
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy ; IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo Foggia, Italy
| | - Raffaella Romano
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Marina Mancini
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Annabella Di Giorgio
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy ; IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo Foggia, Italy
| | - Linda A Antonucci
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Leonardo Fazio
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy ; IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo Foggia, Italy
| | - Antonio Rampino
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Tiziana Quarto
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy ; Department of Behavioural Sciences, Cognitive Brain Research Unit, University of Helsinki Helsinki, Finland
| | - Barbara Gelao
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Annamaria Porcelli
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Apostolos Papazacharias
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Gianluca Ursini
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy ; Lieber Institute for Brain Development, Johns Hopkins University Medical Campus Baltimore, MD, USA
| | - Grazia Caforio
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Rita Masellis
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Artor Niccoli-Asabella
- Department of Internal Medicine and of Public Medicine, Nuclear Medicine Unit, University of Bari Aldo Moro Bari, Italy
| | - Orlando Todarello
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Teresa Popolizio
- IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo Foggia, Italy
| | - Giuseppe Rubini
- Department of Internal Medicine and of Public Medicine, Nuclear Medicine Unit, University of Bari Aldo Moro Bari, Italy
| | - Giuseppe Blasi
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Psychiatric Neuroscience Group, Neuroscience and Sense Organs, University of Bari Aldo Moro Bari, Italy ; IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo Foggia, Italy ; pRED, NORD DTA, Hoffmann-La Roche, Ltd. Basel, Switzerland
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Sepede G, Spano MC, Lorusso M, Berardis DD, Salerno RM, Giannantonio MD, Gambi F. Sustained attention in psychosis: Neuroimaging findings. World J Radiol 2014; 6:261-273. [PMID: 24976929 PMCID: PMC4072813 DOI: 10.4329/wjr.v6.i6.261] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2013] [Revised: 02/07/2014] [Accepted: 05/16/2014] [Indexed: 02/06/2023] Open
Abstract
To provide a systematic review of scientific literature on functional magnetic resonance imaging (fMRI) studies on sustained attention in psychosis. We searched PubMed to identify fMRI studies pertaining sustained attention in both affective and non-affective psychosis. Only studies conducted on adult patients using a sustained attention task during fMRI scanning were included in the final review. The search was conducted on September 10th, 2013. 15 fMRI studies met our inclusion criteria: 12 studies were focused on Schizophrenia and 3 on Bipolar Disorder Type I (BDI). Only half of the Schizophrenia studies and two of the BDI studies reported behavioral abnormalities, but all of them evidenced significant functional differences in brain regions related to the sustained attention system. Altered functioning of the insula was found in both Schizophrenia and BDI, and therefore proposed as a candidate trait marker for psychosis in general. On the other hand, other brain regions were differently impaired in affective and non-affective psychosis: alterations of cingulate cortex and thalamus seemed to be more common in Schizophrenia and amygdala dysfunctions in BDI. Neural correlates of sustained attention seem to be of great interest in the study of psychosis, highlighting differences and similarities between Schizophrenia and BDI.
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