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Cho S, van Es M, Woolrich M, Gohil C. Comparison between EEG and MEG of static and dynamic resting-state networks. Hum Brain Mapp 2024; 45:e70018. [PMID: 39230193 PMCID: PMC11372824 DOI: 10.1002/hbm.70018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/29/2024] [Accepted: 08/20/2024] [Indexed: 09/05/2024] Open
Abstract
The characterisation of resting-state networks (RSNs) using neuroimaging techniques has significantly contributed to our understanding of the organisation of brain activity. Prior work has demonstrated the electrophysiological basis of RSNs and their dynamic nature, revealing transient activations of brain networks with millisecond timescales. While previous research has confirmed the comparability of RSNs identified by electroencephalography (EEG) to those identified by magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), most studies have utilised static analysis techniques, ignoring the dynamic nature of brain activity. Often, these studies use high-density EEG systems, which limit their applicability in clinical settings. Addressing these gaps, our research studies RSNs using medium-density EEG systems (61 sensors), comparing both static and dynamic brain network features to those obtained from a high-density MEG system (306 sensors). We assess the qualitative and quantitative comparability of EEG-derived RSNs to those from MEG, including their ability to capture age-related effects, and explore the reproducibility of dynamic RSNs within and across the modalities. Our findings suggest that both MEG and EEG offer comparable static and dynamic network descriptions, albeit with MEG offering some increased sensitivity and reproducibility. Such RSNs and their comparability across the two modalities remained consistent qualitatively but not quantitatively when the data were reconstructed without subject-specific structural MRI images.
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Affiliation(s)
- SungJun Cho
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Mats van Es
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Chetan Gohil
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
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Cattarinussi G, Grimaldi DA, Aarabi MH, Sambataro F. Static and Dynamic Dysconnectivity in Early Psychosis: Relationship With Symptom Dimensions. Schizophr Bull 2024:sbae142. [PMID: 39212653 DOI: 10.1093/schbul/sbae142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
BACKGROUND AND HYPOTHESIS Altered functional connectivity (FC) has been frequently reported in psychosis. Studying FC and its time-varying patterns in early-stage psychosis allows the investigation of the neural mechanisms of this disorder without the confounding effects of drug treatment or illness-related factors. STUDY DESIGN We employed resting-state functional magnetic resonance imaging (rs-fMRI) to explore FC in individuals with early psychosis (EP), who also underwent clinical and neuropsychological assessments. 96 EP and 56 demographically matched healthy controls (HC) from the Human Connectome Project for Early Psychosis database were included. Multivariate analyses using spatial group independent component analysis were used to compute static FC and dynamic functional network connectivity (dFNC). Partial correlations between FC measures and clinical and cognitive variables were performed to test brain-behavior associations. STUDY RESULTS Compared to HC, EP showed higher static FC in the striatum and temporal, frontal, and parietal cortex, as well as lower FC in the frontal, parietal, and occipital gyrus. We found a negative correlation in EP between cognitive function and FC in the right striatum FC (pFWE = 0.009). All dFNC parameters, including dynamism and fluidity measures, were altered in EP, and positive symptoms were negatively correlated with the meta-state changes and the total distance (pFWE = 0.040 and pFWE = 0.049). CONCLUSIONS Our findings support the view that psychosis is characterized from the early stages by complex alterations in intrinsic static and dynamic FC, that may ultimately result in positive symptoms and cognitive deficits.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia, USA
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
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Ma L, Yang Y, Li S, Upreti B, Liu S, Wang X, Bai R, Cheng Y, Xu J. Interaction of 5-HTTLPR and SLE disease status on resting-state brain function. Arthritis Res Ther 2024; 26:38. [PMID: 38297395 PMCID: PMC10829289 DOI: 10.1186/s13075-024-03276-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 01/23/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Neuropsychiatric involvement in systemic lupus erythematosus (SLE) is a common clinical manifestation. In SLE patients, cerebral function is a more sensitive predictor of central nervous system damage, and abnormalities in cerebral function may be apparent before substantial neuropsychiatric symptoms occur. The 5-hydroxynyptamine(5-HT) system has the ability to interact with the majority of the neurochemical systems in the central nervous system (CNS), influencing brain function. Serotonin transporter gene-linked polymorphic region (5-HTTLPR) is an essential element of the 5-HT system gene polymorphism and is directly related to the control of 5-hydroxytryptamine transporter (5-HTT)gene expression. The relationship between 5-HTTLPR and functional brain measurements in SLE patients requires more investigation because it is one of the most attractive imaging genetics targets for shedding light on the pathophysiology of neuropsychiatric lupus. METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) images were collected from 51 SLE patients without obvious neuropsychiatric manifestations and 44 healthy volunteers. Regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) were selected as indicators for evaluating brain function. In accordance with the Anatomical Automatic Labeling template, the gray matter was divided into 116 regions. The mean ReHo value, mean ALFF value, and mean fALFF value of each brain region were extracted. 5-HTTLPR genotypes of all research objects were tested by polymerase chain reaction and agarose gel electrophoresis. Two-way analysis of covariance was used to investigate whether there is an interaction effect between SLE disease status and 5-HTTLPR genotype on resting-state brain function. RESULTS In SLE patients with S/S homozygosity, there were notably lower mean ReHo, mean ALFF, and mean fALFF values observed in the right parietal, inferior angular gyrus, and the right paracentral lobule compared to healthy controls. However, this distinction was not evident among carriers of the L allele. Within the S/S genotype, SLE patients exhibited decreased mean ReHo in the left posterior cingulate gyrus, reduced mean fALFF in the left caudate nucleus, and diminished mean ALFF in the left temporal pole: superior temporal gyrus, in contrast to the HC group. Conversely, no such differences were discerned among carriers of the L allele. Notably, among L allele carriers, SLE patients displayed a higher mean ReHo value in the right hippocampus compared to the HC group, while demonstrating a lower mean ALFF value in the left medial and paracingulate gyrus in contrast to the HC group. Conversely, these differences were not apparent among S/S homozygotes. CONCLUSIONS Brain function in the right parietal and inferior angular gyrus and the right paracentral lobule is affected by the interaction effect of SLE disease status and 5-HTTLPR genotype.
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Affiliation(s)
- Lihua Ma
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yifan Yang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shu Li
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Bibhuti Upreti
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuang Liu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiangyu Wang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ru Bai
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.
| | - Jian Xu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
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Guan S, Jiang R, Chen DY, Michael A, Meng C, Biswal B. Multifractal long-range dependence pattern of functional magnetic resonance imaging in the human brain at rest. Cereb Cortex 2023; 33:11594-11608. [PMID: 37851793 DOI: 10.1093/cercor/bhad393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/01/2023] [Accepted: 10/02/2023] [Indexed: 10/20/2023] Open
Abstract
Long-range dependence is a prevalent phenomenon in various biological systems that characterizes the long-memory effect of temporal fluctuations. While recent research suggests that functional magnetic resonance imaging signal has fractal property, it remains unknown about the multifractal long-range dependence pattern of resting-state functional magnetic resonance imaging signals. The current study adopted the multifractal detrended fluctuation analysis on highly sampled resting-state functional magnetic resonance imaging scans to investigate long-range dependence profile associated with the whole-brain voxels as specific functional networks. Our findings revealed the long-range dependence's multifractal properties. Moreover, long-term persistent fluctuations are found for all stations with stronger persistency in whole-brain regions. Subsets with large fluctuations contribute more to the multifractal spectrum in the whole brain. Additionally, we found that the preprocessing with band-pass filtering provided significantly higher reliability for estimating long-range dependence. Our validation analysis confirmed that the optimal pipeline of long-range dependence analysis should include band-pass filtering and removal of daily temporal dependence. Furthermore, multifractal long-range dependence characteristics in healthy control and schizophrenia are different significantly. This work has provided an analytical pipeline for the multifractal long-range dependence in the resting-state functional magnetic resonance imaging signal. The findings suggest differential long-memory effects in the intrinsic functional networks, which may offer a neural marker finding for understanding brain function and pathology.
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Affiliation(s)
- Sihai Guan
- College of Electronic and Information, Southwest Minzu University, Chengdu 610041, China
- Key Laboratory of Electronic and Information Engineering, State Ethnic Affairs Commission, Chengdu 610041, China
| | - Runzhou Jiang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
- Medical Equipment Department, Xiangyang No.1 People's Hospital, Xiangyang 441000, China
| | - Donna Y Chen
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
| | - Andrew Michael
- Duke Institute for Brain Sciences, Duke University, Durham, NC 27708, United States
| | - Chun Meng
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Bharat Biswal
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
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Cattarinussi G, Grimaldi DA, Sambataro F. Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies. Schizophr Bull 2023; 49:1494-1507. [PMID: 38029279 PMCID: PMC10686347 DOI: 10.1093/schbul/sbad044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND HYPOTHESIS Several studies have shown that spontaneous brain activity, including the total and fractional amplitude of low-frequency fluctuations (LFF) and regional homogeneity (ReHo), is altered in psychosis. Nonetheless, neuroimaging results show a high heterogeneity. For this reason, we gathered the extant literature on spontaneous brain activity in first-episode psychosis (FEP), where the effects of long-term treatment and chronic disease are minimal. STUDY DESIGN A systematic research was conducted on PubMed, Scopus, and Web of Science to identify studies exploring spontaneous brain activity and local connectivity in FEP estimated using functional magnetic resonance imaging. 20 LFF and 15 ReHo studies were included. Coordinate-Based Activation Likelihood Estimation Meta-Analyses stratified by brain measures, age (adolescent vs adult), and drug-naïve status were performed to identify spatially-convergent alterations in spontaneous brain activity in FEP. STUDY RESULTS We found a significant increase in LFF in FEP compared to healthy controls (HC) in the right striatum and in ReHo in the left striatum. When pooling together all studies on LFF and ReHo, spontaneous brain activity was increased in the bilateral striatum and superior and middle frontal gyri and decreased in the right precentral gyrus and the right inferior frontal gyrus compared to HC. These results were also replicated in the adult and drug-naïve samples. CONCLUSIONS Abnormalities in the frontostriatal circuit are present in early psychosis independently of treatment status. Our findings support the view that altered frontostriatal can represent a core neural alteration of the disorder and could be a target of treatment.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
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Wang Q, Yao W, Bai D, Yi W, Yan W, Wang J. Schizophrenia MEG Network Analysis Based on Kernel Granger Causality. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1006. [PMID: 37509953 PMCID: PMC10378589 DOI: 10.3390/e25071006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 06/22/2023] [Accepted: 06/28/2023] [Indexed: 07/30/2023]
Abstract
Network analysis is an important approach to explore complex brain structures under different pathological and physiological conditions. In this paper, we employ the multivariate inhomogeneous polynomial kernel Granger causality (MKGC) to construct directed weighted networks to characterize schizophrenia magnetoencephalography (MEG). We first generate data based on coupled autoregressive processes to test the effectiveness of MKGC in comparison with the bivariate linear Granger causality and bivariate inhomogeneous polynomial kernel Granger causality. The test results suggest that MKGC outperforms the other two methods. Based on these results, we apply MKGC to construct effective connectivity networks of MEG for patients with schizophrenia (SCZs). We measure three network features, i.e., strength, nonequilibrium, and complexity, to characterize schizophrenia MEG. Our results suggest that MEG of the healthy controls (HCs) has a denser effective connectivity network than that of SCZs. The most significant difference in the in-connectivity strength is observed in the right frontal network (p=0.001). The strongest out-connectivity strength for all subjects occurs in the temporal area, with the most significant between-group difference in the left occipital area (p=0.0018). The total connectivity strength of the frontal, temporal, and occipital areas of HCs exhibits higher values compared with SCZs. The nonequilibrium feature over the whole brain of SCZs is significantly higher than that of the HCs (p=0.012); however, the results of Shannon entropy suggest that healthy MEG networks have higher complexity than schizophrenia networks. Overall, MKGC provides a reliable approach to construct MEG brain networks and characterize the network characteristics.
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Affiliation(s)
- Qiong Wang
- School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
- School of Physics and Information Engineering, Jiangsu Second Normal University, Nanjing 210013, China
| | - Wenpo Yao
- Smart Health Big Data Analysis and Location Services Engineering Research Center of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
| | - Dengxuan Bai
- School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
| | - Wanyi Yi
- School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
| | - Wei Yan
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Jun Wang
- Smart Health Big Data Analysis and Location Services Engineering Research Center of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
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Cao Y, Xu Y, Xia Q, Shan F, Liang J. Peripheral Complement Factor-Based Biomarkers for Patients with First-Episode Schizophrenia. Neuropsychiatr Dis Treat 2023; 19:1455-1462. [PMID: 37384352 PMCID: PMC10295471 DOI: 10.2147/ndt.s420475] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 06/20/2023] [Indexed: 06/30/2023] Open
Abstract
Objective Schizophrenia (SCZ) is a severe, protracted neurological disorder that causes disruptive conduct in millions of individuals globally. Discovery of potential biomarkers in clinical settings would lead to the development of efficient diagnostic techniques and an awareness of the disease's pathogenesis and prognosis. The aim of the present study was to discover and identify serum complement factor-based biomarkers in discriminating patients with first-episode SCZ from healthy controls. Methods Eighty-nine patients with first-episode SCZ and 89 healthy controls were included in this study. Psychiatric symptom severity of patients with SCZ was measured with the Brief Psychiatric Rating Scale-18 Item Version (BPRS) and the Scales for the Assessment of Negative/Positive Symptoms (SANS/SAPS). A total of 5 complement factors including complement component 1 (C1), C2, C3, C4, and 50% hemolytic complement (CH50) were measured using commercially available enzyme-linked immunosorbent assay (ELISA) kits. The levels of serum complement factors in the SCZ and control groups were compared, and the receiver operating characteristic (ROC) curve method was used to assess the diagnostic values of various complement factors for separating SCZ patients from healthy controls. Pearson's correlation test was used to assess the relationships between serum complement factor concentrations and the psychiatric symptom severity. Results There was an increase in serum levels of C1, C2, C3, C4, and CH50 among patients with SCZ. Moreover, based on ROC curve analysis, the AUC value of a combined panel of C1, C2, C3, C4, and CH50 was 0.857 when used to discriminate patients with SCZ from healthy controls. Furthermore, serum C2, C3, and CH50 levels were positively correlated to the scores of SANS, SAPS, and BPRS in patients with SCZ, respectively. Conclusion These results suggested that circulating complement factors including C1, C2, C3, C4, and CH50 may have potential in discovering biomarkers for diagnosing first-episode SCZ.
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Affiliation(s)
- Yin Cao
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China
- Department of Pharmacy, Hefei Fourth People’s Hospital, Hefei, People’s Republic of China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, People’s Republic of China
- Anhui Clinical Research Center for Mental Disorders, Hefei, People’s Republic of China
| | - Yayun Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, People’s Republic of China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, Anhui Medical University, Hefei, People’s Republic of China
- The Key Laboratory of Anti-Inflammatory and Immune Medicines, Ministry of Education, Hefei, People’s Republic of China
| | - Qingrong Xia
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China
- Department of Pharmacy, Hefei Fourth People’s Hospital, Hefei, People’s Republic of China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, People’s Republic of China
- Anhui Clinical Research Center for Mental Disorders, Hefei, People’s Republic of China
| | - Feng Shan
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China
- Department of Pharmacy, Hefei Fourth People’s Hospital, Hefei, People’s Republic of China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, People’s Republic of China
- Anhui Clinical Research Center for Mental Disorders, Hefei, People’s Republic of China
| | - Jun Liang
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China
- Department of Pharmacy, Hefei Fourth People’s Hospital, Hefei, People’s Republic of China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, People’s Republic of China
- Anhui Clinical Research Center for Mental Disorders, Hefei, People’s Republic of China
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Keyvanfard F, Nasab AR, Nasiraei-Moghaddam A. Brain subnetworks most sensitive to alterations of functional connectivity in Schizophrenia: a data-driven approach. Front Neuroinform 2023; 17:1175886. [PMID: 37274751 PMCID: PMC10232974 DOI: 10.3389/fninf.2023.1175886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/24/2023] [Indexed: 06/06/2023] Open
Abstract
Functional connectivity (FC) of the brain changes in various brain disorders. Its complexity, however, makes it difficult to obtain a systematic understanding of these alterations, especially when they are found individually and through hypothesis-based methods. It would be easier if the variety of brain connectivity alterations is extracted through data-driven approaches and expressed as variation modules (subnetworks). In the present study, we modified a blind approach to determine inter-group brain variations at the network level and applied it specifically to schizophrenia (SZ) disorder. The analysis is based on the application of independent component analysis (ICA) over the subject's dimension of the FC matrices, obtained from resting-state functional magnetic resonance imaging (rs-fMRI). The dataset included 27 SZ people and 27 completely matched healthy controls (HC). This hypothesis-free approach led to the finding of three brain subnetworks significantly discriminating SZ from HC. The area associated with these subnetworks mostly covers regions in visual, ventral attention, and somatomotor areas, which are in line with previous studies. Moreover, from the graph perspective, significant differences were observed between SZ and HC for these subnetworks, while there was no significant difference when the same parameters (path length, network strength, global/local efficiency, and clustering coefficient) across the same limited data were calculated for the whole brain network. The increased sensitivity of those subnetworks to SZ-induced alterations of connectivity suggested whether an individual scoring method based on their connectivity values can be applied to classify subjects. A simple scoring classifier was then suggested based on two of these subnetworks and resulted in acceptable sensitivity and specificity with an area under the ROC curve of 77.5%. The third subnetwork was found to be a less specific building block (module) for describing SZ alterations. It projected a wider range of inter-individual variations and, therefore, had a lower chance to be considered as a SZ biomarker. These findings confirmed that investigating brain variations from a modular viewpoint can help to find subnetworks that are more sensitive to SZ-induced alterations. Altogether, our study results illustrated the developed method's ability to systematically find brain alterations caused by SZ disorder from a network perspective.
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Affiliation(s)
- Farzaneh Keyvanfard
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Alireza Rahimi Nasab
- Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
| | - Abbas Nasiraei-Moghaddam
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
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Rubinstein DY, Eisenberg DP, Carver FW, Holroyd T, Apud JA, Coppola R, Berman KF. Spatiotemporal Alterations in Working Memory-Related Beta Band Neuromagnetic Activity of Patients With Schizophrenia On and Off Antipsychotic Medication: Investigation With MEG. Schizophr Bull 2023; 49:669-678. [PMID: 36772948 PMCID: PMC10154700 DOI: 10.1093/schbul/sbac178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
BACKGROUND AND HYPOTHESIS We used the uniquely high combined spatial and temporal resolution of magnetoencephalography to characterize working memory (WM)-related modulation of beta band activity in neuroleptic-free patients with schizophrenia in comparison to a large sample of performance-matched healthy controls. We also tested for effects of antipsychotic medication on identified differences in these same patients. STUDY DESIGN Inpatients with schizophrenia (n = 21) or psychotic disorder not otherwise specified (n = 4) completed N-back and control tasks during magnetoencephalography while on placebo and during antipsychotic medication treatment, in a blinded, randomized, counterbalanced manner. Healthy, performance-matched controls (N = 100) completed the same tasks. WM-related neural activation was estimated as beta band (14-30 Hz) desynchronization throughout the brain in successive 400 ms time windows. Voxel-wise statistical comparisons were performed between controls and patients while off-medication at each time window. Significant clusters resulting from this between-groups analysis were then used as regions-of-interest, the activations of which were compared between on- and off-medication conditions in patients. STUDY RESULTS Controls showed beta-band desynchronization (activation) of a fronto-parietal network immediately preceding correct button press responses-the time associated with WM updating and task execution. Altered activation in medication-free patients occurred largely during this time, in prefrontal, parietal, and visual cortices. Medication altered patients' neural responses such that the activation time courses in these regions-of-interest more closely resembled those of controls. CONCLUSIONS These findings demonstrate that WM-related beta band alterations in schizophrenia are time-specific and associated with neural systems targeted by antipsychotic medications. Future studies may investigate this association by examining its potential neurochemical basis.
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Affiliation(s)
- Daniel Y Rubinstein
- Section on Integrative Neuroimaging, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
| | - Daniel P Eisenberg
- Section on Integrative Neuroimaging, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
| | | | - Tom Holroyd
- MEG Core Facility, NIH, DHHS, Bethesda, MD, USA
| | - Jose A Apud
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
| | - Richard Coppola
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
- MEG Core Facility, NIH, DHHS, Bethesda, MD, USA
| | - Karen F Berman
- Section on Integrative Neuroimaging, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
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Wu H, Peng D, Yan H, Yang Y, Xu M, Zeng W, Chang C, Wang N. Occupation-modulated language networks and its lateralization: A resting-state fMRI study of seafarers. Front Hum Neurosci 2023; 17:1095413. [PMID: 36992794 PMCID: PMC10040660 DOI: 10.3389/fnhum.2023.1095413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 02/27/2023] [Indexed: 03/14/2023] Open
Abstract
IntroductionStudies have revealed that the language network of Broca’s area and Wernicke’s area is modulated by factors such as disease, gender, aging, and handedness. However, how occupational factors modulate the language network remains unclear.MethodsIn this study, taking professional seafarers as an example, we explored the resting-state functional connectivity (RSFC) of the language network with seeds (the original and flipped Broca’s area and Wernicke’s area).ResultsThe results showed seafarers had weakened RSFC of Broca’s area with the left superior/middle frontal gyrus and left precentral gyrus, and enhanced RSFC of Wernicke’s area with the cingulate and precuneus. Further, seafarers had a less right-lateralized RSFC with Broca’s area in the left inferior frontal gyrus, while the controls showed a left-lateralized RSFC pattern in Broca’s area and a right-lateralized one in Wernicke’s area. Moreover, seafarers displayed stronger RSFC with the left seeds of Broca’s area and Wernicke’s area.DiscussionThese findings suggest that years of working experience significantly modulates the RSFC of language networks and their lateralization, providing rich insights into language networks and occupational neuroplasticity.
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Affiliation(s)
- Huijun Wu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Deyuan Peng
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
- Hongjie Yan,
| | - Yang Yang
- CAS Key Laboratory of Behavioral Science, Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Min Xu
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Weiming Zeng
- Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai, China
| | - Chunqi Chang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
- Chunqi Chang,
| | - Nizhuan Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
- *Correspondence: Nizhuan Wang,
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11
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Nair S, Szaflarski JP, Wang Y, Pizarro D, Killen JF, Allendorfer JB. Assessing dynamic brain activity during verbal associative learning using MEG/fMRI co-processing. NEUROIMAGE: REPORTS 2023. [DOI: 10.1016/j.ynirp.2022.100154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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12
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Li Y, Zhu H, Chen Q, Yang L, Chen F, Ma H, Xu H, Chen K, Bu J, Zhang R. Immediate Effects of Vagal Nerve Stimulation in Drug-Resistant Epilepsy Revealed by Magnetoencephalographic Recordings. Brain Connect 2023; 13:51-59. [PMID: 35974665 DOI: 10.1089/brain.2022.0011] [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: 11/12/2022] Open
Abstract
Objective: Vagus nerve stimulation (VNS) has been a neuromodulatory option for treating drug-resistant epilepsy (DRE), but its mechanism remains unclear. To obtain insight into the mechanism by which VNS reduces epileptic seizures, the immediate effects of VNS in brain networks of DRE patients were investigated when the patients' vagal nerve stimulators were turned on. Methods: The brain network properties of 14 DRE patients with a vagal nerve stimulator and 14 healthy controls were evaluated using magnetoencephalography recordings for 6 main frequency bands. Results: Compared with healthy controls, DRE patients exhibited significant increases in functional connectivity in the theta, alpha, beta, and gamma bands and significant reductions in the small-world measure in the theta and beta bands. During periods when patients' vagal nerve stimulators were turned on, DRE patients showed significant reductions in functional connectivity in the theta and alpha bands and a significant increase in the small-world measure in the theta band when compared with periods when patients' vagal nerve stimulators were turned off. Conclusions: Our results indicate that the brain networks of DRE patients were pathologically hypersynchronous and instantaneous VNS can decrease the synchronization of brain networks of epileptic patients, which might play a key role in the mechanism by which VNS reduces epileptic seizures. In the theta band, instantaneous VNS can increase the network efficiency of DRE patients, and the increment in network efficiency may be helpful for improving brain cognitive function in epileptic patients. Impact statement For the first time, we investigated the immediate effects of vagus nerve stimulation (VNS) in the brain networks of drug-resistant epilepsy patients using magnetoencephalography. Our results show that instantaneous VNS can decrease the hypersynchronization of epileptic networks and increase the network efficiency of epileptic patients. Our results are helpful in understanding the mechanism of action by which VNS reduces epileptic seizures and improves the cognitive function in epileptic patients and the brain network reorganization caused by long-term VNS.
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Affiliation(s)
- Yuejun Li
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.,Department of Magnetoencephalography, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Haitao Zhu
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Qiqi Chen
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.,Department of Magnetoencephalography, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Lu Yang
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Fangqing Chen
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Haiyan Ma
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Honghao Xu
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Kefan Chen
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jinxin Bu
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Rui Zhang
- Department of Functional Neurosurgery and Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
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13
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Tarchi L, Damiani S, Fantoni T, Pisano T, Castellini G, Politi P, Ricca V. Centrality and interhemispheric coordination are related to different clinical/behavioral factors in attention deficit/hyperactivity disorder: a resting-state fMRI study. Brain Imaging Behav 2022; 16:2526-2542. [PMID: 35859076 PMCID: PMC9712307 DOI: 10.1007/s11682-022-00708-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/10/2022] [Indexed: 11/26/2022]
Abstract
Eigenvector-Centrality (EC) has shown promising results in the field of Psychiatry, with early results also pertaining to ADHD. Parallel efforts have focused on the description of aberrant interhemispheric coordination in ADHD, as measured by Voxel-Mirrored-Homotopic-Connectivity (VMHC), with early evidence of altered Resting-State fMRI. A sample was collected from the ADHD200-NYU initiative: 86 neurotypicals and 89 participants with ADHD between 7 and 18 years old were included after quality control for motion. After preprocessing, voxel-wise EC and VMHC values between diagnostic groups were compared, and network-level values from 15 functional networks extracted. Age, ADHD severity (Connor's Parent Rating-Scale), IQ (Wechsler-Abbreviated-Scale), and right-hand dominance were correlated with EC/VMHC values in the whole sample and within groups, both at the voxel-wise and network-level. Motion was controlled by censoring time-points with Framewise-Displacement > 0.5 mm, as well as controlling for group differences in mean Framewise-Displacement values. EC was significantly higher in ADHD compared to neurotypicals in the left inferior Frontal lobe, Lingual gyri, Peri-Calcarine cortex, superior and middle Occipital lobes, right inferior Occipital lobe, right middle Temporal gyrus, Fusiform gyri, bilateral Cuneus, right Precuneus, and Cerebellum (FDR-corrected-p = 0.05). No differences were observed between groups in voxel-wise VMHC. EC was positively correlated with ADHD severity scores at the network level (at p-value < 0.01, Inattentive: Cerebellum rho = 0.273; Hyper/Impulsive: High-Visual Network rho = 0.242, Cerebellum rho = 0.273; Global Index Severity: High-Visual Network rho = 0.241, Cerebellum rho = 0.293). No differences were observed between groups for motion (p = 0.443). While EC was more related to ADHD psychopathology, VMHC was consistently and negatively correlated with age across all networks.
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Affiliation(s)
- Livio Tarchi
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy.
| | - Stefano Damiani
- Department of Brain and Behavioral Science, University of Pavia, 27100, Pavia, Italy
| | - Teresa Fantoni
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Tiziana Pisano
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Giovanni Castellini
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
| | - Pierluigi Politi
- Department of Brain and Behavioral Science, University of Pavia, 27100, Pavia, Italy
| | - Valdo Ricca
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
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14
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Yao S, Kendrick KM. Reduced homotopic interhemispheric connectivity in psychiatric disorders: evidence for both transdiagnostic and disorder specific features. PSYCHORADIOLOGY 2022; 2:129-145. [PMID: 38665271 PMCID: PMC11003433 DOI: 10.1093/psyrad/kkac016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/24/2022] [Accepted: 10/28/2022] [Indexed: 04/28/2024]
Abstract
There is considerable interest in the significance of structural and functional connections between the two brain hemispheres in terms of both normal function and in relation to psychiatric disorders. In recent years, many studies have used voxel mirrored homotopic connectivity analysis of resting state data to investigate the importance of connectivity between homotopic regions in the brain hemispheres in a range of neuropsychiatric disorders. The current review summarizes findings from these voxel mirrored homotopic connectivity studies in individuals with autism spectrum disorder, addiction, attention deficit hyperactivity disorder, anxiety and depression disorders, and schizophrenia, as well as disorders such as Alzheimer's disease, mild cognitive impairment, epilepsy, and insomnia. Overall, other than attention deficit hyperactivity disorder, studies across psychiatric disorders report decreased homotopic resting state functional connectivity in the default mode, attention, salience, sensorimotor, social cognition, visual recognition, primary visual processing, and reward networks, which are often associated with symptom severity and/or illness onset/duration. Decreased homotopic resting state functional connectivity may therefore represent a transdiagnostic marker for general psychopathology. In terms of disorder specificity, the extensive decreases in homotopic resting state functional connectivity in autism differ markedly from attention deficit hyperactivity disorder, despite both occurring during early childhood and showing extensive co-morbidity. A pattern of more posterior than anterior regions showing reductions in schizophrenia is also distinctive. Going forward, more studies are needed to elucidate the functions of these homotopic functional connections in both health and disorder and focusing on associations with general psychopathology, and not only on disorder specific symptoms.
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Affiliation(s)
- Shuxia Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
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15
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Dabiri M, Dehghani Firouzabadi F, Yang K, Barker PB, Lee RR, Yousem DM. Neuroimaging in schizophrenia: A review article. Front Neurosci 2022; 16:1042814. [PMID: 36458043 PMCID: PMC9706110 DOI: 10.3389/fnins.2022.1042814] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/28/2022] [Indexed: 11/16/2022] Open
Abstract
In this review article we have consolidated the imaging literature of patients with schizophrenia across the full spectrum of modalities in radiology including computed tomography (CT), morphologic magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and magnetoencephalography (MEG). We look at the impact of various subtypes of schizophrenia on imaging findings and the changes that occur with medical and transcranial magnetic stimulation (TMS) therapy. Our goal was a comprehensive multimodality summary of the findings of state-of-the-art imaging in untreated and treated patients with schizophrenia. Clinical imaging in schizophrenia is used to exclude structural lesions which may produce symptoms that may mimic those of patients with schizophrenia. Nonetheless one finds global volume loss in the brains of patients with schizophrenia with associated increased cerebrospinal fluid (CSF) volume and decreased gray matter volume. These features may be influenced by the duration of disease and or medication use. For functional studies, be they fluorodeoxyglucose positron emission tomography (FDG PET), rs-fMRI, task-based fMRI, diffusion tensor imaging (DTI) or MEG there generally is hypoactivation and disconnection between brain regions. However, these findings may vary depending upon the negative or positive symptomatology manifested in the patients. MR spectroscopy generally shows low N-acetylaspartate from neuronal loss and low glutamine (a neuroexcitatory marker) but glutathione may be elevated, particularly in non-treatment responders. The literature in schizophrenia is difficult to evaluate because age, gender, symptomatology, comorbidities, therapy use, disease duration, substance abuse, and coexisting other psychiatric disorders have not been adequately controlled for, even in large studies and meta-analyses.
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Affiliation(s)
- Mona Dabiri
- Department of Radiology, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Kun Yang
- Department of Psychiatry, Molecular Psychiatry Program, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Peter B. Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, Baltimore, MD, United States
| | - Roland R. Lee
- Department of Radiology, UCSD/VA Medical Center, San Diego, CA, United States
| | - David M. Yousem
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, Baltimore, MD, United States
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16
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Guan S, Wan D, Zhao R, Canario E, Meng C, Biswal BB. The complexity of spontaneous brain activity changes in schizophrenia, bipolar disorder, and ADHD was examined using different variations of entropy. Hum Brain Mapp 2022; 44:94-118. [PMID: 36358029 PMCID: PMC9783493 DOI: 10.1002/hbm.26129] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 08/02/2022] [Accepted: 08/07/2022] [Indexed: 11/13/2022] Open
Abstract
Adult attention deficit/hyperactivity disorder (ADHD), schizophrenia (SCHZ), and bipolar disorder (BP) have common symptoms and differences, and the underlying neural mechanisms are still unclear. This article will thoroughly discuss the differences between ADHD, BP, and SCHZ (31 healthy control and 31 ADHD; 34 healthy control and 34 BP; 42 healthy control and 42 SCHZ) relative to healthy subjects in combination with three atlases (et al., the Brainnetome atlas, the Dosenbach atlas, the Power atlas) and seven entropies (et al., approximate entropy (ApEn), sample entropy (SaEn), permutation entropy (PeEn), fuzzy entropy (FuEn), differential entropy (DiffEn), range entropy (RaEn), and dispersion entropy (DispEn)), as well as the prominent significant brain regions, in the hope of giving information that is more suitable for analyzing different diseases' entropy. First, the reliability (et al., intraclass correlation coefficient [ICC]) of seven kinds of entropy is calculated and analyzed by using the MSC dataset (10 subjects and 100 sessions in total) and simulation data; then, seven types of entropy and multiscale entropy expanded based on seven kinds of entropy are used to explore the differences and brain regions of ADHD, BP, and SCHZ relative to healthy subjects; and finally, by verifying the classification performance of the seven information entropies on ADHD, BP, and SCHZ, the effectiveness of the seven entropy methods is evaluated through these three methods. The core brain regions that affect the classification are given, and DiffEn performed best on ADHD, SaEn for BP, and RaEn for SCHZ.
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Affiliation(s)
- Sihai Guan
- Key Laboratory of Electronic and Information EngineeringState Ethnic Affairs Commission, College of Electronic and Information, Southwest Minzu UniversityChengduChina
| | - Dongyu Wan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Rong Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Edgar Canario
- Department of Biomedical EngineeringNew Jersey Institute of TechnologyNewarkNew JerseyUSA
| | - Chun Meng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Bharat B. Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina,Department of Biomedical EngineeringNew Jersey Institute of TechnologyNewarkNew JerseyUSA
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17
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Huang R, Zhou X, Chen G, Su L, Liu Z, Zhou P, Weng J, Min Y. Advances of functional nanomaterials for magnetic resonance imaging and biomedical engineering applications. WILEY INTERDISCIPLINARY REVIEWS. NANOMEDICINE AND NANOBIOTECHNOLOGY 2022; 14:e1800. [PMID: 35445588 DOI: 10.1002/wnan.1800] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/21/2022] [Accepted: 03/25/2022] [Indexed: 11/12/2022]
Abstract
Functional nanomaterials have been widely used in biomedical fields due to their good biocompatibility, excellent physicochemical properties, easy surface modification, and easy regulation of size and morphology. Functional nanomaterials for magnetic resonance imaging (MRI) can target specific sites in vivo and more easily detect disease-related specific biomarkers at the molecular and cellular levels than traditional contrast agents, achieving a broad application prospect in MRI. This review focuses on the basic principles of MRI, the classification, synthesis and surface modification methods of contrast agents, and their clinical applications to provide guidance for designing novel contrast agents and optimizing the contrast effect. Furthermore, the latest biomedical advances of functional nanomaterials in medical diagnosis and disease detection, disease treatment, the combination of diagnosis and treatment (theranostics), multi-model imaging and nanozyme are also summarized and discussed. Finally, the bright application prospects of functional nanomaterials in biomedicine are emphasized and the urgent need to achieve significant breakthroughs in the industrial transformation and the clinical translation is proposed. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Diagnostic Tools > Diagnostic Nanodevices Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.
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Affiliation(s)
- Ruijie Huang
- Department of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.,Department of Chemistry, University of Science and Technology of China, Hefei, China
| | - Xingyu Zhou
- Department of Chemistry, University of Science and Technology of China, Hefei, China
| | - Guiyuan Chen
- Department of Chemistry, University of Science and Technology of China, Hefei, China
| | - Lanhong Su
- Department of Chemistry, University of Science and Technology of China, Hefei, China
| | - Zhaoji Liu
- Department of Chemistry, University of Science and Technology of China, Hefei, China
| | - Peijie Zhou
- Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Jianping Weng
- Department of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yuanzeng Min
- Department of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.,Department of Chemistry, University of Science and Technology of China, Hefei, China
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18
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Jiang W, Sun J, Xiang J, Sun Y, Tang L, Zhang K, Chen Q, Wang X. Altered Neuromagnetic Activity in Persistent Postural-Perceptual Dizziness: A Multifrequency Magnetoencephalography Study. Front Hum Neurosci 2022; 16:759103. [PMID: 35350444 PMCID: PMC8957837 DOI: 10.3389/fnhum.2022.759103] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 01/10/2022] [Indexed: 12/12/2022] Open
Abstract
Objective The aim of our study was to investigate abnormal changes in brain activity in patients with persistent postural-perceptual dizziness (PPPD) using magnetoencephalography (MEG). Methods Magnetoencephalography recordings from 18 PPPD patients and 18 healthy controls were analyzed to determine the source of brain activity in seven frequency ranges using accumulated source imaging (ASI). Results Our study showed that significant changes in the patterns of localization in the temporal-parietal junction (TPJ) were observed at 1–4, 4–8, and 12–30 Hz in PPPD patients compared with healthy controls, and changes in the frontal cortex were found at 1–4, 80–250, and 250–500 Hz in PPPD patients compared with controls. The neuromagnetic activity in TPJ was observed increased significantly in 1–4 and 4–8 Hz, while the neuromagnetic activity in frontal cortex was found increased significantly in 1–4 Hz. In addition, the localized source strength in TPJ in 1–4 Hz was positively correlated with DHI score (r = 0.7085, p < 0.05), while the localized source strength in frontal cortex in 1–4 Hz was positively correlated with HAMA score (r = 0.5542, p < 0.05). Conclusion Our results demonstrated that alterations in the TPJ and frontal cortex may play a critical role in the pathophysiological mechanism of PPPD. The neuromagnetic activity in TPJ may be related to dizziness symptom of PPPD patients, while the neuromagnetic activity in frontal lobe may be related to emotional symptoms of PPPD patients. In addition, frequency-dependent changes in neuromagnetic activity, especially neuromagnetic activity in low frequency bands, were involved in the pathophysiology of PPPD.
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Affiliation(s)
- Weiwei Jiang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jing Xiang
- Division of Neurology, MEG Center, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Yulei Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Lu Tang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Ke Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Qiqi Chen
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
- *Correspondence: Xiaoshan Wang,
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19
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Chen C, Yao J, Lv Y, Zhao X, Zhang X, Lei J, Li Y, Sui Y. Aberrant Functional Connectivity of the Orbitofrontal Cortex Is Associated With Excited Symptoms in First-Episode Drug-Naïve Patients With Schizophrenia. Front Psychiatry 2022; 13:922272. [PMID: 35966466 PMCID: PMC9366470 DOI: 10.3389/fpsyt.2022.922272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 06/06/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Schizophrenia (SZ) is associated with the highest disability rate among serious mental disorders. Excited symptoms are the core symptoms of SZ, which appear in the early stage, followed by other stages of the disease subsequently. These symptoms are destructive and more prone to violent attacks, posing a serious economic burden to the society. Abnormal spontaneous activity in the orbitofrontal cortex had been reported to be associated with excited symptoms in patients with SZ. However, whether the abnormality appears in first-episode drug-naïve patients with SZ has still remained elusive. METHODS A total of 56 first-episode drug-naïve patients with SZ and 27 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI) and positive and negative syndrome scale (PANSS). First, differences in fractional amplitude of low-frequency fluctuations (fALFF) between first-episode drug-naïve patients with SZ and healthy controls were examined to identify cerebral regions exhibiting abnormal local spontaneous activity. Based on the fALFF results, the resting-state functional connectivity analysis was performed to determine changes in cerebral regions exhibiting abnormal local spontaneous activity. Finally, the correlation between abnormal functional connectivity and exciting symptoms was analyzed. RESULTS Compared with the healthy controls, first-episode drug-naïve patients with SZ showed a significant decrease in intrinsic activity in the bilateral precentral gyrus, bilateral postcentral gyrus, and the left orbitofrontal cortex. In addition, first-episode drug-naïve patients with SZ had significantly reduced functional connectivity values between the left orbitofrontal cortex and several cerebral regions, which were mainly distributed in the bilateral postcentral gyrus, the right middle frontal gyrus, bilateral paracentral lobules, the left precentral gyrus, and the right median cingulate. Further analyses showed that the functional connectivity between the left orbitofrontal cortex and the left postcentral gyrus, as well as bilateral paracentral lobules, was negatively correlated with excited symptoms in first-episode drug-naïve patients with SZ. CONCLUSION Our results indicated the important role of the left orbitofrontal cortex in first-episode drug-naïve patients with SZ and suggested that the abnormal spontaneous activity of the orbitofrontal cortex may be valuable to predict the occurrence of excited symptoms. These results may provide a new direction to explore the excited symptoms of SZ.
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Affiliation(s)
- Congxin Chen
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | | | - Yiding Lv
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Xiaoxin Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Jiaxi Lei
- Chengdu No. 4 People's Hospital, Chengdu, China
| | - Yuan Li
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yuxiu Sui
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
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20
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Yuan L, Ma X, Li D, Li Z, Ouyang L, Fan L, Yang Z, Zhang Z, Li C, He Y, Chen X. Abnormal Brain Network Interaction Associated With Positive Symptoms in Drug-Naive Patients With First-Episode Schizophrenia. Front Psychiatry 2022; 13:870709. [PMID: 35656348 PMCID: PMC9152123 DOI: 10.3389/fpsyt.2022.870709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 04/14/2022] [Indexed: 11/23/2022] Open
Abstract
Positive symptoms are marked features of schizophrenia, and emerging evidence has suggested that abnormalities of the brain network underlying these symptoms may play a crucial role in the pathophysiology of the disease. We constructed two brain functional networks based on the positive and negative correlations between positive symptom scores and brain connectivity in drug-naive patients with first-episode schizophrenia (FES, n = 45) by using a machine-learning approach (connectome-based predictive modeling, CPM). The accuracy of the model was r = 0.47 (p = 0.002). The positively and negatively associated network strengths were then compared among FES subjects, individuals at genetic high risk (GHR, n = 41) for schizophrenia, and healthy controls (HCs, n = 48). The results indicated that the positively associated network contained more cross-subnetwork connections (96.02% of 176 edges), with a focus on the default-mode network (DMN)-salience network (SN) and the DMN-frontoparietal task control (FPT) network. The negatively associated network had fewer cross-subnetwork connections (71.79% of 117 edges) and focused on the sensory/somatomotor hand (SMH)-Cingulo opercular task control (COTC) network, the DMN, and the visual network with significantly decreased connectivity in the COTC-SMH network in FES (FES < GHR, p = 0.01; FES < HC, p = 0.01). Additionally, the connectivity strengths of the right supplementary motor area (SMA) (p < 0.001) and the right precentral gyrus (p < 0.0001) were reduced in FES. To the best of our knowledge, this is the first study to generate two brain networks associated with positive symptoms by utilizing CPM in FES. Abnormal segregation, interactions of brain subnetworks, and impaired SMA might lead to salience attribution abnormalities and, thus, as a result, induce positive symptoms in schizophrenia.
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Affiliation(s)
- Liu Yuan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Xiaoqian Ma
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - David Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zongchang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Lijun Ouyang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Lejia Fan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zihao Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zhenmei Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Chunwang Li
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Ying He
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Xiaogang Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
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21
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Lavigne KM, Kanagasabai K, Palaniyappan L. Ultra-high field neuroimaging in psychosis: A narrative review. Front Psychiatry 2022; 13:994372. [PMID: 36506432 PMCID: PMC9730890 DOI: 10.3389/fpsyt.2022.994372] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/08/2022] [Indexed: 11/27/2022] Open
Abstract
Schizophrenia and related psychoses are complex neuropsychiatric diseases representing dysconnectivity across multiple scales, through the micro (cellular), meso (brain network), manifest (behavioral), and social (interpersonal) levels. In vivo human neuroimaging, particularly at ultra-high field (UHF), offers unprecedented opportunity to examine multiscale dysconnectivity in psychosis. In this review, we provide an overview of the literature to date on UHF in psychosis, focusing on microscale findings from magnetic resonance spectroscopy (MRS), mesoscale studies on structural and functional magnetic resonance imaging (fMRI), and multiscale studies assessing multiple neuroimaging modalities and relating UHF findings to behavior. We highlight key insights and considerations from multiscale and longitudinal studies and provide recommendations for future research on UHF neuroimaging in psychosis.
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Affiliation(s)
- Katie M Lavigne
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.,Montreal Neurological Institute-Hospital, McGill University, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Kesavi Kanagasabai
- Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada.,Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
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22
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Overbeek G, Gawne TJ, Reid MA, Kraguljac NV, Lahti AC. A multimodal neuroimaging study investigating resting-state connectivity, glutamate and GABA at 7 T in first-episode psychosis. J Psychiatry Neurosci 2021; 46:E702-E710. [PMID: 34933941 PMCID: PMC8695527 DOI: 10.1503/jpn.210107] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 10/05/2021] [Accepted: 10/18/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The major excitatory and inhibitory neurometabolites in the brain, glutamate and γ-aminobutyric acid (GABA), respectively, are related to the functional MRI signal. Disruption of resting-state functional MRI signals has been reported in psychosis spectrum disorders, but few studies have investigated the role of these metabolites in this context. METHODS We included 19 patients with first-episode psychosis and 21 healthy controls in this combined magnetic resonance spectroscopy (MRS) and resting-state functional connectivity study. All imaging was performed on a Siemens Magnetom 7 T MRI scanner. Both the MRS voxel and the seed for functional connectivity analysis were located in the dorsal anterior cingulate cortex (ACC). We used multiple regressions to test for an interaction between ACC brain connectivity, diagnosis and neurometabolites. RESULTS ACC brain connectivity was altered in first-episode psychosis. The relationship between ACC glutamate and ACC functional connectivity differed between patients with first-episode psychosis and healthy controls in the precuneus, retrosplenial cortex, supramarginal gyrus and angular gyrus. As well, the relationship between ACC GABA and ACC functional connectivity differed between groups in the caudate, putamen and supramarginal gyrus. LIMITATIONS We used a small sample size. As well, although they were not chronically medicated, all participants were medicated during the study. CONCLUSION We demonstrated a link between the major excitatory and inhibitory brain metabolites and resting-state functional connectivity in healthy participants, as well as an alteration in this relationship in patients with first-episode psychosis. Combining data from different imaging modalities may help our mechanistic understanding of the relationship between major neurometabolites and brain network dynamics, and shed light on the pathophysiology of first-episode psychosis.
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Affiliation(s)
- Gregory Overbeek
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Timothy J Gawne
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Meredith A Reid
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Nina V Kraguljac
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Adrienne C Lahti
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
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23
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Tarchi L, Damiani S, La Torraca Vittori P, Marini S, Nazzicari N, Castellini G, Pisano T, Politi P, Ricca V. The colors of our brain: an integrated approach for dimensionality reduction and explainability in fMRI through color coding (i-ECO). Brain Imaging Behav 2021; 16:977-990. [PMID: 34689318 PMCID: PMC9107439 DOI: 10.1007/s11682-021-00584-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/06/2021] [Indexed: 11/29/2022]
Abstract
Several systematic reviews have highlighted the role of multiple sources in the investigation of psychiatric illness. For what concerns fMRI, the focus of recent literature preferentially lies on three lines of research, namely: functional connectivity, network analysis and spectral analysis. Data was gathered from the UCLA Consortium for Neuropsychiatric Phenomics. The sample was composed by 130 neurotypicals, 50 participants diagnosed with Schizophrenia, 49 with Bipolar disorder and 43 with ADHD. Single fMRI scans were reduced in their dimensionality by a novel method (i-ECO) averaging results per Region of Interest and through an additive color method (RGB): local connectivity values (Regional Homogeneity), network centrality measures (Eigenvector Centrality), spectral dimensions (fractional Amplitude of Low-Frequency Fluctuations). Average images per diagnostic group were plotted and described. The discriminative power of this novel method for visualizing and analyzing fMRI results in an integrative manner was explored through the usage of convolutional neural networks. The new methodology of i-ECO showed between-groups differences that could be easily appreciated by the human eye. The precision-recall Area Under the Curve (PR-AUC) of our models was > 84.5% for each diagnostic group as evaluated on the test-set – 80/20 split. In conclusion, this study provides evidence for an integrative and easy-to-understand approach in the analysis and visualization of fMRI results. A high discriminative power for psychiatric conditions was reached. This proof-of-work study may serve to investigate further developments over more extensive datasets covering a wider range of psychiatric diagnoses.
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Affiliation(s)
- Livio Tarchi
- Psychiatry Unit, Department of Health Sciences, University of Florence, viale della Maternità, Padiglione 8b, AOU Careggi, Firenze, Florence, FI, 50134, Italy.
| | - Stefano Damiani
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy
| | | | - Simone Marini
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
| | - Nelson Nazzicari
- Council for Agricultural Research and Economics (CREA), Research Centre for Fodder Crops and Dairy Productions, Lodi, LO, Italy
| | - Giovanni Castellini
- Psychiatry Unit, Department of Health Sciences, University of Florence, viale della Maternità, Padiglione 8b, AOU Careggi, Firenze, Florence, FI, 50134, Italy
| | - Tiziana Pisano
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Pierluigi Politi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy
| | - Valdo Ricca
- Psychiatry Unit, Department of Health Sciences, University of Florence, viale della Maternità, Padiglione 8b, AOU Careggi, Firenze, Florence, FI, 50134, Italy
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24
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Reinforcement learning abnormalities in the attenuated psychosis syndrome and first episode psychosis. Eur Neuropsychopharmacol 2021; 47:11-19. [PMID: 33819817 PMCID: PMC8197752 DOI: 10.1016/j.euroneuro.2021.03.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 03/11/2021] [Accepted: 03/15/2021] [Indexed: 11/23/2022]
Abstract
Prior studies indicate that chronic schizophrenia (SZ) is associated with a specific profile of reinforcement learning abnormalities. These impairments are characterized by: 1) reductions in learning rate, and 2) impaired Go learning and intact NoGo learning. Furthermore, each of these deficits are associated with greater severity of negative symptoms, consistent with theoretical perspectives positing that avolition and anhedonia are associated with impaired value representation. However, it is unclear whether these deficits extend to earlier phases of psychotic illness and when individuals are unmedicated. Two studies were conducted to examine reinforcement learning deficits in earlier phases of psychosis and in high risk patients. In study 1, participants included 35 participants with first episode psychosis (FEP) with limited antipsychotic medication exposure and 25 healthy controls (HC). Study 2 included 17 antipsychotic naïve individuals who were at clinical high-risk for psychosis (CHR) (i.e., attenuated psychosis syndrome) and 18 matched healthy controls (HC). In both studies, participants completed the Temporal Utility Integration Task, a measure of probabilistic reinforcement learning that contained Go and NoGo learning blocks. FEP displayed impaired Go and NoGo learning. In contrast, CHR did not display impairments in Go or NoGo learning. Impaired Go learning was not significantly associated with clinical outcomes in the CHR or FEP samples. Findings provide new evidence for areas of spared and impaired reinforcement learning in early phases of psychosis.
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25
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Bianciardi B, Uhlhaas PJ. Do NMDA-R antagonists re-create patterns of spontaneous gamma-band activity in schizophrenia? A systematic review and perspective. Neurosci Biobehav Rev 2021; 124:308-323. [PMID: 33581223 DOI: 10.1016/j.neubiorev.2021.02.005] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/29/2021] [Accepted: 02/03/2021] [Indexed: 12/13/2022]
Abstract
NMDA-R hypofunctioninig is a core pathophysiological mechanism in schizophrenia. However, it is unclear whether the physiological changes observed following NMDA-R antagonist administration are consistent with gamma-band alterations in schizophrenia. This systematic review examined the effects of NMDA-R antagonists on the amplitude of spontaneous gamma-band activity and functional connectivity obtained from preclinical (n = 24) and human (n = 9) studies and compared these data to resting-state EEG/MEG-measurements in schizophrenia patients (n = 27). Overall, the majority of preclinical and human studies observed increased gamma-band power following acute administration of NMDA-R antagonists. However, the direction of gamma-band power alterations in schizophrenia were inconsistent, which involved upregulation (n = 10), decreases (n = 7), and no changes (n = 8) in spectral power. Five out of 6 preclinical studies observed increased connectivity, while in healthy controls receiving Ketamine and in schizophrenia patients the direction of connectivity results was also inconsistent. Accordingly, the effects of NMDA-R hypofunctioning on gamma-band oscillations are different than pathophysiological signatures observed in schizophrenia. The implications of these findings for current E/I balance models of schizophrenia are discussed.
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Affiliation(s)
- Bianca Bianciardi
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK; Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany.
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26
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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: 1.0] [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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27
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A multimodal magnetoencephalography 7 T fMRI and 7 T proton MR spectroscopy study in first episode psychosis. NPJ SCHIZOPHRENIA 2020; 6:23. [PMID: 32887887 PMCID: PMC7473853 DOI: 10.1038/s41537-020-00113-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 07/23/2020] [Indexed: 11/08/2022]
Abstract
We combined magnetoencephalography (MEG), 7 T proton magnetic resonance spectroscopy (MRS), and 7 T fMRI during performance of a task in a group of 23 first episode psychosis (FEP) patients and 26 matched healthy controls (HC). We recorded both the auditory evoked response to 40 Hz tone clicks and the resting state in MEG. Neurometabolite levels were obtained from the anterior cingulate cortex (ACC). The fMRI BOLD response was obtained during the Stroop inhibitory control task. FEP showed a significant increase in resting state low frequency theta activity (p < 0.05; Cohen d = 0.69), but no significant difference in the 40 Hz auditory evoked response compared to HC. An across-groups whole brain analysis of the fMRI BOLD response identified eight regions that were significantly activated during task performance (p < 0.01, FDR-corrected); the mean signal extracted from those regions was significantly different between the groups (p = 0.0006; d = 1.19). In the combined FEP and HC group, there was a significant correlation between the BOLD signal during task performance and MEG resting state low frequency activity (p < 0.05). In FEP, we report significant alteration in resting state low frequency MEG activity, but no alterations in auditory evoked gamma band response, suggesting that the former is a more robust biomarker of early psychosis. There were no correlations between gamma oscillations and GABA levels in either HC or FEP. Finally, in this study, each of the three imaging modalities differentiated FEP from HC; fMRI with good and MEG and MRS with moderate effect size.
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28
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Moreno-Ayure M, Páez C, López-Arias MA, Mendez-Betancurt JL, Ordóñez-Rubiano EG, Rudas J, Pulido C, Gómez F, Martínez D, Enciso-Olivera CO, Rivera-Triana DP, Casanova-Libreros R, Aguilera N, Marín-Muñoz JH. Establishing an acquisition and processing protocol for resting state networks with a 1.5 T scanner: A case series in a middle-income country. Medicine (Baltimore) 2020; 99:e21125. [PMID: 32664139 PMCID: PMC7360246 DOI: 10.1097/md.0000000000021125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
OBJECTIVE The aim of this study was to characterize the capability of detection of the resting state networks (RSNs) with functional magnetic resonance imaging (fMRI) in healthy subjects using a 1.5T scanner in a middle-income country. MATERIALS AND METHODS Ten subjects underwent a complete blood-oxygen-level dependent imaging (BOLD) acquisition on a 1.5T scanner. For the imaging analysis, we used the spatial independent component analysis (sICA). We designed a computer tool for 1.5 T (or above) scanners for imaging processing. We used it to separate and delineate the different components of the RSNs of the BOLD signal. The sICA was also used to differentiate the RSNs from noise artifact generated by breathing and cardiac cycles. RESULTS For each subject, 20 independent components (IC) were computed from the sICA (a total of 200 ICs). From these ICs, a spatial pattern consistent with RSNs was identified in 161 (80.5%). From the 161, 131 (65.5%) were fit for study. The networks that were found in all subjects were: the default mode network, the right executive control network, the medial visual network, and the cerebellar network. In 90% of the subjects, the left executive control network and the sensory/motor network were observed. The occipital visual network was present in 80% of the subjects. In 39 (19.5%) of the images, no any neural network was identified. CONCLUSIONS Reproduction and differentiation of the most representative RSNs was achieved using a 1.5T scanner acquisitions and sICA processing of BOLD imaging in healthy subjects.
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Affiliation(s)
| | | | | | - Johan L. Mendez-Betancurt
- Department of Critical Care and Intensive Care Unit, Fundación Universitaria de Ciencias de la Salud (FUCS), Hospital Infantil Universitario de San José
| | - Edgar G. Ordóñez-Rubiano
- Department of Neurological Surgery, Fundación Universitaria de Ciencias de la Salud (FUCS), Hospital de San José
| | | | | | | | - Darwin Martínez
- Department of Computer Science, Universidad Nacional de Colombia
- Department of Computer Science, Universidad Central
| | - Cesar O. Enciso-Olivera
- Department of Critical Care and Intensive Care Unit, Fundación Universitaria de Ciencias de la Salud (FUCS), Hospital Infantil Universitario de San José
| | - Diana P. Rivera-Triana
- Division of Clinical Research, Fundación Universitaria de Ciencias de la Salud (FUCS), Hospital de San José, Hospital Infantil Universitario de San José, Bogotá, Colombia
| | - Rosangela Casanova-Libreros
- Division of Clinical Research, Fundación Universitaria de Ciencias de la Salud (FUCS), Hospital de San José, Hospital Infantil Universitario de San José, Bogotá, Colombia
| | - Natalia Aguilera
- Division of Clinical Research, Fundación Universitaria de Ciencias de la Salud (FUCS), Hospital de San José, Hospital Infantil Universitario de San José, Bogotá, Colombia
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29
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Yang J, Gohel S, Vachha B. Current methods and new directions in resting state fMRI. Clin Imaging 2020; 65:47-53. [PMID: 32353718 DOI: 10.1016/j.clinimag.2020.04.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 03/24/2020] [Accepted: 04/08/2020] [Indexed: 12/12/2022]
Abstract
Resting state functional connectivity magnetic resonance imaging (rsfcMRI) has become a key component of investigations of neurocognitive and psychiatric behaviors. Over the past two decades, several methods and paradigms have been adopted to utilize and interpret data from resting-state fluctuations in the brain. These findings have increased our understanding of changes in many disease states. As the amount of resting state data available for research increases with big datasets and data-sharing projects, it is important to review the established traditional analysis methods and recognize areas where research methodology can be adapted to better accommodate the scale and complexity of rsfcMRI analysis. In this paper, we review established methods of analysis as well as areas that have been receiving increasing attention such as dynamic rsfcMRI, independent vector analysis, multiband rsfcMRI and network of networks.
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Affiliation(s)
- Jackie Yang
- NYU Grossman School of Medicine, 550 1(st) Avenue, New York, NY 10016, USA
| | - Suril Gohel
- Department of Health Informatics, Rutgers University School of Health Professions, 65 Bergen Street, Newark, NJ 07107, USA
| | - Behroze Vachha
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA.
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30
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Rudas J, Martínez D, Castellanos G, Demertzi A, Martial C, Carriére M, Aubinet C, Soddu A, Laureys S, Gómez F. Time-Delay Latency of Resting-State Blood Oxygen Level-Dependent Signal Related to the Level of Consciousness in Patients with Severe Consciousness Impairment. Brain Connect 2020; 10:83-94. [DOI: 10.1089/brain.2019.0716] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Affiliation(s)
- Jorge Rudas
- Institute of Biotechnology, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Darwin Martínez
- Department of Computer Science, Universidad Nacional de Colombia, Bogotá, Colombia
- Department of Computer Science, Universidad Central de Colombia, Bogotá, Colombia
| | - Gabriel Castellanos
- Department of Physiological Sciences, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Athena Demertzi
- Physiology of Cognition Research Lab, GIGA-Consciousness, GIGA Institute, University of Liege, Liège, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
| | - Manon Carriére
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
| | - Charlène Aubinet
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
| | - Andrea Soddu
- Department of Physics and Astronomy, University of Western Ontario, London, Ontario
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
| | - Francisco Gómez
- Department of Mathematics, Universidad Nacional de Colombia, Bogotá, Colombia
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31
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Candelaria-Cook FT, Stephen JM. Test-Retest Reliability of Magnetoencephalography Resting-State Functional Connectivity in Schizophrenia. Front Psychiatry 2020; 11:551952. [PMID: 33391043 PMCID: PMC7772354 DOI: 10.3389/fpsyt.2020.551952] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 11/23/2020] [Indexed: 12/17/2022] Open
Abstract
The reliability of magnetoencephalography (MEG) resting-state functional connectivity in schizophrenia (SZ) is unknown as previous research has focused on healthy controls (HC). Here, we examined reliability in 26 participants (13-SZ, 13-HC). Eyes opened and eyes closed resting-state data were collected on 4 separate occasions during 2 visits, 1 week apart. For source modeling, we used minimum norm software to apply dynamic statistical parametric mapping. Source analyses compared the following functional connectivity metrics from each data run: coherence (coh), imaginary coherence (imcoh), pairwise phase consistency (ppc), phase-locking value (plv), phase lag index (pli), weighted phase lag index (wpli), and weighted phase lag index debiased (wpli2). Intraclass correlation coefficients (ICCs) were calculated for whole brain, network, and network pair averages. For reliability, ICCs above 0.75 = excellent, above 0.60 = good, above 0.40 = fair, and below 0.40 = poor reliability. We found the reliability of these metrics varied greatly depending on frequency band, network, network pair, and participant group examined. Broadband (1-58 Hz) whole brain averages in both HC and SZ showed excellent reliability for wpli2, and good to fair reliability for ppc, plv, and coh. Broadband network averages showed excellent to good reliability across 1 hour and 1 week for coh, imcoh, ppc, plv, wpli within default mode, cognitive control, and visual networks in HC, while the same metrics had excellent to fair reliability in SZ. Regional network pair averages showed good to fair reliability for coh, ppc, plv within default mode, cognitive control and visual network pairs in HC and SZ. In general, HC had higher reliability compared to SZ, and the default mode, cognitive control, and visual networks had higher reliability compared to somatosensory and auditory networks. Similar reliability levels occurred for both eyes opened and eyes closed resting-states for most metrics. The functional connectivity metrics of coh, ppc, and plv performed best across 1 hour and 1 week in HC and SZ. We also found that SZ had reduced coh, plv, and ppc in the dmn average and pair values indicating dysconnectivity in SZ. These findings encourage collecting both eyes opened and eyes closed resting-state MEG, while demonstrating that clinical populations may differ in reliability.
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