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Bagheri S, Yu JC, Gallucci J, Tan V, Oliver LD, Dickie EW, Rashidi AG, Foussias G, Lai MC, Buchanan RW, Malhotra AK, Voineskos AN, Ameis SH, Hawco C. Transdiagnostic Neurobiology of Social Cognition and Individual Variability as Measured by Fractional Amplitude of Low-Frequency Fluctuation in Schizophrenia and Autism Spectrum Disorders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601737. [PMID: 39005278 PMCID: PMC11245004 DOI: 10.1101/2024.07.02.601737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Fractional amplitude of low-frequency fluctuation (fALFF) is a validated measure of resting-state spontaneous brain activity. Previous fALFF findings in autism and schizophrenia spectrum disorders (ASDs and SSDs) have been highly heterogeneous. We aimed to use fALFF in a large sample of typically developing control (TDC), ASD and SSD participants to explore group differences and relationships with inter-individual variability of fALFF maps and social cognition. fALFF from 495 participants (185 TDC, 68 ASD, and 242 SSD) was computed using functional magnetic resonance imaging as signal power within two frequency bands (i.e., slow-4 and slow-5), normalized by the power in the remaining frequency spectrum. Permutation analysis of linear models was employed to investigate the relationship of fALFF with diagnostic groups, higher-level social cognition, and lower-level social cognition. Each participant's average distance of fALFF map to all others was defined as a variability score, with higher scores indicating less typical maps. Lower fALFF in the visual and higher fALFF in the frontal regions were found in both SSD and ASD participants compared with TDCs. Limited differences were observed between ASD and SSD participants in the cuneus regions only. Associations between slow-4 fALFF and higher-level social cognitive scores across the whole sample were observed in the lateral occipitotemporal and temporoparietal junction. Individual variability within the ASD and SSD groups was also significantly higher compared with TDC. Similar patterns of fALFF and individual variability in ASD and SSD suggest some common neurobiological deficits across these related heterogeneous conditions.
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Affiliation(s)
- Soroush Bagheri
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Ju-Chi Yu
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Vinh Tan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Lindsay D. Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Erin W. Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ayesha G. Rashidi
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - George Foussias
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Research Institute, and Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Robert W. Buchanan
- Maryland Psychiatric Research Centre, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Anil K. Malhotra
- Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, NY, USA
- The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry, Hempstead, NY, USA
- Centre for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Stephanie H. Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Research Institute, and Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
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Jin X, Zhang K, Lu B, Li X, Yan CG, Du Y, Liu Y, Lu J, Luo X, Gao X, Liu J. Shared atypical spontaneous brain activity pattern in early onset schizophrenia and autism spectrum disorders: evidence from cortical surface-based analysis. Eur Child Adolesc Psychiatry 2024; 33:2387-2396. [PMID: 38147111 PMCID: PMC11255015 DOI: 10.1007/s00787-023-02333-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 11/28/2023] [Indexed: 12/27/2023]
Abstract
Schizophrenia and autism spectrum disorders (ASD) were considered as two neurodevelopmental disorders and had shared clinical features. we hypothesized that they have some common atypical brain functions and the purpose of this study was to explored the shared brain spontaneous activity strength alterations in early onset schizophrenia (EOS) and ASD in the children and adolescents with a multi-center large-sample study. A total of 171 EOS patients (aged 14.25 ± 1.87), 188 ASD patients (aged 9.52 ± 5.13), and 107 healthy controls (aged 11.52 ± 2.82) had scanned with Resting-fMRI and analyzed surface-based amplitude of low-frequency fluctuations (ALFF). Results showed that both EOS and ASD had hypoactivity in the primary sensorimotor regions (bilateral primary and early visual cortex, left ventral visual stream, left primary auditory cortex) and hyperactivity in the high-order transmodal regions (bilateral SFL, bilateral DLPFC, right frontal eye fields), and bilateral thalamus. EOS had more severe abnormality than ASD. This study revealed shared functional abnormalities in the primary sensorimotor regions and the high-order transmodal regions in EOS and ASD, which provided neuroimaging evidence of common changes in EOS and ASD, and may help with better early recognition and precise treatment for EOS and ASD.
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Affiliation(s)
- Xingyue Jin
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Kun Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Bin Lu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Xue Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 51 Huayuan Road, Haidian District, Beijing, 100191, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Yasong Du
- Shanghai Mental Health Center, No.600 Wanping Nan Road, Shanghai, China
| | - Yi Liu
- Shanghai Mental Health Center, No.600 Wanping Nan Road, Shanghai, China
| | - Jianping Lu
- Department of Child Psychiatry of Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, China
| | - Xuerong Luo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| | - Xueping Gao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| | - Jing Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 51 Huayuan Road, Haidian District, Beijing, 100191, China.
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Weinstein SM, Tu D, Hu F, Pan R, Zhang R, Vandekar SN, Baller EB, Gur RC, Gur RE, Alexander-Bloch AF, Satterthwaite TD, Park JY. Mapping Individual Differences in Intermodal Coupling in Neurodevelopment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.26.600817. [PMID: 38979274 PMCID: PMC11230458 DOI: 10.1101/2024.06.26.600817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Within-individual coupling between measures of brain structure and function evolves in development and may underlie differential risk for neuropsychiatric disorders. Despite increasing interest in the development of structure-function relationships, rigorous methods to quantify and test individual differences in coupling remain nascent. In this article, we explore and address gaps in approaches for testing and spatially localizing individual differences in intermodal coupling. We propose a new method, called CIDeR, which is designed to simultaneously perform hypothesis testing in a way that limits false positive results and improve detection of true positive results. Through a comparison across different approaches to testing individual differences in intermodal coupling, we delineate subtle differences in the hypotheses they test, which may ultimately lead researchers to arrive at different results. Finally, we illustrate the utility of CIDeR in two applications to brain development using data from the Philadelphia Neurodevelopmental Cohort.
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Affiliation(s)
- Sarah M. Weinstein
- Department of Epidemiology and Biostatistics, Temple University College of Public Health, Philadelphia, PA, USA
| | - Danni Tu
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Fengling Hu
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruyi Pan
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Rongqian Zhang
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | - Simon N. Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Erica B. Baller
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, Philadelphia, PA, USA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute (LiBI), Philadelphia, PA, USA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute (LiBI), Philadelphia, PA, USA
| | - Aaron F. Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute (LiBI), Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Theodore D. Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute (LiBI), Philadelphia, PA, USA
| | - Jun Young Park
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
- Department of Psychology, University of Toronto, Toronto, ON, Canada
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Bryant AG, Aquino K, Parkes L, Fornito A, Fulcher BD. Extracting interpretable signatures of whole-brain dynamics through systematic comparison. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.573372. [PMID: 38915560 PMCID: PMC11195072 DOI: 10.1101/2024.01.10.573372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures. While simple statistical representations of fMRI dynamics performed surprisingly well (e.g., properties within a single brain region), combining intra-regional properties with inter-regional coupling generally improved performance, underscoring the distributed, multifaceted changes to fMRI dynamics in neuropsychiatric disorders. The comprehensive, data-driven method introduced here enables systematic identification and interpretation of quantitative dynamical signatures of multivariate time-series data, with applicability beyond neuroimaging to diverse scientific problems involving complex time-varying systems.
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Affiliation(s)
- Annie G. Bryant
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
| | - Kevin Aquino
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
- Brain Key Incorporated, San Francisco, CA, USA
| | - Linden Parkes
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
- Turner Institute for Brain & Mental Health, Monash University, VIC, Australia
| | - Alex Fornito
- Turner Institute for Brain & Mental Health, Monash University, VIC, Australia
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
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Chen W, Liang J, Qiu X, Sun Y, Xie Y, Shangguan W, Zhang C, Wu W. Differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognitive function between untreated major depressive disorder and schizophrenia with depressive mood patients. BMC Psychiatry 2024; 24:313. [PMID: 38658896 PMCID: PMC11044294 DOI: 10.1186/s12888-024-05777-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 04/18/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Distinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients. METHODS The study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands. RESULTS Significant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups. CONCLUSIONS Alterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.
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Affiliation(s)
- Wensheng Chen
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China
| | - Xiangna Qiu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China
| | - Yaqiao Sun
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China
| | - Yong Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China
| | - Wenbo Shangguan
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China
| | - Chunguo Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China.
| | - Weibin Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China.
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Shan X, Yan H, Li H, Liu F, Li P, Zhao J, Guo W. Abnormal regional activity in the prefrontal-limbic circuit at rest: Potential imaging markers and treatment predictors in drug-naive anxiety disorders. CNS Neurosci Ther 2024; 30:e14523. [PMID: 37990350 PMCID: PMC11017453 DOI: 10.1111/cns.14523] [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: 06/06/2023] [Revised: 10/07/2023] [Accepted: 10/29/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Previous research has identified functional impairments within the prefrontal-limbic circuit in individuals with anxiety disorders. However, the link between these deficiencies, clinical symptoms, and responses to antipsychotic treatment is still not fully understood. This study aimed to investigate abnormal regional activity within the prefrontal-limbic circuit among drug-naive individuals diagnosed with generalized anxiety disorder (GAD) and panic disorder (PD) and to analyze changes following treatment. METHODS Resting-state magnetic resonance imaging was performed on a cohort of 118 anxiety disorder patients (64 GAD, 54 PD) and 61 healthy controls (HCs) at baseline. Among them, 52 patients with GAD and 44 patients with PD underwent a 4-week treatment regimen of paroxetine. Fractional amplitude of low-frequency fluctuation (fALFF) measurements and pattern classification techniques were employed to analyze the data in accordance with the human Brainnetome atlas. RESULTS Both patients with GAD and PD demonstrated decreased fALFF in the right cHipp subregion of the hippocampus and increased fALFF in specified subregions of the cingulate and orbitofrontal lobe. Notably, patients with PD exhibited significantly higher fALFF in the left A24cd subregion compared to patients with GAD, while other ROI subregions showed no significant variations between the two patient groups. Whole-brain analysis revealed abnormal fALFF in both patient groups, primarily in specific areas of the cingulate and parasingulate gyrus, as well as the inferior and medial orbitofrontal gyrus (OFG). Following a 4-week treatment period, specific subregions in the GAD and PD groups showed a significant decrease in fALFF. Further analysis using support vector regression indicated that fALFF measurements in the right A13 and right A24cd subregions may be predictive of treatment response among anxiety disorder patients. CONCLUSIONS Aberrant functional activity in certain subregions of the prefrontal-limbic circuit appears to be linked to the manifestation of anxiety disorders. These findings suggest potential imaging indicators for individual responses to antipsychotic treatment.
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Affiliation(s)
- Xiaoxiao Shan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
- Department of Psychiatry, Shandong Mental Health CenterShandong UniversityJinanShandongChina
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Huabing Li
- Department of RadiologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Feng Liu
- Department of RadiologyTianjin Medical University General HospitalTianjinChina
| | - Ping Li
- Department of PsychiatryQiqihar Medical UniversityQiqiharHeilongjiangChina
| | - Jingping Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
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Huang Y, Li Y, Yuan Y, Zhang X, Yan W, Li T, Niu Y, Xu M, Yan T, Li X, Li D, Xiang J, Wang B, Yan T. Beta-informativeness-diffusion multilayer graph embedding for brain network analysis. Front Neurosci 2024; 18:1303741. [PMID: 38525375 PMCID: PMC10957763 DOI: 10.3389/fnins.2024.1303741] [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: 09/28/2023] [Accepted: 02/07/2024] [Indexed: 03/26/2024] Open
Abstract
Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.
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Affiliation(s)
- Yin Huang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Ying Li
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Yuting Yuan
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Xingyu Zhang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Wenjie Yan
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Ting Li
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Yan Niu
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Mengzhou Xu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Ting Yan
- Translational Medicine Research Center, Shanxi Medical University, Taiyuan, China
| | - Xiaowen Li
- Computer Information Engineering Institute, Shanxi Technology and Business College, Taiyuan, China
| | - Dandan Li
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Jie Xiang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Bin Wang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Tianyi Yan
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
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Roeske MJ, McHugo M, Rogers B, Armstrong K, Avery S, Donahue M, Heckers S. Modulation of hippocampal activity in schizophrenia with levetiracetam: a randomized, double-blind, cross-over, placebo-controlled trial. Neuropsychopharmacology 2024; 49:681-689. [PMID: 37833590 PMCID: PMC10876634 DOI: 10.1038/s41386-023-01730-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/22/2023] [Accepted: 08/28/2023] [Indexed: 10/15/2023]
Abstract
Hippocampal hyperactivity is a novel pharmacological target in the treatment of schizophrenia. We hypothesized that levetiracetam (LEV), a drug binding to the synaptic vesicle glycoprotein 2 A, normalizes hippocampal activity in persons with schizophrenia and can be measured using neuroimaging methods. Thirty healthy control participants and 30 patients with schizophrenia (28 treated with antipsychotic drugs), were randomly assigned to a double-blind, cross-over trial to receive a single administration of 500 mg oral LEV or placebo during two study visits. At each visit, we assessed hippocampal function using resting state fractional amplitude of low frequency fluctuations (fALFF), cerebral blood flow (CBF) with arterial spin labeling, and hippocampal blood-oxygen-level-dependent (BOLD) signal during a scene processing task. After placebo treatment, we found significant elevations in hippocampal fALFF in patients with schizophrenia, consistent with hippocampal hyperactivity. Additionally, hippocampal fALFF in patients with schizophrenia after LEV treatment did not significantly differ from healthy control participants receiving placebo, suggesting that LEV may normalize hippocampal hyperactivity. In contrast to our fALFF findings, we did not detect significant group differences or an effect of LEV treatment on hippocampal CBF. In the context of no significant group difference in BOLD signal, we found that hippocampal recruitment during scene processing is enhanced by LEV more significantly in schizophrenia. We conclude that pharmacological modulation of hippocampal hyperactivity in schizophrenia can be studied with some neuroimaging methods, but not others. Additional studies in different cohorts, employing alternate neuroimaging methods and study designs, are needed to establish levetiracetam as a treatment for schizophrenia.
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Affiliation(s)
- Maxwell J Roeske
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Maureen McHugo
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Baxter Rogers
- Vanderbilt University Institute of Imaging Sciences, Nashville, TN, USA
| | - Kristan Armstrong
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Suzanne Avery
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Manus Donahue
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
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Luo W, Du R, Li Y, Zhang H, Li W, Luo X, Chen Y, Yuan X, Deng J. Identification of genetic features that are associated with amplitude of low-frequency fluctuation changes in schizophrenia using omics analysis. J Neurosci Res 2024; 102:e25297. [PMID: 38361412 DOI: 10.1002/jnr.25297] [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: 08/02/2022] [Revised: 11/14/2023] [Accepted: 01/14/2024] [Indexed: 02/17/2024]
Abstract
Genetic risk for schizophrenia is thought to trigger variation in clinical features of schizophrenia, but biological processes associated with neuronal activity in brain regions remain elusive. In this study, gene expression features were mapped to various sub-regions of the brain by integrating low-frequency amplitude features and gene expression data from the schizophrenia brain and using gene co-expression network analysis of the Allen Transcriptome Atlas of the human brain from six donors to identify genetic features of brain regions and important associations with neuronal features. The results indicate that changes in the dynamic amplitude of low-frequency fluctuation (dALFF) are mainly associated with transcriptome signature factors such as cortical layer synthesis, immune response, and expanded membrane transport. Further modular disease enrichment analysis revealed that the same set of signature genes associated with dALFF levels was enriched for multiple neurological biological processes. Finally, genetic profiling of individual modules identified multiple core genes closely related to schizophrenia, also potentially associated with neuronal activity. Thus, this paper explores genetic features of brain regions in the schizophrenia closely related to low-frequency amplitude ratio levels based on imaging genetics, which suggests structural endophenotypes associated with schizophrenia.
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Affiliation(s)
- Wei Luo
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
- Pazhou Lab, Guangzhou, China
| | - Ruolan Du
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
- Pazhou Lab, Guangzhou, China
| | - Ying Li
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Hua Zhang
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Weixin Li
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
| | - Xiaoqi Luo
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
| | - Yunying Chen
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
| | - Xinying Yuan
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
| | - Jin Deng
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
- Pazhou Lab, Guangzhou, China
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10
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Feng S, Zhou S, Huang Y, Peng R, Han R, Li H, Yi Y, Feng Y, Ning Y, Han W, Zhang Z, Liu C, Li J, Wen X, Wu K, Wu F. Correlation between low frequency fluctuation and cognitive performance in bipolar disorder patients with suicidal ideation. J Affect Disord 2024; 344:628-634. [PMID: 37838272 DOI: 10.1016/j.jad.2023.10.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 09/11/2023] [Accepted: 10/08/2023] [Indexed: 10/16/2023]
Abstract
BACKGROUND Patients with bipolar disorder (BD) are at high risk of suicidal ideation (SI), and BD patients with suicidal ideation (BDSI) have shown marked abnormalities in spontaneous brain function. Cognitive impairment, on the other hand, is considered to be one of the core symptoms of BD. However, few studies have addressed the association between cognitive performance and abnormal spontaneous brain function in BDSI. METHODS In the current study, the MATRICS Consensus Cognitive Battery (MCCB) was used to assess cognitive performance in BDSI (n = 20), BD subjects without suicidal ideation (BDNSI) (n = 24) and healthy controls (HC) (n = 30). Their cognitive performance was then correlated with amplitude of low frequency fluctuation (ALFF) values obtained by resting-state functional magnetic resonance imaging (rs-fMRI). RESULTS We found that ALFF was significantly higher in the left precuneus and right posterior cingulate cortex in the BDSI group and significantly lower in the right precuneus in the BDNSI group than in the HC group. In addition, in the BDSI group, visual learning performance was positively correlated with ALFF values in the left precuneus. CONCLUSIONS Our findings support the notion that BD patients present with ALFF abnormalities, which are associated with cognitive performance in BDSI.
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Affiliation(s)
- Shixuan Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sumiao Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Runlin Peng
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China
| | - Rui Han
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China
| | - Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yun Yi
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yangdong Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuping Ning
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wei Han
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziyun Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenyu Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhao Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xitong Wen
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China; National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China; Guangdong Province Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou, China; Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China.
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China.
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11
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Xue S, Kong F, Song Y, Liu J. Neural correlates of social interaction anxiety and their relation to emotional intelligence: A resting-state fMRI study. Neurosci Lett 2024; 818:137475. [PMID: 37717816 DOI: 10.1016/j.neulet.2023.137475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 08/29/2023] [Accepted: 09/08/2023] [Indexed: 09/19/2023]
Abstract
Social interaction anxiety refers to a state of anxiety resulting from the prospect or presence of interpersonal evaluation in real or imagined social settings. Previous neuroimaging studies have revealed neural basis of social anxiety disorder. However, little is known about the neural correlates of individual differences in social interaction anxiety in nonclinical population. In the present study, we used resting-state functional magnetic resonance imaging to explore the relationship between individual's spontaneous neural activity and social interaction anxiety, and the role that emotional intelligence played in the relationship. To this end, the correlation between the regional fractional amplitude of low-frequency fluctuations (fALFF) of the brain and individuals' social interaction anxiety scores was examined. We found that social interaction anxiety was correlated with the fALFF in the insula, parahippocampal gyrus, bilateral superior temporal gyrus, and superior parietal lobule. Furthermore, we also found that emotional intelligence partially mediated the association between the fALFF in these regions and social interaction anxiety. Taken together, our study provided the first evidence for the spontaneous neural basis of social interaction anxiety in normal population, and highlighted the neural substrates through which emotional intelligence might play an important role in social interaction anxiety.
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Affiliation(s)
- Song Xue
- School of Psychology, Nanjing Normal University, Nanjing, China.
| | - Feng Kong
- School of Psychology, Shaanxi Normal University, Xi'an, China
| | - Yiying Song
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jia Liu
- School of Psychology, Beijing Normal University, Beijing, China
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12
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Li Q, Zhang X, Yang X, Pan N, He M, Suo X, Li X, Gong Q, Wang S. Pre-COVID resting-state brain activity in the fusiform gyrus prospectively predicts social anxiety alterations during the pandemic. J Affect Disord 2024; 344:380-388. [PMID: 37838273 DOI: 10.1016/j.jad.2023.10.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 09/24/2023] [Accepted: 10/09/2023] [Indexed: 10/16/2023]
Abstract
BACKGROUND Social anxiety (SA) has been linked to the coronavirus disease 2019 (COVID-19) pandemic, but the neurobiopsychological mechanisms underlying this relationship remain unclear. This study aimed to elucidate the neurofunctional markers for COVID-induced SA development and the potential role of COVID-related posttraumatic stress symptoms (PTSS) in the brain-SA alterations link. METHODS Before the COVID-19 pandemic (T1), 100 general college students underwent resting-state magnetic resonance imaging and behavioral tests. During the period of community-level outbreaks (T2), these students were re-contacted to undergo follow-up behavioral assessments. RESULTS Whole-brain correlation and prediction analyses found that pre-pandemic spontaneous neural activity (measured by fractional amplitude of low-frequency fluctuations) in the right fusiform gyrus (FG) was positively correlated to SA alterations (T2 - T1). Mediation analyses revealed that COVID-specific PTSS mediated the effects of right FG on SA alterations. LIMITATIONS The results should be interpreted carefully because only one-session neuroimaging data in a sample of normal adults were included. CONCLUSIONS The results provide evidence for neurofunctional markers of COVID-induced SA and may help develop targeted brain-based interventions that reduce SA.
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Affiliation(s)
- Qingyuan Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Department of Interventional Therapy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xun Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing, China
| | - Nanfang Pan
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Min He
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xueling Suo
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xiao Li
- Department of Interventional Therapy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, China.
| | - Song Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
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13
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Park M, Jang JH, Yoo SY, Choi A, Kim H, Choi JS. Regional brain activity of resting-state fMRI and auditory oddball ERP with multimodal approach in individuals with internet gaming disorder. J Behav Addict 2023; 12:895-906. [PMID: 37987778 PMCID: PMC10786222 DOI: 10.1556/2006.2023.00063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/08/2023] [Accepted: 10/28/2023] [Indexed: 11/22/2023] Open
Abstract
Background and aims Resting-state brain activity may be associated with the ability to perform tasks; however, a multimodal approach involving resting-state functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) has not been widely used to investigate addictive disorders. Methods We explored resting-state fMRI and auditory oddball ERP values from 26 with internet gaming disorder (IGD) patients and 27 age- and intelligence quotient-matched healthy controls (HCs). To assess the characteristics of resting-state fMRI, we calculated regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and fractional amplitude of low-frequency fluctuation (fALFF); we also calculated the P3 component of the ERPs. Results Compared with HCs, the individuals with IGD exhibited significant decreases in ReHo and fALFF values in the left inferior occipital gyrus, increased ReHo and ALFF values in the right precuneus, increased ALFF in the left superior frontal gyrus, and lower P3 amplitudes in the midline centro-parietal area during the auditory ERP task. Furthermore, the regional activity of resting-state fMRI in the right inferior temporal gyrus and the occipital regions were positively correlated with the P3 amplitudes in IGD patients, whereas ReHo values of the left hippocampus and the right amygdala were negatively correlated with P3. Discussion and conclusions Our results suggest that IGD patients have difficulty interacting effectively with cognitive function and sensory processing, although its interpretations need some cautions. The findings in this study will broaden the overall understanding of the neurobiological mechanisms that underlie IGD pathophysiology.
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Affiliation(s)
- Minkyung Park
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Joon Hwan Jang
- Department of Psychiatry, Seoul National University Health Service Center, Seoul, Republic of Korea
- Department of Human Systems Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - So Young Yoo
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Areum Choi
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Heejung Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
- Institute of Radiation Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Jung-Seok Choi
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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14
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Buciuman MO, Oeztuerk OF, Popovic D, Enrico P, Ruef A, Bieler N, Sarisik E, Weiske J, Dong MS, Dwyer DB, Kambeitz-Ilankovic L, Haas SS, Stainton A, Ruhrmann S, Chisholm K, Kambeitz J, Riecher-Rössler A, Upthegrove R, Schultze-Lutter F, Salokangas RKR, Hietala J, Pantelis C, Lencer R, Meisenzahl E, Wood SJ, Brambilla P, Borgwardt S, Falkai P, Antonucci LA, Bertolino A, Liddle P, Koutsouleris N. Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1207-1217. [PMID: 37343661 DOI: 10.1016/j.bpsc.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 06/01/2023] [Accepted: 06/03/2023] [Indexed: 06/23/2023]
Abstract
BACKGROUND Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level. METHODS Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up. RESULTS Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%. CONCLUSIONS We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.
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Affiliation(s)
- Madalina-Octavia Buciuman
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Oemer Faruk Oeztuerk
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - David Popovic
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Paolo Enrico
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Anne Ruef
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Nadia Bieler
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Elif Sarisik
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Johanna Weiske
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Mark Sen Dong
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Dominic B Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Orygen, the National Centre of Excellence for Youth Mental Health, Melbourne, Victoria, Australia
| | - Lana Kambeitz-Ilankovic
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Alexandra Stainton
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | | | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | | | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom
| | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-Universität, Düsseldorf, Germany; Department of Psychology, Faculty of Psychology, Airlangga University, Surabaya, Indonesia; University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Jarmo Hietala
- Department of Psychiatry, University of Turku, Turku, Finland
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Carlton South, Melbourne, Victoria, Australia; NorthWestern Mental Health, Royal Melbourne Hospital, Parkville, Melbourne, Victoria, Australia
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Stephen J Wood
- Orygen, the National Centre of Excellence for Youth Mental Health, Melbourne, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia; School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lüebeck, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Linda A Antonucci
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy; Department of Translational Biomedicine and Neuroscience (DiBraiN) - University of Bari "Aldo Moro," Bari, Italy
| | - Peter Liddle
- Division of Mental Health and Clinical Neuroscience, Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
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15
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Türk Y, Devecioğlu İ, Küskün A, Öge C, Beyazyüz E, Albayrak Y. ROI-based analysis of diffusion indices in healthy subjects and subjects with deficit or non-deficit syndrome schizophrenia. Psychiatry Res Neuroimaging 2023; 336:111726. [PMID: 37925764 DOI: 10.1016/j.pscychresns.2023.111726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 09/29/2023] [Accepted: 10/14/2023] [Indexed: 11/07/2023]
Abstract
We analyzed DTI data involving 22 healthy subjects (HC), 15 patients with deficit syndrome schizophrenia (DSZ), and 25 patients with non-deficit syndrome schizophrenia (NDSZ). We used a 1.5-T MRI scanner to collect diffusion-weighted images and T1 images, which were employed to correct distortions and deformations within the diffusion-weighted images. For 156 regions of interest (ROI), we calculated the average fractional anisotropy (FA), mean diffusion (MD), and radial diffusion (RD). Each ROI underwent a group-wise comparison using permutation F-test, followed by post hoc pairwise comparisons with Bonferroni correction. In general, we observed lower FA in both schizophrenia groups compared to HC (i.e., HC>(DSZ=NDSZ)), while MD and RD showed the opposite pattern. Notably, specific ROIs with reduced FA in schizophrenia patients included bilateral nucleus accumbens, left fusiform area, brain stem, anterior corpus callosum, left rostral and caudal anterior cingulate, right posterior cingulate, left thalamus, left hippocampus, left inferior temporal cortex, right superior temporal cortex, left pars triangularis and right lingual gyrus. Significantly, the right cuneus exhibited lower FA in the DSZ group compared to other groups ((HC=NDSZ)>DSZ), without affecting MD and RD. These results indicate that compromised neural integrity in the cuneus may contribute to the pathophysiological distinctions between DSZ and NDSZ.
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Affiliation(s)
- Yaşar Türk
- Radiology Department, Medical Faculty, Tekirdağ Namık Kemal University. Namik Kemal Mh., Kampus Cd., Suleymanpasa, Tekirdag 59100, Turkey; Radiology Department, İstanbul Health and Technology University Hospital, Kaptanpasa Mh., Darulaceze Cd., Sisli, İstanbul 34384, Turkey
| | - İsmail Devecioğlu
- Biomedical Engineering Department, Çorlu Faculty of Engineering, Tekirdağ Namık Kemal University, NKU Corlu Muhendislik Fakultesi, Silahtaraga Mh., Çorlu, Tekirdağ 59860, Turkey.
| | - Atakan Küskün
- Radiology Department, Medical Faculty, Kırklareli University, Cumhuriyet Mh., Kofcaz Yolu, Kayali Yerleskesi, Merkezi Derslikler 2, No 39/L, Merkez, Kırklareli, Turkey
| | - Cem Öge
- Psychiatry Department, Çorlu State Hospital, Zafer, Mah. Bülent Ecevit Blv. No:33, Çorlu, Tekirdağ 59850, Turkey
| | - Elmas Beyazyüz
- Psychiatry Department, Medical Faculty, Tekirdağ Namık Kemal University. Namik Kemal Mh., Kampus Cd., Suleymanpasa, Tekirdag 59100, Turkey
| | - Yakup Albayrak
- Psychiatry Department, Medical Faculty, Tekirdağ Namık Kemal University. Namik Kemal Mh., Kampus Cd., Suleymanpasa, Tekirdag 59100, Turkey
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16
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Kang Y, Zhang Y, Huang K, Wang Z. Association of dopamine-based genetic risk score with dynamic low-frequency fluctuations in first-episode drug-naïve schizophrenia. Brain Imaging Behav 2023; 17:584-594. [PMID: 37382826 DOI: 10.1007/s11682-023-00786-2] [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: 06/11/2023] [Indexed: 06/30/2023]
Abstract
Alterations in dynamic intrinsic brain activity and signaling of neurotransmitters, such as dopamine, have been independently detected in schizophrenia patients. Yet, it remains unclear whether the dopamine genetic risk variants have association with brain intrinsic activity. We aimed to investigate the schizophrenia-specific dynamic amplitude of low frequency fluctuation (dALFF) altered pattern, and its association with dopamine genetic risk score in first-episode drug-naïve schizophrenia (FES). Fifty-two FES and 51 healthy controls were included. A sliding-window method based on the dALFF was adopted to estimate the dynamic alterations in intrinsic brain activity. Subjects were genotyped, and a genetic risk score (GRS), which combined the additive effects of ten risk genotypes from five dopamine-related genes, was calculated. We used the voxel-wise correlation analysis to explore the association of dopamine-GRS with dALFF. FES showed significantly increased dALFF left medial prefrontal cortex and significantly decreased dALFF in the right posterior cingulate cortex compared with healthy controls. Greater dopamine GRS in FES was associated with higher dALFF in the left middle frontal gyrus and left inferior parietal gyrus. Our findings indicate that cumulative dopamine genetic risk is associated with a known imaging phenotype for schizophrenia.
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Affiliation(s)
- Yafei Kang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China
| | - Youming Zhang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Kexin Huang
- West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Zhenhong Wang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China.
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17
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George AB, Beniwal RP, Singh S, Bhatia T, Khushu S, Deshpande SN. Association between thyroid functions, cognition, and functional connectivity of the brain in early-course schizophrenia: A preliminary study. Ind Psychiatry J 2023; 32:S76-S82. [PMID: 38370920 PMCID: PMC10871410 DOI: 10.4103/ipj.ipj_198_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/28/2023] [Accepted: 07/16/2023] [Indexed: 02/20/2024] Open
Abstract
Background The functional outcome of the debilitating mental illness schizophrenia (SZ) has an integral role in cognition. The thyroid hormone has a vital role in the developmental stages and functioning of the human brain. Aim This study aimed to evaluate the relationship between thyroid functions, cognition, and functional imaging of the brain in persons with SZ. Materials and Methods Sixty SZ (Diagnostic and Statistical Manual (DSM-5)) persons, aged 18-50 years of both genders, were recruited in this cross-sectional observational study. Positive and Negative Syndrome Scale (PANSS) and Trail Making Tests (TMTs) A and B were administered to all patients. To assess the level of thyroid hormone, a test was conducted. Functional connectivity of the brain was assessed using resting-state functional magnetic resonance imaging (rs-fMRI). Data analysis was performed by descriptive and analytical statistical methods. FSL version 5.9 (FMRIB's) software was used for analyses of fMRI neuroimages. Results There were no significant differences between the two populations on sociodemographic factors. The average value for thyroid-stimulating hormone (TSH) in the hypothyroid group (n = 12) and the euthyroid group (n = 47) was 8.38 mIU/l and 2.44 mIU/l, respectively. The average time in seconds for TMT-A and TMT-B was 87.27 and 218.27 in the hypothyroid group and 97.07 and 293.27 in the euthyroid group, respectively. Similarly, in the sample matched on age, gender, and age at onset of illness, there were no significant differences in demographic and clinical factors and resting-state network (RSN) between the hypothyroid (N = 10) and euthyroid (N = 10) groups. Conclusion No differences were found in the functional brain network between the hypothyroid and euthyroid groups as the study sample did not include clinically hypothyroid persons with SZ.
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Affiliation(s)
- Aishwariya B George
- Department of Psychiatry, Malabar Medical College Hospital and Research Centre, Kozhikode, Kerala, India
| | - Ram P Beniwal
- Department of Psychiatry, Centre of Excellence in Mental Health, Atal Bihari Vajpayee Institute of Medical Sciences and Dr. Ram Manohar Lohia Hospital, New Delhi, India
| | - Sadhana Singh
- Centre for Brain Research, Indian Institute of Science, Bengaluru, Karnataka, India
| | - Triptish Bhatia
- Department of Psychiatry, Centre of Excellence in Mental Health, Atal Bihari Vajpayee Institute of Medical Sciences and Dr. Ram Manohar Lohia Hospital, New Delhi, India
| | - Subhash Khushu
- Division of Radiological Imaging, and Bio-Medical Imaging, The University of Trans-Disciplinary Health Sciences and Technology, Bengaluru, Karnataka, India
| | - Smita N Deshpande
- Department of Psychiatry, St John's Medical College Hospital, Bengaluru, Karnataka, India
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18
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Li X, Liu Q, Chen Z, Li Y, Yang Y, Wang X, Guo X, Luo B, Zhang Y, Shi H, Zhang L, Su X, Shao M, Song M, Guo S, Fan L, Yue W, Li W, Lv L, Yang Y. Abnormalities of Regional Brain Activity in Patients With Schizophrenia: A Longitudinal Resting-State fMRI Study. Schizophr Bull 2023; 49:1336-1344. [PMID: 37083900 PMCID: PMC10483477 DOI: 10.1093/schbul/sbad054] [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: 04/22/2023]
Abstract
BACKGROUND Evidence from functional and structural research suggests that abnormal brain activity plays an important role in the pathophysiology of schizophrenia (SZ). However, limited studies have focused on post-treatment changes, and current conclusions are inconsistent. STUDY DESIGN We recruited 104 SZ patients to have resting-state functional magnetic resonance imaging scans at baseline and 8 weeks of treatment with second-generation antipsychotics, along with baseline scanning of 86 healthy controls (HCs) for comparison purposes. Individual regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and degree centrality values were calculated to evaluate the functional activity. The Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery were applied to measure psychiatric symptoms and cognitive impairment in SZ patients. RESULTS Compared with HCs at baseline, SZ patients had higher ALFF and ReHo values in the bilateral inferior temporal gyrus, inferior frontal gyrus, and lower ALFF and ReHo values in fusiform gyrus and precuneus. Following 8 weeks of treatment, ReHo was increased in right medial region of the superior frontal gyrus (SFGmed) and decreased in the left middle occipital gyrus and the left postcentral gyrus. Meanwhile, ReHo of the right SFGmed was increased after treatment in the response group (the reduction rate of PANSS ≥50%). Enhanced ALFF in the dorsolateral of SFG correlated with improvement in depressive factor score. CONCLUSIONS These findings provide novel evidence for the abnormal functional activity hypothesis of SZ, suggesting that abnormality of right SFGmed can be used as a biomarker of treatment response in SZ.
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Affiliation(s)
- Xue Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Qing Liu
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Zhaonian Chen
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yalin Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Ying Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Xiujuan Wang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Xiaoge Guo
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Binbin Luo
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yan Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Han Shi
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Luwen Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Xi Su
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Minglong Shao
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Meng Song
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Suqin Guo
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Lingzhong Fan
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Weihua Yue
- Institute of Mental Health, Peking University, Beijing, China
- Key Laboratory for Mental Health, Ministry of Health, Beijing, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
- International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
- Henan Collaborative Innovation Center of Prevention and treatment of mental disorder, Xinxiang, China
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19
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Dai R, Herold CJ, Wang X, Kong L, Schröder J. Structural brain networks in schizophrenia based on nonnegative matrix factorization. Psychiatry Res Neuroimaging 2023; 334:111690. [PMID: 37480705 DOI: 10.1016/j.pscychresns.2023.111690] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 06/11/2023] [Accepted: 07/18/2023] [Indexed: 07/24/2023]
Abstract
Schizophrenia is a severe mental disease with significant morphometric reductions in gray matter volume and cortical thickness in a variety of brain regions. However, most studies only focused on the voxel level alterations in specific cerebral regions and ignored the spatial relationship between voxels. In the present study, we used a novel, data-driven technique-nonnegative matrix factorization (NMF) to group voxels with similar information into a network, and studied the structural covariance at the network level in schizophrenia. Our sample included 36 patients with schizophrenia and 21 healthy controls. Compared with healthy controls, patients with schizophrenia showed significant gray matter volume reductions in six structural covariance networks (dorsal striatum, thalamus, hippocampus-parahippocampus, supplementary motor area-fusiform, middle/inferior temporal network, frontal-parietal-occipital network). Our findings confirmed the assumption of a disturbance in the cortical-subcortical circuit in schizophrenia and suggested that NMF is a useful multivariate method to identify brain networks, which provides a new perspective to study the neural mechanism in schizophrenia.
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Affiliation(s)
- Rongjie Dai
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | - Christina J Herold
- Section of Geriatric Psychiatry, Department of Psychiatry, University of Heidelberg, Germany
| | - Xingsong Wang
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | - Li Kong
- Department of Psychology, Shanghai Normal University, Shanghai, China.
| | - Johannes Schröder
- Section of Geriatric Psychiatry, Department of Psychiatry, University of Heidelberg, Germany
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20
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Zhang X, Xu M, Yang X, Yang Y. Individual Differences in Emotion Attenuation Brought by Indirect Replies Is Related to Resting-State Brain Activity. Brain Sci 2023; 13:1053. [PMID: 37508985 PMCID: PMC10377414 DOI: 10.3390/brainsci13071053] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023] Open
Abstract
During daily conversations, people prefer indirect replies in face-threatening situations. Existent studies have indicated that recipients tend to perceive the information conveyed by indirect replies as negative and emotion regions are engaged in indirect replies processing in face-threatening situations. In this study, we examined whether indirect replies can reduce recipients' experience of negative emotion and what are the underlying cerebral structures that may give rise to individual differences in the effectiveness of such replies in attenuating negative emotion. Behavior ratings and resting-stating functional magnetic resonance imaging (rs-fMRI) techniques were combined to explore these questions. We created dialogues expressing refusal or negative opinion with direct/indirect replies. Participants were asked to rate their emotional valence and arousal when they received such replies. The rating scores were used to correlate with spontaneous brain activity. Results showed that indirect replies indeed attenuated recipients' negative emotion experience. Moreover, the left caudate, the right anterior cingulate cortex (rACC), and the connectivity of rACC and left medial prefrontal cortex (lmPFC) were found to be positively correlated to individual differences in such emotion attenuation. Our findings provide direct empirical evidence for the face-saving function of indirect replies and reveal that the intrinsic brain activities of emotion network and theory of mind (ToM) network are related to individual differences in such emotion attenuation.
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Affiliation(s)
- Xiuping Zhang
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Maoyao Xu
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Xiaohong Yang
- Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Yufang Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
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21
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Shi Y, Shen Z, Zeng W, Luo S, Zhou L, Wang N. A schizophrenia study based on multi-frequency dynamic functional connectivity analysis of fMRI. Front Hum Neurosci 2023; 17:1164685. [PMID: 37250690 PMCID: PMC10213427 DOI: 10.3389/fnhum.2023.1164685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/17/2023] [Indexed: 05/31/2023] Open
Abstract
At present, fMRI studies mainly focus on the entire low-frequency band (0. 01-0.08 Hz). However, the neuronal activity is dynamic, and different frequency bands may contain different information. Therefore, a novel multi-frequency-based dynamic functional connectivity (dFC) analysis method was proposed in this study, which was then applied to a schizophrenia study. First, three frequency bands (Conventional: 0.01-0.08 Hz, Slow-5: 0.0111-0.0302 Hz, and Slow-4: 0.0302-0.0820 Hz) were obtained using Fast Fourier Transform. Next, the fractional amplitude of low-frequency fluctuations was used to identify abnormal regions of interest (ROIs) of schizophrenia, and dFC among these abnormal ROIs was implemented by the sliding time window method at four window-widths. Finally, recursive feature elimination was employed to select features, and the support vector machine was applied for the classification of patients with schizophrenia and healthy controls. The experimental results showed that the proposed multi-frequency method (Combined: Slow-5 and Slow-4) had a better classification performance compared with the conventional method at shorter sliding window-widths. In conclusion, our results revealed that the dFCs among the abnormal ROIs varied at different frequency bands and the efficiency of combining multiple features from different frequency bands can improve classification performance. Therefore, it would be a promising approach for identifying brain alterations in schizophrenia.
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Affiliation(s)
- Yuhu Shi
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Zehao Shen
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Weiming Zeng
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Sizhe Luo
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Lili Zhou
- Surgery Department of Tongji University Affiliated Yangpu Central Hospital, Shanghai, China
| | - Nizhuan Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
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22
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Xu L, Wei H, Sun Z, Chu T, Li M, Liu R, Jiang L, Liang Z. Dynamic alterations of spontaneous neural activity in post-stroke aphasia: a resting-state functional magnetic resonance imaging study. Front Neurosci 2023; 17:1177930. [PMID: 37250389 PMCID: PMC10213748 DOI: 10.3389/fnins.2023.1177930] [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: 03/02/2023] [Accepted: 04/20/2023] [Indexed: 05/31/2023] Open
Abstract
Background and purpose The dynamic alterations in spontaneous neural activity of the brain during the acute phase of post-stroke aphasia (PSA) remain unclear. Therefore, in this study, dynamic amplitude of low-frequency fluctuation (dALFF) was applied to explore abnormal temporal variability in local functional activity of the brain during acute PSA. Materials and methods Resting-state functional magnetic resonance imaging (rs-fMRI) data from 26 patients with PSA and 25 healthy controls (HCs) were acquired. The sliding window method was used to assess dALFF, with the k-means clustering method used to identify dALFF states. The two-sample t-test was applied to compare differences in dALFF variability and state metrics between the PSA and HC groups. Results (1) In the PSA group, greater variance of dALFF in the cerebellar network (CBN) and left fronto-temporo-parietal network (FTPN) was observed. (2) Three dALFF states were identified among all subjects. States 1 and 2 were identified in the PSA patients, and the two dALFF states shared a similar proportion. Moreover, the number of transitions between the two dALFF states was higher in the patients compared with that in HCs. Conclusion The results of this study provide valuable insights into brain dysfunction that occurs during the acute phase (6.00 ± 3.52 days) of PSA. The observed increase in variability of local functional activities in CBN and left FTPN may be related to the spontaneous functional recovery of language during acute PSA, and it also suggests that cerebellum plays an important role in language.
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Affiliation(s)
- Luyao Xu
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Hongchun Wei
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Zhongwen Sun
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Min Li
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Ruhui Liu
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Li Jiang
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Zhigang Liang
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
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23
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Wang B, Chen Y, Chen K, Lu H, Zhang Z. From local properties to brain-wide organization: A review of intraregional temporal features in functional magnetic resonance imaging data. Hum Brain Mapp 2023; 44:3926-3938. [PMID: 37086446 DOI: 10.1002/hbm.26302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 03/15/2023] [Accepted: 03/21/2023] [Indexed: 04/24/2023] Open
Abstract
Based on the fluctuations ensembled over neighbouring neurons, blood oxygen level-dependent (BOLD) signal is a mesoscale measurement of brain signals. Intraregional temporal features (IRTFs) of BOLD signal, extracted from regional neural activities, are utilized to investigate how the brain functions in local brain areas. This literature highlights four types of IRTFs and their representative calculations including variability in the temporal domain, variability in the frequency domain, entropy, and intrinsic neural timescales, which are tightly related to cognitions. In the brain-wide spatial organization, these brain features generally organized into two spatial hierarchies, reflecting structural constraints of regional dynamics and hierarchical functional processing workflow in brain. Meanwhile, the spatial organization gives rise to the link between neuronal properties and cognitive performance. Disrupted or unbalanced spatial conditions of IRTFs emerge with suboptimal cognitive states, which improved our understanding of the aging process and/or neuropathology of brain disease. This review concludes that IRTFs are important properties of the brain functional system and IRTFs should be considered in a brain-wide manner.
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Affiliation(s)
- Bolong Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, Arizona, USA
| | - Hui Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
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24
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Ma X, Yang WFZ, Zheng W, Li Z, Tang J, Yuan L, Ouyang L, Wang Y, Li C, Jin K, Wang L, Bearden CE, He Y, Chen X. Neuronal dysfunction in individuals at early stage of schizophrenia, A resting-state fMRI study. Psychiatry Res 2023; 322:115123. [PMID: 36827856 DOI: 10.1016/j.psychres.2023.115123] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 02/14/2023] [Accepted: 02/18/2023] [Indexed: 02/22/2023]
Abstract
Schizophrenia has been associated with abnormal intrinsic brain activity, involving various cognitive impairments. Qualitatively similar abnormalities are seen in individuals at ultra-high risk (UHR) for psychosis. In this study, resting-state fMRI (rs-fMRI) data were collected from 44 drug-naïve first-episode schizophrenia (Dn-FES) patients, 48 UHR individuals, and 40 healthy controls (HCs). The fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and functional connectivity (FC), were performed to evaluate resting brain function. A support vector machine (SVM) was applied for classification analysis. Compared to HCs, both clinical groups showed increased fALFF in the central executive network (CEN), decreased ReHo in the ventral visual pathway (VVP) and decreased FC in temporal-sensorimotor regions. Excellent performance was achieved by using fALFF value in distinguishing both FES (sensitivity=83.21%, specificity=80.58%, accuracy=81.37%, p=0.009) and UHR (sensitivity=75.88%, specificity=85.72%, accuracy=80.72%, p<0.001) from HC group. Moreover, the study highlighted the importance of frontal and temporal alteration in the pathogenesis of schizophrenia. However, no fMRI features were observed that could well distinguish Dn-FES from UHR group. To conclude, fALFF in the CEN may provide potential power for identifying individuals at the early stage of schizophrenia and the alteration in the frontal and temporal lobe may be important to these individuals.
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Affiliation(s)
- Xiaoqian Ma
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, United States
| | - Winson Fu Zun Yang
- Department of Psychological Sciences, Texas Tech University, Lubbock, United States
| | - Wenxiao Zheng
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China; Department of Clinical Medicine, Third Xiangya Hospital, Central South University, Changsha, China
| | - Zongchang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China
| | - Jinsong Tang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China
| | - Liu Yuan
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China
| | - Lijun Ouyang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China
| | - Yujue Wang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China
| | - Chunwang Li
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Ke Jin
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Lingyan Wang
- Department of Deratology&Traditional Chinese Medicine, Changsha Hospital of Traditional Chinese Medicine (Changsha Eighth Hospital)
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, United States
| | - Ying He
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China; Mental Health Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; National Technology Institute of Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China; Hunan Medical Center for Mental Health, Changsha, Hunan, China.
| | - Xiaogang Chen
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, No.139, Renmin Rd, Second Xiangya Hospital, Changsha, Hunan, China; Mental Health Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; National Technology Institute of Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China; Hunan Medical Center for Mental Health, Changsha, Hunan, China.
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25
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Xu K, Liu R, Chen X, Chen X, Yang Y, Wang Q, Yang J. Research on brain functions related to visual information processing and body coordination function of pilots based on the low-frequency amplitude method. Front Hum Neurosci 2023; 17:796526. [PMID: 37007677 PMCID: PMC10050347 DOI: 10.3389/fnhum.2023.796526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 02/27/2023] [Indexed: 03/17/2023] Open
Abstract
ObjectiveResearch on the differences in physiological and psychological mechanisms of practitioners in different occupations is a current hot spot, such as pilots. This study explores the frequency-dependent changes of pilots’ low-frequency amplitudes in the classical frequency band and sub-frequency band between pilots and general occupations. The goal of the current work is to provide objective brain images for the selection and evaluation of outstanding pilots.MethodsTwenty-six pilots and 23 age-, sex-, and education-matched healthy controls were included in this study. Then the mean low-frequency amplitude (mALFF) of the classical frequency band and sub-frequency band was calculated. The two-sample t-test was performed on SPM12 to analyze the differences between the flight group and control group in the classic frequency band. To explore the main effects and the inter-band effects of the mean low-frequency amplitude (mALFF), the mixed design analysis of variance was applied in the sub-frequency bands.ResultsCompared with the control group, left cuneiform lobe and the right cerebellum six area of pilots show significant difference in the classic frequency band. And the main effect results in the sub-frequency bands show that the area with higher mALFF in the flight group is located on the left middle occipital gyrus, the left cuneiform lobe, the right superior occipital gyrus, the right superior gyrus, and the left lateral central lobule. However, the area where the value of mALFF decreased is mainly located on the left rectangular cleft with surrounding cortex and the right dorsolateral superior frontal gyrus. Besides, compared with the slow-4 frequency band, the mALFF of the left middle orbital middle frontal gyrus of the slow-5 frequency band was increased, while the mALFF value of the left putamen, left fusiform gyrus, and right thalamus was decreased. The sensitivity of the slow-5 frequency band and the slow-4 frequency band to the pilots’ different brain areas was also different. Also, the different brain areas in the classic frequency band and the sub-frequency band were significantly correlated with pilots’ flight hours.ConclusionOur findings showed that the left cuneiform brain area and the right cerebellum of pilots changed significantly during resting state. And there was a positive correlation between the mALFF value of those brain area and flight hours. The comparative analysis of sub-frequency bands found that the slow-5 band could elucidate a wider range of different brain regions, providing new ideas for exploring the brain mechanisms of pilots.
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Duan J, Gong X, Womer FY, Sun K, Tang L, Liu J, Zheng J, Zhu Y, Tang Y, Zhang X, Wang F. Neurodevelopmental trajectories, polygenic risk, and lipometabolism in vulnerability and resilience to schizophrenia. BMC Psychiatry 2023; 23:153. [PMID: 36894907 PMCID: PMC9999573 DOI: 10.1186/s12888-023-04597-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 02/07/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND Schizophrenia (SZ) arises from a complex interplay involving genetic and molecular factors. Early intervention of SZ hinges upon understanding its vulnerability and resiliency factors in study of SZ and genetic high risk for SZ (GHR). METHODS Herein, using integrative and multimodal strategies, we first performed a longitudinal study of neural function as measured by amplitude of low frequency function (ALFF) in 21 SZ, 26 GHR, and 39 healthy controls to characterize neurodevelopmental trajectories of SZ and GHR. Then, we examined the relationship between polygenic risk score for SZ (SZ-PRS), lipid metabolism, and ALFF in 78 SZ, and 75 GHR in cross-sectional design to understand its genetic and molecular substrates. RESULTS Across time, SZ and GHR diverge in ALFF alterations of the left medial orbital frontal cortex (MOF). At baseline, both SZ and GHR had increased left MOF ALFF compared to HC (P < 0.05). At follow-up, increased ALFF persisted in SZ, yet normalized in GHR. Further, membrane genes and lipid species for cell membranes predicted left MOF ALFF in SZ; whereas in GHR, fatty acids best predicted and were negatively correlated (r = -0.302, P < 0.05) with left MOF. CONCLUSIONS Our findings implicate divergence in ALFF alteration in left MOF between SZ and GHR with disease progression, reflecting vulnerability and resiliency to SZ. They also indicate different influences of membrane genes and lipid metabolism on left MOF ALFF in SZ and GHR, which have important implications for understanding mechanisms underlying vulnerability and resiliency in SZ and contribute to translational efforts for early intervention.
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Affiliation(s)
- Jia Duan
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Xiaohong Gong
- State Key Laboratory of Genetic Engineering and Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - Fay Y Womer
- Dept of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kaijin Sun
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China
| | - Lili Tang
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Juan Liu
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Junjie Zheng
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China
| | - Yue Zhu
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Yanqing Tang
- Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.
| | - Fei Wang
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China. .,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
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Li J, Xu F, Gao N, Zhu Y, Hao Y, Qiao C. Sparse non-convex regularization based explainable DBN in the analysis of brain abnormalities in schizophrenia. Comput Biol Med 2023; 155:106664. [PMID: 36803794 DOI: 10.1016/j.compbiomed.2023.106664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 02/06/2023] [Accepted: 02/10/2023] [Indexed: 02/16/2023]
Abstract
Deep belief networks have been widely used in medical image analysis. However, the high-dimensional but small-sample-size characteristic of medical image data makes the model prone to dimensional disaster and overfitting. Meanwhile, the traditional DBN is driven by performance and ignores the explainability which is important for medical image analysis. In this paper, a sparse non-convex based explainable deep belief network is proposed by combining DBN with non-convex sparsity learning. For sparsity, the non-convex regularization and Kullback-Leibler divergence penalty are embedded into DBN to obtain the sparse connection and sparse response representation of the network. It effectively reduces the complexity of the model and improves the generalization ability of the model. Considering explainability, the crucial features for decision-making are selected through the feature back-selection based on the row norm of each layer's weight after network training. We apply the model to schizophrenia data and demonstrate it achieves the best performance among several typical feature selection models. It reveals 28 functional connections highly correlated with schizophrenia, which provides an effective foundation for the treatment and prevention of schizophrenia and methodological assurance for similar brain disorders.
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Affiliation(s)
- Jiajia Li
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Faming Xu
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Na Gao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| | - Yuewen Hao
- Xi'an Jiaotong University Affiliated Children's Hospital, Xi'an, 710003, China.
| | - Chen Qiao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
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Tang X, Li B, Wang M, Gao L, He Y, Xia G. Frequency-Dependent Alterations in the Amplitude of Low-Frequency Fluctuations in Patients with Acute Pericoronitis: A Resting-State fMRI Study. J Pain Res 2023; 16:501-511. [PMID: 36815124 PMCID: PMC9939792 DOI: 10.2147/jpr.s397523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 01/25/2023] [Indexed: 02/17/2023] Open
Abstract
Background Acute pericoronitis (AP) is a common cause of odontogenic toothache. Pain significantly affects the structure and function of the brain, but alterations in spontaneous brain activity in patients with AP are unclear. Purpose To apply the amplitude of low-frequency fluctuations (ALFF) method in resting-state functional magnetic resonance imaging to investigate altered spontaneous brain activity characteristics in patients with AP in different frequency bands (typical, slow-4, and slow-5 bands) and assess their correlation with clinical scores. Patients and Methods Thirty-four right-handed patients with AP and 31 healthy controls (HC), matched for age, sex, education, and right-handedness, were enrolled. All subjects underwent resting-state functional magnetic resonance imaging. DPABI software was used for data preprocessing and extracting the ALFF values in different frequency bands. Subsequently, differences in ALFF values in the three bands were compared between the two groups. Correlation between ALFF values in the differential brain regions and clinical scores was assessed. Results In the typical band, ALFF values were higher in the left insula, left superior occipital gyrus, left inferior parietal lobule, left posterior cerebellar lobule, and right postcentral gyrus in the AP than in the HC group. In the slow-4 band, ALFF values in the left superior occipital gyrus, right superior occipital gyrus, and right middle occipital gyrus were higher, and those in the right cingulate gyrus and right superior temporal gyrus were lower in the AP than in the HC group. In the slow-5 band, the ALFF values in the left insula and left superior occipital gyrus were higher in the AP than in the HC group. The ALFF values of the typical bands in the left insula, left inferior parietal lobule, and right postcentral gyrus correlated negatively, those of the slow-4 band in the right middle occipital gyrus correlated positively, and those of the slow-5 band in the left insula correlated negatively with the visual analogue scale score in the AP group. Conclusion Our results suggested that the intrinsic brain activity of AP patients was abnormal and frequency-dependent. This provides new insights to explore the neurophysiological mechanisms of AP.
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Affiliation(s)
- Xin Tang
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| | - Bin Li
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| | - Mengting Wang
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| | - Lei Gao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China
| | - Yulin He
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China,Correspondence: Yulin He; Guojin Xia, Department of Radiology, the First Affiliated Hospital of Nanchang University, 17 Yongwaizheng Street, Nanchang, Jiang Xi, 330006, People’s Republic of China, Tel +86 0791 8869 3802, Email ;
| | - Guojin Xia
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
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Wang S, Wang H, Liu X, Yan W, Wang M, Zhao R. A resting-state functional MRI study in patients with vestibular migraine during interictal period. Acta Neurol Belg 2023; 123:99-105. [PMID: 33683634 DOI: 10.1007/s13760-021-01639-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 02/26/2021] [Indexed: 12/21/2022]
Abstract
To evaluate the spontaneous neuronal activities and the changes of brain functional network in patients with vestibular migraine (VM). Three groups including18 patients with VM, 21 patients with migraine without aura (MWoA) and 21 healthy controls (HCs) underwent the scanning of the resting-state fMRI. Covariance analysis and bonferroni multiple comparisons were used to obtain brain regions with significant differences in amplitude of low-frequency fluctuation (ALFF) values. Furthermore, the brain regions with the most significant differences of ALFF values were recognized as a region of interest (ROI) and functional connectivity (FC) analysis was performed in these regions. (1) ALFF: Compared with HCs, patients with VM showed significantly lower ALFF in the right putamen (P < 0.05), and significantly higher ALFF in the right lingual gyrus (P < 0.05). In addition, compared with MWoA patients, patients with VM showed significantly higher ALFF in the right lingual gyrus (P < 0.05). (2) Compared with HCs, VM patients showed significantly higher FC among the cerebellum, the left dorsolateral superior frontal gyrus and the right putamen (P < 0.05) but significantly lower FC among the left median cingulate, paracingulate gyri and the right putamen (P < 0.05). Compared with MWoA patients, VM patients showed significantly higher FC between the cerebellum and the right putamen (P < 0.05) but significantly lower FC among the left median cingulate, paracingulate gyri and the right putamen (P < 0.05). There are functional abnormalities in nociceptive, vestibular and visual cortex regions in patients with VM during the interictal period.
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Affiliation(s)
- Shuqing Wang
- Department of Neurology, The Affiliated Hospital of Qingdao University, Jiangsu Road 16, Qingdao, 266003, China
| | - Haiping Wang
- Department of Neurology, The Affiliated Hospital of Qingdao University, Jiangsu Road 16, Qingdao, 266003, China.
| | - Xuejun Liu
- Department of Radiology, The Affiliated Hospital of Qingdao University, Jiangsu Road 16, Qingdao, 266003, China
| | - Wenjing Yan
- Department of Neurology, The Affiliated Hospital of Qingdao University, Jiangsu Road 16, Qingdao, 266003, China
| | - Minghui Wang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Jiangsu Road 16, Qingdao, 266003, China
| | - Renliang Zhao
- Department of Neurology, The Affiliated Hospital of Qingdao University, Jiangsu Road 16, Qingdao, 266003, China
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Torrens WA, Pablo JN, Shires J, Haigh SM, Berryhill ME. People with high schizotypy experience more illusions in the Pattern Glare Test: Consistent with the hyperexcitability hypothesis. Eur J Neurosci 2023; 57:388-399. [PMID: 36484768 PMCID: PMC9847329 DOI: 10.1111/ejn.15886] [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: 08/10/2022] [Accepted: 11/30/2022] [Indexed: 12/14/2022]
Abstract
Individuals diagnosed with schizophrenia spectrum disorders (SSD) exhibit a constellation of sensory and perceptual impairments, including hyporeactivity to external input. However, individuals with SSD also report subjective experiences of sensory flooding, suggesting sensory hyperexcitability. To identify the extent to which behavioural indices of hyperexcitability are related to non-psychotic symptoms of schizophrenia, we tested a non-clinical population measured for schizophrenia-like traits (schizotypy), and a behavioural measure of sensory hyperexcitability, specifically the number of illusions seen in the Pattern Glare Test. Two samples totaling 913 individuals completed an online version of the Schizotypal Personality Questionnaire - Brief Revised (SPQ-BR) and the Pattern Glare Test. Individuals with higher schizotypy traits reported more illusions in the Pattern Glare Test. Additionally, one of the three SPQ-BR factors, the disorganized factor, significantly predicted the number of illusions reported. These data illustrate the potential for research in non-clinical samples to inform clinically relevant research.
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Affiliation(s)
- Wendy A Torrens
- Department of Psychology, University of Nevada, Reno, Reno, Nevada, USA
| | - Jenna N Pablo
- Department of Psychology, University of Nevada, Reno, Reno, Nevada, USA
| | - Jorja Shires
- Department of Psychology, University of Nevada, Reno, Reno, Nevada, USA
| | - Sarah M Haigh
- Department of Psychology, University of Nevada, Reno, Reno, Nevada, USA
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Marino M, Spironelli C, Mantini D, Craven AR, Ersland L, Angrilli A, Hugdahl K. Default mode network alterations underlie auditory verbal hallucinations in schizophrenia. J Psychiatr Res 2022; 155:24-32. [PMID: 35981441 DOI: 10.1016/j.jpsychires.2022.08.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/08/2022] [Accepted: 08/04/2022] [Indexed: 10/31/2022]
Abstract
Although alterations of the default mode network (DMN) in schizophrenia (SZ) have been largely investigated, less research has been carried out on DMN alterations in different sub-phenotypes of this disorder. The aim of this pilot study was to compare DMN features among SZ patients with and without auditory verbal hallucinations (AVH). Three groups of 17 participants each were considered: patients with hallucinations (AVH-SZ), patients without hallucinations (nAVH-SZ) and age-matched healthy controls (HC). The DMN spatial pattern was similar between the nAVH-SZ and HC, but the comparison between these two groups and the AVH-SZ group revealed alterations in the left Angular Gyrus (lAG) node of the DMN. Using a novel approach based on normalized fractional Amplitude of Low-Frequency Fluctuations (fALFF), the AVH-SZ subgroup showed altered spectral activity in the DMN compared with the other two groups, especially in the lower-frequency bands (0.017-0.04 Hz). Significant positive correlations were found for both SZ groups collapsed, and for the nAVH-SZ group alone between delusional scores (PANSS-P1) and slow fALFF bands of the DMN. Narrowing the analysis to the ROI centered on the lAG, significant correlations were found in the AVH-SZ group for hallucination scores (PANSS-P3) and Slow-5 and Slow-4 (both positive), and Slow-3 (negative) fALFF bands. Our results reveal the central role of the lAG in relation to hallucinations, an important cortical area connecting auditory cortex with several hubs (including frontal linguistic centers) and involved in auditory process monitoring.
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Affiliation(s)
- Marco Marino
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium; IRCCS San Camillo Hospital, Venice, Italy.
| | - Chiara Spironelli
- Department of General Psychology, University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy.
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway; Division of Psychiatry and NORMENT Centre of Excellence, Haukeland University Hospital, Bergen, Norway
| | - Lars Ersland
- Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Alessandro Angrilli
- Department of General Psychology, University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy
| | - Kenneth Hugdahl
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; Division of Psychiatry and NORMENT Centre of Excellence, Haukeland University Hospital, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
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Gao Z, Xiao Y, Zhang Y, Zhu F, Tao B, Tang X, Lui S. Comparisons of resting-state brain activity between insomnia and schizophrenia: a coordinate-based meta-analysis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:80. [PMID: 36207333 PMCID: PMC9547062 DOI: 10.1038/s41537-022-00291-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 09/19/2022] [Indexed: 11/05/2022]
Abstract
Growing evidence shows that insomnia is closely associated with schizophrenia (SCZ), but the neural mechanism under the association remains unclear. A direct comparison of the patterns of resting-state brain activities would help understand the above question. Using meta-analytic approach, 11 studies of insomnia vs. healthy controls (HC) and 39 studies of SCZ vs. HC were included to illuminate the common and distinct patterns between insomnia and SCZ. Results showed that SCZ and insomnia shared increased resting-state brain activities in frontolimbic structures including the right medial prefrontal gyrus (mPFC) and left parahippocampal gyrus. SCZ additionally revealed greater increased activities in subcortical areas including bilateral putamen, caudate and right insula and greater decreased activities in precentral gyrus and orbitofrontal gyrus. Our study reveals both shared and distinct activation patterns in SCZ and insomnia, which may provide novel insights for understanding the neural basis of the two disorders and enlighten the possibility of the development of treatment strategies for insomnia in SCZ in the future.
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Affiliation(s)
- Ziyang Gao
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Xiao
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Ye Zhang
- grid.412901.f0000 0004 1770 1022Sleep Medicine Center, Department of Respiratory and Critical Care Medicine, Mental Health Center, Translational Neuroscience Center, and State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Fei Zhu
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Bo Tao
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Xiangdong Tang
- grid.412901.f0000 0004 1770 1022Sleep Medicine Center, Department of Respiratory and Critical Care Medicine, Mental Health Center, Translational Neuroscience Center, and State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Su Lui
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
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Lee SW, Kim E, Jang TY, Choi H, Kim S, Song H, Hwang MJ, Chang Y, Lee SJ. Alterations of Power Spectral Density in Salience Network during Thought-action Fusion Induction Paradigm in Obsessive-compulsive Disorder. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2022; 20:415-426. [PMID: 35879026 PMCID: PMC9329118 DOI: 10.9758/cpn.2022.20.3.415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 03/30/2021] [Accepted: 04/29/2021] [Indexed: 11/18/2022]
Abstract
Objective Methods Results Conclusion
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Affiliation(s)
- Sang Won Lee
- Department of Psychiatry, Kyungpook National University Chilgok Hospital, Daegu, Korea
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Eunji Kim
- Department of Medical and Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Tae Yang Jang
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
| | - Heajung Choi
- Department of Medical and Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Seungho Kim
- Department of Medical and Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Huijin Song
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | | | - Yongmin Chang
- Department of Molecular Medicine, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Radiology, Kyungpook National University Hospital, Daegu, Korea
| | - Seung Jae Lee
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
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Li T, Pei Z, Zhu Z, Wu X, Feng C. Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity. Hum Brain Mapp 2022; 43:5616-5629. [PMID: 36054523 PMCID: PMC9704792 DOI: 10.1002/hbm.26038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/06/2022] [Accepted: 07/25/2022] [Indexed: 01/15/2023] Open
Abstract
Reciprocity is prevalent across human societies, but individuals are heterogeneous regarding their reciprocity propensity. Although a large body of task-based brain imaging measures has shed light on the neural underpinnings of reciprocity at group level, the neural basis underlying the individual differences in reciprocity propensity remains largely unclear. Here, we combined brain imaging and machine learning techniques to individually predict reciprocity propensity from resting-state brain activity measured by fractional amplitude of low-frequency fluctuation. The brain regions contributing to the prediction were then analyzed for functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that patterns of resting-state brain activity across multiple brain systems were capable of predicting individual reciprocity propensity, with the contributing regions distributed across the salience (e.g., ventrolateral prefrontal cortex), fronto-parietal (e.g., dorsolateral prefrontal cortex), default mode (e.g., ventromedial prefrontal cortex), and sensorimotor (e.g., supplementary motor area) networks. Those contributing brain networks are implicated in emotion and cognitive control, mentalizing, and motor-based processes, respectively. Collectively, these findings provide novel evidence on the neural signatures underlying the individual differences in reciprocity, and lend support the assertion that reciprocity emerges from interactions among regions embodied in multiple large-scale brain networks.
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Affiliation(s)
- Ting Li
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University)Ministry of EducationGuangzhouChina,School of Psychology, Institute of Brain Research and Rehabilitation (IBRR), Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive ScienceSouth China Normal UniversityGuangzhouChina,Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
| | - Zhaodi Pei
- School of Artificial IntelligenceBeijing Normal UniversityBeijingChina,Engineering Research Center of Intelligent Technology and Educational Application of Ministry of EducationBeijing Normal UniversityBeijingChina
| | - Zhiyuan Zhu
- School of Artificial IntelligenceBeijing Normal UniversityBeijingChina,Engineering Research Center of Intelligent Technology and Educational Application of Ministry of EducationBeijing Normal UniversityBeijingChina
| | - Xia Wu
- School of Artificial IntelligenceBeijing Normal UniversityBeijingChina,Engineering Research Center of Intelligent Technology and Educational Application of Ministry of EducationBeijing Normal UniversityBeijingChina
| | - Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University)Ministry of EducationGuangzhouChina,School of Psychology, Institute of Brain Research and Rehabilitation (IBRR), Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive ScienceSouth China Normal UniversityGuangzhouChina
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Sun Y, Yang SX, Xie M, Zou K, Tang X. Aberrant amplitude of low-frequency fluctuations in different frequency bands and changes after one-night positive airway pressure treatment in severe obstructive sleep apnea. Front Neurol 2022; 13:985321. [PMID: 36071907 PMCID: PMC9441702 DOI: 10.3389/fneur.2022.985321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 08/05/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveThis study was aimed to investigate the characteristics of the amplitude of low-frequency fluctuation (ALFF) at specific frequencies in severe obstructive sleep apnea (OSA) patients. A comparison was made between pre-CPAP treatment and one night after continuous positive airway pressure (CPAP) treatment.Methods30 severe OSA patients and 19 healthy controls (HC) were recruited. The ALFF method was used to assess the local features of spontaneous brain activity and calculated at different bands (slow-5 and slow-4). A correlation analysis was performed to evaluate the relationship between the changes of the ALFF and polysomnography data.ResultsCompared with HC, in slow-5 frequency band, OSA patients showed significantly decreased ALFF in the left inferior temporal gyrus, and significantly increased ALFF in the left middle frontal gyrus, left inferior frontal gyrus, triangular part, right superior frontal gyrus, dorsolateral and right middle temporal gyrus. In slow-4 frequency, there was significantly decreased ALFF in the right inferior temporal gyrus, and significantly increased ALFF in the left precuneus, right posterior cingulate gyrus and right median cingulate besides the slow-5 difference band showed. Compared with pre-CPAP, we found that after CPAP treatment, ALFF signals in the left insula in slow-5 and left caudate in slow-4 increased, but the calcarine in slow-4 significantly reduced. Correlation analysis showed that the left angular slow-4 band change was positively correlated with the slow wave sleep change (r = 0.4933, p = 0.0056). The left cerebellum 6 slow-5 band change was positively correlated with the duration of the REM sleep change (r = 0.4563, p = 0.0113), and the left cerebellum 6 slow-4 band change was also positively correlated with the mean blood oxygen change in the REM (r = 0.4591, p = 0.0107) and NREM sleep (r = 0.4492, p = 0.0128).ConclusionWe found that the use of slow-4 was more specific in OSA studies. These results suggested that the severe OSA patients have frequency-related abnormal spontaneous neural activity, which may contribute to a better understanding of the pathological basis of OSA-related diseases and provide a potential therapeutic target for OSA patients.
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Affiliation(s)
- Yuanfeng Sun
- Sleep Medicine Center, West China Hospital, Sichuan University, Chengdu, China
| | - Sophine Xin Yang
- Business Administration of Business School, Sichuan University, Chengdu, China
| | - Min Xie
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ke Zou
- Sleep Medicine Center, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Ke Zou
| | - Xiangdong Tang
- Sleep Medicine Center, West China Hospital, Sichuan University, Chengdu, China
- Xiangdong Tang
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Kong C, Xu D, Wang Y, Wang B, Wen J, Wang X, Zhan L, Sun Z, Jia X, Li M, Tang S, Hou D. Amplitude of low-frequency fluctuations in multiple-frequency bands in patients with intracranial tuberculosis: a prospective cross-sectional study. Quant Imaging Med Surg 2022; 12:4120-4134. [PMID: 35919063 PMCID: PMC9338357 DOI: 10.21037/qims-22-17] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 04/19/2022] [Indexed: 12/11/2022]
Abstract
Background Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to study brain functional alteration, but there have been no reports of research regarding the application of rs-fMRI in intracranial tuberculosis. The purpose of this prospective, cross-sectional study was to investigate spontaneous neural activity at different frequency bands in patients with intracranial tuberculosis using rs-fMRI with amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) methods. Methods The rs-fMRI data of 31 patients with intracranial tuberculosis and 30 gender-, age-, and education-matched healthy controls (HCs) were included. The ALFF and fALFF values in the conventional frequency band (0.01−0.08 Hz) and 2 sub-frequency bands (slow-4: 0.027–0.073 Hz; slow-5: 0.01–0.027 Hz) were calculated and compared between the groups. The resultant T-maps were corrected using the Gaussian random field (GRF) theory (voxel P<0.01, cluster P<0.05). Correlations between the ALFF and fALFF values and neurocognitive scores were assessed. Results Compared with the HCs, patients with intracranial tuberculosis showed decreased ALFF in the right paracentral lobule (T=−4.69) in the conventional frequency band, in the right supplementary motor area (T=−4.85) in the slow-4 band, and in the left supplementary motor area (T=−3.76) in the slow-5 band. Compared to the slow-5 band, the voxels with decreased ALFF were spatially more extensive in the slow-4 band. Compared with HCs, patients with intracranial tuberculosis showed decreased fALFF in the opercular parts of the right inferior frontal gyrus (T=−4.50) and the left inferior parietal lobe (T=−4.86) and increased fALFF in the left inferior cerebellum (T=5.84) in the conventional frequency band. In the slow-4 band, fALFF decreased in the opercular parts of the right inferior frontal gyrus (T=−5.29) and right precuneus (T=−4.34). In the slow-5 band, fALFF decreased in the left middle occipital gyrus (T=−4.65) and right middle frontal gyrus (T=−5.05). Conclusions Patients with intracranial tuberculosis showed abnormal intrinsic brain activity at different frequency bands, and ALFF abnormalities in different brain regions could be better detected in the slow-4 band. This preliminary study might provide new insights into understanding the pathophysiological mechanism in intracranial tuberculosis.
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Affiliation(s)
- Chengcheng Kong
- Translational Medicine Center, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Dong Xu
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Yichuan Wang
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Bing Wang
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Jianjie Wen
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Xinguang Wang
- School of Information Science and Electronic Technology, Jiamusi University, Jiamusi, China
| | - Linlin Zhan
- Faculty of Western Languages, Heilongjiang University, Harbin, China
| | - Zhaogang Sun
- Translational Medicine Center, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Xize Jia
- School of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Mengting Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Shenjie Tang
- Tuberculosis Clinical Medical Center, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Dailun Hou
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
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Qiu X, Zhang R, Wen L, Jiang F, Mao H, Yan W, Xie S, Pan X. Alterations in Spontaneous Brain Activity in Drug-Naïve First-Episode Schizophrenia: An Anatomical/Activation Likelihood Estimation Meta-Analysis. Psychiatry Investig 2022; 19:606-613. [PMID: 36059049 PMCID: PMC9441467 DOI: 10.30773/pi.2022.0074] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 06/21/2022] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE The etiology of schizophrenia is unknown and is associated with abnormal spontaneous brain activity. There are no consistent results regarding the change in spontaneous brain activity of people with schizophrenia. In this study, we determined the specific changes in the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF) and regional homogeneity (ReHo) in patients with drug-naïve first-episode schizophrenia (Dn-FES). METHODS A comprehensive search of databases such as PubMed, Web of Science, and Embase was conducted to find articles on resting-state functional magnetic resonance imaging using ALFF/fALFF and ReHo in schizophrenia patients compared to healthy controls (HCs) and then, anatomical/activation likelihood estimation was performed. RESULTS Eighteen eligible studies were included in this meta-analysis. Compared to the spontaneous brain activity of HCs, we found changes in spontaneous brain activity in Dn-FES based on these two methods, mainly including the frontal lobe, putamen, lateral globus pallidus, insula, cerebellum, and posterior cingulate cortex. CONCLUSION We found that widespread abnormalities of spontaneous brain activity occur in the early stages of the onset of schizophrenia and may provide a reference for the early intervention of schizophrenia.
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Affiliation(s)
- Xiaolei Qiu
- Department of Psychiatry, Jiangning District Second People's Hospital, Nanjing, China
| | - Rongrong Zhang
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Lu Wen
- Department of Psychiatry, Jiangning District Second People's Hospital, Nanjing, China
| | - Fuli Jiang
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Hongjun Mao
- Department of Psychiatry, Jiangning District Second People's Hospital, Nanjing, China
| | - Wei Yan
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Shiping Xie
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xinming Pan
- Department of Psychiatry, Jiangning District Second People's Hospital, Nanjing, China
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Rączy K, Hölig C, Guerreiro MJS, Lingareddy S, Kekunnaya R, Röder B. Typical resting state activity of the brain requires visual input during an early sensitive period. Brain Commun 2022; 4:fcac146. [PMID: 35836836 PMCID: PMC9275761 DOI: 10.1093/braincomms/fcac146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 03/02/2022] [Accepted: 06/01/2022] [Indexed: 11/17/2022] Open
Abstract
Sensory deprivation, following a total loss of one sensory modality e.g. vision, has been demonstrated to result in compensatory plasticity. It is yet not known to which extent neural changes, e.g. higher resting-state activity in visual areas (cross-modal plasticity) as a consequence of blindness, reverse, when sight is restored. Here, we used functional MRI to acquire blood oxygen level-dependent resting-state activity during an eyes open and an eyes closed state in congenital cataract-reversal individuals, developmental cataract-reversal individuals, congenitally permanently blind individuals and sighted controls. The amplitude of low frequency fluctuation of the blood oxygen level-dependent signal—a neural marker of spontaneous brain activity during rest—was analyzed. In accordance with previous reports, in normally sighted controls we observed an increase in amplitude of low-frequency fluctuation during rest with the eyes open compared with rest with eyes closed in visual association areas and in parietal cortex but a decrease in auditory and sensorimotor regions. In congenital cataract-reversal individuals, we found an increase of the amplitude of slow blood oxygen level-dependent fluctuations in visual cortex during rest with eyes open compared with rest with eyes closed too but this increase was larger in amplitude than in normally sighted controls. In contrast, congenital cataract-reversal individuals lagged a similar increase in parietal regions and did not show the typical decrease of amplitude of low-frequency fluctuation in auditory cortex. Congenitally blind individuals displayed an overall higher amplitude in slow blood oxygen level-dependent fluctuations in visual cortex compared with sighted individuals and compared with congenital cataract-reversal individuals in the eyes closed condition. Higher amplitude of low-frequency fluctuation in visual cortex of congenital cataract-reversal individuals than in normally sighted controls during eyes open might indicate an altered excitatory–inhibitory balance of visual neural circuits. By contrast, the lower parietal increase and the missing downregulation in auditory regions suggest a reduced influence of the visual system on multisensory and the other sensory systems after restoring sight in congenitally blind individuals. These results demonstrate a crucial dependence of visual and multisensory neural system functioning on visual experience during a sensitive phase in human brain development.
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Affiliation(s)
- Katarzyna Rączy
- University of Hamburg Biological Psychology and Neuropsychology, , 20146 Hamburg, Germany
| | - Cordula Hölig
- University of Hamburg Biological Psychology and Neuropsychology, , 20146 Hamburg, Germany
| | - Maria J. S. Guerreiro
- University of Hamburg Biological Psychology and Neuropsychology, , 20146 Hamburg, Germany
- Biological Psychology, Department of Psychology, Carl Von Ossietzky University of Oldenburg , 26111, Oldenburg, Germany
| | | | - Ramesh Kekunnaya
- Child Sight Institute, LV Prasad Eye Institute Jasti V Ramanamma Children's Eye Care Center, , 500034 Hyderabad, India
| | - Brigitte Röder
- University of Hamburg Biological Psychology and Neuropsychology, , 20146 Hamburg, Germany
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Algumaei AH, Algunaid RF, Rushdi MA, Yassine IA. Feature and decision-level fusion for schizophrenia detection based on resting-state fMRI data. PLoS One 2022; 17:e0265300. [PMID: 35609033 PMCID: PMC9129055 DOI: 10.1371/journal.pone.0265300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 02/28/2022] [Indexed: 12/01/2022] Open
Abstract
Mental disorders, especially schizophrenia, still pose a great challenge for diagnosis in early stages. Recently, computer-aided diagnosis techniques based on resting-state functional magnetic resonance imaging (Rs-fMRI) have been developed to tackle this challenge. In this work, we investigate different decision-level and feature-level fusion schemes for discriminating between schizophrenic and normal subjects. Four types of fMRI features are investigated, namely the regional homogeneity, voxel-mirrored homotopic connectivity, fractional amplitude of low-frequency fluctuations and amplitude of low-frequency fluctuations. Data denoising and preprocessing were first applied, followed by the feature extraction module. Four different feature selection algorithms were applied, and the best discriminative features were selected using the algorithm of feature selection via concave minimization (FSV). Support vector machine classifiers were trained and tested on the COBRE dataset formed of 70 schizophrenic subjects and 70 healthy subjects. The decision-level fusion method outperformed the single-feature-type approaches and achieved a 97.85% accuracy, a 98.33% sensitivity, a 96.83% specificity. Moreover, feature-fusion scheme resulted in a 98.57% accuracy, a 99.71% sensitivity, a 97.66% specificity, and an area under the ROC curve of 0.9984. In general, decision-level and feature-level fusion schemes boosted the performance of schizophrenia detectors based on fMRI features.
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Affiliation(s)
- Ali H. Algumaei
- Department of Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Rami F. Algunaid
- Department of Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Muhammad A. Rushdi
- Department of Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Inas A. Yassine
- Department of Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
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Association of reduced local activities in the default mode and sensorimotor networks with clinical characteristics in first-diagnosed of schizophrenia. Neuroscience 2022; 495:47-57. [DOI: 10.1016/j.neuroscience.2022.05.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 01/10/2023]
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Wang L, Li Q, Wu Y, Ji GJ, Wu X, Xiao G, Qiu B, Hu P, Chen X, He K, Wang K. Intermittent theta burst stimulation improved visual-spatial working memory in treatment-resistant schizophrenia: A pilot study. J Psychiatr Res 2022; 149:44-53. [PMID: 35231791 DOI: 10.1016/j.jpsychires.2022.02.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 02/05/2022] [Accepted: 02/18/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Visual-spatial working memory (vsWM) impairment in treatment-resistant schizophrenia (TRS) currently has no satisfactory treatment. Our study aimed to improve vsWM function in TRS through intermittent theta burst stimulation (iTBS) using neuronavigation equipment to target the left dorsolateral prefrontal cortex. METHOD TRS patients (n = 59) were randomly allocated to receive iTBS (n = 33) or a sham treatment (n = 26) over 2 weeks. The participants including TRS patients and healthy controls (HCs) performed the vsWM n-back task, and TRS patients' neuroimaging data were acquired before and after treatment. All patients also underwent a battery of symptom measures to assess the severity of illness. The main outcome measure was the accuracy (ACC) of n-back target responses, particularly 3-back ACC. RESULTS The iTBS group showed considerable improvement in n-back ACC compared to the sham group, especially 3-back ACC. After iTBS, performance on the n-back task was comparable to that of HCs. The interaction (group × time) results showed increased fractional amplitude of low frequency fluctuations (fALFF) in the right occipital areas and decreased fALFF in the right precuneus. However, there was a negative correlation between the 3-back ACC and improved clinical symptoms scores. Improvements in 3-back ACC were positively correlated with activity in the right visual cortex. CONCLUSIONS Our study suggested that 2 weeks of iTBS intervention may be a novel, efficacious treatment for vsWM deficits in TRS, which can modulate the activity of local brain regions. iTBS can provide a solution for clinical treatment of TRS and may help patients approach normalcy.
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Affiliation(s)
- Lu Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Qianqian Li
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China; Department of Psychiatry, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yang Wu
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Gong-Jun Ji
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Xingqi Wu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Guixian Xiao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Bensheng Qiu
- Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Xingui Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China.
| | | | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Provincial Institute of Translational Medicine, Anhui Medical University, Hefei, China.
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Al Zoubi O, Misaki M, Tsuchiyagaito A, Zotev V, White E, Paulus M, Bodurka J. Machine Learning Evidence for Sex Differences Consistently Influences Resting-State Functional Magnetic Resonance Imaging Fluctuations Across Multiple Independently Acquired Data Sets. Brain Connect 2022; 12:348-361. [PMID: 34269609 PMCID: PMC9131354 DOI: 10.1089/brain.2020.0878] [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] [Indexed: 11/12/2022] Open
Abstract
Background/Introduction: Sex classification using functional connectivity from resting-state functional magnetic resonance imaging (rs-fMRI) has shown promising results. This suggested that sex difference might also be embedded in the blood-oxygen-level-dependent properties such as the amplitude of low-frequency fluctuation (ALFF) and the fraction of ALFF (fALFF). This study comprehensively investigates sex differences using a reliable and explainable machine learning (ML) pipeline. Five independent cohorts of rs-fMRI with over than 5500 samples were used to assess sex classification performance and map the spatial distribution of the important brain regions. Methods: Five rs-fMRI samples were used to extract ALFF and fALFF features from predefined brain parcellations and then were fed into an unbiased and explainable ML pipeline with a wide range of methods. The pipeline comprehensively assessed unbiased performance for within-sample and across-sample validation. In addition, the parcellation effect, classifier selection, scanning length, spatial distribution, reproducibility, and feature importance were analyzed and evaluated thoroughly in the study. Results: The results demonstrated high sex classification accuracies from healthy adults (area under the curve >0.89), while degrading for nonhealthy subjects. Sex classification showed moderate to good intraclass correlation coefficient based on parcellation. Linear classifiers outperform nonlinear classifiers. Sex differences could be detected even with a short rs-fMRI scan (e.g., 2 min). The spatial distribution of important features overlaps with previous results from studies. Discussion: Sex differences are consistent in rs-fMRI and should be considered seriously in any study design, analysis, or interpretation. Features that discriminate males and females were found to be distributed across several different brain regions, suggesting a complex mosaic for sex differences in rs-fMRI. Impact statement The presented study unraveled that sex differences are embedded in the blood-oxygen-level dependent (BOLD) and can be predicted using unbiased and explainable machine learning pipeline. The study revealed that psychiatric disorders and demographics might influence the BOLD signal and interact with the classification of sex. The spatial distribution of the important features presented here supports the notion that the brain is a mosaic of male and female features. The findings emphasize the importance of controlling for sex when conducting brain imaging analysis. In addition, the presented framework can be adapted to classify other variables from resting-state BOLD signals.
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Affiliation(s)
- Obada Al Zoubi
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
- Department of Psychiatry, Harvard Medical School/McLean Hospital, Boston, Massachusetts, USA
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | | | - Vadim Zotev
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Evan White
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Martin Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
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Increased cingulo-orbital connectivity is associated with violent behaviours in schizophrenia. J Psychiatr Res 2022; 147:183-189. [PMID: 35051717 DOI: 10.1016/j.jpsychires.2022.01.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/23/2021] [Accepted: 01/03/2022] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Although schizophrenia patients are at a heightened risk of exhibiting violent behaviours compared to the general population, few functional neuroimaging studies have explored the aberrant neurocircuitry underpinning such behaviours. This study aimed to identify disrupted resting-state activity and functional connectivity in schizophrenia patients with a history of violence. METHODS Resting state functional magnetic resonance imaging data was collected from 62 schizophrenia patients and 25 healthy controls. Voxel-wise analyses of fractional amplitude of low frequency fluctuations (fALFF) were implemented to investigate disrupted regional patterns of spontaneous brain activity. Brain regions which yielded significant differences between groups were subsequently used as data-driven seeds for functional connectivity analyses. Finally, significant alterations (activity and connectivity) were correlated with lifetime violent behaviours. RESULTS When compared to healthy controls, schizophrenia patients exhibited reduced fALFF in multiple brain regions including the (subgenual) anterior cingulate cortex (ACC), posterior cingulate cortex, precuneus cortex and left lateral orbitofrontal cortex (OFC). Seed-to-voxel analyses yielded significantly enhanced connectivity between the ACC and left OFC. The heightened functional connectivity between the latter two regions predicted the number of violent behaviours reported by schizophrenia patients. CONCLUSION The current study demonstrated that the functional connectivity of brain regions associated with emotion regulation is impaired in schizophrenia and associated with violent antecedents among patients. This result is consistent with predominant theoretical models proposing that the OFC plays a critical role in the neurobiology of violence.
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Mei T, Ma ZH, Guo YQ, Lu B, Cao QJ, Chen X, Yang L, Wang H, Tang XZ, Ji ZZ, Liu JR, Xu LZ, Wang LQ, Yang YL, Li X, Yan CG, Liu J. Frequency-specific age-related changes in the amplitude of spontaneous fluctuations in autism. Transl Pediatr 2022; 11:349-358. [PMID: 35378963 PMCID: PMC8976680 DOI: 10.21037/tp-21-412] [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: 09/01/2021] [Accepted: 12/30/2021] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Autism spectrum disorder is characterized by atypical developmental changes during brain maturation, but regional brain functional changes that occur with age and across different frequency bands are unknown. Therefore, the current study aimed to explore potential age and frequency band-related changes in the regional brain activities in autism. METHODS A total of 65 participants who met the DSM-IV criteria for autistic disorder and 55 typically developed (TD) participants (both age 6-30 years) were recruited in the current study. The two groups were matched in age (t=-1.314, P=0.191) and gender (χ2=2.760, P=0.097). The amplitude of low-frequency fluctuations (ALFF) was employed to explore the effect of development on spontaneous brain activity in individuals with autism and in TD participants across slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), and slow-3 (0.073-0.1 Hz) frequency bands. The diagnosis-by-age interaction effect in the whole brain voxels in autism and TD groups was investigated. RESULTS Autism individuals showed significantly higher ALFF in the dorsal striatum in childhood (Caudate cluster: t=3.626, P=0.001; Putamen cluster: t=2.839, P=0.007) and remarkably lower ALFF in the dorsal striatum in adulthood (Caudate cluster: t=-2.198, P=0.038; Putamen cluster: t=-2.314, P=0.030) relative to TD, while no significant differences were observed in adolescence (all P>0.05). In addition, abnormal ALFF amplitudes were specific to the slow-4 (0.027-0.073 Hz) frequency band in the clusters above. CONCLUSIONS The current study indicated abnormal development patterns in the spontaneous activity of the dorsal striatum in autism and highlighted the potential role of the slow-4 frequency band in the pathology of autism. Also, the potential brain mechanism of autism was revealed, suggesting that autism-related variations should be investigated in a specific frequency.
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Affiliation(s)
- Ting Mei
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Zeng-Hui Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yan-Qing Guo
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Bin Lu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Qing-Jiu Cao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Liu Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hui Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xin-Zhou Tang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Zhao-Zheng Ji
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jing-Ran Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Ling-Zi Xu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Li-Qi Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yu-Lu Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xue Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,International Big-Data Research Center for Depression (IBRCD), Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Jing Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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45
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Chen Y, Womer FY, Feng R, Zhang X, Zhang Y, Duan J, Chang M, Yin Z, Jiang X, Wei S, Wei Y, Tang Y, Wang F. A Real-World Observation of Antipsychotic Effects on Brain Volumes and Intrinsic Brain Activity in Schizophrenia. Front Neurosci 2022; 15:749316. [PMID: 35221884 PMCID: PMC8863862 DOI: 10.3389/fnins.2021.749316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe confounding effects of antipsychotics that led to the inconsistencies of neuroimaging findings have long been the barriers to understanding the pathophysiology of schizophrenia (SZ). Although it is widely accepted that antipsychotics can alleviate psychotic symptoms during the early most acute phase, the longer-term effects of antipsychotics on the brain have been unclear. This study aims to look at the susceptibility of different imaging measures to longer-term medicated status through real-world observation.MethodsWe compared gray matter volume (GMV) with amplitude of low-frequency fluctuations (ALFFs) in 89 medicated-schizophrenia (med-SZ), 81 unmedicated-schizophrenia (unmed-SZ), and 235 healthy controls (HC), and the differences were explored for relationships between imaging modalities and clinical variables. We also analyzed age-related effects on GMV and ALFF values in the two patient groups (med-SZ and unmed-SZ).ResultsMed-SZ demonstrated less GMV in the prefrontal cortex, temporal lobe, cingulate gyri, and left insula than unmed-SZ and HC (p < 0.05, family-wise error corrected). Additionally, GMV loss correlated with psychiatric symptom relief in all SZ. However, medicated status did not influence ALFF values: all SZ showed increased ALFF in the anterior cerebrum and decreased ALFF in posterior visual cortices compared with HC (p < 0.05, family-wise error corrected). Age-related GMV effects were seen in all regions, which showed group-level differences except fusiform gyrus. No significant correlation was found between ALFF values and psychiatric symptoms.ConclusionGMV loss appeared to be pronounced to longer-term antipsychotics, whereby imbalanced alterations in regional low-frequency fluctuations persisted unaffected by antipsychotic treatment. Our findings may help to understand the disease course of SZ and potentially identify a reliable neuroimaging feature for diagnosis.
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Affiliation(s)
- Yifan Chen
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fay Y. Womer
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Ruiqi Feng
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Xizhe Zhang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yanbo Zhang
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Jia Duan
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Miao Chang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Zhiyang Yin
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xiaowei Jiang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Shengnan Wei
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yange Wei
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- *Correspondence: Yanqing Tang,
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Fei Wang,
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46
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Wu Y, Ren P, Chen R, Xu H, Xu J, Zeng L, Wu D, Jiang W, Tang N, Liu X. Detection of functional and structural brain alterations in female schizophrenia using elastic net logistic regression. Brain Imaging Behav 2022; 16:281-290. [PMID: 34313906 PMCID: PMC8825615 DOI: 10.1007/s11682-021-00501-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/05/2021] [Indexed: 12/19/2022]
Abstract
Neuroimaging technique is a powerful tool to characterize the abnormality of brain networks in schizophrenia. However, the neurophysiological substrate of schizophrenia is still unclear. Here we investigated the patterns of brain functional and structural changes in female patients with schizophrenia using elastic net logistic regression analysis of resting-state functional magnetic resonance imaging data. Data from 52 participants (25 female schizophrenia patients and 27 healthy controls) were obtained. Using an elastic net penalty, the brain regions most relevant to schizophrenia pathology were defined in the models using the amplitude of low-frequency fluctuations (ALFF) and gray matter, respectively. The receiver operating characteristic analysis showed reliable classification accuracy with 85.7% in ALFF analysis, and 77.1% in gray matter analysis. Notably, our results showed eight common regions between the ALFF and gray matter analyses, including the Frontal-Inf-Orb-R, Rolandic-Oper-R, Olfactory-R, Angular-L, Precuneus-L, Precuenus-R, Heschl-L, and Temporal-Pole-Mid-R. In addition, the severity of symptoms was found positively associated with the ALFF within the Rolandic-Oper-R and Frontal-Inf-Orb-R. Our findings indicated that elastic net logistic regression could be a useful tool to identify the characteristics of schizophrenia -related brain deterioration, which provides novel insights into schizophrenia diagnosis and prediction.
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Affiliation(s)
- Ying Wu
- Key Lab of Statistical Modeling and Data Analysis of Yunnan, Yunnan University, Kunming, China
| | - Ping Ren
- Lab of Brain Health Assessment and Research, Shenzhen Mental Health Center, Shenzhen, China
- Department of Geriatric Psychiatry, Shenzhen Kangning Hospital, Shenzhen, China
| | - Rong Chen
- Female Ward of Acute Psychiatric Department, Shenzhen Kangning Hospital, Shenzhen, China
| | - Hong Xu
- Female Ward of Acute Psychiatric Department, Shenzhen Kangning Hospital, Shenzhen, China
| | - Jianxing Xu
- Neuropsychiatry Imaging Center, Shenzhen Mental Health Center, Shenzhen, China
- Department of Radiology, Shenzhen Kangning Hospital, Shenzhen, China
| | - Lin Zeng
- Neuropsychiatry Imaging Center, Shenzhen Mental Health Center, Shenzhen, China
- Department of Radiology, Shenzhen Kangning Hospital, Shenzhen, China
| | - Donghui Wu
- Department of Geriatric Psychiatry, Shenzhen Kangning Hospital, Shenzhen, China
- School of Mental Health, Jining Medical University, Jining, China
| | - Wentao Jiang
- Neuropsychiatry Imaging Center, Shenzhen Mental Health Center, Shenzhen, China
- Department of Radiology, Shenzhen Kangning Hospital, Shenzhen, China
| | - NianSheng Tang
- Key Lab of Statistical Modeling and Data Analysis of Yunnan, Yunnan University, Kunming, China.
| | - Xia Liu
- Neuropsychiatry Imaging Center, Shenzhen Mental Health Center, Shenzhen, China.
- Department of Radiology, Shenzhen Kangning Hospital, Shenzhen, China.
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47
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Frequency-Specific Changes of Amplitude of Low-Frequency Fluctuations in Patients with Acute Basal Ganglia Ischemic Stroke. Neural Plast 2022; 2022:4106131. [PMID: 35111218 PMCID: PMC8803449 DOI: 10.1155/2022/4106131] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/18/2021] [Accepted: 01/10/2022] [Indexed: 11/18/2022] Open
Abstract
Objective. The purpose of this study was to investigate the characteristics of different frequency bands in the spontaneous brain activity among patients with acute basal ganglia ischemic stroke (BGIS). Methods. In the present study, thirty-four patients with acute BGIS and forty-four healthy controls were examined by resting-state functional magnetic resonance imaging (rs-fMRI) from May 2019 to December 2020. Two amplitude methods including amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) calculated in three frequency bands (conventional frequency band: 0.01-0.08 Hz; slow-5 frequency band: 0.01-0.027 Hz; and slow-4 frequency band: 0.027-0.073 Hz) were conducted to evaluate the spontaneous brain activity in patients with acute BGIS and healthy controls (HCs). Gaussian Random Field Theory (GRF, voxel
and cluster
) correction was applied. The correlation analyses were performed between clinical scores and altered metrics values. Results. Compared to HCs, patients with acute BGIS showed decreased ALFF in the right supramarginal gyrus (SMG) in the conventional and slow-4 bands, increased fALFF in the right middle frontal gyrus (MFG) in the conventional and slow-4 bands, and increased fALFF in the bilateral caudate in the slow-5 frequency band. The fALFF value of the right caudate in the slow-5 frequency band was negatively correlated with the clinical scores. Conclusion. In conclusion, this study showed the alterations in ALFF and fALFF in three frequency bands between patients with acute BGIS and HCs. The results reflected that the abnormal LFO amplitude might be related with different frequency bands and promoted our understanding of pathophysiological mechanism in acute BGIS.
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48
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Sbaihat H, Rajkumar R, Ramkiran S, Assi AAN, Felder J, Shah NJ, Veselinović T, Neuner I. Test-retest stability of spontaneous brain activity and functional connectivity in the core resting-state networks assessed with ultrahigh field 7-Tesla resting-state functional magnetic resonance imaging. Hum Brain Mapp 2022; 43:2026-2040. [PMID: 35044722 PMCID: PMC8933332 DOI: 10.1002/hbm.25771] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/26/2021] [Accepted: 12/14/2021] [Indexed: 12/12/2022] Open
Abstract
The growing demand for precise and reliable biomarkers in psychiatry is fueling research interest in the hope that identifying quantifiable indicators will improve diagnoses and treatment planning across a range of mental health conditions. The individual properties of brain networks at rest have been highlighted as a possible source for such biomarkers, with the added advantage that they are relatively straightforward to obtain. However, an important prerequisite for their consideration is their reproducibility. While the reliability of resting‐state (RS) measurements has often been studied at standard field strengths, they have rarely been investigated using ultrahigh‐field (UHF) magnetic resonance imaging (MRI) systems. We investigated the intersession stability of four functional MRI RS parameters—amplitude of low‐frequency fluctuations (ALFF) and fractional ALFF (fALFF; representing the spontaneous brain activity), regional homogeneity (ReHo; measure of local connectivity), and degree centrality (DC; measure of long‐range connectivity)—in three RS networks, previously shown to play an important role in several psychiatric diseases—the default mode network (DMN), the central executive network (CEN), and the salience network (SN). Our investigation at individual subject space revealed a strong stability for ALFF, ReHo, and DC in all three networks, and a moderate level of stability in fALFF. Furthermore, the internetwork connectivity between each network pair was strongly stable between CEN/SN and moderately stable between DMN/SN and DMN/SN. The high degree of reliability and reproducibility in capturing the properties of the three major RS networks by means of UHF‐MRI points to its applicability as a potentially useful tool in the search for disease‐relevant biomarkers.
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Affiliation(s)
- Hasan Sbaihat
- Institute of Neuroscience and Medicine, INM-4, Jülich, Germany.,Department of Medical Imaging, Arab-American University Palestine (AAUP), Jenin, Palestine.,Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany
| | - Ravichandran Rajkumar
- Institute of Neuroscience and Medicine, INM-4, Jülich, Germany.,Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN-Translational Medicine, Aachen, Germany
| | - Shukti Ramkiran
- Institute of Neuroscience and Medicine, INM-4, Jülich, Germany.,Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN-Translational Medicine, Aachen, Germany
| | - Abed Al-Nasser Assi
- Department of Medical Imaging, Arab-American University Palestine (AAUP), Jenin, Palestine
| | - Jörg Felder
- Institute of Neuroscience and Medicine, INM-4, Jülich, Germany.,Department of Medical Imaging, Arab-American University Palestine (AAUP), Jenin, Palestine
| | - Nadim Jon Shah
- Institute of Neuroscience and Medicine, INM-4, Jülich, Germany.,JARA-BRAIN-Translational Medicine, Aachen, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany.,Institute of Neuroscience and Medicine, INM-11, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Tanja Veselinović
- Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany
| | - Irene Neuner
- Institute of Neuroscience and Medicine, INM-4, Jülich, Germany.,Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN-Translational Medicine, Aachen, Germany
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49
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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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50
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Tu Z, Wu F, Jiang X, Kong L, Tang Y. Gender differences in major depressive disorders: A resting state fMRI study. Front Psychiatry 2022; 13:1025531. [PMID: 36440430 PMCID: PMC9685621 DOI: 10.3389/fpsyt.2022.1025531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/17/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Major depressive disorder (MDD) has a high disability rate and brings a large disease burden to patients and the country. Significant sex differences exist in both the epidemiological and clinical features in MDD. The effect of sex on brain function in MDD is not clear now. Regional homogeneity (ReHo) and ALFF are widely used research method in the study of brain function. This research aimed to use ReHo and ALFF to explore gender differences in brain function images in MDD. METHODS Eighty first-episode drug-naive patients (47 women and 30 men) with MDD and 85 age, education matched healthy volunteers (47 women and 31 men) were recruited in our study and participated in resting-state functional magnetic resonance imaging scans. ReHo and ALFF were used to assess brain activity, two-way ANOVA and post hoc analysis was conducted to explore the sex difference in MDD. Correlation analysis was used to explore the relationship between abnormal brain functioning and clinical symptoms. RESULTS We observed sex-specific patterns and diagnostic differences in MDD Patients, further post hoc comparisons indicated that women with MDD showed decreased ALFF value in the right superior occipital gyrus and decreased ReHo value in the left calcarine and left dorsolateral superior frontal gyrus compared with HC females and men with MDD. Men with MDD showed decreased ReHo value in the right median cingulate gyrus compared with HC males and increased ReHo value in the left dorsolateral superior frontal gyrus compared with HC males, we also found that HC males showed higher ReHo value in the right median cingulate gyrus than HC females. CONCLUSIONS Men and women do have sex differences in brain function, the occipital lobe, calcarine, DLPFC, and DCG were the main different brain regions found between male and female in MDD, which may be the biomarker brain regions that can help diagnose and treat MDD in men and women.
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Affiliation(s)
- Zhaoyuan Tu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Feng Wu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Xiaowei Jiang
- Department of Radiology, The First Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Lingtao Kong
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China.,Department of Gerontology, The First Hospital of China Medical University, Shenyang, China
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