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Yi X, Ma M, Wang X, Zhang J, Wu F, Huang H, Xiao Q, Xie A, Liu P, Grecucci A. Joint resting state and structural networks characterize pediatric bipolar patients compared to healthy controls: a multimodal fusion approach. Neuroimage 2025; 312:121225. [PMID: 40252878 DOI: 10.1016/j.neuroimage.2025.121225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2024] [Revised: 03/19/2025] [Accepted: 04/16/2025] [Indexed: 04/21/2025] Open
Abstract
Pediatric bipolar disorder (PBD) is a highly debilitating condition, characterized by alternating episodes of mania and depression, with intervening periods of remission. Limited information is available about the functional and structural abnormalities in PBD, particularly when comparing type I with type II subtypes. Resting-state brain activity and structural grey matter, assessed through MRI, may provide insight into the neurobiological biomarkers of this disorder. In this study, Resting state Regional Homogeneity (ReHo) and grey matter concentration (GMC) data of 58 PBD patients, and 21 healthy controls matched for age, gender, education and IQ, were analyzed in a data fusion unsupervised machine learning approach known as transposed Independent Vector Analysis. Two networks significantly differed between BPD and HC. The first network included fronto- medial regions, such as the medial and superior frontal gyrus, the cingulate, and displayed higher ReHo and GMC values in PBD compared to HC. The second network included temporo-posterior regions, as well as the insula, the caudate and the precuneus and displayed lower ReHo and GMC values in PBD compared to HC. Additionally, two networks differ between type-I vs type-II in PBD: an occipito-cerebellar network with increased ReHo and GMC in type-I compared to type-II, and a fronto-parietal network with decreased ReHo and GMC in type-I compared to type-II. Of note, the first network positively correlated with depression scores. These findings shed new light on the functional and structural abnormalities displayed by pediatric bipolar patients.
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Affiliation(s)
- Xiaoping Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; Clinical Research Center (CRC), Medical Pathology Center (MPC), Cancer Early Detection and Treatment Center (CEDTC) and Translational Medicine Research Center (TMRC), Chongqing University Three Gorges Hospital, Chongqing University, Chongqing 404000, PR China; School of Medicine, Chongqing University, Chongqing 400030, PR China; National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha 410008, Hunan, PR China
| | - Mingzhao Ma
- Department of Radiology, The Second Xiangya Hospital of Central South University, Central South University, Changsha 410008, Hunan, PR China
| | - Xueying Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - Jinfan Zhang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - Feifei Wu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - Haimiao Huang
- Department of Emergency, Hainan Provincial People's Hospital, Haikou 410008, Hainan, PR China
| | - Qian Xiao
- Mental Health Center of Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.
| | - An Xie
- Department of Radiology, The Second Xiangya Hospital of Central South University, Central South University, Changsha 410008, Hunan, PR China; Department of Emergency, Hainan Provincial People's Hospital, Haikou 410008, Hainan, PR China.
| | - Peng Liu
- Department of Radiology, The People's Hospital of Hunan Province (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, PR China; Center for Mind & Brain Sciences, Hunan Normal University, Changsha, Hunan, PR China.
| | - Alessandro Grecucci
- Department of Psychology and Cognitive Science, University of Trento, Italy; Center for Medical Sciences, University of Trento, Italy.
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Fan S, Zhang Y, Qian R, Hu J, Zheng H, Dai W, Ji Y, Wu Y, Xie X, Xu S, Ji GJ, Tian Y, Wang K. Genetic and molecular basis of abnormal BOLD signaling variability in patients with major depressive disorder after electroconvulsive therapy. Transl Psychiatry 2025; 15:117. [PMID: 40175334 PMCID: PMC11965524 DOI: 10.1038/s41398-025-03330-6] [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: 11/05/2024] [Revised: 02/24/2025] [Accepted: 03/18/2025] [Indexed: 04/04/2025] Open
Abstract
Electroconvulsive therapy (ECT) is an effective and rapid neuromodulatory intervention for treatment-resistant major depressive disorders (MDD). However, the precise mechanisms underlying their efficacies remain unclear. Resting-state functional magnetic resonance imaging (fMRI) data were collected from 84 individuals with MDD and healthy controls before and after ECT, and coefficient of variation of the BOLD signal (CVBOLD) analysis was combined with region of interest (ROI) functional connectivity (FC) analysis. To assess the reliability of the antidepressant mechanism of ECT, we analyzed the changes in CVBOLD in a separate cohort consisting of 35 patients with MDD who underwent ECT. Moreover, transcriptomic and neurotransmitter receptor data were used to reveal the genetic and molecular bases of the changes in CVBOLD. Patients with MDD who underwent ECT demonstrated increased CVBOLD in the left angular cortex and left precuneus. Following ECT, an increase in FC between the left precuneus and right lingual lobes was associated with improvements in Hamilton Depression Rating Scale (HAMD) scores. validation analysis consistently demonstrated similar changes in CVBOLD in two independent cohorts of patients with MDD. Moreover, these changes in CVBOLD were closely associated with thyroid hormone synthesis, oxidative phosphorylation, endocytosis, and the insulin signaling pathway, and were significantly correlated with the receptor/transporter density of serotonin and dopamine. These findings suggest that ECT modulates abnormal functions in the left angular cortex and left precuneus, leading to widespread changes in functional connectivity and neuroplasticity, especially in the default mode network, and exerts an antidepressant effect.
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Affiliation(s)
- Siyu Fan
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yulin Zhang
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Rui Qian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jie Hu
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Hao Zheng
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wentao Dai
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yang Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yue Wu
- Department of Psychology and Sleep Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiaohui Xie
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Si Xu
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China.
| | - Gong-Jun Ji
- Department of Psychology and Sleep Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, China.
- The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.
| | - Yanghua Tian
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China.
- The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
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Yu Y, Zhang T, Li Q, Song M, Qi L, Sun J, Ji G, Tian Y, Wang K. Distinction in the function and microstructure of white matter between major depressive disorder and generalized anxiety disorder. J Affect Disord 2025; 374:55-62. [PMID: 39793621 DOI: 10.1016/j.jad.2025.01.018] [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: 07/17/2024] [Revised: 12/18/2024] [Accepted: 01/07/2025] [Indexed: 01/13/2025]
Abstract
BACKGROUND Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are two of the leading causes of impairment to human mental health. These two psychiatric disorders overlap in many symptoms and neurobiological features thus difficult to distinguish in some cases. METHODS We enrolled 102 participants, comprising 40 patients with MDD, 32 patients with GAD and 30 matched healthy controls (HCs), to undergo multimodal magnetic resonance imaging (MRI) scans. We identified 18 major white matter (WM) tracts with automated fiber quantification (AFQ) method, to evaluated microstructure with fractional anisotropy (FA) and function with amplitude of low-frequency fluctuation (ALFF). An analysis of variance (ANOVA) was employed to identify differences among groups. We further explored the correlations of FA and ALFF features with clinical symptoms. RESULTS We identified the white matter microstructure and function of 89 participants. ANOVA and post-hoc analysis revealed that GAD group exhibited significantly higher FA of right anterior thalamic radiation (ATR) than in MDD and HC groups. Additionally, MDD group exhibited significantly decreased ALFF in forceps major (FMA), forceps minor (FMI), bilateral corticospinal tracts (CST) and left inferior fronto-occipital fasciculus (IFOF) compared to both GAD and HC group. ALFF of right CST was significantly negatively correlated to HAMA and a moderate effect size and marginal significance was found between FA of the right ATR and HAMA in GAD group. LIMITATIONS This study used cross-sectional data and sample size was small. CONCLUSION Tracking microstructure and function of WM with AFQ method has the potential to distinguish different psychiatric diseases.
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Affiliation(s)
- Yue Yu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Ting Zhang
- Department of Psychology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Qianqian Li
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei 230601, China
| | - Mengyu Song
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Li Qi
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Jinmei Sun
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Gongjun Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei 230601, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China.
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
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4
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Ji GJ, Fox MD, Morton-Dutton M, Wang Y, Sun J, Hu P, Chen X, Jiang Y, Zhu C, Tian Y, Zhang Z, Akkad H, Nordberg J, Joutsa J, Torres Diaz CV, Groppa S, Gonzalez-Escamilla G, Toledo MD, Dalic LJ, Archer JS, Selway R, Stavropoulos I, Valentin A, Yang J, Isbaine F, Gross RE, Park S, Gregg NM, Cukiert A, Middlebrooks EH, Dosenbach NUF, Turner J, Warren AEL, Chua MMJ, Cohen AL, Larivière S, Neudorfer C, Horn A, Sarkis RA, Bubrick EJ, Fisher RS, Rolston JD, Wang K, Schaper FLWVJ. A generalized epilepsy network derived from brain abnormalities and deep brain stimulation. Nat Commun 2025; 16:2783. [PMID: 40128186 PMCID: PMC11933423 DOI: 10.1038/s41467-025-57392-7] [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: 12/23/2023] [Accepted: 02/14/2025] [Indexed: 03/26/2025] Open
Abstract
Idiopathic generalized epilepsy (IGE) is a brain network disease, but the location of this network and its relevance for treatment remain unclear. We combine the locations of brain abnormalities in IGE (131 coordinates from 21 studies) with the human connectome to identify an IGE network. We validate this network by showing alignment with structural brain abnormalities previously identified in IGE and brain areas activated by generalized epileptiform discharges in simultaneous electroencephalogram-functional magnetic resonance imaging. The topography of the IGE network aligns with brain networks involved in motor control and loss of consciousness consistent with generalized seizure semiology. To investigate therapeutic relevance, we analyze data from 21 patients with IGE treated with deep brain stimulation (DBS) for generalized seizures. Seizure frequency reduced a median 90% after DBS and stimulation sites intersect an IGE network peak in the centromedian nucleus of the thalamus. Together, this study helps unify prior findings in IGE and identify a brain network target that can be tested in clinical trials of brain stimulation to control generalized seizures.
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Affiliation(s)
- Gong-Jun Ji
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, 230032, China
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230032, China
- Anhui Institute of Translational Medicine, Hefei, 230032, China
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Mae Morton-Dutton
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Yingru Wang
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230032, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
| | - Xingui Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
| | - Yubao Jiang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
| | - Chunyan Zhu
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230032, China
| | - Yanghua Tian
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230032, China
| | - Zhiqiang Zhang
- Department of Diagnostic Radiology, Jinling Hospital, the First School of Clinical Medicine, Southern Medical University, Nanjing, 210002, China
| | - Haya Akkad
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- Queen Square Institute of Cognitive Neuroscience, University College London, London, UK
| | - Janne Nordberg
- Neurocenter, Department of Clinical Neurophysiology, Turku University Hospital, Turku, Finland
- Turku Brain and Mind Center, Clinical Neurosciences, University of Turku, Turku, Finland
| | - Juho Joutsa
- Neurocenter, Department of Clinical Neurophysiology, Turku University Hospital, Turku, Finland
- Turku Brain and Mind Center, Clinical Neurosciences, University of Turku, Turku, Finland
| | - Cristina V Torres Diaz
- Department of Neurourgery, Hospital Universitario La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Rhine Main Neuroscience Network (rmn2), Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Rhine Main Neuroscience Network (rmn2), Mainz, Germany
| | - Maria de Toledo
- Department of Neurology, Hospital Universitario La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
| | - Linda J Dalic
- Department of Medicine (Austin Health), The University of Melbourne, Victoria, Australia
| | - John S Archer
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, USA
| | - Richard Selway
- Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, UK
| | - Ioannis Stavropoulos
- Department of Basic and Clinical Neuroscience, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
- Department of Clinical Neurophysiology, King's College Hospital NHS Foundation Trust, London, UK
| | - Antonio Valentin
- Department of Basic and Clinical Neuroscience, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
- Department of Clinical Neurophysiology, King's College Hospital NHS Foundation Trust, London, UK
- Department of Clinical Neurophysiology, Alder Hey Children's Hospital Trust, Liverpool, UK
| | - Jimmy Yang
- Department of Neurological Surgery, The Ohio State University College of Medicine, Columbus, OH, USA
- Department of Neurosurgery, Emory University, 1365 Clifton Road NE, Suite B6200, Atlanta, GA, 30322, USA
| | - Faical Isbaine
- Departments of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Robert E Gross
- Department of Neurosurgery, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Sihyeong Park
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Nico U F Dosenbach
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
| | - Joseph Turner
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Aaron E L Warren
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Melissa M J Chua
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Alexander L Cohen
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, USA
| | - Sara Larivière
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Clemens Neudorfer
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Andreas Horn
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Rani A Sarkis
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Ellen J Bubrick
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Robert S Fisher
- Department of Neurology and Neurological Sciences and Neurosurgery by courtesy, Stanford University School of Medicine, Palo Alto, California, USA
| | - John D Rolston
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, 230032, China.
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China.
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230032, China.
- Anhui Institute of Translational Medicine, Hefei, 230032, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China.
| | - Frederic L W V J Schaper
- Center for Brain Circuit Therapeutics, Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
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Tang J, Xing W, Wang D, Qin Y, Li J, Zhang Y, Yang F, Zhou G, Jiang H, Liao W. White matter functional and structural alterations of spinocerebellar ataxia type 3: A longitudinal MRI study. Neuroscience 2025; 567:77-85. [PMID: 39746644 DOI: 10.1016/j.neuroscience.2024.12.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Revised: 12/23/2024] [Accepted: 12/28/2024] [Indexed: 01/04/2025]
Abstract
Widespread white matter (WM) microstructural abnormalities have been reported in patients with spinocerebellar ataxia type 3 (SCA3) using diffusion tensor imaging (DTI), whereas the ability of DTI to detect WM degeneration over short-term period remains insufficiently explored. Additionally, WM dysfunction remains entirely unknown in this disease. This study aims to investigate WM structural and functional alterations in SCA3, and provide promising progression biomarkers for short-term clinical trials. DTI and resting-state functional magnetic resonance imaging data of 52 SCA3 patients and 56 healthy controls (HCs) were collected at baseline. After a mean follow-up of 1 year, MRI scans were performed on a subset of 28 SCA3 patients. Compared with HCs, widespread WM structural and functional abnormalities were observed in patients with SCA3. Between-group differences of both structural and functional MR metrics showed remarkable similarities, with large differences located in pons and corticospinal tracts, involving cerebellar WM, cerebellar and cerebral peduncles, medial lemniscus and bilateral posterior limb of internal capsule (PLIC). The longitudinal analysis further showed decreased ALFF in the right PLIC and increased mean diffusivity in the left inferior cerebellar peduncle and right medial lemniscus over time in SCA3 patients. These findings emphasized that pons and the CST were the most vulnerable WM areas in SCA3, and have the potential to become therapeutic targets of SCA3 for upcoming interventional trials. In addition, both DT metrics and WM ALFF were efficient progression biomarkers for SCA3 even in short-term period.
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Affiliation(s)
- Jingyi Tang
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Wu Xing
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Dongcui Wang
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Yan Qin
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Junfeng Li
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, 046000, China
| | - Youming Zhang
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Fangxue Yang
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Gaofeng Zhou
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Hong Jiang
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital of Central South University, Changsha, 410008, China; FuRong Laboratory, Changsha, 410078, Hunan, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Neurology, The Third Xiangya Hospital of Central South University, Changsha, Hunan, 410008, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, 410008, China; Brain Research Center, Central South University, Changsha, Hunan, 410008, China.
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital of Central South University, Changsha, 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital of Central South University, Changsha, 410008, China; National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital of Central South University, Changsha, 410008, China; Hunan Engineering Research Center for Intelligent Medical Imaging, Changsha, 410078, Hunan, China; FuRong Laboratory, Changsha, 410078, Hunan, China.
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6
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Yang R, Chen J, Yue S, Yu Y, Fan J, Luo Y, He H, Duan M, Jiang S, Yao D, Luo C. Disturbed hierarchy and mediation in reward-related circuits in depression. Neuroimage Clin 2025; 45:103739. [PMID: 39864168 PMCID: PMC11803893 DOI: 10.1016/j.nicl.2025.103739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2024] [Revised: 01/12/2025] [Accepted: 01/21/2025] [Indexed: 01/28/2025]
Abstract
BACKGROUNDS/OBJECTIVE Deep brain stimulation (DBS) has proved the viability of alleviating depression symptoms by stimulating deep reward-related nuclei. This study aims to investigate the abnormal connectivity profiles among superficial, intermediate, and deep brain regions within the reward circuit in major depressive disorder (MDD) and therefore provides references for identifying potential superficial cortical targets for non-invasive neuromodulation. METHODS Resting-state functional magnetic resonance imaging data were collected from a cohort of depression patients (N = 52) and demographically matched healthy controls (N = 60). Utilizing existing DBS targets as seeds, we conducted step-wise functional connectivity (sFC) analyses to delineate hierarchical pathways linking to cerebral cortices. Subsequently, the mediation effects of cortical regions on the interaction within reward-related circuits were further explored by constructing mediation models. RESULTS In both cohorts, sFC analysis revealed two reward-related pathways from the deepest DBS targets to intermediate regions including the thalamus, insula, and anterior cingulate cortex (ACC), then to the superficial cortical cortex including medial frontal cortex, posterior default mode network (pDMN), and right dorsolateral prefrontal cortex (DLPFC). Patients exhibited reduced sFC in bilateral thalamus and medial frontal cortex in short and long steps respectively compared to healthy controls. We also discovered the disappearance of the mediation effects of superficial cortical regions on the interaction between DBS targets and intermediate regions in reward-related pathways in patients with MDD. CONCLUSION Our findings support abnormal hierarchical connectivity and mediation effects in reward-related brain regions at different depth levels in MDD, which might elucidate the underlying pathophysiological mechanisms and inspire novel targets for non-invasive interventions.
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Affiliation(s)
- Ruikun Yang
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Junxia Chen
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Suping Yue
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Yue Yu
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Jiamin Fan
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province Center for Information in Medicine University of Electronic Science and Technology of China Chengdu PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province Center for Information in Medicine University of Electronic Science and Technology of China Chengdu PR China; Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu PR China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu PR China; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province Center for Information in Medicine University of Electronic Science and Technology of China Chengdu PR China; Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu PR China.
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Hadi Z, Mahmud M, Calzolari E, Chepisheva M, Zimmerman KA, Tahtis V, Smith RM, Rust HM, Sharp DJ, Seemungal BM. Balance recovery and its link to vestibular agnosia in traumatic brain injury: a longitudinal behavioural and neuro-imaging study. J Neurol 2025; 272:132. [PMID: 39812836 PMCID: PMC11735511 DOI: 10.1007/s00415-024-12876-2] [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] [Received: 11/22/2024] [Revised: 12/16/2024] [Accepted: 12/18/2024] [Indexed: 01/16/2025]
Abstract
BACKGROUND Vestibular dysfunction causing imbalance affects c. 80% of acute hospitalized traumatic brain injury (TBI) cases. Poor balance recovery is linked to worse return-to-work rates and reduced longevity. We previously showed that white matter network disruption, particularly of right inferior longitudinal fasciculus, mediates the overlap between imbalance and impaired vestibular perception of self-motion (i.e., vestibular agnosia) in acute hospitalized TBI. However, there are no prior reports tracking the acute-longitudinal trajectory of objectively measured vestibular function for hospitalized TBI patients. We hypothesized that recovery of vestibular agnosia and imbalance is linked and mediated by overlapping brain networks. METHODS We screened 918 acute major trauma in-patients, assessed 146, recruited 39 acutely, and retested 34 at 6 months. Inclusion criteria were 18-65-year-old adults hospitalized for TBI with laboratory-confirmed preserved peripheral vestibular function. Benign paroxysmal positional vertigo and migraine were treated prior to testing. Vestibular agnosia was quantified by participants' ability to perceive whole-body yaw plane rotations via an automated rotating-chair algorithm. Subjective symptoms of imbalance (via questionnaires) and objective imbalance (via posturography) were also assessed. RESULTS Acute vestibular agnosia predicted poor balance recovery at 6 months. Recovery of vestibular agnosia and linked imbalance was mediated by bihemispheric fronto-posterior cortical circuits. Recovery of subjective symptoms of imbalance and objective imbalance were not correlated. CONCLUSION Vestibular agnosia mediates balance recovery post-TBI. The link between subjective dizziness and brain injury recovery, although important, is unclear. Therapeutic trials of vestibular recovery post-TBI should target enhancing bi-hemispheric connectivity and linked objective clinical measures (e.g., posturography).
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Affiliation(s)
- Zaeem Hadi
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK.
| | - Mohammad Mahmud
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK
| | - Elena Calzolari
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK
| | - Mariya Chepisheva
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK
| | - Karl A Zimmerman
- Department of Brain Sciences, Hammersmith Hospital, Imperial College London, London, W12 0NN, UK
- Care Research & Technology Centre, UK Dementia Research Institute, Imperial College London, London, UK
| | - Vassilios Tahtis
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK
- King's College Hospital NHS Foundation Trust, London, SE5 9RS, UK
| | - Rebecca M Smith
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK
| | - Heiko M Rust
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - David J Sharp
- Department of Brain Sciences, Hammersmith Hospital, Imperial College London, London, W12 0NN, UK
- Care Research & Technology Centre, UK Dementia Research Institute, Imperial College London, London, UK
| | - Barry M Seemungal
- Centre for Vestibular Neurology (CVeN), Department of Brain Sciences, Charing Cross Hospital, Imperial College London, London, W6 8RF, UK.
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8
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Huang T, Hua Q, Zhao X, Tian W, Cao H, Xu W, Sun J, Zhang L, Wang K, Ji GJ. Abnormal functional lateralization and cooperation in bipolar disorder are associated with neurotransmitter and cellular profiles. J Affect Disord 2025; 369:970-977. [PMID: 39447972 DOI: 10.1016/j.jad.2024.10.108] [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: 06/14/2024] [Revised: 10/18/2024] [Accepted: 10/21/2024] [Indexed: 10/26/2024]
Abstract
BACKGROUND Hemispheric lateralization and cooperation are essential for efficient brain function, and aberrations in both have been found in psychiatric disorders such as schizophrenia. This study investigated alterations in hemispheric lateralization and cooperation among patients with bipolar disorder (BD) and associations with neurotransmitter and cell-type density distributions to identify potential molecular and cellular pathomechanisms. METHODS Sixty-seven BD patients and 127 healthy controls (HCs) were examined by resting-state functional MRI (rs-fMRI). Whole-brain maps of the autonomy index (AI) and connectivity between functionally homotopic voxels (CFH) were constructed to reveal BD-specific changes in brain functional lateralization and interhemispheric cooperation, respectively. Spatial associations of regional AI and CFH abnormalities with neurotransmitter and cell-type density distributions were examined by correlation analyses. RESULTS Bipolar disorder patients exhibited higher AI values in left superior parietal gyrus, cerebellar right Crus I, and cerebellar right Crus II, and these regional abnormalities were associated with the relative densities (proportions) of oligodendrocyte precursor cells and microglia. Patients also exhibited lower CFH values in right inferior parietal gyrus, bilateral middle occipital gyrus, left postcentral gyrus, and bilateral cerebellar crus II, and these regional abnormalities were associated with the densities of serotonin 1A and dopamine D2 receptors, oligodendrocyte precursor cells, astrocytes, and neurons. CONCLUSIONS These findings indicate that abnormal functional lateralization and cooperation in BD with potential molecular and cellular basis.
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Affiliation(s)
- Tongqing Huang
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Qiang Hua
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Xiya Zhao
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Weichao Tian
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Hai Cao
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Wenqiang Xu
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Li Zhang
- Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, Hefei, Anhui Province, China.
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
| | - Gong-Jun Ji
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
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9
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Li Z, Liu J, Zheng J, Li L, Fu Y, Yang Z. White Matter-Gray Matter Correlation Analysis Based on White Matter Functional Gradient. Brain Sci 2024; 15:26. [PMID: 39851394 PMCID: PMC11763486 DOI: 10.3390/brainsci15010026] [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: 11/12/2024] [Revised: 12/18/2024] [Accepted: 12/27/2024] [Indexed: 01/26/2025] Open
Abstract
BACKGROUND The spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals of the brain's gray matter (GM) have been interpreted as representations of neural activity variations. In previous research, white matter (WM) signals, often considered noise, have also been demonstrated to reflect characteristics of functional activity and interactions among different brain regions. Recently, functional gradients have gained significant attention due to their success in characterizing the functional organization of the whole brain. However, previous studies on brain functional gradients have predominantly focused on GM, neglecting valuable functional information within WM. METHODS In this paper, we have elucidated the symmetrical nature of the functional hierarchy in the left and right brain hemispheres in healthy individuals, utilizing the principal functional gradient of the whole-brain WM while also accounting for gender differences. RESULTS Interestingly, both males and females exhibit a similar degree of asymmetry in their brain regions, albeit with distinct regional variations. Additionally, we have thoroughly examined and analyzed the distribution of functional gradient values in the spatial structure of the corpus callosum (CC) independently, revealing that a simple one-to-one correspondence between structure and function is absent. This phenomenon may be associated with the intricacy of their internal structural connectivity. CONCLUSIONS We suggest that the functional gradients within the WM regions offer a fresh perspective for investigating the structural and functional characteristics of WM and may provide insights into the regulation of neural activity between GM and WM.
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Affiliation(s)
- Zhengjie Li
- College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China; (Z.L.); (J.L.); (J.Z.); (Y.F.)
| | - Jiajun Liu
- College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China; (Z.L.); (J.L.); (J.Z.); (Y.F.)
| | - Jianhui Zheng
- College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China; (Z.L.); (J.L.); (J.Z.); (Y.F.)
| | - Luying Li
- Department of Radiology, Huaxi MR Research Center, West China Hospital, Sichuan University, Chengdu 610017, China;
| | - Ying Fu
- College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China; (Z.L.); (J.L.); (J.Z.); (Y.F.)
| | - Zhipeng Yang
- College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China; (Z.L.); (J.L.); (J.Z.); (Y.F.)
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10
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Ji GJ, Cui Z, D'Arcy RCN, Liao W, Biswal BB, Zhang Q, Luo C, Zang YF, Ding Z, Zuo XN, Gore JC, Wang K. Imaging brain white matter function using resting-state functional MRI. Sci Bull (Beijing) 2024:S2095-9273(24)00794-1. [PMID: 39532560 DOI: 10.1016/j.scib.2024.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2024]
Affiliation(s)
- Gong-Jun Ji
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei 230032, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Ryan C N D'Arcy
- BrainNET, Health and Technology District, Simon Fraser University, Surrey BC V3V 0E8, Canada
| | - Wei Liao
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Bharat B Biswal
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark NJ 07102, USA
| | - Qing Zhang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Cheng Luo
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yu-Feng Zang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310000, China
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Nashville TN 37232-2310, USA
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Nashville TN 37232-2310, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville TN 37212, USA.
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei 230032, China; Anhui Institute of Translational Medicine, Hefei 230032, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China.
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11
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Li J, Jin S, Li Z, Zeng X, Yang Y, Luo Z, Xu X, Cui Z, Liu Y, Wang J. Morphological Brain Networks of White Matter: Mapping, Evaluation, Characterization, and Application. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2400061. [PMID: 39005232 PMCID: PMC11425219 DOI: 10.1002/advs.202400061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 06/27/2024] [Indexed: 07/16/2024]
Abstract
Although white matter (WM) accounts for nearly half of adult brain, its wiring diagram is largely unknown. Here, an approach is developed to construct WM networks by estimating interregional morphological similarity based on structural magnetic resonance imaging. It is found that morphological WM networks showed nontrivial topology, presented good-to-excellent test-retest reliability, accounted for phenotypic interindividual differences in cognition, and are under genetic control. Through integration with multimodal and multiscale data, it is further showed that morphological WM networks are able to predict the patterns of hamodynamic coherence, metabolic synchronization, gene co-expression, and chemoarchitectonic covariance, and associated with structural connectivity. Moreover, the prediction followed WM functional connectomic hierarchy for the hamodynamic coherence, is related to genes enriched in the forebrain neuron development and differentiation for the gene co-expression, and is associated with serotonergic system-related receptors and transporters for the chemoarchitectonic covariance. Finally, applying this approach to multiple sclerosis and neuromyelitis optica spectrum disorders, it is found that both diseases exhibited morphological dysconnectivity, which are correlated with clinical variables of patients and are able to diagnose and differentiate the diseases. Altogether, these findings indicate that morphological WM networks provide a reliable and biologically meaningful means to explore WM architecture in health and disease.
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Affiliation(s)
- Junle Li
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhou510631China
| | - Suhui Jin
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhou510631China
| | - Zhen Li
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhou510631China
| | - Xiangli Zeng
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhou510631China
| | - Yuping Yang
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhou510631China
| | - Zhenzhen Luo
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhou510631China
| | - Xiaoyu Xu
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijing100875China
- Chinese Institute for Brain ResearchBeijing102206China
| | - Zaixu Cui
- Chinese Institute for Brain ResearchBeijing102206China
| | - Yaou Liu
- Department of RadiologyBeijing Tiantan HospitalBeijing100070China
| | - Jinhui Wang
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhou510631China
- Key Laboratory of BrainCognition and Education SciencesMinistry of EducationGuangzhou510631China
- Center for Studies of Psychological ApplicationSouth China Normal UniversityGuangzhou510631China
- Guangdong Key Laboratory of Mental Health and Cognitive ScienceSouth China Normal UniversityGuangzhou510631China
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12
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Yang X, Shang T, Ding Z, Qin X, Qi J, Han J, Lv D, Li T, Ma J, Zhan C, Xiao J, Sun Z, Wang N, Yu Z, Li C, Meng X, Chen Y, Li P. Abnormal structure and function of white matter in obsessive-compulsive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2024; 134:111061. [PMID: 38901756 DOI: 10.1016/j.pnpbp.2024.111061] [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: 12/04/2023] [Revised: 05/19/2024] [Accepted: 06/17/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND Abnormal structure and function of gray matter (GM) have been discovered in the cortico-striatal-thalamic-cortical (CSTC) circuit in obsessive-compulsive disorder (OCD). The GM structure and function may be influenced by the structure and function of the white matter (WM). Therefore, it is crucial to explore the characteristics of WM in OCD. METHODS Diffusion tensor imaging and resting-state functional magnetic resonance imaging data of 52 patients with OCD and 39 healthy controls (HCs) were collected. The tract-based spatial statistics, amplitude of low-frequency fluctuations (ALFF), and structural-functional coupling approaches were utilized to explore the WM structure and function. Furthermore, the relationship between the abnormal WM structure and function and clinical symptoms of OCD was investigated using Pearson's correlation. Support vector machine was performed to evaluate whether patients with OCD could be identified with the changed WM structure and function. RESULTS Compared to HCs, the lower fractional anisotropy (FA) values of four clusters including the superior corona radiata, anterior corona radiata, right superior longitudinal fasciculus, corpus callosum, left posterior corona radiata, fornix, and the right anterior limb of internal capsule, reduced ALFF/FA ratio in the left anterior thalamic radiation (ATR), and the decreased functional connectivity between the left ATR and the left dorsal lateral prefrontal cortex within CSTC circuit at rest were observed in OCD. The decreased ALFF/FA ratio in the left ATR negatively correlated with Yale-Brown Obsessive-Compulsive Scale obsessive thinking scores and Hamilton Anxiety Rating Scale scores in OCD. Furthermore, the features that combined the abnormal WM structure and function performed best in distinguishing OCD from HCs with the appropriate accuracy (0.80), sensitivity (0.82), as well as specificity (0.80). CONCLUSION Current research discovered changed WM structure and function in OCD. Furthermore, abnormal WM structural-functional coupling may lead to aberrant GM connectivity within the CSTC circuit at rest in OCD. TRIAL REGISTRATION Study on the mechanism of brain network in obsessive-compulsive disorder with multi-model magnetic resonance imaging (ChiCTR-COC-17013301).
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Affiliation(s)
- Xu Yang
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Tinghuizi Shang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Zhipeng Ding
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Xiaoqing Qin
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Jiale Qi
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Jiaqi Han
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Dan Lv
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Tong Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Jidong Ma
- Department of Psychiatry, Baiyupao Psychiatric Hospital of Harbin, Harbin, Heilongjiang 150050, China
| | - Chuang Zhan
- Department of Psychiatry, Baiyupao Psychiatric Hospital of Harbin, Harbin, Heilongjiang 150050, China
| | - Jian Xiao
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Zhenghai Sun
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Na Wang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Zengyan Yu
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Chengchong Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Xiangyu Meng
- Department of Psychiatry, Baiyupao Psychiatric Hospital of Harbin, Harbin, Heilongjiang 150050, China
| | - Yunhui Chen
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China.
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China.
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Cao H, Sun J, Hua Q, Huang T, Wei Y, Zhan Y, Yao X, Zhang T, Yang Y, Xu W, Bai T, Tian Y, Zhang L, Wang K, Ji GJ. Decreased inter-hemispheric cooperation in major depressive disorder and its association with neurotransmitter profiles. J Affect Disord 2024; 359:109-116. [PMID: 38768823 DOI: 10.1016/j.jad.2024.05.072] [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: 12/28/2023] [Revised: 05/09/2024] [Accepted: 05/17/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Inter-hemispheric cooperation is a prominent feature of the human brain, and previous neuroimaging studies have revealed aberrant inter-hemispheric cooperation patterns in patients with major depressive disorder (MDD). Typically, inter-hemispheric cooperation is examined by calculating the functional connectivity (FC) between each voxel in one hemisphere and its anatomical (structurally homotopic) counterpart in the opposite hemisphere. However, bilateral hemispheres are actually asymmetric in anatomy. METHODS In the present study, we utilized connectivity between functionally homotopic voxels (CFH) to investigate abnormal inter-hemispheric cooperation in 96 MDD patients compared to 173 age- and sex-matched healthy controls (HCs). In addition, we analyzed the spatial correlations between abnormal CFH and the density maps of 13 neurotransmitter receptors and transporters. RESULTS The CFH values in bilateral orbital frontal gyri and bilateral postcentral gyri were abnormally decreased in patients with MDD. Furthermore, these CFH abnormalities were correlated with clinical symptoms. In addition, the abnormal CFH pattern in MDD patients was spatially correlated with the distribution pattern of 5-HT1AR. LIMITATIONS drug effect; the cross-sectional research design precludes causal inferences; the neurotransmitter atlases selected were constructed from healthy individuals rather than MDD patients. CONCLUSION These findings characterized the abnormal inter-hemispheric cooperation in MDD using a novel method and the underlying neurotransmitter mechanism, which promotes our understanding of the pathophysiology of depression.
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Affiliation(s)
- Hai Cao
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Qiang Hua
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Tongqing Huang
- 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yuqing Wei
- 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yuqian Zhan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Xiaoqing Yao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Ting Zhang
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Department of Psychiatry, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yinian Yang
- 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Wenqiang Xu
- 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Tongjian Bai
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yanghua Tian
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lei Zhang
- 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China.
| | - Kai Wang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
| | - Gong-Jun Ji
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, China; Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
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14
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Owens-Walton C, Nir TM, Al-Bachari S, Ambrogi S, Anderson TJ, Aventurato ÍK, Cendes F, Chen YL, Ciullo V, Cook P, Dalrymple-Alford JC, Dirkx MF, Druzgal J, Emsley HCA, Guimarães R, Haroon HA, Helmich RC, Hu MT, Johansson ME, Kim HB, Klein JC, Laansma M, Lawrence KE, Lochner C, Mackay C, McMillan CT, Melzer TR, Nabulsi L, Newman B, Opriessnig P, Parkes LM, Pellicano C, Piras F, Piras F, Pirpamer L, Pitcher TL, Poston KL, Roos A, Silva LS, Schmidt R, Schwingenschuh P, Shahid-Besanti M, Spalletta G, Stein DJ, Thomopoulos SI, Tosun D, Tsai CC, van den Heuvel OA, van Heese E, Vecchio D, Villalón-Reina JE, Vriend C, Wang JJ, Wu YR, Yasuda CL, Thompson PM, Jahanshad N, van der Werf Y. A worldwide study of white matter microstructural alterations in people living with Parkinson's disease. NPJ Parkinsons Dis 2024; 10:151. [PMID: 39128907 PMCID: PMC11317500 DOI: 10.1038/s41531-024-00758-3] [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: 01/17/2024] [Accepted: 07/22/2024] [Indexed: 08/13/2024] Open
Abstract
The progression of Parkinson's disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences. Diffusion-weighted MRI data from 1654 participants diagnosed with PD (age: 20-89 years; 33% female) and 885 controls (age: 19-84 years; 47% female) were analyzed using the ENIGMA-DTI protocol to evaluate white matter microstructure. Skeletonized maps of fractional anisotropy (FA) and mean diffusivity (MD) were compared across Hoehn and Yahr (HY) disease groups and controls to reveal the profile of white matter alterations at different stages. We found an enhanced, more widespread pattern of microstructural alterations with each stage of PD, with eventually lower FA and higher MD in almost all regions of interest: Cohen's d effect sizes reached d = -1.01 for FA differences in the fornix at PD HY Stage 4/5. The early PD signature in HY stage 1 included higher FA and lower MD across the entire white matter skeleton, in a direction opposite to that typical of other neurodegenerative diseases. FA and MD were associated with motor and non-motor clinical dysfunction. While overridden by degenerative changes in the later stages of PD, early PD is associated with paradoxically higher FA and lower MD in PD, consistent with early compensatory changes associated with the disorder.
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Grants
- R01 AG058854 NIA NIH HHS
- P41 EB015922 NIBIB NIH HHS
- R01NS107513 U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)
- R01 MH117601 NIMH NIH HHS
- R01 NS107513 NINDS NIH HHS
- U19 AG062418 NIA NIH HHS
- F32 MH122057 NIMH NIH HHS
- R01 AG059874 NIA NIH HHS
- U.S. Alzheimer’s Association (AARG-23-1149996)
- Health Research Council of New Zealand (20/538; 21/165)
- São Paulo Research Foundation FAPESP-BRAINN Grants# 2013-07559-3 / FAPESP #2022-1178-4
- São Paulo Research Foundation FAPESP-BRAINN Grant # 2013–07559-3.
- Health Research Council of New Zealand (20/538); Marsden Fund New Zealand (UOC2105); Neurological Foundation of New Zealand (2232 PRG); Research and Education Trust Pacific Radiology (MRIJDA).
- Grant from ParkinsonNL (P2023-14); Honoraria from Movement Disorders Society Quebec.
- NINDS R01NS107513
- Engineering and Physical Sciences Research Council (EPSRC) UK
- Parkinson's UK, Cure Parkinsons Trust, Oxford Biomedical Research Centre, GSK-Oxford IMCM.
- JK is supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), and the NIHR Oxford Health Clinical Research Facility. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
- NIMH 32MH122057
- U19 AG062418
- Health Research Council of New Zealand (20/538); Neurological Foundation of New Zealand (2232 PRG); Research and Education Trust Pacific Radiology (MRIJDA).
- EPSRC UK, MRC UK, GE medical systems, Academy of Medical Sciences UK
- Italian Ministry of Health, grant number RF-2019-12370182
- Health Research Council of New Zealand (21/165)
- Personal fees from Bial, AbbVie and Boston Scientific.
- NIH/NIA
- São Paulo Research Foundation FAPESP-BRAINN Grant # 2013–07559-3; CNPQ (#315953/2021-7) National Council for Scientific and Technological Development
- U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)
- R01AG059874, R01MH117601, R01NS107513, R01AG058854, P41EB015922
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Affiliation(s)
- Conor Owens-Walton
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Talia M Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Tim J Anderson
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Neurology Department, Te Whatu Ora-Health New Zealand Waitaha Canterbury, Christchurch, New Zealand
| | - Ítalo Karmann Aventurato
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Fernando Cendes
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Yao-Liang Chen
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung, Taiwan, ROC
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan City, Taiwan, ROC
| | - Valentina Ciullo
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Phil Cook
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John C Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Te Kura Mahi ā- Hirikapo | School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Michiel F Dirkx
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Hedley C A Emsley
- Lancaster Medical School, Lancaster University, Lancaster, UK
- Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Rachel Guimarães
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Hamied A Haroon
- Division of Psychology, Communication & Human Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Rick C Helmich
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Michele T Hu
- Oxford Parkinson's Disease Centre, Nuffield, Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - Martin E Johansson
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Ho Bin Kim
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre, Nuffield, Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - Max Laansma
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Katherine E Lawrence
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Clare Mackay
- Oxford Parkinson's Disease Centre, Nuffield, Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - Corey T McMillan
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tracy R Melzer
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Te Kura Mahi ā- Hirikapo | School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Leila Nabulsi
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ben Newman
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Peter Opriessnig
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Laura M Parkes
- Division of Psychology, Communication & Human Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Clelia Pellicano
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federica Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Lukas Pirpamer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Toni L Pitcher
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Kathleen L Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Annerine Roos
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Lucas Scárdua Silva
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Petra Schwingenschuh
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Marian Shahid-Besanti
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | | | - Dan J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Chih-Chien Tsai
- Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan, ROC
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan, ROC
| | - Odile A van den Heuvel
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam UMC, Department of Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eva van Heese
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Julio E Villalón-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Chris Vriend
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Department of Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging program, Amsterdam, The Netherlands
| | - Jiun-Jie Wang
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung, Taiwan, ROC
- Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan, ROC
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan, ROC
- Department of Chemical Engineering, Ming-Chi University of Technology, New Taipei City, Taiwan, ROC
| | - Yih-Ru Wu
- Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan City, Taiwan, ROC
- Department of Neurology, College of Medicine, Chang Gung University, Taoyuan City, Taiwan, ROC
| | - Clarissa Lin Yasuda
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ysbrand van der Werf
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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15
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Sun J, Xing F, Feng J, Chen X, Lv L, Yao X, Wang M, Zhao Z, Zhou Q, Liu T, Zhan Y, Gong-Jun J, Wang K, Hu P. Differential symptom cluster responses and predictors to repetitive transcranial magnetic stimulation treatment in Parkinson's disease: A retrospective study. Heliyon 2024; 10:e32799. [PMID: 38975093 PMCID: PMC11226850 DOI: 10.1016/j.heliyon.2024.e32799] [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: 11/25/2023] [Revised: 06/08/2024] [Accepted: 06/10/2024] [Indexed: 07/09/2024] Open
Abstract
Background Repetitive transcranial magnetic stimulation (rTMS) is an effective noninvasive neuromodulation technique for Parkinson's disease (PD). However, the efficacy of rTMS varies widely between individuals. This study aimed to investigate the factors related to the response to rTMS in PD patients. Methods We retrospectively analyzed the response of 70 idiopathic PD patients who underwent rTMS for 14 consecutive days targeting the supplementary motor area (SMA) in either an open-label trail (n = 31) or a randomized, double-blind, placebo-controlled trial (RCT) (n = 39). The motor symptoms of PD patients were assessed by the United Parkinson's Disease Rating Scale Part III (UPDRSIII). Based on previous studies, the UPDRSIII were divided into six symptom clusters: axial dysfunction, resting tremor, rigidity, bradykinesia affecting right and left extremities, and postural tremor. Subsequently, the efficacy of rTMS to different motor symptom clusters and clinical predictors were analyzed in these two trails. Results After 14 days of treatment, only the total UPDRSIII scores and rigidity scores improved in both the open-label trial and the RCT. The results of multiple linear regression analysis indicated that baseline rigidity scores (β = 0.37, p = 0.047) and RMT (β = 0.30, P = 0.02) positively predicted the improvement of UPDRSIII. The baseline rigidity score (β = 0.55, P < 0.0001) was identified as an independent factor to predict the improvement of rigidity. Conclusion This study demonstrated significant improvements in total UPDRSIII scores and rigidity after 14-day treatment, with baseline rigidity scores and RMT identified as predictors of treatment response, underscoring the need for individualized therapy.
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Affiliation(s)
- Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Fengbo Xing
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Jingjing Feng
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Xin Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Lingling Lv
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Xiaoqing Yao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Mengqi Wang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Ziye Zhao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Qian Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Tingting Liu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Yuqian Zhan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - J.I. Gong-Jun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- Anhui Institute of Translational Medicine, Hefei, 230000, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- Anhui Institute of Translational Medicine, Hefei, 230000, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- Anhui Institute of Translational Medicine, Hefei, 230000, China
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16
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Lin K, Gao Y, Ji W, Li Y, Wang W, Du M, Liu J, Hong Z, Jiang T, Wang Y. Attentional impairment and altered brain activity in healthcare workers after mild COVID-19. Brain Imaging Behav 2024; 18:566-575. [PMID: 38296922 PMCID: PMC11222278 DOI: 10.1007/s11682-024-00851-4] [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: 01/05/2024] [Indexed: 02/02/2024]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is highly transmissible and pathogenic. Patients with mild cases account for the majority of those infected with coronavirus disease 2019 (COVID-19). Although there is evidence that many patients with COVID-19 have varying degrees of attentional impairment, little is known about how SARS-COV-2 affects attentional function. This study included a high-risk healthcare population divided into groups of healthcare workers (HCWs) with mild COVID-19 (patient group, n = 45) and matched healthy HCWs controls (HC group, n = 42), who completed general neuropsychological background tests and Attention Network Test (ANT), and underwent resting-state functional magnetic resonance imaging (rs-fMRI) using amplitude of low-frequency fluctuation (ALFF) to assess altered brain activity; Selective impairment occurred in orienting and executive control networks, but not in alert network, in the patient group, and widespread cognitive impairment encompassing general attention, memory, and executive dysfunction. Moreover, the patient group had significantly lower ALFF values in the left superior and left middle frontal gyri than the HC group. SARS-COV-2 infection may have led to reduced brain activity in the left superior and left middle frontal gyri, thus impairing attentional orienting and executive control networks, which may explain the development of attentional deficits after COVID-19.
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Affiliation(s)
- Keyi Lin
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Public Health Clinical Center, Hefei, China
| | - Yaotian Gao
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Public Health Clinical Center, Hefei, China
| | - Wei Ji
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Public Health Clinical Center, Hefei, China
- Department of Neurosurgery, Hefei Huaan Brain Hospital, Hefei, China
| | - Yan Li
- Anhui Public Health Clinical Center, Hefei, China
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wei Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mengcheng Du
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jia Liu
- Anhui Public Health Clinical Center, Hefei, China
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhengyu Hong
- Anhui Public Health Clinical Center, Hefei, China
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Tao Jiang
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
- Anhui Public Health Clinical Center, Hefei, China.
- Anhui Provincial Institute of Translational Medicine, Hefei, China.
| | - Yuyang Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
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17
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Zhang F, Li L, Liu B, Shao Y, Tan Y, Niu Q, Zhang H. Decoupling of gray and white matter functional networks in cognitive impairment induced by occupational aluminum exposure. Neurotoxicology 2024; 103:1-8. [PMID: 38777096 DOI: 10.1016/j.neuro.2024.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/21/2024] [Accepted: 05/10/2024] [Indexed: 05/25/2024]
Abstract
Aluminum (Al) is a low-toxic, accumulative substance with neurotoxicity properties that adversely affect human cognitive function. This study aimed to investigate the neurobiological mechanisms underlying cognitive impairment resulting from occupational Al exposure. Resting-state functional magnetic resonance imaging was conducted on 54 individuals with over 10 years of Al exposure. Al levels were measured, and cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Subsequently, the K-means clustering algorithm was employed to identify functional gray matter (GM) and white matter (WM) networks. Two-sample t-tests were conducted between the cognition impairment group and the control group. Al exhibited a negative correlation with MoCA scores. Participants with cognitive impairment demonstrated reduced functional connectivity (FC) between the middle cingulum network (WM1) and anterior cingulum network (WM2), as well as between the executive control network (WM6) and limbic network (WM10). Notably, decreased FCs were observed between the executive control network (GM5) and WM1, WM4, WM6, and WM10. Additionally, the FC of GM5-GM4 and WM1-WM2 negatively correlated with Trail Making Test Part A (TMT-A) scores. Prolonged Al accumulation detrimentally affects cognition, primarily attributable to executive control and limbic network disruptions.
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Affiliation(s)
- Feifei Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China
| | - Lina Li
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China
| | - Bo Liu
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China
| | - Yingbo Shao
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China
| | - Yan Tan
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China
| | - Qiao Niu
- Department of Occupational Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China.
| | - Hui Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China.
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18
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Ke M, Hou Y, Zhang L, Liu G. Brain functional network changes in patients with juvenile myoclonic epilepsy: a study based on graph theory and Granger causality analysis. Front Neurosci 2024; 18:1363255. [PMID: 38774788 PMCID: PMC11106382 DOI: 10.3389/fnins.2024.1363255] [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: 12/30/2023] [Accepted: 04/04/2024] [Indexed: 05/24/2024] Open
Abstract
Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown that the brain networks are disrupted in adolescent patients with juvenile myoclonic epilepsy (JME). However, previous studies have mainly focused on investigating brain connectivity disruptions from the perspective of static functional connections, overlooking the dynamic causal characteristics between brain network connections. In our study involving 37 JME patients and 35 Healthy Controls (HC), we utilized rs-fMRI to construct whole-brain functional connectivity network. By applying graph theory, we delved into the altered topological structures of the brain functional connectivity network in JME patients and identified abnormal regions as key regions of interest (ROIs). A novel aspect of our research was the application of a combined approach using the sliding window technique and Granger causality analysis (GCA). This method allowed us to delve into the dynamic causal relationships between these ROIs and uncover the intricate patterns of dynamic effective connectivity (DEC) that pervade various brain functional networks. Graph theory analysis revealed significant deviations in JME patients, characterized by abnormal increases or decreases in metrics such as nodal betweenness centrality, degree centrality, and efficiency. These findings underscore the presence of widespread disruptions in the topological features of the brain. Further, clustering analysis of the time series data from abnormal brain regions distinguished two distinct states indicative of DEC patterns: a state of strong connectivity at a lower frequency (State 1) and a state of weak connectivity at a higher frequency (State 2). Notably, both states were associated with connectivity abnormalities across different ROIs, suggesting the disruption of local properties within the brain functional connectivity network and the existence of widespread multi-functional brain functional networks damage in JME patients. Our findings elucidate significant disruptions in the local properties of whole-brain functional connectivity network in patients with JME, revealing causal impairments across multiple functional networks. These findings collectively suggest that JME is a generalized epilepsy with localized abnormalities. Such insights highlight the intricate network dysfunctions characteristic of JME, thereby enriching our understanding of its pathophysiological features.
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Affiliation(s)
- Ming Ke
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Yaru Hou
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Li Zhang
- Hospital of Lanzhou University of Technology, Lanzhou University of Technology, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
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19
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Li M, Schilling KG, Gao F, Xu L, Choi S, Gao Y, Zu Z, Anderson AW, Ding Z, Landman BA, Gore JC. Quantification of mediation effects of white matter functional characteristics on cognitive decline in aging. Cereb Cortex 2024; 34:bhae114. [PMID: 38517178 PMCID: PMC10958767 DOI: 10.1093/cercor/bhae114] [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: 12/12/2023] [Revised: 02/29/2024] [Accepted: 03/03/2024] [Indexed: 03/23/2024] Open
Abstract
Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.
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Affiliation(s)
- Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Fei Gao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Lyuan Xu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, United States
| | - Soyoung Choi
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
- Department of Computer Science, Vanderbilt University, Nashville, TN 37240, United States
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
- Department of Computer Science, Vanderbilt University, Nashville, TN 37240, United States
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
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20
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Li Y, Peng J, Yang Z, Zhang F, Liu L, Wang P, Biswal BB. Altered white matter functional pathways in Alzheimer's disease. Cereb Cortex 2024; 34:bhad505. [PMID: 38436465 DOI: 10.1093/cercor/bhad505] [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: 10/13/2023] [Revised: 10/13/2023] [Accepted: 12/03/2023] [Indexed: 03/05/2024] Open
Abstract
Alzheimer's disease (AD) is associated with functional disruption in gray matter (GM) and structural damage to white matter (WM), but the relationship to functional signal in WM is unknown. We performed the functional connectivity (FC) and graph theory analysis to investigate abnormalities of WM and GM functional networks and corpus callosum among different stages of AD from a publicly available dataset. Compared to the controls, AD group showed significantly decreased FC between the deep WM functional network (WM-FN) and the splenium of corpus callosum, between the sensorimotor/occipital WM-FN and GM visual network, but increased FC between the deep WM-FN and the GM sensorimotor network. In the clinical groups, the global assortativity, modular interaction between occipital WM-FN and visual network, nodal betweenness centrality, degree centrality, and nodal clustering coefficient in WM- and GM-FNs were reduced. However, modular interaction between deep WM-FN and sensorimotor network, and participation coefficients of deep WM-FN and splenium of corpus callosum were increased. These findings revealed the abnormal integration of functional networks in different stages of AD from a novel WM-FNs perspective. The abnormalities of WM functional pathways connect downward to the corpus callosum and upward to the GM are correlated with AD.
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Affiliation(s)
- Yilu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Jinzhong Peng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Zhenzhen Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Fanyu Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Lin Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, 154 Summit Street, Newark 07102, NJ, United States
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21
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Ni MH, Yu Y, Yang Y, Li ZY, Ma T, Xie H, Li SN, Dai P, Cao XY, Cui YY, Zhu JL, Cui GB, Yan LF. Functional-structural decoupling in visual network is associated with cognitive decline in patients with type 2 diabetes mellitus: evidence from a multimodal MRI analysis. Brain Imaging Behav 2024; 18:73-82. [PMID: 37874444 DOI: 10.1007/s11682-023-00801-6] [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: 09/07/2023] [Indexed: 10/25/2023]
Abstract
Type 2 diabetes mellitus (T2DM) and cognitive dysfunction are highly prevalent disorders worldwide. Although visual network (VN) alteration and functional-structural coupling are potential warning factors for mild cognitive impairment (MCI) in T2DM patients, the relationship between the three in T2DM without MCI is unclear. Thirty T2DM patients without MCI and twenty-nine healthy controls (HC) were prospectively enrolled. Visual components (VC) were estimated by independent component analysis (ICA). Degree centrality (DC), amplitude of low frequency fluctuation (ALFF) and fractional anisotropy (FA) were established to reflect functional and structural characteristics in these VCs respectively. Functional-structural coupling coefficients were further evaluated using combined FA and DC or ALFF. Partial correlations were performed among neuroimaging indicators and neuropsychological scores and clinical variables. Three VCs were selected using group ICA. Deteriorated DC, ALFF and DC-FA coefficients in the VC1 were observed in the T2DM group compared with the HC group, while FA and ALFF-FA coefficients in these three VCs showed no significant differences. In the T2DM group, DC in the VC1 positively correlated with 2 dimensions in the California Verbal Learning Test, including Trial 4 and Total trial 1-5. The impaired DC-FA coefficients in the VC1 markedly affected the Total perseverative responses % of the Wisconsin Card Sorting Test. These findings indicate that DC and DC-FA coefficients in VN may be potential imaging biomarkers revealing early cognitive deficits in T2DM.
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Affiliation(s)
- Min-Hua Ni
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
- Faculty of Medical Technology, Shaanxi University of Chinese Medicine, 1 Middle Section of Shiji Road, Xianyang, 712046, Shaanxi, China
| | - Ying Yu
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
| | - Yang Yang
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
| | - Ze-Yang Li
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
| | - Teng Ma
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
| | - Hao Xie
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
| | - Si-Ning Li
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
- Faculty of Medical Technology, Xi`an Medical University, 1 Xinwang Road, Xi'an, 710016, Shaanxi, China
| | - Pan Dai
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
- Faculty of Medical Technology, Xi`an Medical University, 1 Xinwang Road, Xi'an, 710016, Shaanxi, China
| | - Xin-Yu Cao
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
- Faculty of Medical Technology, Yan'an University, 580 Shengdi Road, Yan'an, 716000, Shaanxi, China
| | - Yan-Yan Cui
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
- Faculty of Medical Technology, Shaanxi University of Chinese Medicine, 1 Middle Section of Shiji Road, Xianyang, 712046, Shaanxi, China
| | - Jun-Ling Zhu
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China
| | - Guang-Bin Cui
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Lin-Feng Yan
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
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22
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Wang P, Jiang Y, Biswal BB. Aberrant interhemispheric structural and functional connectivity within whole brain in schizophrenia. Schizophr Res 2024; 264:336-344. [PMID: 38218019 DOI: 10.1016/j.schres.2023.12.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/27/2023] [Accepted: 12/26/2023] [Indexed: 01/15/2024]
Abstract
OBJECTIVE Schizophrenia is a serious mental disorder whose etiology remains unclear. Although numerous studies have analyzed the abnormal gray matter functional activity and whole-brain anatomical changes in schizophrenia, fMRI signal fluctuations from white matter have usually been ignored and rarely reported in the literature. METHODS We employed 45 schizophrenia subjects and 75 healthy controls (HCs) from a publicly available fMRI dataset. By combining the voxel-mirrored homotopic connectivity (VMHC) measure and fiber tracking method, we investigated the interhemispheric functional and structural connectivity within whole brain in schizophrenia. RESULTS Compared to HCs, patients with schizophrenia exhibited significantly reduced VMHC in the bilateral middle occipital gyrus, precentral gyrus, postcentral gyrus and corpus callosum. Fiber tracking results showed the changes in structural connectivity for the bilateral precentral gyrus, and the bilateral corpus callosum, and the fiber bundles connecting bilateral precentral gyrus and connecting the bilateral corpus callosum passed through the posterior midbody, isthmus and splenium of mid-sagittal corpus callosum, which closely related to the interhemispheric integration of visual and auditory information. More importantly, we observed a negative correlation between averaged VMHC values in the postcentral gyrus and SAPS scores, and a positive correlation between the fractional anisotropy of fiber bundle connecting the bilateral precentral gyrus and Matrix Reasoning scores in schizophrenia. CONCLUSION Our findings provide a novel perspective of white matter functional images on understanding abnormal interhemispheric visual and auditory information transfer in schizophrenia.
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Affiliation(s)
- Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuan Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
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23
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Hu Y, Li S, Li J, Zhao Y, Li M, Cui W, Peng X, Dong Z, Zhang L, Xu H, Gao L, Huang X, Kuang W, Gong Q, Liu H. Impaired visual-motor functional connectivity in first-episode medication-naïve patients with major depressive disorder. Cereb Cortex 2024; 34:bhad387. [PMID: 37991260 PMCID: PMC10793073 DOI: 10.1093/cercor/bhad387] [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: 04/30/2023] [Revised: 09/29/2023] [Indexed: 11/23/2023] Open
Abstract
The perceptual dysfunctions have been fundamental causes of cognitive and emotional problems in patients with major depressive disorder. However, visual system impairment in depression has been underexplored. Here, we explored functional connectivity in a large cohort of first-episode medication-naïve patients with major depressive disorder (n = 190) and compared it with age- and sex-matched healthy controls (n = 190). A recently developed individual-oriented approach was applied to parcellate the cerebral cortex into 92 regions of interest using resting-state functional magnetic resonance imaging data. Significant reductions in functional connectivities were observed between the right lateral occipitotemporal junction within the visual network and 2 regions of interest within the sensorimotor network in patients. The volume of right lateral occipitotemporal junction was also significantly reduced in major depressive disorder patients, indicating that this visual region is anatomically and functionally impaired. Behavioral correlation analysis showed that the reduced functional connectivities were significantly associated with inhibition control in visual-motor processing in patients. Taken together, our data suggest that functional connectivity between visual network and sensorimotor network already shows a significant reduction in the first episode of major depressive disorder, which may interfere with the inhibition control in visual-motor processing. The lateral occipitotemporal junction may be a hub of disconnection and may play a role in the pathophysiology of major depressive disorder.
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Affiliation(s)
- Yongbo Hu
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
- Department of Neurology, The Third People’s Hospital of Chengdu, Chengdu 610031, China
| | - Shiyi Li
- Changping Laboratory, Science Park Road, Changping District, Beijing 100001, China
| | - Jin Li
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Youjin Zhao
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Meiling Li
- Changping Laboratory, Science Park Road, Changping District, Beijing 100001, China
| | - Weigang Cui
- School of Engineering Medicine, Beihang University, Bejing 100083, China
| | - Xiaolong Peng
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425, United States
| | - Zaiquan Dong
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Lianqing Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Haizhen Xu
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Li Gao
- Department of Neurology, The Third People’s Hospital of Chengdu, Chengdu 610031, China
| | - Xiaoqi Huang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen 361000, China
| | - Hesheng Liu
- Changping Laboratory, Science Park Road, Changping District, Beijing 100001, China
- Biomedical Pioneering Innovation Center, Peking University, Beijing 100871, China
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24
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Chen K, Zhuang W, Zhang Y, Yin S, Liu Y, Chen Y, Kang X, Ma H, Zhang T. Alteration of the large-scale white-matter functional networks in autism spectrum disorder. Cereb Cortex 2023; 33:11582-11593. [PMID: 37851712 DOI: 10.1093/cercor/bhad392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/02/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023] Open
Abstract
Autism spectrum disorder is a neurodevelopmental disorder whose core deficit is social dysfunction. Previous studies have indicated that structural changes in white matter are associated with autism spectrum disorder. However, few studies have explored the alteration of the large-scale white-matter functional networks in autism spectrum disorder. Here, we identified ten white-matter functional networks on resting-state functional magnetic resonance imaging data using the K-means clustering algorithm. Compared with the white matter and white-matter functional network connectivity of the healthy controls group, we found significantly decreased white matter and white-matter functional network connectivity mainly located within the Occipital network, Middle temporo-frontal network, and Deep network in autism spectrum disorder. Compared with healthy controls, findings from white-matter gray-matter functional network connectivity showed the decreased white-matter gray-matter functional network connectivity mainly distributing in the Occipital network and Deep network. Moreover, we compared the spontaneous activity of white-matter functional networks between the two groups. We found that the spontaneous activity of Middle temporo-frontal and Deep network was significantly decreased in autism spectrum disorder. Finally, the correlation analysis showed that the white matter and white-matter functional network connectivity between the Middle temporo-frontal network and others networks and the spontaneous activity of the Deep network were significantly correlated with the Social Responsiveness Scale scores of autism spectrum disorder. Together, our findings indicate that changes in the white-matter functional networks are associated behavioral deficits in autism spectrum disorder.
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Affiliation(s)
- Kai Chen
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Wenwen Zhuang
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Yanfang Zhang
- Department of Ultrasonic Medicine, Baiyun Branch, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province, China
| | - Shunjie Yin
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Yinghua Liu
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Yuan Chen
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Xiaodong Kang
- The Department of Sichuan 81 Rehabilitation Center, Chengdu University of TCM, No. 81 Bayi Road, Yongning Street, Wenjiang District, Chengdu City 610075, China
| | - Hailin Ma
- Plateau Brain Science Research Center, Tibet University, 10 Zangda East Road, Lhasa City 510631, China
| | - Tao Zhang
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
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Hu P, Wang P, Zhao R, Yang H, Biswal BB. Characterizing the spatiotemporal features of functional connectivity across the white matter and gray matter during the naturalistic condition. Front Neurosci 2023; 17:1248610. [PMID: 38027509 PMCID: PMC10665512 DOI: 10.3389/fnins.2023.1248610] [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: 06/27/2023] [Accepted: 10/25/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction The naturalistic stimuli due to its ease of operability has attracted many researchers in recent years. However, the influence of the naturalistic stimuli for whole-brain functions compared with the resting state is still unclear. Methods In this study, we clustered gray matter (GM) and white matter (WM) masks both at the ROI- and network-levels. Functional connectivity (FC) and inter-subject functional connectivity (ISFC) were calculated in GM, WM, and between GM and WM under the movie-watching and the resting-state conditions. Furthermore, intra-class correlation coefficients (ICC) of FC and ISFC were estimated on different runs of fMRI data to denote the reliability of them during the two conditions. In addition, static and dynamic connectivity indices were calculated with Pearson correlation coefficient to demonstrate the associations between the movie-watching and the resting-state. Results As the results, we found that the movie-watching significantly affected FC in whole-brain compared with the resting-state, but ISFC did not show significant connectivity induced by the naturalistic condition. ICC of FC and ISFC was generally higher during movie-watching compared with the resting-state, demonstrating that naturalistic stimuli could promote the reliability of connectivity. The associations between static and dynamic ISFC were weakly negative correlations in the naturalistic stimuli while there is no correlation between them under resting-state condition. Discussion Our findings confirmed that compared to resting-state condition, the connectivity indices under the naturalistic stimuli were more reliable and stable to investigate the normal functional activities of the human brain, and might promote the applications of FC in the cerebral dysfunction in various mental disorders.
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Affiliation(s)
- Peng Hu
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Pan Wang
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Rong Zhao
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hang Yang
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Chinese Institute for Brain Research, Beijing, China
| | - Bharat B. Biswal
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
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26
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Ji GJ, Sun J, Hua Q, Zhang L, Zhang T, Bai T, Wei L, Wang X, Qiu B, Wang A, Sun H, Liao W, Yu F, Zhu C, Tian Y, He K, Wang K. White matter dysfunction in psychiatric disorders is associated with neurotransmitter and genetic profiles. NATURE MENTAL HEALTH 2023; 1:655-666. [DOI: 10.1038/s44220-023-00111-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 07/21/2023] [Indexed: 04/02/2025]
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Huang Y, Wei PH, Xu L, Chen D, Yang Y, Song W, Yi Y, Jia X, Wu G, Fan Q, Cui Z, Zhao G. Intracranial electrophysiological and structural basis of BOLD functional connectivity in human brain white matter. Nat Commun 2023; 14:3414. [PMID: 37296147 PMCID: PMC10256794 DOI: 10.1038/s41467-023-39067-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 05/25/2023] [Indexed: 06/12/2023] Open
Abstract
While functional MRI (fMRI) studies have mainly focused on gray matter, recent studies have consistently found that blood-oxygenation-level-dependent (BOLD) signals can be reliably detected in white matter, and functional connectivity (FC) has been organized into distributed networks in white matter. Nevertheless, it remains unclear whether this white matter FC reflects underlying electrophysiological synchronization. To address this question, we employ intracranial stereotactic-electroencephalography (SEEG) and resting-state fMRI data from a group of 16 patients with drug-resistant epilepsy. We find that BOLD FC is correlated with SEEG FC in white matter, and this result is consistent across a wide range of frequency bands for each participant. By including diffusion spectrum imaging data, we also find that white matter FC from both SEEG and fMRI are correlated with white matter structural connectivity, suggesting that anatomical fiber tracts underlie the functional synchronization in white matter. These results provide evidence for the electrophysiological and structural basis of white matter BOLD FC, which could be a potential biomarker for psychiatric and neurological disorders.
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Affiliation(s)
- Yali Huang
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Peng-Hu Wei
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Longzhou Xu
- Chinese Institute for Brain Research, Beijing, 102206, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Desheng Chen
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Yanfeng Yang
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Wenkai Song
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Yangyang Yi
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Xiaoli Jia
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Guowei Wu
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Qingchen Fan
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, 102206, China.
| | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
- National Medical Center for Neurological Diseases, Beijing, 100053, China.
- Beijing Municipal Geriatric Medical Research Center, Beijing, 100053, China.
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Yang C, Gao X, Liu N, Sun H, Gong Q, Yao L, Lui S. Convergent and distinct neural structural and functional patterns of mild cognitive impairment: a multimodal meta-analysis. Cereb Cortex 2023:7169132. [PMID: 37197764 DOI: 10.1093/cercor/bhad167] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/23/2023] [Accepted: 04/25/2023] [Indexed: 05/19/2023] Open
Abstract
Mild cognitive impairment (MCI) is regarded as a transitional stage between normal aging and Alzheimer's disease. Numerous voxel-based morphometry (VBM) and resting-state fMRI (rs-fMRI) studies have provided strong evidence of abnormalities in the structure and intrinsic function of brain regions in MCI. Studies have recently begun to explore their association but have not employed systematic information in this pursuit. Herein, a multimodal meta-analysis was performed, which included 43 VBM datasets (1,247 patients and 1,352 controls) of gray matter volume (GMV) and 42 rs-fMRI datasets (1,468 patients and 1,605 controls) that combined 3 metrics: amplitude of low-frequency fluctuation, the fractional amplitude of low-frequency fluctuation, and regional homogeneity. Compared to controls, patients with MCI displayed convergent reduced regional GMV and altered intrinsic activity, mainly in the default mode network and salience network. Decreased GMV alone in ventral medial prefrontal cortex and altered intrinsic function alone in bilateral dorsal anterior cingulate/paracingulate gyri, right lingual gyrus, and cerebellum were identified, respectively. This meta-analysis investigated complex patterns of convergent and distinct brain alterations impacting different neural networks in MCI patients, which contributes to a further understanding of the pathophysiology of MCI.
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Affiliation(s)
- Chengmin Yang
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Xiang, Chengdu 610041, China
| | - Xin Gao
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Xiang, Chengdu 610041, China
| | - Naici Liu
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Xiang, Chengdu 610041, China
| | - Hui Sun
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Xiang, Chengdu 610041, China
| | - Qiyong Gong
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Xiang, Chengdu 610041, China
| | - Li Yao
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Xiang, Chengdu 610041, China
| | - Su Lui
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Xiang, Chengdu 610041, China
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Lu F, Guo Y, Luo W, Yu Y, Zhao Y, Chen J, Cai X, Shen C, Wang X, He J, Yang G, Gao Q, He Z, Zhou J. Disrupted functional networks within white-matter served as neural features in adolescent patients with conduct disorder. Behav Brain Res 2023; 447:114422. [PMID: 37030546 DOI: 10.1016/j.bbr.2023.114422] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/17/2023] [Accepted: 04/05/2023] [Indexed: 04/09/2023]
Abstract
BACKGROUND Conduct disorder (CD) has been conceptualized as a psychiatric disorder associated with white-matter (WM) structural abnormalities. Although diffusion tensor imaging could identify WM structural architecture changes, it cannot characterize functional connectivity (FC) within WM. Few studies have focused on disentangling the WM dysfunctions in CD patients by using functional magnetic resonance imaging (fMRI). METHODS The resting-state fMRI data were first obtained from both adolescent CD and typically developing (TD) controls. A voxel-based clustering analysis was utilized to identify the large-scale WM FC networks. Then, we examined the disrupted WM network features in CD, and further investigated whether these features could predict the impulsive symptoms in CD using support vector regression prediction model. RESULTS We identified 11 WM functional networks. Compared with TDs, CD patients showed increased FCs between occipital network (ON) and superior temporal network (STN), between orbitofrontal network (OFN) and corona radiate network (CRN), as well as between deep network and CRN. Further, the disrupted FCs between ON and STN and between OFN and CRN were significantly negatively associated with non-planning impulsivity scores in CD. Moreover, the disrupted WM networks could be served as features to predict the motor impulsivity scores in CD. CONCLUSIONS Our results provided further support on the existence of WM functional networks and could extended our knowledge about the WM functional abnormalities related with emotional and perception processing in CD patients from the view of WM dysfunction.
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Rashidi F, Khanmirzaei MH, Hosseinzadeh F, Kolahchi Z, Jafarimehrabady N, Moghisseh B, Aarabi MH. Cingulum and Uncinate Fasciculus Microstructural Abnormalities in Parkinson's Disease: A Systematic Review of Diffusion Tensor Imaging Studies. BIOLOGY 2023; 12:biology12030475. [PMID: 36979166 PMCID: PMC10045759 DOI: 10.3390/biology12030475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 03/12/2023] [Accepted: 03/15/2023] [Indexed: 03/30/2023]
Abstract
Diffusion tensor imaging (DTI) is gaining traction in neuroscience research as a tool for evaluating neural fibers. The technique can be used to assess white matter (WM) microstructure in neurodegenerative disorders, including Parkinson disease (PD). There is evidence that the uncinate fasciculus and the cingulum bundle are involved in the pathogenesis of PD. These fasciculus and bundle alterations correlate with the symptoms and stages of PD. PRISMA 2022 was used to search PubMed and Scopus for relevant articles. Our search revealed 759 articles. Following screening of titles and abstracts, a full-text review, and implementing the inclusion criteria, 62 papers were selected for synthesis. According to the review of selected studies, WM integrity in the uncinate fasciculus and cingulum bundles can vary according to symptoms and stages of Parkinson disease. This article provides structural insight into the heterogeneous PD subtypes according to their cingulate bundle and uncinate fasciculus changes. It also examines if there is any correlation between these brain structures' structural changes with cognitive impairment or depression scales like Geriatric Depression Scale-Short (GDS). The results showed significantly lower fractional anisotropy values in the cingulum bundle compared to healthy controls as well as significant correlations between FA and GDS scores for both left and right uncinate fasciculus regions suggesting that structural damage from disease progression may be linked to cognitive impairments seen in advanced PD patients. This review help in developing more targeted treatments for different types of Parkinson's disease, as well as providing a better understanding of how cognitive impairments may be related to these structural changes. Additionally, using DTI scans can provide clinicians with valuable information about white matter tracts which is useful for diagnosing and monitoring disease progression over time.
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Affiliation(s)
- Fatemeh Rashidi
- School of Medicine, Tehran University of Medical Science, Tehran 1417613151, Iran
| | | | - Farbod Hosseinzadeh
- School of Medicine, Tehran University of Medical Science, Tehran 1417613151, Iran
| | - Zahra Kolahchi
- School of Medicine, Tehran University of Medical Science, Tehran 1417613151, Iran
| | - Niloofar Jafarimehrabady
- Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Bardia Moghisseh
- School of Medicine, Arak University of Medical Science, Arak 3848176941, Iran
| | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, 35128 Padua, Italy
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Chen Z, Wu B, Li G, Zhou L, Zhang L, Liu J. Age and sex differentially shape brain networks in Parkinson's disease. CNS Neurosci Ther 2023. [PMID: 36890620 DOI: 10.1111/cns.14149] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 02/18/2023] [Accepted: 02/20/2023] [Indexed: 03/10/2023] Open
Abstract
AIMS Age and sex are important individual factors modifying the clinical symptoms of patients with Parkinson's disease (PD). Our goal is to evaluate the effects of age and sex on brain networks and clinical manifestations of PD patients. METHODS Parkinson's disease participants (n = 198) receiving functional magnetic resonance imaging from Parkinson's Progression Markers Initiative database were investigated. Participants were classified into lower quartile group (age rank: 0%~25%), interquartile group (age rank: 26%~75%), and upper quartile group (age rank: 76%~100%) according to their age quartiles to examine how age shapes brain network topology. The differences of brain network topological properties between male and female participants were also investigated. RESULTS Parkinson's disease patients in the upper quartile age group exhibited disrupted network topology of white matter networks and impaired integrity of white matter fibers compared to lower quartile age group. In contrast, sex preferentially shaped the small-world topology of gray matter covariance network. Differential network metrics mediated the effects of age and sex on cognitive function of PD patients. CONCLUSION Age and sex have diverse effects on brain structural networks and cognitive function of PD patients, highlighting their roles in the clinical management of PD.
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Affiliation(s)
- Zhichun Chen
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Bin Wu
- Department of Neurology, Xuchang Central Hospital affiliated with Henan University of Science and Technology, Henan, China
| | - Guanglu Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lina Zhang
- Department of Biostatistics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Altered white matter functional network in nicotine addiction. Psychiatry Res 2023; 321:115073. [PMID: 36716553 DOI: 10.1016/j.psychres.2023.115073] [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: 10/13/2022] [Revised: 01/17/2023] [Accepted: 01/22/2023] [Indexed: 01/25/2023]
Abstract
Nicotine addiction is a neuropsychiatric disorder with dysfunction in cortices as well as white matter (WM). The nature of the functional alterations in WM remains unclear. The small-world model can well characterize the structure and function of the human brain. In this study, we utilized the small-world model to compare the WM functional connectivity between 62 nicotine addiction participants (called the discovery sample) and 66 matched healthy controls (called the control sample). We also recruited an independent sample comprising 32 nicotine addicts (called the validation sample) for clinical application. The WM functional network data at the network level showed that the nicotine addiction group revealed decreased small-worldness index (σ) and normalized clustering coefficient (γ) compared with healthy controls. For clinical application, the small-world topology of WM functional connectivity could distinguish nicotine addicts from healthy controls (classification accuracy=0.59323, p = 0.0464). We trained abnormal small-world properties on the discovery sample to identify the severity of nicotine addiction, and the identification was successfully applied to the validation sample (classification accuracy=0.65625, p = 0.0106). Our neuroimaging findings provide direct evidence for WM functional changes in nicotine addiction and suggest that the small-world properties of WM function could be qualified as potential biomarkers in nicotine addiction.
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Abnormal dynamics of brain functional networks in children with Tourette syndrome. J Psychiatr Res 2023; 159:249-257. [PMID: 36764224 DOI: 10.1016/j.jpsychires.2023.01.046] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/30/2022] [Accepted: 01/26/2023] [Indexed: 01/29/2023]
Abstract
Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder characterized by the presence of multiple motor and vocal tics. Research using resting-state functional magnetic resonance imaging (rfMRI) have found aberrant static functional connectivity (FC) and its topological properties in the brain networks of TS. Our study is the first to investigate the dynamic functional connectivity (dFC) in the whole brain network of TS patients, focusing on the temporal properties of dFC states and the temporal variability of topological organization. The rfMRI data of 36 male children with TS and 27 matched healthy controls were collected and further analyzed by group spatial independent component analysis, sliding windows approach based dFC analysis, k-means clustering analysis, and graph theory analysis. The clustering analysis identified three dFC states. Of these states, state 2, characterized by increased inter-network connections in subcortical network (SCN), sensorimotor network (SMN), and default mode network (DMN), and decreased inter-network connections between salience network (SAN) and executive control network (ECN), was found to have higher fractional window and dwell time in TS, which was also positively correlated with tic severity. TS patients also exhibited higher temporal variability of whole-brain-network global efficiency and local efficiency, and higher temporal variability of nodal efficiency and local efficiency in SCN, DMN, ECN, SAN, and SMN. Additionally, temporal variability of the efficiency and local efficiency in insula was positively correlated with tic severity. Our findings revealed abnormal temporal property of dFC states and temporal variability of topological organization in TS, providing new insights into clinical diagnoses and neuropathology of TS.
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Yan Y, Wu Y, Xiao G, Wang L, Zhou S, Wei L, Tian Y, Wu X, Hu P, Wang K. White Matter Changes as an Independent Predictor of Alzheimer's Disease. J Alzheimers Dis 2023; 93:1443-1455. [PMID: 37182867 DOI: 10.3233/jad-221037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND Abnormalities in white matter (WM) may be a crucial physiologic feature of Alzheimer's disease (AD). However, neuroimaging's ability to visualize the underlying functional degradation of the WM region in AD is unclear. OBJECTIVE This study aimed to explore the differences in amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) in the WM region of patients with AD and healthy controls (HC) and to investigate further whether these values can provide supplementary information for diagnosing AD. METHODS Forty-eight patients with AD and 46 age-matched HC were enrolled and underwent resting-state functional magnetic resonance imaging and a neuropsychological battery assessment. We analyzed the differences in WM activity between the two groups and further explored the correlation between WM activity in the different regions and cognitive function in the AD group. Finally, a machine learning algorithm was adopted to construct a classifier in detecting the clinical classification ability of the values of ALFF/ALFF in the WM. RESULTS Compared with HCs, patients with AD had lower WM activity in the right anterior thalamic radiation, left frontal aslant tract, and left forceps minor, which are all positively related to global cognitive function, memory, and attention function (all p < 0.05). Based on the combined WM ALFF and fALFF characteristics in the different regions, individuals not previously assessed were classified with moderate accuracy (75%), sensitivity (71%), specificity (79%), and area under the receiver operating characteristic curve (85%). CONCLUSION Our results suggest that WM activity is reduced in AD and can be used for disease classification.
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Affiliation(s)
- Yibing Yan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yue Wu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Guixian Xiao
- Department of Sleep Psychology, The Second Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Lu Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Shanshan Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Ling Wei
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the 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 of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, Hefei, China
- Department of Sleep Psychology, The Second Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Xingqi Wu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, Hefei, China
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Li H, Jiang S, Dong D, Hu J, He C, Hou C, He H, Huang H, Shen D, Pei H, Zhao G, Dong L, Yao D, Luo C. Vascular feature as a modulator of the aging brain. Cereb Cortex 2022; 32:5609-5621. [PMID: 35174854 DOI: 10.1093/cercor/bhac039] [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: 12/10/2021] [Revised: 01/17/2022] [Accepted: 01/18/2022] [Indexed: 01/25/2023] Open
Abstract
The cerebral functional reorganization and declined cognitive function of aging might associate with altered vascular features. Here, we explored the altered cerebral hierarchical functional network of 2 conditions (task-free and naturalistic stimuli) in older adults and its relationship with vascular features (systemic microvascular and perfusion features, measured by magnetic resonance imaging) and behavior. Using cerebral gradient analysis, we found that compressive gradient of resting-state mainly located on the primary sensory-motor system and transmodal regions in aging, and further compress in these regions under the continuous naturalistic stimuli. Combining cerebral functional gradient, vascular features, and cognitive performance, the more compressive gradient in the resting-state, the worse vascular state, the lower cognitive function in older adults. Further modulation analysis demonstrated that both vascular features can regulate the relationship between gradient scores in the insula and behavior. Interestingly, systemic microvascular oxygenation also can modulate the relationship between cerebral gradient and cerebral perfusion. Furthermore, the less alteration of the compressive gradient with naturalistic stimuli came with lower cognitive function. Our findings demonstrated that the altered cerebral hierarchical functional structure in aging was linked with changed vascular features and behavior, offering a new framework for studying the physiological mechanism of functional connectivity in aging.
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Affiliation(s)
- Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
- Radiology Department, Chengdu Mental Health Center, Chengdu 610036, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, P. R. China
| | - Debo Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Jian Hu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
| | - Chuan He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
| | - Changyue Hou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- Radiology Department, Chengdu Mental Health Center, Chengdu 610036, P. R. China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
| | - Dai Shen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
| | - Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
| | - Guocheng Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- Radiology Department, Chengdu Mental Health Center, Chengdu 610036, P. R. China
| | - Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, P. R. China
- Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Cancer Hospital affiliate to School of Medicine, University of Electronic Science and Technology of China, Chengdu 610042, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, P. R. China
- Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Cancer Hospital affiliate to School of Medicine, University of Electronic Science and Technology of China, Chengdu 610042, P. R. China
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Ma H, Xie Z, Huang L, Gao Y, Zhan L, Hu S, Zhang J, Ding Q. The White Matter Functional Abnormalities in Patients with Transient Ischemic Attack: A Reinforcement Learning Approach. Neural Plast 2022; 2022:1478048. [PMID: 36300173 PMCID: PMC9592236 DOI: 10.1155/2022/1478048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/28/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022] Open
Abstract
Background Transient ischemic attack (TIA) is a known risk factor for stroke. Abnormal alterations in the low-frequency range of the gray matter (GM) of the brain have been studied in patients with TIA. However, whether there are abnormal neural activities in the low-frequency range of the white matter (WM) in patients with TIA remains unknown. The current study applied two resting-state metrics to explore functional abnormalities in the low-frequency range of WM in patients with TIA. Furthermore, a reinforcement learning method was used to investigate whether altered WM function could be a diagnostic indicator of TIA. Methods We enrolled 48 patients with TIA and 41 age- and sex-matched healthy controls (HCs). Resting-state functional magnetic resonance imaging (rs-fMRI) and clinical/physiological/biochemical data were collected from each participant. We compared the group differences between patients with TIA and HCs in the low-frequency range of WM using two resting-state metrics: amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). The altered ALFF and fALFF values were defined as features of the reinforcement learning method involving a Q-learning algorithm. Results Compared with HCs, patients with TIA showed decreased ALFF in the right cingulate gyrus/right superior longitudinal fasciculus/left superior corona radiata and decreased fALFF in the right cerebral peduncle/right cingulate gyrus/middle cerebellar peduncle. Based on these two rs-fMRI metrics, an optimal Q-learning model was obtained with an accuracy of 82.02%, sensitivity of 85.42%, specificity of 78.05%, precision of 82.00%, and area under the curve (AUC) of 0.87. Conclusion The present study revealed abnormal WM functional alterations in the low-frequency range in patients with TIA. These results support the role of WM functional neural activity as a potential neuromarker in classifying patients with TIA and offer novel insights into the underlying mechanisms in patients with TIA from the perspective of WM function.
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Affiliation(s)
- Huibin Ma
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
- Integrated Medical School, Jiamusi University, Jiamusi, China
| | - Zhou Xie
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Lina Huang
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Yanyan Gao
- 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
| | - Linlin Zhan
- Faculty of Western Languages, Heilongjiang University, Heilongjiang 150080, China
| | - Su Hu
- 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
| | - Jiaxi Zhang
- 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
| | - Qingguo Ding
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
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Guo J, Jiang Z, Liu X, Li H, Biswal BB, Zhou B, Sheng W, Gao Q, Chen H, Fan Y, Zhu W, Wang J, Chen H, Liu C. Cerebello-cerebral resting-state functional connectivity in spinocerebellar ataxia type 3. Hum Brain Mapp 2022; 44:927-936. [PMID: 36250694 PMCID: PMC9875927 DOI: 10.1002/hbm.26113] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 08/24/2022] [Accepted: 09/26/2022] [Indexed: 01/28/2023] Open
Abstract
Spinocerebellar ataxia type 3 (SCA3) is a neurodegenerative disorder characterized by progressive motor and nonmotor deficits concomitant with degenerative pathophysiological changes within the cerebellum. The cerebellum is topographically organized into cerebello-cerebral circuits that create distinct functional networks regulating movement, cognition, and affect. SCA3-associated motor and nonmotor symptoms are possibly related not only to intracerebellar changes but also to disruption of the connectivity within these cerebello-cerebral circuits. However, to date, no comprehensive investigation of cerebello-cerebral connectivity in SCA3 has been conducted. The present study aimed to identify cerebello-cerebral functional connectivity alterations and associations with downstream clinical phenotypes and upstream topographic markers of cerebellar neurodegeneration in patients with SCA3. This study included 45 patients with SCA3 and 49 healthy controls. Voxel-based morphometry and resting-state functional magnetic resonance imaging (MRI) were performed to characterize the cerebellar atrophy and to examine the cerebello-cerebral functional connectivity patterns. Structural MRI confirmed widespread gray matter atrophy in the motor and cognitive cerebellum of patients with SCA3. We found reduced functional connectivity between the cerebellum and the cerebral cortical networks, including the somatomotor, frontoparietal, and default networks; however, increased connectivity was observed between the cerebellum and the dorsal attention network. These abnormal patterns correlated with the CAG repeat expansion and deficits in global cognition. Our results indicate the contribution of cerebello-cerebral networks to the motor and cognitive impairments in patients with SCA3 and reveal that such alterations occur in association with cerebellar atrophy. These findings add important insights into our understanding of the role of the cerebellum in SCA3.
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Affiliation(s)
- Jing Guo
- The Center of Psychosomatic MedicineSichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of ChinaChengduChina,The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,Department of RadiologySouthwest Hospital, Army Medical University (Third Military Medical University)ChongqingChina
| | - Zhouyu Jiang
- The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Xinyuan Liu
- The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Haoru Li
- The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Bharat B. Biswal
- The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,Department of Biomedical EngineeringNew Jersey Institute of TechnologyNewarkNew JerseyUSA
| | - Bo Zhou
- The Center of Psychosomatic MedicineSichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of ChinaChengduChina
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Qing Gao
- The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Hui Chen
- Department of RadiologySouthwest Hospital, Army Medical University (Third Military Medical University)ChongqingChina
| | - Yunshuang Fan
- The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Wenyan Zhu
- Data Processing DepartmentYidu Cloud Technology, Inc.BeijingChina
| | - Jian Wang
- Department of RadiologySouthwest Hospital, Army Medical University (Third Military Medical University)ChongqingChina
| | - Huafu Chen
- The Center of Psychosomatic MedicineSichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of ChinaChengduChina,The Clinical Hospital of Chengdu Brain Science InstituteSchool of Life Science and Technology, University of Electronic Science and Technology of ChinaChengduChina,Department of RadiologySouthwest Hospital, Army Medical University (Third Military Medical University)ChongqingChina
| | - Chen Liu
- Department of RadiologySouthwest Hospital, Army Medical University (Third Military Medical University)ChongqingChina
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Meng L, Wang H, Zou T, Wang X, Chen H, Xie F, Li R. Attenuated brain white matter functional network interactions in Parkinson's disease. Hum Brain Mapp 2022; 43:4567-4579. [PMID: 35674466 PMCID: PMC9491278 DOI: 10.1002/hbm.25973] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/24/2022] [Accepted: 05/29/2022] [Indexed: 01/21/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by extensive structural abnormalities in cortical and subcortical brain areas. However, an association between changes in the functional networks in brain white matter (BWM) and Parkinson's symptoms remains unclear. With confirming evidence that resting-state functional magnetic resonance imaging (rs-fMRI) of BWM signals can effectively describe neuronal activity, this study investigated the interactions among BWM functional networks in PD relative to healthy controls (HC). Sixty-eight patients with PD and sixty-three HC underwent rs-fMRI. Twelve BWM functional networks were identified by K-means clustering algorithm, which were further classified as deep, middle, and superficial layers. Network-level interactions were examined via coefficient Granger causality analysis. Compared with the HC, the patients with PD displayed significantly weaker functional interaction strength within the BWM networks, particularly excitatory influences from the superficial to deep networks. The patients also showed significantly weaker inhibitory influences from the deep to superficial networks. Additionally, the sum of the absolutely positive/negative regression coefficients of the tri-layered networks in the patients was lower relative to HC (p < .05, corrected for false discovery rate). Moreover, we found the functional interactions involving the deep BWM networks negatively correlated with part III of the Unified Parkinson's Disease Rating Scales and Hamilton Depression Scales. Taken together, we demonstrated attenuated BWM interactions in PD and these abnormalities were associated with clinical motor and nonmotor symptoms. These findings may aid understanding of the neuropathology of PD and its progression throughout the nervous system from the perspective of BWM function.
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Affiliation(s)
- Li Meng
- Department of Radiology, Xiangya HospitalCentral South UniversityChangshaPeople's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Hongyu Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Ting Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xuyang Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Fangfang Xie
- Department of Radiology, Xiangya HospitalCentral South UniversityChangshaPeople's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Rong Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
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Hua Q, Zhang Y, Li Q, Gao X, Du R, Wang Y, Zhou Q, Zhang T, Sun J, Zhang L, Ji GJ, Wang K. Efficacy of twice-daily high-frequency repetitive transcranial magnetic stimulation on associative memory. Front Hum Neurosci 2022; 16:973298. [PMID: 36310842 PMCID: PMC9596967 DOI: 10.3389/fnhum.2022.973298] [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: 06/20/2022] [Accepted: 08/24/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives Several studies have examined the effects of repetitive transcranial magnetic stimulation (rTMS) on associative memory (AM) but findings were inconsistent. Here, we aimed to test whether twice-daily rTMS could significantly improve AM. Methods In this single-blind, sham-controlled experiment, 40 participants were randomized to receive twice-daily sham or real rTMS sessions for five consecutive days (a total of 16,000 pulses). The stimulation target in left inferior parietal lobule (IPL) exhibiting peak functional connectivity to the left hippocampus was individually defined for each participant. Participants completed both a picture-cued word association task and Stroop test at baseline and 1 day after the final real or sham rTMS session. Effects of twice-daily rTMS on AM and Stroop test performance were compared using two-way repeated measures analysis of variance with main factors Group (real vs. sham) and Time (baseline vs. post-rTMS). Results There was a significant Group × Time interaction effect. AM score was significantly enhanced in the twice-daily real group after rTMS, but this difference could not survive the post hoc analysis after multiple comparison correction. Further, AM improvement in the twice-daily real group was not superior to a previously reported once-daily rTMS group receiving 8,000 pulses. Then, we combined the twice- and once-daily real groups, and found a significant Group × Time interaction effect. Post hoc analysis indicated that the AM score was significantly enhanced in the real group after multiple comparisons correction. Conclusion Our prospective experiment did not show significant rTMS effect on AM, but this effect may become significant if more participants could be recruited as revealed by our retrospective analysis.
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Affiliation(s)
- Qiang Hua
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Yuanyuan Zhang
- 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Qianqian Li
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
- Department of Psychiatry, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiaoran Gao
- 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Rongrong Du
- 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Yingru Wang
- 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Qian Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Ting Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Lei Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Gong-jun Ji
- 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
- Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 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 Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
- Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei, China
- Anhui Institute of Translational Medicine, Hefei, China
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Zhao Y, Gao Y, Zu Z, Li M, Schilling KG, Anderson AW, Ding Z, Gore JC. Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping. Neuroimage 2022; 258:119399. [PMID: 35724855 PMCID: PMC9388229 DOI: 10.1016/j.neuroimage.2022.119399] [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: 02/22/2022] [Revised: 06/13/2022] [Accepted: 06/17/2022] [Indexed: 01/12/2023] Open
Abstract
A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by convolving the time course of the expected neural activity with a canonical hemodynamic response function (HRF) obtained a priori. The maps of brain activity produced reflect the magnitude of local BOLD responses. However, detecting BOLD signals in white matter (WM) is more challenging as the BOLD signals are weaker and the HRF is different, and may vary more across the brain. Here we propose a model-free approach to detect changes in BOLD signals in WM by measuring task-evoked increases of BOLD signal synchrony in WM fibers. The proposed approach relies on a simple assumption that, in response to a functional task, BOLD signals in relevant fibers are modulated by stimulus-evoked neural activity and thereby show greater synchrony than when measured in a resting state, even if their magnitudes do not change substantially. This approach is implemented in two technical stages. First, for each voxel a fiber-architecture-informed spatial window is created with orientation distribution functions constructed from diffusion imaging data. This provides the basis for defining neighborhoods in WM that share similar local fiber architectures. Second, a modified principal component analysis (PCA) is used to estimate the synchrony of BOLD signals in each spatial window. The proposed approach is validated using a 3T fMRI dataset from the Human Connectome Project (HCP) at a group level. The results demonstrate that neural activity can be reliably detected as increases in fMRI signal synchrony within WM fibers that are engaged in a task with high sensitivities and reproducibility.
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Affiliation(s)
- Yu Zhao
- Vanderbilt University Institute of Imaging Science, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, United States.
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, United States,Department of Biomedical Engineering, Vanderbilt University, United States
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, United States
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, United States
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, United States,Department of Biomedical Engineering, Vanderbilt University, United States
| | - Adam W. Anderson
- Vanderbilt University Institute of Imaging Science, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, United States,Department of Biomedical Engineering, Vanderbilt University, United States
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, United States; Department of Biomedical Engineering, Vanderbilt University, United States; Department of Electrical and Computer Engineering, Vanderbilt University, United States.
| | - John C. Gore
- Vanderbilt University Institute of Imaging Science, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, United States,Department of Biomedical Engineering, Vanderbilt University, United States,Department of Molecular Physiology and Biophysics, Vanderbilt University, United States,Department of Physics and Astronomy, Vanderbilt University, United States
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Combined functional and structural imaging of brain white matter reveals stage-dependent impairment in multiple system atrophy of cerebellar type. NPJ Parkinsons Dis 2022; 8:105. [PMID: 35977953 PMCID: PMC9385720 DOI: 10.1038/s41531-022-00371-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 07/26/2022] [Indexed: 12/04/2022] Open
Abstract
Advances in fMRI of brain white matter (WM) have established the feasibility of understanding how functional signals of WM evolve with brain diseases. By combining functional signals with structural features of WM, the current study characterizes functional and structural impairments of WM in cerebelar type multiple system atrophy, with the goal to derive new mechanistic insights into the pathological progression of this disease. Our analysis of 30 well-diagnosed patients revealed pronounced decreases in functional connectivity in WM bundles of the cerebellum and brainstem, and concomitant local structural alterations that depended on the disease stage. The novel findings implicate a critical time point in the pathological evolution of the disease, which could guide optimal therapeutic interventions. Furthermore, fMRI signals of impaired WM bundles exhibited superior sensitivity in differentiating initial disease development, which demonstrates great potential of using these signals to inform disease management.
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Jiang Y, Wang P, Wen J, Wang J, Li H, Biswal BB. Hippocampus-based static functional connectivity mapping within white matter in mild cognitive impairment. Brain Struct Funct 2022; 227:2285-2297. [PMID: 35864361 DOI: 10.1007/s00429-022-02521-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 06/04/2022] [Indexed: 11/28/2022]
Abstract
Mild cognitive impairment (MCI) is clinically characterized by memory loss and cognitive impairment closely associated with the hippocampal atrophy. Accumulating studies have confirmed the presence of neural signal changes within white matter (WM) in resting-state functional magnetic resonance imaging (fMRI). However, it remains unclear how abnormal hippocampus activity affects the WM regions in MCI. The current study employs 43 MCI, 71 very MCI (VMCI) and 87 age-, gender-, and education-matched healthy controls (HCs) from the public OASIS-3 dataset. Using the left and right hippocampus as seed points, we obtained the whole-brain functional connectivity (FC) maps for each subject. We then perform one-way ANOVA analysis to investigate the abnormal FC regions among HCs, VMCI, and MCI. We further performed probabilistic tracking to estimate whether the abnormal FC correspond to structural connectivity disruptions. Compared to HCs, MCI and VMCI groups exhibited reduced FC in the right middle temporal gyrus within gray matter, and right temporal pole, right inferior frontal gyrus within white matter. Specific dysconnectivity is shown in the cerebellum Crus II, left inferior temporal gyrus within gray matter, and right frontal gyrus within white matter. In addition, the fiber bundles connecting the left hippocampus and right temporal pole within white matter show abnormally increased mean diffusivity in MCI. The current study proposes a new functional imaging direction for exploring the mechanism of memory decline and pathophysiological mechanisms in different stages of Alzheimer's disease.
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Affiliation(s)
- Yuan Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Jiaping Wen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jianlin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongyi Li
- The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China. .,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, 07102, USA.
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Loss of superiority illusion in bipolar depressive disorder: A combined functional and structural MRI study. J Psychiatr Res 2022; 151:391-398. [PMID: 35580402 DOI: 10.1016/j.jpsychires.2022.04.034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 04/02/2022] [Accepted: 04/25/2022] [Indexed: 11/23/2022]
Abstract
Superiority illusion (SI) is a positive cognitive bias related to self, manifested as overestimated self-appraisal. Negative self-schema is a core feature of the cognitive model of depression, including bipolar depressive disorder (BDD). However, only little research has explored the impaired self-processing in BDD. The potential alteration of positive self-bias and the corresponding neural mechanism in BDD remains unclear. This study aimed to investigate the underlying neural mechanism of self-processing in BDD combining task-related functional magnetic resonance imaging and high-resolution T1 structural imaging. Forty-three BDD and forty-eight healthy controls were recruited and underwent a self-related task, where participants were required to evaluate how they compared with their average peers on a serial of positive and negative traits. We defined the ratio of neural activation and gray matter volume (GMV) in a region as the functional-structural coupling index to detect the changes of brain image in BDD. Furthermore, we used moderation analysis to explore the relationship among functional-structural coupling, behavioral scores and depression symptoms. BDD exhibited decreased task activation, GMV, and functional-structural coupling in bilateral anterior insula (AI) and inferior parietal lobule (IPL). The associations between functional-structural coupling in the right AI, IPL and negative trait self-rating scores were moderated by depressive symptom severity. The study revealed disturbed self-related processing and provided new evidences to neuropsychological dysfunction in BDD.
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Wu Y, Ji Y, Bai T, Wei Q, Zu M, Guo Y, Lv H, Zhang A, Qiu B, Wang K, Tian Y. Nodal degree changes induced by electroconvulsive therapy in major depressive disorder: Evidence in two independent cohorts. J Affect Disord 2022; 307:46-52. [PMID: 35331825 DOI: 10.1016/j.jad.2022.03.045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/15/2022] [Accepted: 03/17/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVE Electroconvulsive therapy (ECT), a rapidly acting treatment for major depressive disorder (MDD), has been reported to regulate brain networks. Nodes and their connections are the main components of the brain network and are essential for establishing and maintaining effective information transmission. This study aimed to evaluate the role of nodes in mediating antidepressant effects of ECT. METHODS Voxel-based nodal degree analysis was performed in 42 patients with MDD receiving ECT and 42 matched healthy controls at two time points to identify the nodal changes induced by ECT. Verification analysis was evaluated in a second, independent cohort of 23 MDD patients. RESULTS MDD patients showed improved nodal degree of the bilateral angular cortex (AG), precuneus, inferior frontal gyrus (IFG) and the right superior frontal gyrus (SFG) after ECT, and the increased nodal degree index (IND) rate of the AG and precuneus were negatively correlated to the depressive changes following ECT. Furthermore, validation analysis revealed a similar pattern of IND abnormalities in the first and second cohort of MDD patients. CONCLUSION ECT regulates the disrupted nodal degree of the AG and precuneus to achieve an antidepressant effect. This study may provide further insights into the pathogenesis of depression and provide potential targets for antidepressant pharmacotherapies.
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Affiliation(s)
- Yue Wu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Yang Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Tongjian Bai
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
| | - Qiang Wei
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
| | - Meidan Zu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Yuanyuan Guo
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Huaming Lv
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Aiguo Zhang
- Anhui Mental Health Center, Hefei 230022, China
| | - Bensheng Qiu
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China; The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China; The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
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45
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Ma T, Ji YY, Yan LF, Lin JJ, Li ZY, Wang W, Li JL, Cui GB. Gray Matter Volume Abnormality in Chronic Pain Patients With Depressive Symptoms: A Systemic Review and Meta-Analysis of Voxel-Based Morphometry Studies. Front Neurosci 2022; 16:826759. [PMID: 35733934 PMCID: PMC9207409 DOI: 10.3389/fnins.2022.826759] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 04/19/2022] [Indexed: 12/21/2022] Open
Abstract
Background Gray matter volume (GMV) alteration in specific brain regions has been widely regarded as one of the most important neuroplasticity features in chronic pain patients with depressive symptoms (CP-D). However, the consistent and significant results were still lacking. Thus, further exploration was suggested to be performed. Objectives This study aimed to comprehensively collect the voxel-based morphometry (VBM) studies on GMV alteration between CP-D and healthy controls (HCs). And a systemic review and meta-analysis were made to explore the characteristic brain regions in chronic pain and depression comorbidity. Methods Search of PubMed, MEDLINE, Web of Science, and Cochrane Library databases updated to July 13, 2021. The altered GMV between CP-D and HCs in VBM studies was included in this meta-analysis. In total, 18 studies (20 datasets) and 1320 participants (520 patients and 800 HCs) were included. The significant coordinate information (x, y, z) reported in standard space and the effect size (t-value or z-score) were extracted and analyzed by anisotropic effect size-signed differential mapping (AES-SDM) 5.15 software. Results According to the main analysis results, CP-D showed significant and consistent increased GMV in the left hippocampus (HIP. L) and decreased GMV in the medial part of the left superior frontal gyrus (SFG. L, BA 10) compared to HCs. Subgroup analysis showed significant decreased GMV in the medial orbital part of SFG.R (BA 10) in neuropathic pain, as well as significant increased GMV in the right parahippocampal gyrus (PHG.R, BA 35), left hippocampus (HIP.L, BA 20), and right middle frontal gyrus (MFG.R) in musculoskeletal pain. Furthermore, meta-regression showed a positive relationship between the decreased GMV in the medial part of SFG.L and the percentage of female patients. Conclusion GMV abnormality in specific brain areas (e.g., HIP.L and SFG) was robust and reproducible, which could be significantly involved in this comorbidity disease. The findings in this study may be a valuable reference for future research. Systematic Review Registration [www.crd.york.ac.uk/prospero/].
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Affiliation(s)
- Teng Ma
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - Yuan-Yuan Ji
- College of Forensic Medicine, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Ministry of Public Health for Forensic Science, Xi’an Jiaotong University, Xi’an, China
| | - Lin-Feng Yan
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - Jia-Ji Lin
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Ze-Yang Li
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - Wen Wang
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - Jin-Lian Li
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - Guang-Bin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
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Yang Y, Wang S, Liu J, Zou G, Jiang J, Jiang B, Cao W, Zou Q. Changes in white matter functional networks during wakefulness and sleep. Hum Brain Mapp 2022; 43:4383-4396. [PMID: 35615855 PMCID: PMC9435017 DOI: 10.1002/hbm.25961] [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: 12/05/2021] [Revised: 05/10/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
Blood oxygenation level‐dependent (BOLD) signals in the white matter (WM) have been demonstrated to encode neural activities by showing structure‐specific temporal correlations during resting‐state and task‐specific imaging of fiber pathways with various degrees of correlations in strength and time delay. Previous neuroimaging studies have shown state‐dependent functional connectivity and regional amplitude of signal fluctuations in brain gray matter across wakefulness and nonrapid eye movement (NREM) sleep cycles. However, the functional characteristics of WM during sleep remain unknown. Using simultaneous electroencephalography and functional magnetic resonance imaging data during wakefulness and NREM sleep collected from 66 healthy participants, we constructed 10 stable WM functional networks using clustering analysis. Functional connectivity between these WM functional networks and regional amplitude of WM signal fluctuations across multiple low‐frequency bands were evaluated. In general, decreased WM functional connectivity between superficial and middle layer WM functional networks was observed from wakefulness to sleep. In addition, functional connectivity between the deep and cerebellar networks was higher during light sleep and lower during both wakefulness and deep sleep. The regional fluctuation amplitude was always higher during light sleep and lower during deep sleep. Importantly, slow‐wave activity during deep sleep negatively correlated with functional connectivity between WM functional networks but positively correlated with fluctuation strength in the WM. These observations provide direct physiological evidence that neural activities in the WM are modulated by the sleep–wake cycle. This study provided the initial mapping of functional changes in WM during sleep.
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Affiliation(s)
- Yang Yang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Shilei Wang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Jiayi Liu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Guangyuan Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Jun Jiang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Binghu Jiang
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China
| | - Wentian Cao
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,National Clinical Research Center for Mental Health, Peking University Sixth Hospital, China
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Jiang Y, Yao D, Zhou J, Tan Y, Huang H, Wang M, Chang X, Duan M, Luo C. Characteristics of disrupted topological organization in white matter functional connectome in schizophrenia. Psychol Med 2022; 52:1333-1343. [PMID: 32880241 DOI: 10.1017/s0033291720003141] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Neuroimaging characteristics have demonstrated disrupted functional organization in schizophrenia (SZ), involving large-scale networks within grey matter (GM). However, previous studies have ignored the role of white matter (WM) in supporting brain function. METHODS Using resting-state functional MRI and graph theoretical approaches, we investigated global topological disruptions of large-scale WM and GM networks in 93 SZ patients and 122 controls. Six global properties [clustering coefficient (Cp), shortest path length (Lp), local efficiency (Eloc), small-worldness (σ), hierarchy (β) and synchronization (S) and three nodal metrics [nodal degree (Knodal), nodal efficiency (Enodal) and nodal betweenness (Bnodal)] were utilized to quantify the topological organization in both WM and GM networks. RESULTS At the network level, both WM and GM networks exhibited reductions in Eloc, Cp and S in SZ. The SZ group showed reduced σ and β only for the WM network. Furthermore, the Cp, Eloc and S of the WM network were negatively correlated with negative symptoms in SZ. At the nodal level, the SZ showed nodal disturbances in the corpus callosum, optic radiation, posterior corona radiata and tempo-occipital WM tracts. For GM, the SZ manifested increased nodal centralities in frontoparietal regions and decreased nodal centralities in temporal regions. CONCLUSIONS These findings provide the first evidence for abnormal global topological properties in SZ from the perspective of a substantial whole brain, including GM and WM. Nodal centralities enhance GM areas, along with a reduction in adjacent WM, suggest that WM functional alterations may be compensated for adjacent GM impairments in SZ.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, P. R. China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yue Tan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - MeiLin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Department of Psychiatry, Chengdu Mental Health Center, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
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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: 13] [Impact Index Per Article: 4.3] [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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49
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Ma L, Liu M, Xue K, Ye C, Man W, Cheng M, Liu Z, Zhu D, Liu F, Wang J. Abnormal regional spontaneous brain activities in white matter in patients with autism spectrum disorder. Neuroscience 2022; 490:1-10. [PMID: 35218886 DOI: 10.1016/j.neuroscience.2022.02.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/01/2022] [Accepted: 02/18/2022] [Indexed: 10/19/2022]
Abstract
Previous studies have demonstrated patients with autism spectrum disorder (ASD) are accompanied by alterations of spontaneous brain activity in gray matter. However, whether the alterations of spontaneous brain activity exist in white matter remains largely unclear. In this study, 88 ASD patients and 87 typical controls (TCs) were included and regional homogeneity (ReHo) was calculated to characterize spontaneous brain activity in white matter. Voxel-wise two-sample t-tests were performed to investigate ReHo alterations, and cluster-level analyses were conducted to examine structural-functional coupling changes. Compared with TCs, the ASD group showed significantly decreased ReHo in the left superior corona radiata and left posterior limb of internal capsule, and decreased ReHo in the left anterior corona radiata with a trend level of significance. In addition, significantly weaker structural-functional coupling was observed in the left superior corona radiata and left posterior limb of internal capsule in ASD patients. Taken together, these findings highlighted abnormalities of white matter's regional spontaneous brain activity in ASD, which may provide new insights into the pathophysiological mechanisms of this disorder.
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Affiliation(s)
- Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Kaizhong Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Caihua Ye
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Weiqi Man
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Meng Cheng
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zhixuan Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Dan Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China; Department of Radiology, Tianjin Medical University General Hospital Airport Hospital, Tianjin 300308, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Junping Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
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Shih YC, Tseng WYI, Montaser-Kouhsari L. Recent advances in using diffusion tensor imaging to study white matter alterations in Parkinson's disease: A mini review. Front Aging Neurosci 2022; 14:1018017. [PMID: 36910861 PMCID: PMC9992993 DOI: 10.3389/fnagi.2022.1018017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 12/26/2022] [Indexed: 02/24/2023] Open
Abstract
Parkinson's disease (PD) is the second most common age-related neurodegenerative disease with cardinal motor symptoms. In addition to motor symptoms, PD is a heterogeneous disease accompanied by many non-motor symptoms that dominate the clinical manifestations in different stages or subtypes of PD, such as cognitive impairments. The heterogeneity of PD suggests widespread brain structural changes, and axonal involvement appears to be critical to the pathophysiology of PD. As α-synuclein pathology has been suggested to cause axonal changes followed by neuronal degeneration, diffusion tensor imaging (DTI) as an in vivo imaging technique emerges to characterize early detectable white matter changes due to PD. Here, we reviewed the past 5-year literature to show how DTI has helped identify axonal abnormalities at different PD stages or in different PD subtypes and atypical parkinsonism. We also showed the recent clinical utilities of DTI tractography in interventional treatments such as deep brain stimulation (DBS). Mounting evidence supported by multisite DTI data suggests that DTI along with the advanced analytic methods, can delineate dynamic pathophysiological processes from the early to late PD stages and differentiate distinct structural networks affected in PD and other parkinsonism syndromes. It indicates that DTI, along with recent advanced analytic methods, can assist future interventional studies in optimizing treatments for PD patients with different clinical conditions and risk profiles.
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Affiliation(s)
- Yao-Chia Shih
- Graduate Institute of Medicine, Yuan Ze University, Taoyuan, Taiwan
| | - Wen-Yih Isaac Tseng
- AcroViz Inc., Taipei, Taiwan.,Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
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