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Ashayeri H, Salehi-Pourmehr H, Ghojazadeh M. Letter to the editor. J Affect Disord 2024; 347:568. [PMID: 38092281 DOI: 10.1016/j.jad.2023.12.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 12/08/2023] [Indexed: 01/08/2024]
Affiliation(s)
- Hamidreza Ashayeri
- Research Center for Evidence-Based Medicine, Iranian EBM Centre: A JBI Centre of Excellence, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Hanieh Salehi-Pourmehr
- Research Center for Evidence-Based Medicine, Iranian EBM Centre: A JBI Centre of Excellence, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Morteza Ghojazadeh
- Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.
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Rezaei S, Gharepapagh E, Rashidi F, Cattarinussi G, Sanjari Moghaddam H, Di Camillo F, Schiena G, Sambataro F, Brambilla P, Delvecchio G. Machine learning applied to functional magnetic resonance imaging in anxiety disorders. J Affect Disord 2023; 342:54-62. [PMID: 37683943 DOI: 10.1016/j.jad.2023.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 08/21/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023]
Abstract
BACKGROUND Brain functional abnormalities have been commonly reported in anxiety disorders, including generalized anxiety disorder, social anxiety disorder, panic disorder, agoraphobia, and specific phobias. The role of functional abnormalities in the discrimination of these disorders can be tested with machine learning (ML) techniques. Here, we aim to provide a comprehensive overview of ML studies exploring the potential discriminating role of functional brain alterations identified by functional magnetic resonance imaging (fMRI) in anxiety disorders. METHODS We conducted a search on PubMed, Web of Science, and Scopus of ML investigations using fMRI as features in patients with anxiety disorders. A total of 12 studies (resting-state fMRI n = 5, task-based fMRI n = 6, resting-state and task-based fMRI n=1) met our inclusion criteria. RESULTS Overall, the studies showed that, regardless of the classifiers, alterations in functional connectivity and aberrant neural activation involving the amygdala, anterior cingulate cortex, hippocampus, insula, orbitofrontal cortex, temporal pole, cerebellum, default mode network, dorsal attention network, sensory network, and affective network were able to discriminate patients with anxiety from controls, with accuracies spanning from 36 % to 94 %. LIMITATIONS The small sample size, different ML approaches and heterogeneity in the selection of regions included in the multivariate pattern analyses limit the conclusions of the present review. CONCLUSIONS ML methods using fMRI as features can distinguish patients with anxiety disorders from healthy controls, indicating that these techniques could be used as a helpful tool for the diagnosis and the development of more targeted treatments for these disorders.
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Affiliation(s)
- Sahar Rezaei
- Connective Tissue Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Department of Nuclear Medicine, Medical School, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Esmaeil Gharepapagh
- Connective Tissue Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Department of Nuclear Medicine, Medical School, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Fatemeh Rashidi
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Fabio Di Camillo
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | - Giandomenico Schiena
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
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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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Ma H, Cao Y, Li M, Zhan L, Xie Z, Huang L, Gao Y, Jia X. Abnormal amygdala functional connectivity and deep learning classification in multifrequency bands in autism spectrum disorder: A multisite functional magnetic resonance imaging study. Hum Brain Mapp 2023; 44:1094-1104. [PMID: 36346215 PMCID: PMC9875923 DOI: 10.1002/hbm.26141] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 10/19/2022] [Accepted: 10/25/2022] [Indexed: 11/11/2022] Open
Abstract
Previous studies have explored resting-state functional connectivity (rs-FC) of the amygdala in patients with autism spectrum disorder (ASD). However, it remains unclear whether there are frequency-specific FC alterations of the amygdala in ASD and whether FC in specific frequency bands can be used to distinguish patients with ASD from typical controls (TCs). Data from 306 patients with ASD and 314 age-matched and sex-matched TCs were collected from 28 sites in the Autism Brain Imaging Data Exchange database. The bilateral amygdala, defined as the seed regions, was used to perform seed-based FC analyses in the conventional, slow-5, and slow-4 frequency bands at each site. Image-based meta-analyses were used to obtain consistent brain regions across 28 sites in the three frequency bands. By combining generative adversarial networks and deep neural networks, a deep learning approach was applied to distinguish patients with ASD from TCs. The meta-analysis results showed frequency band specificity of FC in ASD, which was reflected in the slow-5 frequency band instead of the conventional and slow-4 frequency bands. The deep learning results showed that, compared with the conventional and slow-4 frequency bands, the slow-5 frequency band exhibited a higher accuracy of 74.73%, precision of 74.58%, recall of 75.05%, and area under the curve of 0.811 to distinguish patients with ASD from TCs. These findings may help us to understand the pathological mechanisms of ASD and provide preliminary guidance for the clinical diagnosis of ASD.
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Affiliation(s)
- Huibin Ma
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Yikang Cao
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Mengting Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- Faculty of Western Languages, Heilongjiang University, Harbin, 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, China
| | - Yanyan Gao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Xize Jia
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, China
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Functional Connectivity Changes in Multiple-Frequency Bands in Acute Basal Ganglia Ischemic Stroke Patients: A Machine Learning Approach. Neural Plast 2022; 2022:1560748. [PMID: 35356364 PMCID: PMC8958111 DOI: 10.1155/2022/1560748] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 02/07/2022] [Accepted: 02/21/2022] [Indexed: 11/17/2022] Open
Abstract
Purpose Several functional magnetic resonance imaging (fMRI) studies have investigated the resting-state functional connectivity (rs-FC) changes in the primary motor cortex (M1) in patients with acute basal ganglia ischemic stroke (BGIS). However, the frequency-specific FC changes of M1 in acute BGIS patients are still unclear. Our study was aimed at exploring the altered FC of M1 in three frequency bands and the potential features as biomarkers for the identification by using a support vector machine (SVM). Methods We included 28 acute BGIS patients and 42 healthy controls (HCs). Seed-based FC of two regions of interest (ROI, bilateral M1s) were calculated in conventional, slow-5, and slow-4 frequency bands. The abnormal voxel-wise FC values were defined as the features for SVM in different frequency bands. Results In the ipsilesional M1, the acute BGIS patients exhibited decreased FC with the right lingual gyrus in the conventional and slow-4 frequency band. Besides, the acute BGIS patients showed increased FC with the right medial superior frontal gyrus (SFGmed) in the conventional and slow-5 frequency band and decreased FC with the left lingual gyrus in the slow-5 frequency band. In the contralesional M1, the BGIS patients showed lower FC with the right SFGmed in the conventional frequency band. The higher FC values with the right lingual gyrus and left SFGmed were detected in the slow-4 frequency band. In the slow-5 frequency band, the BGIS patients showed decreased FC with the left calcarine sulcus. SVM results showed that the combined features (slow-4+slow-5) had the highest accuracy in classification prediction of acute BGIS patients, with an area under curve (AUC) of 0.86. Conclusion Acute BGIS patients had frequency-specific alterations in FC; SVM is a promising method for exploring these frequency-dependent FC alterations. The abnormal brain regions might be potential targets for future researchers in the rehabilitation and treatment of stroke patients.
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Joseph JE, Sekar S, Kannath SK, Menon RN, Thomas B. Impaired intrinsic functional connectivity among medial temporal lobe and sub-regions related to memory deficits in intracranial dural arteriovenous fistula. Neuroradiology 2021; 63:1679-1687. [PMID: 33837804 DOI: 10.1007/s00234-021-02707-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 03/29/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE The functional changes concerning memory deficits in dural arteriovenous fistula (dAVF) brain are inadequately understood. This study aimed to understand the functional connectivity alterations of brain regions widely affirmed for explicit and implicit memory functions in dAVF patients (DP) and look into the frequency effects of the altered functional networks. METHODS Resting-state functional magnetic resonance imaging (rsfMRI) analysis was done in the memory-associated regions of 30 DP and 30 healthy controls (HC). Frequency decomposition was used to determine potential frequency-dependent functional connectivity changes. They underwent neuropsychological tests and were correlated with changes in memory networks compared with HC. RESULTS The results showed weaker functional connectivity among the medial temporal lobe and sub-regions in DP suggestive of dysfunction of explicit and implicit memory functions, which corroborated with the positive correlation between memory scores and hippocampal-parahippocampal connectivity of DP, along with a significant group difference of lower memory and cognitive performance in DP assessed by neuropsychological tests. A frequency-dependent study of the altered rsFC revealed lower functional connectivity strength and impaired neural coupling manifested at some sub-band frequencies indicative of disturbed cortical rhythm in DP. CONCLUSION This pilot study gives insights into significant intrinsic functional connectivity changes in the memory regions of the dAVF brain. The results may have clinical implications in the choice of interventional management of dAVF and can impact clinical decision making for realizable prevention of progressive memory impairment and irreversible brain damage in such patients.
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Affiliation(s)
- Josline Elsa Joseph
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Sabarish Sekar
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Santhosh Kumar Kannath
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Ramshekhar N Menon
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Bejoy Thomas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
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Guo X, Yang F, Fan L, Gu Y, Ma J, Zhang J, Liao M, Zhai T, Zhang Y, Li L, Su L, Dai Z. Disruption of functional and structural networks in first-episode, drug-naïve adolescents with generalized anxiety disorder. J Affect Disord 2021; 284:229-237. [PMID: 33618206 DOI: 10.1016/j.jad.2021.01.088] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 01/11/2021] [Accepted: 01/31/2021] [Indexed: 02/01/2023]
Abstract
BACKGROUND Individuals with generalized anxiety disorder (GAD) tend to worry exaggeratedly and uncontrollably about various daily routines. Previous studies have demonstrated that the GAD patients exhibited widespread alternations in both functional networks (FN) and structural networks (SN). However, the simultaneous alternations of the topological organization of FN, SN, as well as their couplings in GAD still remain unknown. METHODS Using multimodal approach, we constructed FN from resting-state functional magnetic imaging (R-fMRI) data and SN from diffusion magnetic resonance imaging (dMRI) data of 32 adolescent GAD patients and 25 healthy controls (HC). Graph theory analysis was employed to investigate the topological properties of FN, SN, and FN-SN coupling. RESULTS Compared to HC, the GAD patients showed disruptions in global (i.e., decreased clustering coefficient, global, and local efficiency) and subnetwork (i.e., reduced intermodular connections, rich club, and feeder connections) levels in FN. Abnormal global level properties (i.e., increased characteristic path length and reduced global efficiency) were also observed in SN. Altered FN-SN couplings in normalized characteristic path length and feeder connections were identified in the GAD patients. The identified network measures were correlated with anxiety severity in the GAD patients. LIMITATIONS The sample size of the current study is small and the cross-sectional nature can not infer causal relationship. CONCLUSIONS Our findings identified GAD-related topological alternations in both FN and SN, together with the couplings between FN and SN, providing us with a novel perspective for understanding the pathophysiological mechanisms of GAD.
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Affiliation(s)
- Xiaotong Guo
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Fan Yang
- Guangdong mental health center, Guangdong general hospital & Guangdong academy of medical sciences, Guangzhou, China
| | - Linlin Fan
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
| | - Yue Gu
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Junji Ma
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Jinbo Zhang
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Mei Liao
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China..
| | - Tianyi Zhai
- Department of Psychiatry, Guangzhou Huiai Hospital, Guangzhou, China
| | - Yan Zhang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Lingjiang Li
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Linyan Su
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhengjia Dai
- Department of Psychology, Sun Yat-sen University, Guangzhou, China.
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Zhang B, Yan G, Yang Z, Su Y, Wang J, Lei T. Brain Functional Networks Based on Resting-State EEG Data for Major Depressive Disorder Analysis and Classification. IEEE Trans Neural Syst Rehabil Eng 2020; 29:215-229. [PMID: 33296307 DOI: 10.1109/tnsre.2020.3043426] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
If the brain is regarded as a system, it will be one of the most complex systems in the universe. Traditional analysis and classification methods of major depressive disorder (MDD) based on electroencephalography (EEG) feature-levels often regard electrode as isolated node and ignore the correlation between them, so it's difficult to find alters of abnormal topological architecture in brain. To solve this problem, we propose a brain functional network framework for MDD of analysis and classification based on resting state EEG. The phase lag index (PLI) was calculated based on the 64-channel resting state EEG to construct the function connection matrix to reduce and avoid the volume conductor effect. Then binarization of brain function network based on small world index was realized. Statistical analyses were performed on different EEG frequency band and different brain regions. The results showed that significant alterations of brain synchronization occurred in frontal, temporal, parietal-occipital regions of left brain and temporal region of right brain. And average shortest path length and clustering coefficient in left central region of theta band and node betweenness centrality in right parietal-occipital region were significantly correlated with PHQ-9 score of MDD, which indicates these three network metrics may be served as potential biomarkers to effectively distinguish MDD from controls and the highest classification accuracy can reach 93.31%. Our findings also point out that the brain function network of MDD patients shows a random trend, and small world characteristics appears to weaken.
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Yang F, Zhang J, Fan L, Liao M, Wang Y, Chen C, Zhai T, Zhang Y, Li L, Su L, Dai Z. White matter structural network disturbances in first-episode, drug-naïve adolescents with generalized anxiety disorder. J Psychiatr Res 2020; 130:394-404. [PMID: 32889357 DOI: 10.1016/j.jpsychires.2020.08.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 07/12/2020] [Accepted: 08/09/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Previous studies have suggested that individuals with generalized anxiety disorder (GAD) would show inefficient whole-brain communication and dysconnectivity in the fronto-parietal-subcortical sub-networks in the white matter (WM) structural network. However, these hypotheses have yet to be tested. METHODS Individual WM structural networks were constructed based on diffusion MRI data and deterministic tractography in 34 first-episode, medication-naïve adolescents with GAD and 27 healthy controls (HCs). Graph theory was applied to investigate the topological organization alterations of the structural network. RESULTS GAD patients showed disrupted small-world configurations (i.e., increased path length and decreased clustering coefficient) and hub organization (i.e., less connection strength in the feeder and local connections). A decreased connection strength was found in a GAD-related sub-network (mainly involving the frontal-subcortical circuits), which was able to distinguish GAD patients from HCs with higher accuracy (area under the curve of 0.96, sensitivity of 94%, specificity of 89%) than clinical scores and other topological alternations. LIMITATIONS The current study just compared GAD patients with HCs based on a small sample, leaving whether the alternations found here are specific to GAD still an open question. Future studies are recommended to recruit patients with other anxiety disorders (e.g., social anxiety disorder) and/or comorbid mood disorders to identify the GAD-specific WM alterations using a larger sample. CONCLUSIONS Our findings highlight the disruption of the topological organization of the whole-brain WM structural network (especially the frontal-subcortical circuits) in GAD, and suggest the potential of using structural connectivity of the GAD-related sub-network as a biomarker for GAD patients.
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Affiliation(s)
- Fan Yang
- Guangdong Mental Health Center, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jinbo Zhang
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Linlin Fan
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
| | - Mei Liao
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yuyin Wang
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Chang Chen
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Tianyi Zhai
- Department of Psychiatry, Guangzhou Huiai Hospital, Guangzhou, China
| | - Yan Zhang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Lingjiang Li
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Linyan Su
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhengjia Dai
- Department of Psychology, Sun Yat-sen University, Guangzhou, China.
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Chen Y, Cui Q, Xie A, Pang Y, Sheng W, Tang Q, Li D, Huang J, He Z, Wang Y, Chen H. Abnormal dynamic functional connectivity density in patients with generalized anxiety disorder. J Affect Disord 2020; 261:49-57. [PMID: 31600587 DOI: 10.1016/j.jad.2019.09.084] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 09/03/2019] [Accepted: 09/30/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND Numerous studies have revealed the abnormal static functional connectivity (FC) among different brain regions in patients with generalized anxiety disorder (GAD). However, little is known about the dynamic changes of FC in patients with GAD. METHODS This study investigated the whole-brain dynamic changes of FC in patients with GAD by combining global FC density (FCD) and sliding window correlation analyses. The standard deviation of dynamic FCD (dFCD) was calculated to evaluate its temporal variability along time. Support vector regression was then employed to predict the symptom severity of patients based on abnormal dynamic connectivity patterns. RESULTS The abnormal dFCD variability between 81 GAD patients and 80 healthy controls showed that the patients had higher dFCD variability in the bilateral dorsomedial prefrontal cortex (dmPFC) and left hippocampus while lower dFCD variability in the right postcentral gyrus. The abnormal dFCD variability of the left dmPFC is an important feature for anxiety prediction. LIMITATIONS The selection of sliding window length remains controversial, and most of our patients have been treated with medications. Future studies are expected to rule out the potential confounding effects from applying different parameters of the sliding window and recruiting large samples of medication-free patients. CONCLUSION The altered patterns of time-varying brain connectivity in the frontolimbic and sensorimotor areas may reflect abnormal dynamic neural communication between these regions and other regions of the brain, which may deepen our understanding of the disease.
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Affiliation(s)
- Yuyan 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, China
| | - Qian Cui
- School of Public Administration, University of Electronic Science and Technology of China, Chengdu, China.
| | - Ailing Xie
- School of Public Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Yajing Pang
- 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, China
| | - Wei Sheng
- 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, China
| | - Qin Tang
- 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, China
| | - Di Li
- 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, China
| | - Jing Huang
- 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, China
| | - Zongling 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, China
| | - Yifeng Wang
- 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, China
| | - Huafu 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, China.
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Faragó P, Tóth E, Kocsis K, Kincses B, Veréb D, Király A, Bozsik B, Tajti J, Párdutz Á, Szok D, Vécsei L, Szabó N, Kincses ZT. Altered Resting State Functional Activity and Microstructure of the White Matter in Migraine With Aura. Front Neurol 2019; 10:1039. [PMID: 31632336 PMCID: PMC6779833 DOI: 10.3389/fneur.2019.01039] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 09/13/2019] [Indexed: 01/18/2023] Open
Abstract
Introduction: Brain structure and function were reported to be altered in migraine. Importantly our earlier results showed that white matter diffusion abnormalities and resting state functional activity were affected differently in the two subtypes of the disease, migraine with and without aura. Resting fluctuation of the BOLD signal in the white matter was reported recently. The question arising whether the white matter activity, that is strongly coupled with gray matter activity is also perturbed differentially in the two subtypes of the disease and if so, is it related to the microstructural alterations of the white matter. Methods: Resting state fMRI, 60 directional DTI images and high-resolution T1 images were obtained from 51 migraine patients and 32 healthy volunteers. The images were pre-processed and the white matter was extracted. Independent component analysis was performed to obtain white matter functional networks. The differential expression of the white matter functional networks in the two subtypes of the disease was investigated with dual-regression approach. The Fourier spectrum of the resting fMRI fluctuations were compared between groups. Voxel-wise correlation was calculated between the resting state functional activity fluctuations and white matter microstructural measures. Results: Three white matter networks were identified that were expressed differently in migraine with and without aura. Migraineurs with aura showed increased functional connectivity and amplitude of BOLD fluctuation. Fractional anisotropy and radial diffusivity showed strong correlation with the expression of the frontal white matter network in patients with aura. Discussion: Our study is the first to describe changes in white matter resting state functional activity in migraine with aura, showing correlation with the underlying microstructure. Functional and structural differences between disease subtypes suggest at least partially different pathomechanism, which may necessitate handling of these subtypes as separate entities in further studies.
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Affiliation(s)
- Péter Faragó
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary.,Central European Institute of Technology, Brno, Czechia
| | - Eszter Tóth
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - Krisztián Kocsis
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - Bálint Kincses
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - Dániel Veréb
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - András Király
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary.,Central European Institute of Technology, Brno, Czechia
| | - Bence Bozsik
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - János Tajti
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - Árpád Párdutz
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - Délia Szok
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary
| | - László Vécsei
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary.,MTA-SZTE, Neuroscience Research Group, Szeged, Hungary
| | - Nikoletta Szabó
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary.,Central European Institute of Technology, Brno, Czechia
| | - Zsigmond Tamás Kincses
- Department of Neurology, Faculty of Medicine, Interdisciplinary Excellent Centre, University of Szeged, Szeged, Hungary.,Department of Radiology, Faculty of Medicine, University of Szeged, Szeged, Hungary
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12
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Yang F, Fan L, Zhai T, Lin Y, Wang Y, Ma J, Liao M, Zhang Y, Li L, Su L, Dai Z. Decreased Intrinsic Functional Connectivity in First-Episode, Drug-Naive Adolescents With Generalized Anxiety Disorder. Front Hum Neurosci 2019; 12:539. [PMID: 30687052 PMCID: PMC6337053 DOI: 10.3389/fnhum.2018.00539] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Accepted: 12/24/2018] [Indexed: 12/27/2022] Open
Abstract
Generalized anxiety disorder (GAD) is characterized by excessive and uncontrollable worry about everyday life. Prior neuroimaging studies have demonstrated that GAD is associated with disruptions in specific brain regions; however, little is known about the global functional connectivity maps in adolescents with GAD. Here, first-episode, medication-naive, adolescent GAD patients (N = 36) and healthy controls (N = 28) (HCs) underwent resting-state functional MRI (R-fMRI) and completed a package of questionnaires to assess clinical symptoms. Functional connectivity strength and seed-based functional connectivity were employed to investigate the functional connectivity architecture. GAD patients showed reduced functional connectivity strength in right supramarginal gyrus (SMG) and right superior parietal gyrus (SPG) compared with HCs. Further seed-based functional connectivity analysis revealed that GAD patients displayed decreased functional connectivity between right SMG and left fusiform gyrus, inferior temporal gyrus, parahippocampal gyrus, bilateral precuneus and cuneus, and between right SPG and bilateral supplementary motor area and middle cingulate gyrus, as well as between the SMG-based network and the SPG-based network. Moreover, the disrupted intra-network connectivity (i.e., the SMG-based network and the SPG-based network) and inter-network connectivity between the SMG-based network and the SPG-based network accounted for 25.5% variance of the State and Trait Anxiety Inventory (STAI) and 39.5% variance of the trait subscale of STAI. Our findings highlight the abnormal functional architecture in the SMG-based network and the SPG-based network in GAD, providing novel insights into the pathological mechanisms of this disorder.
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Affiliation(s)
- Fan Yang
- Guangdong Mental Health Center, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Linlin Fan
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Tianyi Zhai
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, China
| | - Ying Lin
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Yuyin Wang
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Junji Ma
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
| | - Mei Liao
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yan Zhang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Lingjiang Li
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Linyan Su
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhengjia Dai
- Department of Psychology, Sun Yat-sen University, Guangzhou, China
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13
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Yu S, Guo B, Shen Z, Wang Z, Kui Y, Hu Y, Feng F. The imbalanced anterior and posterior default mode network in the primary insomnia. J Psychiatr Res 2018; 103:97-103. [PMID: 29804003 DOI: 10.1016/j.jpsychires.2018.05.013] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Revised: 05/16/2018] [Accepted: 05/16/2018] [Indexed: 12/17/2022]
Abstract
Neuroimaging studies have demonstrated that the brain is altered both structurally and functionally in patients with primary insomnia (PI). However, most previous hypothesis-driven studies of PI might bias observations. Here, we use global functional connectivity density (gFCD), a hypothesis-free approach, to investigate the brain functional alteration in patients with PI. Forty-eight patients with PI and 51 matched healthy control (HC) subjects were recruited and underwent a resting state functional magnetic resonance imaging (fMRI) scan. Analyses of group differences of gFCD in the whole brain and the clinical significances of abnormal brain function were conducted. Compared with the HC group, patients with PI showed increased gFCD in the executive control network, salience network, dorsal attention network, and visual network. Interestingly, the gFCD in the anterior default mode network (DMN) is increased in the PI group, whereas the gFCD in the posterior DMN is decreased. In addition, the increased gFCD in the insula is associated with higher Pittsburgh Sleep Quality Index scores in the PI group. The gender and duration of disease have no significant effects on abnormal gFCD network. This study is the first attempt to explore the gFCD feature in patients with PI. Our findings support the hyperarousal model of insomnia and suggest an imbalanced neural spontaneous fluctuation between anterior and posterior DMN in the resting state in patients with PI. These findings expand our understanding of the neuropathological mechanism of primary insomnia.
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Affiliation(s)
- Siyi Yu
- Department of Acupuncture & Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Baojun Guo
- Department of Acupuncture & Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Zhifu Shen
- Department of Acupuncture & Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Zhengyan Wang
- Sichuan Integrative Medicine Hospital, Chengdu, Sichuan 610041, China
| | - Yu Kui
- Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510120, China
| | - Youping Hu
- Department of Acupuncture & Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Fen Feng
- Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China.
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14
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Zhang Z, Liu G, Yao Z, Zheng W, Xie Y, Hu T, Zhao Y, Yu Y, Zou Y, Shi J, Yang J, Wang T, Zhang J, Hu B. Changes in Dynamics Within and Between Resting-State Subnetworks in Juvenile Myoclonic Epilepsy Occur at Multiple Frequency Bands. Front Neurol 2018; 9:448. [PMID: 29963004 PMCID: PMC6010515 DOI: 10.3389/fneur.2018.00448] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Accepted: 05/28/2018] [Indexed: 12/01/2022] Open
Abstract
Time-varying connectivity analyses have indicated idiopathic generalized epilepsy (IGE) could cause significant abnormalities in dynamic connective pattern within and between resting-state sub-networks (RSNs). However, previous studies mainly focused on the IGE-induced dynamic changes of functional connectivity (FC) in specific frequency band (0.01–0.08 Hz or 0.01–0.15 Hz), ignoring the changes across different frequency bands. Here, 24 patients with IGE characterized by juvenile myoclonic epilepsy (JME) and 24 matched healthy controls were studied using a data-driven frequency decomposition approach and a sliding window approach. The RSN dynamics, including intra-RSN dynamics and inter-RSN dynamics, was further calculated to investigate dynamic FC changes within and between RSNs in JME patients in each decomposed frequency band. Compared to healthy controls, JME patients not only showed frequency-dependent decrease in intra-RSN dynamics within multiple RSNs but also exhibited fluctuant alterations in inter-RSN dynamics among several RSNs over different frequency bands especially in the ventral/dorsal attention network and the subcortical network. Additionally, the disease severity had significantly negative correlations with both intra-RSN dynamics within the subcortical network and inter-RSN dynamics between the subcortical network and the default network at the lower frequency band (0.0095–0.0195 Hz). These results suggested that abnormal dynamic FC within and between RSNs in JME occurs at multiple frequency bands and the lower frequency band (0.0095–0.0195 Hz) was probably more sensitive to JME-caused dynamic FC abnormalities. The frequency subdivision and selection are potentially helpful for detecting particular changes of dynamic FC in JME.
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Affiliation(s)
- Zhe Zhang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Zhijun Yao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Yuanwei Xie
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Tao Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Yu Zhao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Yue Yu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Ying Zou
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Jie Shi
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Jing Yang
- Department of Child Behavior Correction, Lanzhou University Second Hospital, Lanzhou, China
| | - Tiancheng Wang
- The Epilepsy Center of Lanzhou University Second Hospital, Lanzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
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15
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Lu J, Zhang X, Wang H, Qing Z, Han P, Li M, Xia J, Chen F, Yang B, Zhu B, Dai Y, Zhang B. Short- and long-range synergism disorders in lifelong premature ejaculation evaluated using the functional connectivity density and network property. NEUROIMAGE-CLINICAL 2018; 19:607-615. [PMID: 29984168 PMCID: PMC6029581 DOI: 10.1016/j.nicl.2018.05.025] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Revised: 04/26/2018] [Accepted: 05/20/2018] [Indexed: 11/09/2022]
Abstract
This study was aimed to investigate brain function connectivity in premature ejaculation (PE) patients using the functional connectivity density (FCD) and network property of resting-state functional magnetic resonance imaging. Twenty PE patients (mean age: 27.95 ± 4.52 years) and 15 normal controls (mean age: 27.87 ± 3.78 years) with no self-reported history of neurologic or psychiatric disease were enrolled in this study. International Index of Erectile Function-5 and Chinese Index of Sexual Function for Premature Ejaculation-5 questionnaires and self-reported intravaginal ejaculatory latency time (IELT) were obtained from each participant for symptom assessment. Two-sample t-tests (intergroup comparison) were applied in the short-range FCD (SFCD) analysis, long-range FCD (LFCD) analysis, region of interest–based analysis, and network topological organization analysis. Pearson correlation analysis was performed to correlate IELT with FCD or the network property. The patients with PE showed significantly decreased SFCD in the bilateral middle temporal gyrus, left orbitofrontal cortex, nucleus accumbens, fusiform, caudate, and thalamus (p < 0.05, AlphaSim-corrected). Notably, all these aforementioned brain areas are located in the dopamine pathway. In contrast, increased LFCD was observed in the left insula, Heschl's gyrus, putamen, bilateral precuneus, supplementary motor area, middle cingulate cortex, and anterior cingulate cortex in PE patients (p < 0.05, AlphaSim-corrected). In addition, the network topological analysis found reinforced network connectivity between several nodes. The degree of hub nodes increased in the patients with PE. IELT was positively correlated with SFCD and negatively correlated with LFCD or the degree of hub nodes (p < 0.05, Pearson correlation). In summary, our results are important for understanding the brain network in PE patients. The present findings indicate that PE patients have a significant synergism disorder across the region of dopamine pathway, which implied neuronal pathological changes might be related with the change of dopamine. The FCD and network property can serve as new disease severity biomarkers and therapeutic targets in PE. PE patients have different patterns of FCD compared with normal controls. The functional brain network efficiency has changed in PE patients. The FCD and network property can serve as disease severity biomarkers.
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Affiliation(s)
- Jiaming Lu
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Xin Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Huiting Wang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Zhao Qing
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Peng Han
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Ming Li
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Jiadong Xia
- Department of Andrology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China; Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Fei Chen
- Department of Radiology, The Affiliated Yancheng Hospital of Southeast University Medical College, Yancheng, Jiangsu, China
| | - Baibing Yang
- Department of Andrology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Bin Zhu
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Yutian Dai
- Department of Andrology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
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