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Fateh AA, Smahi A, Hassan M, Mo T, Hu Z, Mohammed AAQ, Hu Y, Massé CC, Chen L, Chen Y, Liao J, Zeng H. From brain connectivity to cognitive function: Dissecting the salience network in pediatric BECTS-ESES. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111110. [PMID: 39069247 DOI: 10.1016/j.pnpbp.2024.111110] [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: 03/25/2024] [Revised: 07/19/2024] [Accepted: 07/24/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND Benign childhood epilepsy with centrotemporal spikes (BECTS), a common pediatric epilepsy, may lead to cognitive decline when compounded by Electrical Status Epilepticus during Sleep (ESES). Emerging evidence suggests that disruptions in the Salience Network (SN) contribute significantly to the cognitive deficits observed in BECTS-ESES. Our study rigorously investigates the dynamic functional connectivity (dFC) within the SN and its correlation with cognitive impairments in BECTS-ESES, employing advanced neuroimaging and neuropsychological assessments. METHODS In this research, 45 patients diagnosed with BECTS-ESES and 55 age-matched healthy controls (HCs) participated. We utilized resting-state functional magnetic resonance imaging (fMRI) and Independent Component Analysis (ICA) to identify three fundamental SN nodes: the right Anterior Insula (rAI), left Anterior Insula (lAI), and the Anterior Cingulate Cortex (ACC). A two-sample t-test facilitated the comparison of dFC between these pivotal regions and other brain areas. RESULTS Significantly, the BECTS-ESES group demonstrated increased dFC, particularly between the ACC and the right Middle Occipital Gyrus, and from the rAI to the right Superior Parietal Gyrus and Cerebellum, and from the lAI to the left Postcentral Gyrus. Such dFC augmentations provide neural insights potentially explaining the neuropsychological deficits in BECTS-ESES children. Employing comprehensive neuropsychological evaluations, we mapped these dFC disruptions to specific cognitive impairments encompassing memory, executive functioning, language, and attention. Through multiple regression analysis and path analysis, a preliminary but compelling association was discovered linking dFC disturbances directly to cognitive impairments. These findings underscore the critical role of SN disruptions in BECTS-ESES cognitive dysfunctions. LIMITATION Our cross-sectional design and analytic methods preclude definitive mediation models and causal inferences, leaving the precise nature of dFC's mediating role and its direct impact by BECTS-ESES partially unresolved. Future longitudinal and confirmatory studies are needed to comprehensively delineate these associations. CONCLUSION Our study heralds dFC within the SN as a vital biomarker for cognitive impairment in pediatric epilepsy, advocating for targeted cognitive-specific interventions in managing BECTS-ESES. The preliminary nature of our findings invites further studies to substantiate these associations, offering profound implications for the prognosis and therapeutic strategies in BECTS-ESES, thereby underlining the importance of this research in the field of pediatric neurology and epilepsy management.
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Affiliation(s)
- Ahmed Ameen Fateh
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Abla Smahi
- Shenzhen Graduate School, Peking University, Shenzhen, China
| | - Muhammad Hassan
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Tong Mo
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Zhanqi Hu
- Department of Neurology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Adam A Q Mohammed
- School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
| | - Yan Hu
- Department of Neurology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Cristina Cañete Massé
- Psychology, Sciences of Education and Sport, Blanquerna, Ramon Llull University, Barcelona, Spain; Department of Social Psychology and Quantitative Psychology, Faculty of Psychology, Universitat de Barcelona, Barcelona, Spain
| | - Li Chen
- Department of Neurology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Yan Chen
- Department of Neurology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Jianxiang Liao
- Department of Neurology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Hongwu Zeng
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China.
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Chen G, Guo Z, Chen P, Yang Z, Yan H, Sun S, Ma W, Zhang Y, Qi Z, Fang W, Jiang L, Tao Q, Wang Y. Bright light therapy-induced improvements of mood, cognitive functions and cerebellar functional connectivity in subthreshold depression: A randomized controlled trial. Int J Clin Health Psychol 2024; 24:100483. [PMID: 39101053 PMCID: PMC11296024 DOI: 10.1016/j.ijchp.2024.100483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 06/25/2024] [Indexed: 08/06/2024] Open
Abstract
Background The efficacy of bright light therapy (BLT) in ameliorating depression has been validated. The present study is to investigate the changes of depressive symptoms, cognitive function and cerebellar functional connectivity (FC) following BLT in individuals with subthreshold depression (StD). Method Participants were randomly assigned to BLT group (N = 47) or placebo (N = 41) in this randomized controlled trial between March 2020 and June 2022. Depression severity and cognitive function were assessed, as well as resting-state functional MRI scan was conducted before and after 8-weeks treatment. Seed-based whole-brain static FC (sFC) and dynamic FC (dFC) analyses of the bilateral cerebellar subfields were conducted. Besides, a multivariate regression model examined whether baseline brain FC was associated with changes of depression severity and cognitive function during BLT treatment. Results After 8-week BLT treatment, individuals with StD showed improved depressive symptoms and attention/vigilance cognitive function. BLT also increased sFC between the right cerebellar lobule IX and left temporal pole, and decreased sFC within the cerebellum, and dFC between the right cerebellar lobule IX and left medial prefrontal cortex. Moreover, the fusion of sFC and dFC at baseline could predict the improvement of attention/vigilance in response to BLT. Conclusions The current study identified that BLT improved depressive symptoms and attention/vigilance, as well as changed cerebellum-DMN connectivity, especially in the cerebellar-frontotemporal and cerebellar internal FC. In addition, the fusion features of sFC and dFC at pre-treatment could serve as an imaging biomarker for the improvement of attention/vigilance cognitive function after BLT in StD.
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Affiliation(s)
- Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Zixuan Guo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Zibin Yang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Hong Yan
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Shilin Sun
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Wenhao Ma
- Department of Public Health and Preventive Medicine, School of Basic Medicine, Jinan University, Guangzhou 510632, China
- Division of Medical Psychology and Behavior Science, School of Basic Medicine, Jinan University, Guangzhou 510632, China
| | - Yuan Zhang
- Department of Public Health and Preventive Medicine, School of Basic Medicine, Jinan University, Guangzhou 510632, China
- Division of Medical Psychology and Behavior Science, School of Basic Medicine, Jinan University, Guangzhou 510632, China
| | - Zhangzhang Qi
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Wenjie Fang
- Department of Public Health and Preventive Medicine, School of Basic Medicine, Jinan University, Guangzhou 510632, China
- Division of Medical Psychology and Behavior Science, School of Basic Medicine, Jinan University, Guangzhou 510632, China
| | - Lijun Jiang
- Department of Public Health and Preventive Medicine, School of Basic Medicine, Jinan University, Guangzhou 510632, China
- Division of Medical Psychology and Behavior Science, School of Basic Medicine, Jinan University, Guangzhou 510632, China
| | - Qian Tao
- Department of Public Health and Preventive Medicine, School of Basic Medicine, Jinan University, Guangzhou 510632, China
- Division of Medical Psychology and Behavior Science, School of Basic Medicine, Jinan University, Guangzhou 510632, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
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Huang D, Lai S, Zhong S, Zhang Y, He J, Yan S, Huang X, Lu X, Duan M, Song K, Ye K, Chen Y, Ye S, Lai J, Zhong Q, Song X, Jia Y. Sex-differential cognitive performance on MCCB of youth with BD-II depression. BMC Psychiatry 2024; 24:345. [PMID: 38714952 PMCID: PMC11077867 DOI: 10.1186/s12888-024-05701-7] [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: 02/07/2023] [Accepted: 03/20/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Recent evidences have shown sex-differential cognitive deficits in bipolar disorder (BD) and differences in cognitions across BD subtypes. However, the sex-specific effect on cognitive impairment in BD subtype II (BD-II) remains obscure. The aim of the current study was to examine whether cognitive deficits differ by gender in youth with BD-II depression. METHOD This cross-sectional study recruited 125 unmedicated youths with BD-II depression and 140 age-, sex-, and education-matched healthy controls (HCs). The Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) was used to assess cognitive functions. Mood state was assessed using the 24-item Hamilton Depression Rating Scale (24-HDRS) and the Young Mania Rating Scale (YMRS). Multivariate analysis of covariance (MANCOVA) was conducted. RESULT Compared with HCs, patients with BD-II depression had lower scores on MCCB composite and its seven cognitive domains (all p < 0.001). After controlling for age and education, MANCOVA revealed significant gender-by-group interaction on attention/vigilance (F = 6.224, df = 1, p = 0.013), verbal learning (F = 9.847, df = 1, p = 0.002), visual learning (F = 4.242, df = 1, p = 0.040), and composite (F = 8.819, df = 1, p = 0.003). Post hoc analyses suggested that males performed worse in the above-mentioned MCCB tests than females in BD-II depression. CONCLUSION Our study demonstrated generalized cognitive deficits in unmedicated youths with BD-II depression. Male patients performed more serious cognitive impairment on attention/vigilance, verbal learning, and visual learning compared to female patients.
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Affiliation(s)
- Dong Huang
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Shunkai Lai
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Yiliang Zhang
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Jiali He
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Shuya Yan
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Xiaosi Huang
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Xiaodan Lu
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Manying Duan
- School of Management, Jinan University, Guangzhou, 510316, China
| | - Kailin Song
- School of Management, Jinan University, Guangzhou, 510316, China
| | - Kaiwei Ye
- School of Management, Jinan University, Guangzhou, 510316, China
| | - Yandi Chen
- School of Management, Jinan University, Guangzhou, 510316, China
| | - Suiyi Ye
- School of Management, Jinan University, Guangzhou, 510316, China
| | - Jiankang Lai
- School of Management, Jinan University, Guangzhou, 510316, China
| | - Qilin Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Xiaodong Song
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.
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Wang H, Zhu Z, Bi H, Jiang Z, Cao Y, Wang S, Zou L. Changes in Community Structure of Brain Dynamic Functional Connectivity States in Mild Cognitive Impairment. Neuroscience 2024; 544:1-11. [PMID: 38423166 DOI: 10.1016/j.neuroscience.2024.02.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/22/2024] [Accepted: 02/24/2024] [Indexed: 03/02/2024]
Abstract
Recent researches have noted many changes of short-term dynamic modalities in mild cognitive impairment (MCI) patients' brain functional networks. In this study, the dynamic functional brain networks of 82 MCI patients and 85 individuals in the normal control (NC) group were constructed using the sliding window method and Pearson correlation. The window size was determined using single-scale time-dependent (SSTD) method. Subsequently, k-means was applied to cluster all window samples, identifying three dynamic functional connectivity (DFC) states. Collective sparse symmetric non-negative matrix factorization (cssNMF) was then used to perform community detection on these states and quantify differences in brain regions. Finally, metrics such as within-community connectivity strength, community strength, and node diversity were calculated for further analysis. The results indicated high similarity between the two groups in state 2, with no significant differences in optimal community quantity and functional segregation (p < 0.05). However, for state 1 and state 3, the optimal community quantity was smaller in MCI patients compared to the NC group. In state 1, MCI patients had lower within-community connectivity strength and overall strength than the NC group, whereas state 3 showed results opposite to state 1. Brain regions with statistical difference included MFG.L, ORBinf.R, STG.R, IFGtriang.L, CUN.L, CUN.R, LING.R, SOG.L, and PCUN.R. This study on DFC states explores changes in the brain functional networks of patients with MCI from the perspective of alterations in the community structures of DFC states. The findings could provide new insights into the pathological changes in the brains of MCI patients.
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Affiliation(s)
- Hongwei Wang
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Zhihao Zhu
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Hui Bi
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Zhongyi Jiang
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Yin Cao
- The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, Jiangsu 213164, China
| | - Suhong Wang
- Clinical Psychology, The Third Affiliated Hospital of Soochow University, Juqian Road No. 185, Changzhou, Jiangsu 213164, China
| | - Ling Zou
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, Jiangsu 213164, China; The Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou, Zhejiang 310018, China.
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Zhang X, Zhou Y, Chen Y, Zhao S, Zhou B, Sun X. The association between neuroendocrine/glucose metabolism and clinical outcomes and disease course in different clinical states of bipolar disorders. Front Psychiatry 2024; 15:1275177. [PMID: 38328763 PMCID: PMC10847283 DOI: 10.3389/fpsyt.2024.1275177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 01/04/2024] [Indexed: 02/09/2024] Open
Abstract
Objective The treatment of bipolar disorder (BD) remains challenging. The study evaluated the impact of the hypothalamic-pituitary-adrenal (HPA) axis/hypothalamic-pituitary-thyroid (HPT) axis and glucose metabolism on the clinical outcomes in patients with bipolar depression (BD-D) and manic bipolar (BD-M) disorders. Methods The research design involved a longitudinal prospective study. A total of 500 BD patients aged between 18 and 65 years treated in 15 hospitals located in Western China were enrolled in the study. The Young Mania Rating Scale (YMRS) and Montgomery and Asberg Depression Rating Scale (MADRS) were used to assess the BD symptoms. An effective treatment response was defined as a reduction in the symptom score of more than 25% after 12 weeks of treatment. The score of symptoms was correlated with the homeostatic model assessment of insulin resistance (HOMA-IR) index, the HPA axis hormone levels (adrenocorticotropic hormone (ACTH) and cortisol), and the HPT axis hormone levels (thyroid stimulating hormone (TSH), triiodothyronine (T3), thyroxine (T4), free triiodothyronine (fT3), and free thyroxine (fT4)). Results In the BD-M group, the YMRS was positively correlated with baseline T4 (r = 0.349, p = 0.010) and fT4 (r = 0.335, p = 0.013) and negatively correlated with fasting insulin (r = -0.289, p = 0.013). The pre-treatment HOMA-IR was significantly correlated with adverse course (p = 0.045, OR = 0.728). In the BD-D group, the baseline MADRS was significantly positively correlated with baseline fT3 (r = 0.223, p = 0.032) and fT4 (r = 0.315, p = 0.002), while baseline T3 (p = 0.032, OR = 5.071) was significantly positively related to treatment response. Conclusion The HPT axis and glucose metabolism were closely associated with clinical outcomes at 12 weeks in both BD-D and BD-M groups. If confirmed in further longitudinal studies, monitoring T3 in BD-D patients and HOMA-IR for BD-M could be used as potential treatment response biomarkers.
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Affiliation(s)
- Xu Zhang
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China
| | - Yaling Zhou
- The Fourth People’s Hospital of Chengdu, Chengdu, China
| | - Yuexin Chen
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China
| | - Shengnan Zhao
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Bo Zhou
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xueli Sun
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
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Zhong S, Chen N, Lai S, Shan Y, Li Z, Chen J, Luo A, Zhang Y, Lv S, He J, Wang Y, Yao Z, Jia Y. Association between cognitive impairments and aberrant dynamism of overlapping brain sub-networks in unmedicated major depressive disorder: A resting-state MEG study. J Affect Disord 2023; 320:576-589. [PMID: 36179776 DOI: 10.1016/j.jad.2022.09.069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 08/24/2022] [Accepted: 09/20/2022] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Little is known about the pathogenesis underlying cognitive impairment in major depressive disorder (MDD). We aimed to explore the mechanisms of cognitive impairments among patients with MDD by investigating the dynamics of overlapping brain sub-networks. METHODS Forty unmedicated patients with MDD and 28 healthy controls (HC) were enrolled in this study. Cognitive function was measured using the Chinese versions of MATRICS Consensus Cognitive Battery (MCCB). All participants were scanned using a whole-head resting-state magnetoencephalography (MEG) machine. The dynamism of neural sub-networks was analyzed based on the detection of overlapping communities in five frequency bands of oscillatory brain signals. RESULTS MDD demonstrated poorer cognitive performance in six domains compared to HC. The difference in community detection (functional integration mode) in MDD was frequency-dependent. MDD showed significantly decreased community dynamics in all frequency bands compared to HC. Specifically, differences in the visual network (VN) and default mode network (DMN) were detected in all frequency bands, differences in the cognitive control network (CCN) were detected in the alpha2 and beta frequency bands, and differences in the bilateral limbic network (BLN) were only detected in the beta frequency band. Moreover, community dynamics in the alpha2 frequency band were positively correlated with verbal learning and reasoning problem solving abilities in MDD. CONCLUSIONS Our study found that decreasing in the dynamics of overlapping sub-networks may differ by frequency bands. The aberrant dynamics of overlapping neural sub-networks revealed by frequency-specific MEG signals may provide new information on the mechanism of cognitive impairments that result from MDD.
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Affiliation(s)
- Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Nan Chen
- School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Shunkai Lai
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Yanyan Shan
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Zhinan Li
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Junhao Chen
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Aiming Luo
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Yiliang Zhang
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Sihui Lv
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Jiali He
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital, Jinan University, Guangzhou 510630, China.
| | - Zhijun Yao
- School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China.
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China.
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