Qiyong Gong
@scu.edu.cn
Department of Radiology
Huaxi MR Research Center
To date I have published over 300 peer-reviewed articles relevant to my research focus, and those in recent five years received over 5000 citations. In particular, the MR imaging studies of first episode, medication free patients with mental disorders have been the basis for my invited reviews for journals in the field such as American Journal of Psychiatry (Gong et al. 2016; 173(3):232-43) and Biological Psychiatry (Gong et al. 2015; 77 (3), 223), and in particular, the one entitled " Psychoradiology: The Frontier of Neuroimaging in Psychiatry" has been published in Radiology (2016; 281:357–72）, the leading journal in the field of radiology. I was appointed as the associate editor of the American Journal of Psychiatry. I helped to pioneer the discovery of brain functional impairments in individuals at high risk of mental disorders and the translation of this new knowledge into predictive diagnostics for major depression. My work on multimodal characterization of schizophrenia was a selected subject for clinical CME training that helped to advance the use of MR imaging signatures/biomarkers to inform clinical management of mental health patients. Subsequent to the above accomplishments, I have been awarded with the NIBIB New Horizons Lectureship (only one out of 8000 members is selected each year) at the 23rd International Society of Magnetic Resonance in Medicine (ISMRM) Annual Meeting, where I presented on “Emerging MRI to Uncover the ‘Disordered Mind’: Are We in an Era of Psycho-Radiology?”, and I was elected as ISMRM Senior fellow in 2016. In 2019, I became one of the Highly Cited Researchers 2018 (cross field) by Clariate Analytics.
EDUCATION
Doctor of Medical Imaging, University of Liverpool School of Medicine, UK
Master of Clinical Oncology, Zhongshan Medical University, China
RESEARCH INTERESTS
My research has long been focused on translational imaging characterization of neuropsychiatric disorders with the innovative utilization of MRI in the field of psychoradiology.
Scopus Publications
Scopus Publications
Cynthia H. Y. Fu, Guray Erus, Yong Fan, Mathilde Antoniades, Danilo Arnone, Stephen R. Arnott, Taolin Chen, Ki Sueng Choi, Cherise Chin Fatt, Benicio N. Frey,et al.
Springer Science and Business Media LLC
Abstract Background Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. Methods We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. Results We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. Conclusion We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.
Tianyan Liu, Cesare De Pace, Ridong Huang, Giovanni Bruno, Tao Shao, Yupeng Tian, Bo Chen, Lei Chen, Kui Luo, Qiyong Gong,et al.
Elsevier BV
Lei Gu, Zhenyu Duan, Xue Li, Xin Li, Yinggang Li, Xiaoling Li, Gang Xu, Peng Gao, Hu Zhang, Zhongwei Gu,et al.
Elsevier BV
Lei Wang, Qing Ma, Xiaoyi Sun, Zhilei Xu, Jiaying Zhang, Xuhong Liao, Xiaoqin Wang, Dongtao Wei, Yuan Chen, Bangshan Liu,et al.
Elsevier BV
Yuchao Jiang, Wei Li, Yingjie Qin, Le Zhang, Xin Tong, Fenglai Xiao, Sisi Jiang, Yunfang Li, Qiyong Gong, Dong Zhou,et al.
Wiley
Temporal lobe epilepsy (TLE) is the most common type of intractable epilepsy in adults. Although brain myelination alterations have been observed in TLE, it remains unclear how the myelination network changes in TLE. This study developed a novel method in characterization of myelination structural covariance network (mSCN) by T1‐weighted and T2‐weighted magnetic resonance imaging (MRI). The mSCNs were estimated in 42 left TLE (LTLE), 42 right TLE (RTLE) patients, and 41 healthy controls (HCs). The topology of mSCN was analyzed by graph theory. Voxel‐wise comparisons of myelination laterality were also examined among the three groups. Compared to HC, both patient groups showed decreased myelination in frontotemporal regions, amygdala, and thalamus; however, the LTLE showed lower myelination in left medial temporal regions than RTLE. Moreover, the LTLE exhibited decreased global efficiency compared with HC and more increased connections than RTLE. The laterality in putamen was differently altered between the two patient groups: higher laterality at posterior putamen in LTLE and higher laterality at anterior putamen in RTLE. The putamen may play a transfer station role in damage spreading induced by epileptic seizures from the hippocampus. This study provided a novel workflow by combination of T1‐weighted and T2‐weighted MRI to investigate in vivo the myelin‐related microstructural feature in epileptic patients first time. Disconnections of mSCN implicate that TLE is a system disorder with widespread disruptions at regional and network levels.
Xin Xu, Xue Li, Xu Qi, Xi Jiang, Haoyang Xing, Xiaoqi Huang, and Qiyong Gong
Wiley
Theta burst stimulation (TBS) has been widely used in the treatment of mental disorders, but the cerebral functional difference between intermittent TBS (iTBS) and continuous TBS (cTBS) after one single session of stimulation is not clear. Here we applied resting‐state functional magnetic resonance imaging (RS‐FMRI) to evaluate the alterations in intrinsic brain activity after iTBS and cTBS in the precuneus. We recruited 32 healthy young adults and performed a single session each of iTBS and cTBS at a 1‐week interval. RS‐fMRI was collected at baseline before and immediately after the stimulation. Parameters for regional brain activity (ALFF/fALFF/ReHo) and functional connectivity (FC) with the stimulated site of the precuneus after iTBS and cTBS were calculated and compared between each stimulation using a paired t‐test. Correlation analysis among those parameters was calculated to explore whether changes in functional connectivity were associated with local spontaneous activity. After iTBS stimulation, fALFF increased in the bilateral precuneus, while fALFF decreased in the bilateral middle temporal gyrus. Reductions in precuneus FC were found in the bilateral cuneus, superior occipital gyrus, superior temporal gyrus, precentral gyrus, and postcentral gyrus, which correlated with regional activity. After cTBS, fALFF decreased in the bilateral insula, and precuneus FC was decreased in the bilateral inferior occipital gyrus and increased in the thalamus. In the current study, we observed that one session of iTBS or cTBS could cause inhibitory effects in remote brain regions, but only iTBS caused significant local activation in the target region.
Shengxiang Fu, Zhongyuan Cai, Li Liu, Xiaomin Fu, Changqiang Wu, Liang Du, Chunchao Xia, Su Lui, Qiyong Gong, Bin Song,et al.
American Chemical Society (ACS)
Compared to traditional branched polymers with Gd(III) chelates conjugated on their surface, branched polymers with Gd(III) chelates as the internal skeleton are considered to be a reasonable strategy for preparing efficient magnetic resonance imaging contrast agents. Herein, the Gd(III) ligand DOTA was chosen as the internal skeleton; four different molecular weights (3.5, 5.3, 8.6, and 13.1 kDa) and degrees of branching poly-DOTA branched polymers (P1, P2, P3, and P4) were synthesized by a simple "A2 + B4"-type one-pot polymerization. The Gd(III) chelates of these poly-DOTA branched polymers (P1-Gd, P2-Gd, P3-Gd, and P4-Gd) display excellent kinetic stability, which is significantly higher than those of linear Gd-DTPA and cyclic Gd-DOTA-butrol and slightly lower than that of cyclic Gd-DOTA. The T1 relaxivities of P1-Gd, P2-Gd, P3-Gd, and P4-Gd are 29.4, 38.7, 44.0, and 47.9 Gd mM-1 s-1, respectively, at 0.5 T, which are about 6-11 times higher than that of Gd-DOTA (4.4 Gd mM-1 s-1). P4-Gd was selected for in vivo magnetic resonance angiography (MRA) because of its high kinetic stability, T1 relaxivity, and good biosafety. The results showed excellent MRA effect, sensitive detection of vascular stenosis, and prolonged observation window as compared to Gd-DOTA. Overall, Gd(III) chelates of poly-DOTA branched polymers are good candidates of MRI probes, providing a unique design strategy in which Gd chelation can occur at both the interior and surface of the poly-DOTA branched polymers, resulting in excellent relaxivity enhancement. In vivo animal MRA studies of the probe provide possibilities in discovering small vascular pathologies.
Wenjing Zhang, Chengmin Yang, Zehong Cao, Zhe Li, Lihua Zhuo, Youguo Tan, Yichu He, Li Yao, Qing Zhou, Qiyong Gong,et al.
Elsevier BV
Yuxin Zhang, Jie Zhou, Xiaoting Chen, Zhiqian Li, Lei Gu, Dayi Pan, Xiuli Zheng, Qianfeng Zhang, Rongjun Chen, Hu Zhang,et al.
Elsevier BV
Xueling Suo, Chao Zuo, Huan Lan, Wenbin Li, Lingjiang Li, Graham J. Kemp, Song Wang, and Qiyong Gong
Elsevier BV
Chengmin Yang, Wenjing Zhang, Jiajun Liu, Li Yao, Jeffrey R. Bishop, Rebekka Lencer, Qiyong Gong, Zhipeng Yang, and Su Lui
Springer Science and Business Media LLC
Zhilin Li, Hao Cai, Zhiqian Li, Long Ren, Xuelei Ma, Hongyan Zhu, Qiyong Gong, Hu Zhang, Zhongwei Gu, and Kui Luo
Elsevier BV
Tao Yin, Zhaoxuan He, Yuan Chen, Ruirui Sun, Shuai Yin, Jin Lu, Yue Yang, Xiaoyan Liu, Peihong Ma, Yuzhu Qu,et al.
Oxford University Press (OUP)
Abstract Acupuncture is effective in treating functional dyspepsia (FD), while its efficacy varies significantly from different patients. Predicting the responsiveness of different patients to acupuncture treatment based on the objective biomarkers would assist physicians to identify the candidates for acupuncture therapy. One hundred FD patients were enrolled, and their clinical characteristics and functional brain MRI data were collected before and after treatment. Taking the pre-treatment functional brain network as features, we constructed the support vector machine models to predict the responsiveness of FD patients to acupuncture treatment. These features contributing critically to the accurate prediction were identified, and the longitudinal analyses of these features were performed on acupuncture responders and non-responders. Results demonstrated that prediction models achieved an accuracy of 0.76 ± 0.03 in predicting acupuncture responders and non-responders, and a R2 of 0.24 ± 0.02 in predicting dyspeptic symptoms relief. Thirty-eight functional brain network features associated with the orbitofrontal cortex, caudate, hippocampus, and anterior insula were identified as the critical predictive features. Changes in these predictive features were more pronounced in responders than in non-responders. In conclusion, this study provided a promising approach to predicting acupuncture efficacy for FD patients and is expected to facilitate the optimization of personalized acupuncture treatment plans for FD.
Yinggang Li, Zhenyu Duan, Dayi Pan, Long Ren, Lei Gu, Xiaoling Li, Gang Xu, Hongyan Zhu, Hu Zhang, Zhongwei Gu,et al.
Wiley
Tumor cells are dominant in the nutritional competition in the tumor microenvironment, and their metabolic abnormalities often lead to microenvironmental acidosis and nutrient deprivation, thereby impairing the function of immune cells and diminishing the antitumor therapeutic effect. Herein, a branched polymeric conjugate and its efficacy in attenuating the metabolic competition of tumor cells are reported. Compared with the control nanoparticles prepared from its linear counterpart, the branched‐conjugate‐based nanoparticles can more efficiently accumulate in the tumor tissue and interfere with the metabolic processes of tumor cells to increase the concentration of essential nutrients and reduce the level of immunosuppressive metabolites in the TME, thus creating a favorable environment for infiltrated immune cells. Its combined treatment with an immune checkpoint inhibitor (ICI) achieves an enhanced antitumor effect. The work presents a promising approach for targeting metabolic competition in the TME to enhance the chemo‐immunotherapeutic effect against cancers.
Xipeng Long, Lei Li, Xiuli Wang, Yuan Cao, Baolin Wu, Neil Roberts, Qiyong Gong, Graham J. Kemp, and Zhiyun Jia
Elsevier BV
Feifei Zhang, Hongsheng Xie, Song Wang, Fei Li, Qiyong Gong, and Zhiyun Jia
Elsevier BV
Hengyi Cao, Xia Wei, Wenjing Zhang, Yuan Xiao, Jiaxin Zeng, John A Sweeney, Qiyong Gong, and Su Lui
Oxford University Press (OUP)
Abstract Background Cerebellar functional dysconnectivity has long been implicated in schizophrenia. However, the detailed dysconnectivity pattern and its underlying biological mechanisms have not been well-charted. This study aimed to conduct an in-depth characterization of cerebellar dysconnectivity maps in early schizophrenia. Study design Resting-state fMRI data were processed from 196 drug-naïve patients with first-episode schizophrenia and 167 demographically matched healthy controls. The cerebellum was parcellated into nine functional systems based on a state-of-the-art atlas, and seed-based connectivity for each cerebellar system was examined. The observed connectivity alterations were further associated with schizophrenia risk gene expressions using data from the Allen Human Brain Atlas. Study results Overall, we observed significantly increased cerebellar connectivity with the sensorimotor cortex, default-mode regions, ventral part of visual cortex, insula, and striatum. In contrast, decreased connectivity was shown chiefly within the cerebellum, and between the cerebellum and the lateral prefrontal cortex, temporal lobe, and dorsal visual areas. Such dysconnectivity pattern was statistically similar across seeds, with no significant group by seed interactions identified. Moreover, connectivity strengths of hypoconnected but not hyperconnected regions were significantly correlated with schizophrenia risk gene expressions, suggesting potential genetic underpinnings for the observed hypoconnectivity. Conclusions These findings suggest a common bidirectional dysconnectivity pattern across different cerebellar subsystems, and imply that such bidirectional alterations may relate to different biological mechanisms.
Ying Chen, Xun Yang, Xun Zhang, Hengyi Cao, and Qiyong Gong
Oxford University Press (OUP)
AbstractPrevious fMRI studies have reported more random brain functional graph configurations in social anxiety disorder (SAD). However, it is still unclear whether the same configurations would occur in gray matter (GM) graphs. Structural MRI was performed on 49 patients with SAD and on 51 age- and gender-matched healthy controls (HC). Single-subject GM networks were obtained based on the areal similarities of GM, and network topological properties were analyzed using graph theory. Group differences in each topological metric were compared, and the structure–function coupling was examined. These network measures were further correlated with the clinical characteristics in the SAD group. Compared with controls, the SAD patients demonstrated globally decreased clustering coefficient and characteristic path length. Altered topological properties were found in the fronto-limbic and sensory processing systems. Altered metrics were associated with the illness duration of SAD. Compared with the HC group, the SAD group exhibited significantly decreased structural–functional decoupling. Furthermore, structural–functional decoupling was negatively correlated with the symptom severity in SAD. These findings highlight less-optimized topological configuration of the brain structural networks in SAD, which may provide insights into the neural mechanisms underlying the excessive fear and avoidance of social interactions in SAD.
Yuan Sun, Biqiu Tang, Fei Zhu, Wenjing Zhang, Youjin Zhao, Qi-Yong Gong, Na Hu and S. Lyu
Objective
To compare the structural changes along the longitudinal axis of hippocampus subfields between schizophrenia (SCZ) patients and major depressive disorder (MDD) patients in the early stage of their SCZ and MDD.
Methods
Seventy-nine first-episode drug-naïve patients with SCZ, 48 first-episode drug-naïve patients with MDD, and 79 healthy controls (HC) were recruited and underwent assessment of clinical symptoms and magnetic resonance imaging (MRI) of the head. Following the calculation of hippocampal and subfield volumes with FreeSurfer, the volume of longitudinal subfields were summed up. Inter-group comparison of these indicators was made with the data of different groups and the correlation between clinical symptoms and the volumes of longitudinal subfields was analyzed.
Results
Compared with HC, SCZ patients had smaller bilateral posterior hippocampus (left: t=－2.69, P=0.01; right: t=－2.90, P=0.004), while MDD patients exhibited no changes along the longitudinal axis of hippocampal subfields. In SCZ patients, the volume of bilateral posterior hippocampus was negatively correlated with the negative symptom scores of Positive and Negative Syndrome Scale (left: r=－0.29, P=0.01; right: r=－0.23, P=0.04).
Conclusion
The smaller posterior hippocampus may be an imaging feature for distinguishing SCZ from MDD and may have contributed to the neuropathophysiological mechanism of SCZ in the early stage of the onset of the disease.
Jinping Lin, Lei Li, Nanfang Pan, Xiqin Liu, Xun Zhang, Xueling Suo, Graham J. Kemp, Song Wang, and Qiyong Gong
Elsevier BV
Nynke A. Groenewold, Janna Marie Bas-Hoogendam, Alyssa R. Amod, Max A. Laansma, Laura S. Van Velzen, Moji Aghajani, Kevin Hilbert, Hyuntaek Oh, Ramiro Salas, Andrea P. Jackowski,et al.
Springer Science and Business Media LLC
Du Lei, Wenbin Li, Kun Qin, Yuan Ai, Maxwell J. Tallman, L. Rodrigo Patino, Jeffrey A. Welge, Thomas J. Blom, Christina C. Klein, David E. Fleck,et al.
Springer Science and Business Media LLC
Zhilin Li, Hao Cai, Zhiqian Li, Long Ren, Xuelei Ma, Hongyan Zhu, Qiyong Gong, Hu Zhang, Zhongwei Gu, and Kui Luo
Elsevier BV
Yuan Sun, Na Hu, Mingqi Wang, Lu Lu, Chunyan Luo, Biqiu Tang, Chenyang Yao, John A. Sweeney, Qiyong Gong, Changjian Qiu,et al.
CMA Impact Inc.
Background: Hippocampal disturbances are important in the pathophysiology of both schizophrenia and major depressive disorder (MDD). Imaging studies have shown selective volume deficits across hippocampal subfields in both disorders. We aimed to investigate whether these volumetric alterations in hippocampal subfields are shared or divergent across disorders. Methods: We searched PubMed and Embase from database inception to May 8, 2021. We identified MRI studies in patients with schizophrenia, MDD or both, in which hippocampal subfield volumes were measured. We excluded nonoriginal, animal or postmortem studies, and studies that used other imaging modalities or overlapping data. We conducted a network meta-analysis to estimate and contrast alterations in subfield volumes in the 2 disorders. Results: We identified 45 studies that met the initial criteria for systematic review, of which 15 were eligible for network metaanalysis. Compared to healthy controls, patients with schizophrenia had reduced volumes in the bilateral cornu ammonis (CA) 1, granule cell layer of the dentate gyrus, subiculum, parasubiculum, molecular layer, hippocampal tail and hippocampus–amygdala transition area (HATA); in the left CA4 and presubiculum; and in the right fimbria. Patients with MDD had decreased volumes in the left CA3 and CA4 and increased volumes in the right HATA compared to healthy controls. The bilateral parasubiculum and right HATA were smaller in patients with schizophrenia than in patients with MDD. Limitations: We did not investigate medication effects because of limited information. Study heterogeneity was noteworthy in direct comparisons between patients with MDD and healthy controls. Conclusion: The volumes of multiple hippocampal subfields are selectively altered in patients with schizophrenia and MDD, with overlap and differentiation in subfield alterations across disorders. Rigorous head-to-head studies are needed to validate our findings.
Biqiu Tang, Wenjing Zhang, Jiang Liu, Shikuang Deng, Na Hu, Siyi Li, Youjin Zhao, Nian Liu, Jiaxin Zeng, Hengyi Cao,et al.
Oxford University Press (OUP)
AbstractUnderstanding how structural connectivity alterations affect aberrant dynamic function using network control theory will provide new mechanistic insights into the pathophysiology of schizophrenia. The study included 140 drug-naive schizophrenia patients and 119 healthy controls (HCs). The average controllability (AC) quantifying capacity of brain regions/networks to shift the system into easy-to-reach states was calculated based on white matter connectivity and was compared between patients and HCs as well as functional network topological and dynamic properties. The correlation analysis between AC and duration of untreated psychosis (DUP) were conducted to characterize the controllability progression pattern without treatment effects. Relative to HCs, patients exhibited reduced AC in multiple nodes, mainly distributed in default mode network (DMN), visual network (VN), and subcortical regions, and increased AC in somatomotor network. These networks also had impaired functional topology and increased temporal variability in dynamic functional connectivity analysis. Longer DUP was related to greater reductions of AC in VN and DMN. The current study highlighted potential structural substrates underlying altered functional dynamics in schizophrenia, providing a novel understanding of the relationship of anatomic and functional network alterations.
RECENT SCHOLAR PUBLICATIONS
Publications
1. Lui S, Li T, Deng W, Jiang L, Wu Q, Tang H, Yue Q, Huang X, Chan RC, Collier DA, Meda SA, Pearlson G, Mechelli A, Sweeney JA, Gong Q. Short-term Effects of Antipsychotic Treatment on Cerebral Function in Drug-naive First-episode Schizophrenia Revealed by “Resting-State” Functional Magnetic Resonance Imaging. Archives of General Psychiatry. 2010; 67(8): 783-92. (IF=14.48)
2. Sun H, Lui S, Yao L, Deng W, Xiao Y, Zhang W, Huang X, Hu J, Bi F, Li T, Sweeney JA, Gong Q. Two Patterns of White Matter Abnormalities in Medication-Naive Patients With First-Episode Schizophrenia Revealed by Diffusion Tensor Imaging and Cluster Analysis. JAMA Psychiatry. 2015; 72(7):678-86. (IF=14.417)
3. Lui S, Deng W, Huang X, Jiang L, Ma X, Chen H, Zhang T, Li X, Li D, Zou L, Tang H, Zhou XJ, Mechelli A, Collier DA, Sweeney JA, Li T, Gong Q. Association of cerebral deficits with clinical symptoms in antipsychotic-naive first episode schizophrenia: an optimized voxel-based morphometry and resting state functional connectivity study. Am J Psychiatry. 2009; 166:196-205. (IF=13.505)
4. Lui S, Wu Q, Qiu L, Yang X, Kuang W, Chan RCK, Huang X, Kemp G, Mechelli A, Gong Q. Resting-state functional connectivity in treatment-resistant depression. Am J Psychiatry. 2011;168(6):642-8. (IF=13.505)
5. Jia Z, Huang X, Wu Q, Zhang T, Lui S, Zhang J, Amatya N, Kuang W, Chan RCK, Kemp GJ, Mechelli A, Gong Q. High-field Magnetic Resonance Imaging of Suicidality in Patients with Major Depressive Disorder. Am J Psychiatry. 2010; 167:1381-1390. (IF=13.505)
6. Ren W, Lui S, Deng W, Li F, Li M, Huang X, Wang Y, Li T, Sweeney JA, GongQ. Anatomical and Functional Brain Abnormalities in Drug-Naive First-Episode Schizophrenia. Am J Psychiatry. 2013; 170(11):1308-16. Epub 2013 Jun 4. (IF=13.505)
7. Gong Q, Lui S, Sweeney JA. A Selective Review of Cerebral Abnormalities in Patients with First-Episode Schizophrenia Before and After Treatment. Am J Psychiatry. 2016; 173(3):232-43. (IF=13.505)
8. Gong Q, He Y. Depression, Neuroimaging and Connectomics: A Selective Overview. Biological Psychiatry. 2015; 77(3):223-35. (IF=11.212)
9. Zhang J, Wang J, Wu QZ, Kuang WH, Huang X, He Y, Gong Q. Disrupted Brain Connectivity Networks in Drug-Naive, First-Episode Major DepressiveDisorder. Biological Psychiatry. 2011; 70(4):334-42. (IF=11.212)
10. Lui S, Huang X, Chen L, Tang H, Zhang T, Li X, Li D, Kuang W, Chan RC, Mechelli A, Sweeney JA, Gong Q. High-field MRI Reveals an Acute Impact on Brain Function in Survivors of the Magnitude 8.0 Earthquake in China. P Natl Acad Sci USA. 2009;106 (36):15412–17 (IF= 9.423）
GRANT DETAILS
1. National Natural Science Foundation of China Key International (Regional) Cooperative Research Project (Project Number: 81820108018): Research on biomarkers and subtypes of mood-related disorders
2. National Institutes of Health (NIH)-National Natural Science Foundation (NSFC) Biomedical Cooperative Research Project (NIH/NIMH Project Code: R01MH112189-01; NSFC Project Code: 81761128023): Neurobiological Mechanism of Early Schizophrenia Longitudinal study
3. Major International (Regional) Cooperative Research Project of National Natural Science Foundation of China (Project Code: 81220108013): High-field magnetic resonance imaging research on the efficacy evaluation and treatment plan optimization of affective disorders
4. National Natural Science Instrument Basic Research Project (Project Code: 81227002): Brain functional magnetic resonance visual stimulation and eye movement analysis system based on real-time feedback
5. The Ministry of Science and Technology's Twelfth Five-Year National Science and Technology Support Plan (Project 46: [2012BAI01B00] Key Technology Research for the Prevention and Treatment of Major Mental Diseases) (Project Number: 2012BAI01B03): Establishment and Application of Early Diagnosis and Evaluation System for Depression and Anxiety Disorders
6. National Natural Science Foundation of China (Project Code: 81030027): Research on the diagnosis model and pathological mechanism of depression based on multimodal neuroimaging and massive data
7. National High-Tech Research and Development Program Funding (863 Program Project No.: 2008AA02Z408): Research on New Technology of Magnetic Resonance Imaging Diagnosis of Anxiety Disorders