A5101719245- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Neural dynamics and brain function
- Mental Health Research Topics
- Advanced MRI Techniques and Applications
- EEG and Brain-Computer Interfaces
- Attention Deficit Hyperactivity Disorder
- Fetal and Pediatric Neurological Disorders
- Traumatic Brain Injury Research
- Treatment of Major Depression
- Medical Image Segmentation Techniques
- DNA Repair Mechanisms
- Neural and Behavioral Psychology Studies
- Tryptophan and brain disorders
- Posttraumatic Stress Disorder Research
- Glaucoma and retinal disorders
- Tensor decomposition and applications
- Carcinogens and Genotoxicity Assessment
- Infant Nutrition and Health
- Psychosomatic Disorders and Their Treatments
- Pharmacological Receptor Mechanisms and Effects
- Biological Activity of Diterpenoids and Biflavonoids
- Prostate Cancer Diagnosis and Treatment
- Bioactive Compounds and Antitumor Agents
- Plasma Applications and Diagnostics
Ministry of Ecology and Environment
2024
Xinyang Normal University
2024
West China Hospital of Sichuan University
2014-2023
Sichuan University
2014-2023
University of California, Riverside
2019-2023
Guangzhou Medical University
2023
Zhongda Hospital Southeast University
2023
Affiliated Hospital of Southwest Medical University
2019-2023
Nanfang Hospital
2023
Beijing University of Chinese Medicine
2020
Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power data analysis approaches varied widely. The REST-meta-MDD Project resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups China established the Consortium by contributing R-fMRI from 1,300 patients with 1,128 normal controls (NCs). Data were preprocessed locally a standardized...
Abstract Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures reported have moderate high test-retest reliability, variability data acquisition, experimental designs, and analytic methods precludes generalize results. The Consortium for Reliability Reproducibility (CoRR) is working address this challenge establish...
Catechol estrogens and catecholamines are metabolized to quinones, the metabolite catechol (1,2-dihydroxybenzene) of leukemogenic benzene can also be oxidized its quinone. We report here that quinones obtained by enzymatic oxidation dopamine with horseradish peroxidase, tyrosinase or phenobarbital-induced rat liver microsomes react DNA 1,4-Michael addition form predominantly depurinating adducts at N-7 guanine N-3 adenine. These analogous ones formed enzymatically 4-catechol (Cavalieri,E.L.,...
Purpose To use resting-state functional magnetic resonance (MR) imaging and graph theory approaches to systematically investigate the topological organization of connectome patients with posttraumatic stress disorder (PTSD). Materials Methods This study was approved by research ethics committee, all subjects provided informed consent for participation. Seventy-six PTSD caused an earthquake 76 control who experienced same disaster were matched age, sex, years education. The underwent MR...
Abstract Children exposed to natural disasters are vulnerable the development of posttraumatic stress disorder (PTSD). Recent studies other neuropsychiatric disorders have used graph‐based theoretical analysis investigate topological properties functional brain connectome. However, little is known about this connectome in pediatric PTSD. Twenty‐eight PTSD patients and 26 trauma‐exposed non‐PTSD were recruited from 4,200 screened subjects after 2008 Sichuan earthquake undergo a resting‐state...
Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed characterize using a large multi-site sample novel network-based approach. Resting-state magnetic resonance imaging (fMRI) data were acquired from total 460 473 healthy controls, as part REST-meta-MDD consortium. networks constructed for each subject...
Major depressive disorder (MDD) is heterogeneous associated with aberrant functional connectivity within the default mode network (DMN). This study focused on data-driven identification and validation of potential DMN-pattern-based MDD subtypes to parse heterogeneity disorder. The sample comprised 1397 participants including 690 patients 707 healthy controls (HC) registered from multiple sites based REST-meta-MDD Project in China. Baseline resting-state magnetic resonance imaging (rs-fMRI)...
There have been successful applications of deep learning to functional magnetic resonance imaging (fMRI), where fMRI data were mostly considered be structured grids, and spatial features from Euclidean neighbors usually extracted by the convolutional neural networks (CNNs) in computer vision field. Recently, CNN has extended graph demonstrated superior performance. Here, we define graphs based on connectivity present a connectivity-based network (cGCN) architecture for analysis. Such an...
The thalamus is a relay center between various subcortical brain areas and the cerebral cortex with delineation of its constituent nuclei being particular interest in many applications. While previous studies have demonstrated efficacy connectivity-based segmentation, they used approaches that do not consider dynamic nature thalamo-cortical interactions. In this study, we explicitly exploited variation connections to identify different states functional connectivity performed state-specific...
The nature of hippocampal changes in schizophrenia before first treatment, and whether subfields are affected by antipsychotic treatment important questions for research. Forty-one first-episode antipsychotic-naïve acutely ill inpatients had MRI scans six weeks after treatment. Thirty-nine matched healthy controls were also scanned, twenty-two which scanned a second time later. Volumes measured via FreeSurfer v6.0 using longitudinal analysis pipeline. Before patients no significant total...
Major depressive disorder (MDD) has been associated with disruptions in the topological organization of brain morphological networks group-level data. Such have not yet identified single-patients, which is needed to show relations symptom severity and evaluate their potential as biomarkers for illness. To address this issue, we conducted a cross-sectional structural network study 33 treatment-naive, first-episode MDD patients age-, gender-, education-matched healthy controls (HCs). Weighted...
Background: Autism spectrum disorder (ASD) is a highly heterogeneous developmental with diverse clinical manifestations. Neuroimaging studies have explored functional connectivity (FC) of ASD through resting-state magnetic resonance imaging studies; however, the findings remained inconsistent, thus reflecting possibility multiple subtypes. Identification relationship between symptoms and FC measures may help clarify inconsistencies in earlier advance our understanding Methods: Canonical...
Abstract Neuroimaging studies have revealed functional brain network abnormalities in attention deficit hyperactivity disorder (ADHD), but the results been inconsistent, potentially related to confounding medication effects. Furthermore, specific topological alterations networks and their role behavioral inhibition dysfunction remain be established. Resting‐state magnetic resonance imaging was performed on 51 drug‐naïve children with ADHD 55 age‐matched healthy controls. Brain were...
In most task and resting state fMRI studies, a group consensus is often sought, where individual variability considered nuisance. None the less, biological an important factor that cannot be ignored gaining more attention in field. One recent development identification based on static functional connectome. While original work was connectome, subsequent efforts using recurrent neural networks (RNN) demonstrated inclusion of temporal features greatly improved accuracy. Given convolutional RNN...