A5073577615- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Neural dynamics and brain function
- Mental Health Research Topics
- EEG and Brain-Computer Interfaces
- Advanced MRI Techniques and Applications
- Blind Source Separation Techniques
- Electrocatalysts for Energy Conversion
- Schizophrenia research and treatment
- Electroconvulsive Therapy Studies
- Fuel Cells and Related Materials
- Health, Environment, Cognitive Aging
- Attention Deficit Hyperactivity Disorder
- Advanced battery technologies research
- Treatment of Major Depression
- Infrared Target Detection Methodologies
- Neural and Behavioral Psychology Studies
- Genetic Associations and Epidemiology
- Advancements in Solid Oxide Fuel Cells
- Transcranial Magnetic Stimulation Studies
- Heart Rate Variability and Autonomic Control
- Fractal and DNA sequence analysis
- Quantum Dots Synthesis And Properties
- Radiomics and Machine Learning in Medical Imaging
- Genetics and Neurodevelopmental Disorders
Beijing Normal University
2021-2025
Chinese Institute for Brain Research
2022-2025
Tongji University
2025
Affiliated Hospital of Southwest Medical University
2025
Deyang Stomatological Hospital
2024-2025
Center for Translational Research in Neuroimaging and Data Science
2019-2024
Georgia State University
2019-2024
Georgia Institute of Technology
2019-2024
Emory University
2019-2024
Qingdao University of Science and Technology
2014-2024
Many mental illnesses share overlapping or similar clinical symptoms, confounding the diagnosis. It is important to systematically characterize degree which unique and changing patterns are reflective of brain disorders. Increasing sharing initiatives on neuroimaging data have provided unprecedented opportunities study However, it still an open question replicating translating findings across studies. Standardized approaches for capturing reproducible comparable imaging markers greatly...
ORIGINAL RESEARCH article Front. Psychiatry, 10 January 2012Sec. Neuroimaging Volume 2 - 2011 | https://doi.org/10.3389/fpsyt.2011.00075
Abstract Subcortical ischemic vascular disease (SIVD) is a major subtype of dementia with features that overlap clinically Alzheimer's (AD), confounding diagnosis. Neuroimaging more specific and biologically based approach for detecting brain changes thus may help to distinguish these diseases. There still lack knowledge regarding the shared functional abnormalities, especially connectivity in relation AD SIVD. In this study, we investigated both static network (sFNC) dynamic FNC (dFNC)...
Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage full temporal information.Motivated by ability recurrent neural networks (RNN) in capturing information sequences, we propose a multi-scale RNN model, enables between 558 schizophrenia and 542 healthy controls using fMRI independent components (ICs) directly. To increase interpretability, also...
Brain connectivity alterations associated with mental disorders have been widely reported in both functional MRI (fMRI) and diffusion (dMRI). However, extracting useful information from the vast amount of afforded by brain networks remains a great challenge. Capturing network topology, graph convolutional (GCNs) demonstrated to be superior learning representations tailored for identifying specific disorders. Existing construction techniques generally rely on parcellation define...
Abstract Background Grip strength is a widely used and well-validated measure of overall health that increasingly understood to index risk for psychiatric illness neurodegeneration in older adults. However, existing work has not examined how grip relates comprehensive set mental outcomes, which can detect early signs cognitive decline. Furthermore, whether brain structure mediates associations between cognition remains unknown. Methods Based on cross-sectional longitudinal data from over...
Abstract Cross-sectional studies have demonstrated strong associations between physical frailty and depression. However, the evidence from prospective is limited. Here, we analyze data of 352,277 participants UK Biobank with 12.25-year follow-up. Compared non-frail individuals, pre-frail frail individuals increased risk for incident depression independent many putative confounds. Altogether, account 20.58% 13.16% cases by population attributable fraction analyses. Higher risks are observed...
We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI) single nucleotide polymorphism (SNP) data. The consists of four stages: (1) SNPs with the most discriminating information between controls are selected construct support vector ensemble (SNP-SVME). (2) Voxels in fMRI map contributing classification build another SVME (Voxel-SVME). (3) Components activation obtained independent component...
Abstract Cognitive impairment is a feature of many psychiatric diseases, including schizophrenia. Here we aim to identify multimodal biomarkers for quantifying and predicting cognitive performance in individuals with schizophrenia healthy controls. A supervised learning strategy used guide three-way magnetic resonance imaging (MRI) fusion two independent cohorts both using multiple domain scores. Results highlight the salience network (gray matter, GM), corpus callosum (fractional...
Aberrant topological properties of small-world human brain networks in patients with schizophrenia (SZ) have been documented previous neuroimaging studies. functional network connectivity (FNC, temporal relationships among independent component time courses) has also found SZ by a resting state magnetic resonance imaging (fMRI) study. However, no study yet determined if FNC are altered SZ. In this study, metrics during the were examined both healthy controls (HCs) and subjects. FMRI data...
Major depressive disorder (MDD) is a complex mood characterized by persistent and overwhelming depression. Previous studies have identified abnormalities in large scale functional brain networks MDD, yet most of them were based on static connectivity. In contrast, here we explored disrupted topological organization dynamic network connectivity (dFNC) MDD graph theory. 182 patients 218 healthy controls included this study, all Chinese Han people. By applying group information guided...