A5026540184- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Mental Health Research Topics
- Advanced MRI Techniques and Applications
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Electroconvulsive Therapy Studies
- Treatment of Major Depression
- Genetics and Neurodevelopmental Disorders
- Autism Spectrum Disorder Research
- Neural and Behavioral Psychology Studies
- Transcranial Magnetic Stimulation Studies
- Schizophrenia research and treatment
- Dementia and Cognitive Impairment Research
- Blind Source Separation Techniques
- Brain Tumor Detection and Classification
- Congenital heart defects research
- Complex Network Analysis Techniques
- Child and Adolescent Psychosocial and Emotional Development
- Alzheimer's disease research and treatments
- Attention Deficit Hyperactivity Disorder
- Cognitive Abilities and Testing
- Frailty in Older Adults
- Bioinformatics and Genomic Networks
- Heart Rate Variability and Autonomic Control
Nanjing University of Aeronautics and Astronautics
2021-2025
Yale University
2024
Georgia Institute of Technology
2019-2024
Georgia State University
2019-2024
Emory University
2019-2024
Center for Translational Research in Neuroimaging and Data Science
2019-2024
University of Maryland, College Park
2024
Emory and Henry College
2020-2021
Mind Research Network
2018-2019
University of Chinese Academy of Sciences
2017-2018
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...
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...
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...
Although both resting and task-induced functional connectivity (FC) have been used to characterize the human brain cognitive abilities, potential of FCs in individualized prediction for out-of-scanner traits remains largely unexplored. A recent study Greene et al. (2018) predicted fluid intelligence scores using derived from rest multiple task conditions, suggesting that state manipulation improved individual traits. Here, a large dataset incorporating fMRI data 7 distinct we replicated...
Abstract Scores on intelligence tests are strongly predictive of various important life outcomes. However, the gender discrepancy quotient (IQ) prediction using brain imaging variables has not been studied. To this aim, we predicted individual IQ scores for males and females separately whole-brain functional connectivity (FC). Robust predictions intellectual capabilities were achieved across three independent data sets (680 subjects) two measurements (IQ fluid intelligence) same model within...
Cognitive decline is amongst one of the most commonly reported complaints during normal aging. Despite evidence that age and cognition are linked with similar neural correlates, no previous studies have directly ascertained how these two constructs overlap in brain terms neuroimaging-based prediction. Based on a long lifespan healthy cohort (CamCAN, aged 19-89 years, n = 567), it shown both cognitive function (domains spanning executive function, emotion processing, motor memory) human can...
There is compelling evidence that epigenetic factors contribute to the manifestation of depression, in which microRNA132 (miR-132) suggested play a pivotal role pathogenesis and neuronal mechanisms underlying symptoms depression. Additionally, several depression-associated genes [MECP2, ARHGAP32 (p250GAP), CREB, period genes] were experimentally validated as miR-132 targets. However, most studies regarding major depressive disorder are based on post-mortem, animal models or genetic...
By exploiting cross-information among multiple imaging data, multimodal fusion has often been used to better understand brain diseases. However, most current approaches are blind, without adopting any prior information. There is increasing interest uncover the neurocognitive mapping of specific clinical measurements on enriched data; hence, a supervised, goal-directed model that employs information as reference guide data much needed and becomes natural option. Here, we proposed with called...
Abstract Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia scores (PRS) from healthy white people within the UK Biobank dataset ( N = 22,459), we discovered robust PRS-associated pattern with smaller gray...
Chronic liver diseases of all etiologies exist along a spectrum with varying degrees hepatic fibrosis. Despite accumulating evidence implying associations between fibrosis and cognitive functioning, there is limited research exploring the underlying neurobiological factors possible mediating role inflammation on liver-brain axis.
Abstract Schizophrenia (SZ) is a debilitating mental illness characterized by adolescence or early adulthood onset of psychosis, positive and negative symptoms, as well cognitive impairments. Despite plethora studies leveraging functional connectivity (FC) from magnetic resonance imaging (fMRI) to predict symptoms impairments SZ, the findings have exhibited great heterogeneity. We aimed identify congruous replicable patterns capable predicting in SZ. Predictable connections (FCs) were...
Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such schizophrenia (SZ). In this article, we aim investigate the abnormalities underlying SZ large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four magnetic resonance (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) structural fractional anisotropy (FA) diffusion and...
Abstract Schizophrenia (SZ) and autism spectrum disorder (ASD) share considerable clinical features intertwined historical roots. It is greatly needed to explore their similarities differences in pathophysiologic mechanisms. We assembled a large sample size of neuroimaging data (about 600 SZ patients, 1000 ASD 1700 healthy controls) study the shared unique brain abnormality two illnesses. analyzed multi-scale functional connectivity among networks regions, intra-network connectivity,...
Abstract Background The heterogeneity inherent in autism spectrum disorder (ASD) presents a substantial challenge to diagnosis and precision treatment. Heterogeneity across biological etiologies, genetics, neural systems, neurocognitive attributes clinical subtypes or phenotypes has been observed individuals with ASD. Methods In this study, we aim investigate the ASD from multimodal brain imaging perspective. Autism Diagnostic Observation Schedule (ADOS) was used as reference guide...
Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response ECT remains a priority individually tailor treatment understand mechanisms. This study connectome-based modeling (CPM) approach in 122 patients with DEP determine if pre-ECT whole-brain functional connectivity (FC) predicts rating changes remission status after (47 total subjects or 38.5% sample), whether longitudinal...
There is growing evidence that rather than using a single brain imaging modality to study its association with physiological or symptomatic features, the field paying more attention fusion of multimodal information. However, most current approaches incorporate functional magnetic resonance (fMRI) are restricted second-level 3D original 4D fMRI data. This trade-off valuable temporal information not utilized during step. Here we motivated propose novel approach called "parallel group ICA+ICA"...
Background: Electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder. Recently, there has been increasing attention to evaluate effect ECT on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims compare rs-fMRI disorder (DEP) patients with healthy participants, investigate whether pre-ECT dynamic network connectivity (dFNC) estimated from associated an eventual outcome, and explore brain states. Method: Resting-state...
Predictive modeling of neuroimaging data (predictive neuroimaging) for evaluating individual differences in various behavioral phenotypes and clinical outcomes is growing interest. However, the field experiencing challenges regarding interpretability results. Approaches to defining specific contribution functional connections, regions, or networks prediction models are urgently needed, which may help explore underlying mechanisms. In this article, we systematically review methods...