Noninvasive medical neuroimaging has yielded many discoveries about the brain
connectivity. Several substantial techniques mapping morphological, structural and …

Modern neuroimaging techniques enable us to construct human brains as brain networks or
connectomes. Capturing brain networks' structural information and hierarchical patterns is …

Convolutional neural networks (CNNs) have shown promising results in classifying
individuals with mental disorders such as schizophrenia using resting-state fMRI data …

Static functional connections (sFCs) and dynamic functional connections (dFCs) have been
widely used in the resting-state functional MRI (rs-fMRI) analysis. sFCs, calculated based on …

Subcortical ischemic vascular disease could induce subcortical vascular cognitive
impairments (SVCIs), such as amnestic mild cognitive impairment (aMCI) and non-amnestic …

Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants
underlying the complex activity patterns of biological neuronal networks. In this study, we …

Graphs are a powerful tool for representing and analyzing unstructured, non-Euclidean data
ubiquitous in the healthcare domain. Two prominent examples are molecule property …

Depression stands as one of the most pernicious mental disorders in contemporary society,
characterized by a highly intricate pathological mechanism. Specifically, individuals …

The dynamic functional connectivity (dFC) in functional magnetic resonance imaging (fMRI)
is beneficial for the analysis and diagnosis of neurological brain diseases. The dFCs …

Alzheimer's disease (AD) is a progressive, irreversible neurodegenerative disorder that
requires early diagnosis for timely treatment. Functional magnetic resonance imaging (fMRI) …