Biological networks are commonly used in biomedical and healthcare domains to effectively
model the structure of complex biological systems with interactions linking biological entities …

Multi-agent dynamical systems refer to scenarios where multiple units (aka agents) interact
with each other and evolve collectively over time. For instance, people's health conditions …

The human brain is the central hub of the neurobiological system, controlling behavior and
cognition in complex ways. Recent advances in neuroscience and neuroimaging analysis …

Recent neuroimaging studies have highlighted the importance of network-centric brain
analysis, particularly with functional magnetic resonance imaging. The emergence of Deep …

Brain networks, graphical models such as those constructed from MRI, have been widely
used in pathological prediction and analysis of brain functions. Within the complex brain …

Parkinson's Disease (PD), one of the most common neurological disorders, has long been a
challenge in public health clinical diagnosis as well as scientific understanding. Recently …

Functional magnetic resonance imaging (fMRI) is a commonly used technique to measure
neural activation. Its application has been particularly important in identifying underlying …

In recent years, Graph Neural Networks (GNNs) have made significant advances in
processing structured data. However, most of them primarily adopted a model-centric …

Understanding the complex mechanisms of the brain can be unraveled by extracting the
Dynamic Effective Connectome (DEC). Recently, score-based Directed Acyclic Graph (DAG) …

Recent advancements in neuroimaging techniques have sparked a growing interest in
understanding the complex interactions between anatomical regions of interest (ROIs) …