A graphical model is a statistical model that is associated with a graph whose nodes
correspond to variables of interest. The edges of the graph reflect allowed conditional …

Abstract In 2011, the “ADHD-200 Global Competition” was held with the aim of identifying
biomarkers of attention-deficit/hyperactivity disorder from resting-state functional magnetic …

Many important problems can be modeled as a system of interconnected entities, where
each entity is recording time-dependent observations or measurements. In order to spot …

Brain functional connectivity (FC) network, estimated with resting‐state functional magnetic
resonance imaging (RS‐fMRI) technique, has emerged as a promising approach for …

In conventional resting-state functional MRI (R-fMRI) analysis, functional connectivity is
assumed to be temporally stationary, overlooking neural activities or interactions that may …

The development of advanced medical imaging technologies and high-throughput genomic
measurements has enhanced our ability to understand their interplay as well as their …

Dynamic network analysis using resting-state functional magnetic resonance imaging (rs-
fMRI) provides a great insight into fundamentally dynamic characteristics of human brains …

We consider the problem of learning a high-dimensional graphical model in which there are
a few hub nodes that are densely-connected to many other nodes. Many authors have …

Motivation: Imaging genetics combines brain imaging and genetic information to identify the
relationships between genetic variants and brain activities. When the data samples belong …

Following recent technological revolutions, the investigation of massive biomedical data with
growing scale, diversity, and complexity has taken a center stage in modern data analysis …