Most neuroscience cognitive experiments involve repeated presentations of various stimuli
across several minutes or a few hours. It has been observed that brain responses, even to …

This book explores various state-of-the-art aspects behind the statistical analysis of
neuroimaging data. It examines the development of novel statistical approaches to model …

Human brain effective connectivity characterizes the causal effects of neural activities
among different brain regions. Studies of brain effective connectivity networks (ECNs) for …

We consider the challenges in estimating the state-related changes in brain connectivity
networks with a large number of nodes. Existing studies use the sliding-window analysis or …

Objective: This paper addresses the critical problem of estimating time-evolving effective
brain connectivity. Current approaches based on sliding window analysis or time-varying …

Abstract Model selection is often implicit: when performing an ANOVA, one assumes that the
normal distribution is a good model of the data; fitting a tuning curve implies that an additive …

Understanding the mechanism sustaining cardiac fibrillation can facilitate the
personalization of treatment. Granger causality analysis can be used to determine the …

To study the effective connectivity among sources in a densely voxelated (high-dimensional)
cortical surface, we develop the source-space factor VAR model. The first step in our …

Objective: Brain dynamic effective connectivity (dEC), characterizes the information
transmission patterns between brain regions that change over time, which provides insight …

Granger causality (GC) is one of the most popular measures to investigate causality
influence among brain regions and has been achieved significant results for exploring brain …