Assessing uncertainty in dynamic functional connectivity

Assessing dynamic functional connectivity in heterogeneous samples

Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brain's functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured ...

Dynamic functional connectivity.

Recent studies show that anatomical and functional brain networks exhibit similar small-world properties. However, the networks that are compared often differ in what the nodes represent (e.g. sensors or brain areas), what kind of connectivity is measured, and what temporal and spatial scales are probed. Here, I review studies of large-scale connectivity and recent results from a variety of rea...

Evaluation of Model-Based Methods in Estimating Dynamic Functional Connectivity of Brain Regions

Today, neuroscientists are interested in discovering human brain functions through brain networks. In this regard, the evaluation of dynamic changes in functional connectivity of the brain regions by using functional magnetic resonance imaging data has attracted their attention. In this paper, we focus on two model-based approaches, called the exponential weighted moving average model and the d...

Modeling connectivity in landscape genetics: applications, optimization and assessing uncertainty

Dynamic Functional Connectivity tutorial: solutions