Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has
rapidly become a popular technique for the investigation of brain function in healthy …

Abstract Machine learning techniques are increasingly being used in making relevant
predictions and inferences on individual subjects neuroimaging scan data. Previous studies …

Abstract Background Wiener–Granger causality (“G-causality”) is a statistical notion of
causality applicable to time series data, whereby cause precedes, and helps predict, effect. It …

Granger causality is a method for identifying directed functional connectivity based on time
series analysis of precedence and predictability. The method has been applied widely in …

We investigated the differential spatial covariance pattern of blood oxygen level-dependent
(BOLD) responses to single-task and multitask functional magnetic resonance imaging …

Background A growing population is diagnosed with Attention Deficit Hyperactivity Disorder
(ADHD) and are currently being treated with psychostimulants. Brain Computer Interface …

Functional magnetic resonance imaging (fMRI) is widely used to measure brain function
during various cognitive states. However, it remains a challenge to obtain low-rank models …

As machine learning continues to gain momentum in the neuroscience community, we
witness the emergence of novel applications such as diagnostics, characterization, and …

Area of study is the formation mechanism of the present-day population of elliptical galaxies,
in the context of hierarchical cosmological models accompanied by accretion and minor …

In recent years, a variety of multivariate classifier models have been applied to fMRI, with
different modeling assumptions. When classifying high‐dimensional fMRI data, we must also …