Since its inception in 1992, Functional Magnetic Resonance Imaging (fMRI) has become an
indispensible tool for studying cognition in both the healthy and dysfunctional brain. FMRI …

This article presents a review of recent advances in neuroscience research in the specific
area of brain connectivity as a potential biomarker of Alzheimer's disease with a focus on the …

As the size of functional and structural MRI datasets expands, it becomes increasingly
important to establish a baseline from which diagnostic relevance may be determined, a …

We propose causal recurrent variational autoencoder (CR-VAE), a novel generative model
that is able to learn a Granger causal graph from a multivariate time series x and …

Assessing directed functional connectivity from time series data is a key challenge in
neuroscience. One approach to this problem leverages a combination of Granger causality …

The neural basis of motor response inhibition has drawn considerable attention in recent
imaging literature. Many studies have used the go/no-go or stop signal task to examine the …

As the focus of neuroscience shifts from studying individual brain regions to entire networks
of regions, methods for statistical inference have also become geared toward network …

Abstract Major Depressive Disorder (MDD) has been conceptualized as a neural network-
level disease. Few studies of the neural bases of depression, however, have used analytical …

A recent study showed that people evaluate products more positively when they are
physically associated with art images than similar non-art images. Neuroimaging studies of …

Automated recognition and classification of brain diseases are of tremendous value to
society. Attention deficit hyperactivity disorder (ADHD) is a diverse spectrum disorder whose …