Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular
both with clinicians and researchers as they are capable of providing unique insights into …

Since the discovery of functional connectivity in fMRI data (ie, temporal correlations between
spatially distinct regions of the brain) there has been a considerable amount of work in this …

Dynamic functional connectivity captures temporal variations of functional connectivity
during MRI acquisition and it may be a suitable method to detect cognitive changes in …

In order to localize the neural circuits involved in generating behaviors, it is necessary to
assign activity onto anatomical maps of the nervous system. Using brain registration across …

It has recently been reported (Van Dijk et al., 2011) that in-scanner head motion can have a
substantial impact on MRI measurements of resting-state functional connectivity. This finding …

Kendall's coefficient concordance (KCC) can measure the similarity of a number of time
series. It has been used for purifying a given cluster in functional MRI (fMRI). In the present …

Independent component analysis (ICA) is a promising analysis method that is being
increasingly applied to fMRI data. A principal advantage of this approach is its applicability …

A key challenge for cognitive neuroscience is determining how mental representations map
onto patterns of neural activity. Recently, researchers have started to address this question …

Independent component analysis (ICA) has become an increasingly utilized approach for
analyzing brain imaging data. In contrast to the widely used general linear model (GLM) that …

Autism spectrum disorders (ASDs) are characterized by deficits in social and communication
processes. Recent data suggest that altered functional connectivity (FC), ie synchronous …