Background Once considered mere noise, fMRI-based functional connectivity has become a
major neuroscience tool in part due to early studies demonstrating its reliability. These …

Resting-state fMRI was first described by Biswal et al in 1995 and has since then been
widely used in both healthy subjects and patients with various neurologic, neurosurgical …

A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete
neurobiological “atoms”. Resting-state functional magnetic resonance imaging (rs-fMRI) …

Brain imaging efforts are being increasingly devoted to decode the functioning of the human
brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding …

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to
delineate individual-specific brain networks. A major question is whether individual-specific …

Over the past decade there has been an enormous rise in the application of functional and
structural connectivity approaches to explore the brain's intrinsic organization in healthy and …

The identification of resting state networks (RSNs) and the quantification of their functional
connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts …

Independent Component Analysis (ICA) is one of the most popular techniques for the
analysis of resting state FMRI data because it has several advantageous properties when …

Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …

The development of human cognition results from the emergence of coordinated activity
between distant brain areas. Network science, combined with non-invasive functional …