To date, fMRI research has been concerned primarily with evincing generic principles of
brain function through averaging data from multiple subjects. Given rapid developments in …

The purpose of this review is to communicate and synthesize recent findings related to
motion artifact in resting state fMRI. In 2011, three groups reported that small head …

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

Since initial reports regarding the impact of motion artifact on measures of functional
connectivity, there has been a proliferation of participant-level confound regression methods …

Head motion during functional MRI (fMRI) scanning can induce spurious findings and/or
harm detection of true effects. Solutions have been proposed, including deleting …

Participant motion during functional magnetic resonance image (fMRI) acquisition produces
spurious signal fluctuations that can confound measures of functional connectivity. Without …

The global signal is widely used as a regressor or normalization factor for removing the
effects of global variations in the analysis of functional magnetic resonance imaging (fMRI) …

We proposed ICA-AROMA as a strategy for the removal of motion-related artifacts from fMRI
data (Pruim et al., 2015). ICA-AROMA automatically identifies and subsequently removes …

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

The goal of the Brain Genomics Superstruct Project (GSP) is to enable large-scale
exploration of the links between brain function, behavior, and ultimately genetic variation. To …