In an age where the amount of data collected from brain imaging is increasing constantly, it
is of critical importance to analyse those data within an accepted framework to ensure proper …

There has been much recent interest in using magnetic resonance diffusion imaging to
provide information about anatomical connectivity in the brain, by measuring the anisotropic …

Magnetic resonance imaging (MRI) has transformed our understanding of the human brain
through well-replicated mapping of abilities to specific structures (for example, lesion studies) …

Requiring only minimal assumptions for validity, nonparametric permutation testing provides
a flexible and intuitive methodology for the statistical analysis of data from functional …

Many image enhancement and thresholding techniques make use of spatial neighbourhood
information to boost belief in extended areas of signal. The most common such approach in …

There is strong evidence of brain-related abnormalities in COVID-19 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ,
9 , 10 , 11 , 12 – 13 . However, it remains unknown whether the impact of SARS-CoV-2 …

The most widely used task functional magnetic resonance imaging (fMRI) analyses use
parametric statistical methods that depend on a variety of assumptions. In this work, we use real …

Permutation methods can provide exact control of false positives and allow the use of non-standard
statistics, making only weak assumptions about the data. With the availability of fast …

The rapid growth of the literature on neuroimaging in humans has led to major advances in
our understanding of human brain function but has also made it increasingly difficult to …

There is great interest in estimating brain “networks” from FMRI data. This is often attempted
by identifying a set of functional “nodes” (eg, spatial ROIs or ICA maps) and then conducting …