Functional imaging or diffusion-weighted imaging techniques are widely used to understand
brain connectivity at the systems level and its relation to normal neurodevelopment …

Different brain areas are thought to be integrated into large‐scale networks to support
cognitive function. Recent approaches for investigating structural organization and …

The relationship between anatomic connectivity of large-scale brain networks and their
functional connectivity is of immense importance and an area of active research. Previous …

Structural covariance analysis is a widely used structural MRI analysis method which
characterises the co-relations of morphology between brain regions over a group of …

Brain structure varies between people in a markedly organized fashion. Communities of
brain regions co-vary in their morphological properties. For example, cortical thickness in …

An emerging field of human brain imaging deals with the characterization of the
connectome, a comprehensive global description of structural and functional connectivity …

Models of whole-brain connectivity are valuable for understanding neurological function,
development and disease. This paper presents a machine learning based approach to …

Large-scale covariance of cortical thickness or volume in distributed brain regions has been
consistently reported by human neuroimaging studies. The mechanism of this population …

The success of diffusion MRI is deeply rooted in the fact that during their micrometric random
displacements water molecules explore tissue microstructure. Hence by labeling …

The human brain represents a complex computational system, the function and structure of
which may be measured using various neuroimaging techniques focusing on separate …