Deformable image registration is a fundamental task in medical image processing. Among
its most important applications, one may cite: 1) multi-modality fusion, where information …

Regional specialization and functional integration are often viewed as two fundamental
principles of human brain organization. They are closely intertwined because each …

Statistical machine learning methods are increasingly used for neuroimaging data analysis.
Their main virtue is their ability to model high-dimensional datasets, eg multivariate analysis …

Connectivity analyses and computational modeling of human brain function from fMRI data
frequently require the specification of regions of interests (ROIs). Several analyses have …

Analysis and interpretation of neuroimaging data often require one to divide the brain into a
number of regions, or parcels, with homogeneous characteristics, be these regions defined …

We performed an updated quantitative meta-analysis of 162 neuroimaging studies of
emotion using a novel multi-level kernel-based approach, focusing on locating brain regions …

Graph analysis has become an increasingly popular tool for characterizing topological
properties of brain connectivity networks. Within this approach, the brain is modeled as a …

The aim of group fMRI studies is to relate contrasts of tasks or stimuli to regional brain
activity increases. These studies typically involve 10 to 16 subjects. The average regional …

A variety of methods have been developed to identify brain networks with spontaneous,
coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose …

Small-world networks are a class of networks that exhibit efficient long-distance
communication and tightly interconnected local neighborhoods. In recent years, functional …