Today, neuroscientists are interested in discovering human brain functions through brain networks. In this regard, the evaluation of dynamic changes in functional connectivity of the brain regions by using functional magnetic resonance imaging data has attracted their attention. In this paper, we focus on two model-based approaches, called the exponential weighted moving average model and the d...

Spatial interpolation allows creation of continuous raster surfaces from a subsample of point-based measurements. Most interpolation approaches use Euclidean distance measurements between data points to generate predictions of values at unknown locations. However, there are many spatially distributed data sets that are not properly represented by Euclidean distances and require distance measure...

Two-dimensional mesh-based motion tracking preserves neighboring relations (through connectivity of the mesh) and also allows warping transformations between pairs of frames; thus, it effectively eliminates blocking artifacts that are common in motion compensation by block matching. However, available uniform 2-D mesh model enforces connectivity everywhere within a frame, which is clearly not s...

Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associated with functional impairment in "individual" patients. We investigated whether fMRI allows classification of individual motor impairment after stro...

Brain development is adversely affected by preterm birth. Magnetic resonance image analysis has revealed a complex fusion of structural alterations across all tissue compartments that are apparent by term-equivalent age, persistent into adolescence and adulthood, and associated with wide-ranging neurodevelopment disorders. Although functional MRI has revealed the relatively advanced organisatio...

Eigenvector centrality mapping (ECM) has recently emerged as a measure to spatially characterize connectivity in functional brain imaging by attributing network properties to voxels. The main obstacle for widespread use of ECM in functional magnetic resonance imaging (fMRI) is the cost of computing and storing the connectivity matrix. This article presents fast ECM (fECM), an efficient algorith...

Background Given that adolescence is a critical epoch in the onset of schizophrenia, studying aberrant brain changes in adolescent-onset schizophrenia, particularly in patients with drug-naive first-episode schizophrenia, is important to understand the biological mechanism of this disorder. Previous resting-state functional magnetic resonance imaging studies have shown abnormal functional conne...

A fundamental assumption in neuroscience is that brain function is constrained by its structural properties. This motivates the idea that the brain can be parcellated into functionally coherent regions based on anatomical connectivity patterns that capture how different areas are interconnected. Several studies have successfully implemented this idea in humans using diffusion weighted MRI, allo...

the atom-bond connectivity index of graph is a topological index proposed by estrada et al.as abc (g)  uve (g ) (du dv  2) / dudv , where the summation goes over all edges ofg, du and dv are the degrees of the terminal vertices u and v of edge uv. in the present paper,some upper bounds for the second type of atom-bond connectivity index are computed.