Graph theoretical analysis of human brain structural networks

Abstract

There is a growing interest in exploring the connectivity patterns of the human brain. Specifically, the utility of noninvasive neuroimaging data and graph theoretical analysis have provided important insights into the anatomical connections and topological pattern of human brain structural networks in vivo. This review focuses on recent methodological and application studies, utilizing graph theoretical approaches, on brain structural networks with structural magnetic resonance imaging (MRI) and diffusion MRI. These studies showed many nonrandom properties of structural brain networks, such as small-worldness, modularity, and highly connected hubs. Importantly, topological organization of the networks shows changes during normal development, aging, and neuropsychiatric diseases. Network structures have also been found to correlate with behavioral or cognitive functions, which imply their associations with functional dynamics. These advances not only help us to understand how the healthy human brain is structurally organized, but also provide a novel insight into the biological mechanisms of brain disorders. Future studies will involve the combination of structural/diffusion MRI and functional MRI, to realize how the structural connectivity patterns of the brain underlie its functional states, and will explore whether graph theoretical analysis of structural brain networks could serve as potential imaging biomarkers for disease diagnosis and treatment.

Childhood Maltreatment: Altered Network Centrality of Cingulate, Precuneus, Temporal Pole and Insula

“…This approach is based on the observation that certain pairings of cortical regions (e.g., frontal-temporal, frontal-parietal, intrahemispheric) vary in tandem across individuals in thickness or gray matter volume, and that the statistical dependence between distinct brain regions is due to structural or functional associations between these regions (63, 64). This approach has been used to identify the modular and small-world network structure of the cerebral cortex in normal individuals (65, 66) and network abnormalities in Alzheimer’s disease (62, 67), schizophrenia (61), epilepsy (68–70), multiple sclerosis (71) and aging (72). …”

Graph-based network analysis in schizophrenia

“…During mathematical thinking, the α2 band showed a degree of SWN disorganization in adults compared to children, whereas β and γ bands showed lower synchronization and lower SWN organization [53] . Recently published reviews are helpful to understand the normal organization and development [54][55][56][57][58] . Existing studies related to network development are not sufficient to provide a conclusive and detailed picture.…”

Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI

“…In structural connection analysis, nodes are usually derived by parcellating cortical and subcortical gray matter regions according to anatomical landmarks, or by defining a random parcellation into evenly sized voxel clusters, and edges are usually referred to as the white matter projections linking cortical and subcortical regions (Sporns, 2013). Available graph-theoretical studies have broadly aimed to assess the organization of structural and functional brain networks using MRI during normal development, aging, and organic and neuropsychiatric brain disorders; the results suggest that brain networks are correlated with behavioral and cognitive functions (Bullmore and Bassett, 2011, Gong and He, 2015, Lo et al, 2011, Zhang et al, 2011). …”