Diffusion magnetic resonance imaging for Brainnetome: A critical review
Increasing evidence shows that the human brain is a highly self-organized system that shows attributes of smallworldness, hierarchy and modularity. The "connectome" was conceived several years ago to identify the underpinning physical connectivities of brain networks. The need for an integration of multi-spatial and -temporal approaches is becoming apparent. Therefore, the "Brainnetome" (brain-net-ome) project was proposed. Diffusion magnetic resonance imaging (dMRI) is a non-invasive way to
... dy the anatomy of brain networks. Here, we review the principles of dMRI, its methodologies, and some of its clinical applications for the Brainnetome. Future research in this field is discussed. Introduction Over the past two decades we have learned that, rather than individual regions, a group of intensively interacting brain areas are involved in even simple cognitive processes [1, 2] . Thus, the entire brain can be characterized as a highly self-organized network  . This conceptualizing strategy has been analogously exploited in such other facets of our society as social networks and computer networks  . One or several sub-networks of the brain are disrupted in neurological or psychiatric disease, as evidenced in major depressive disorder (MDD)  , bipolar disorder  , Alzheimer's disease (AD)  , and schizophrenia [2, 5] , as well as in normal development [7, 8] and aging  . The term "human connectome" was proposed to emphasize "a comprehensive structural description of the network of elements and connections forming the human brain" [3, 10, 11] . Subsequently, many studies emerged to explore the networks of the human brain, comprising data collection and the development of toolkits [11, 12] to investigate healthy development and neuropsychiatric diseases [2,      . Extending the connectome, the Brainnetome was conceived to reveal not only physical structural connectivities but also functional connectivities by various levels of in-vivo imaging methods and ex-vivo imaging/staining techniques. The Brainnetome seeks not only a static description of the network state at a certain time point, but also to describe the dynamic processes throughout natural development and neuropsychiatric evolution [13, 14] . This review focuses on one of the most promising techniques, diffusion magnetic resonance imaging (dMRI), and its use for modeling and analysis in the Brainnetome. tions of sub-networks are also attractive, such as the language [109, 110] and prefrontal-cingulate-insula  networks during maturation, the cortico-striatal network in aging  and epilepsy, the prefrontal-limbic network in MDD    , the motor  and frontal-temporal  networks in epilepsy, the language [117, 118] network in dyslexia, and the corticosubcortical network in autism  , AD  , stroke [121, 122] , and schizophrenia  . Those individual sub-networks allow specification of the underlying dysmodulation of functional units occurring in a neuropsychiatric state. Globally exploring changes across the entire brain Appendix. (Continued) Brain Connectivity Toolbox Matlab-based routines for computing network properties https://sites.google.com/a/brain-connectivity-toolbox.net/bct DTI Tracking System DTI data processing, tracking (determined/probabilistic), statistical analysis and visualization. Batch-processing support http://www.brainnetome.org/software.html, http://www.brainnetome.org/wiki Brainnetome Toolkit Matlab-based GUI, with functions computing most network properties, including degree, clustering, efficiency/shortestpath, small-worldness, betweenness, assortative, resilience, etc, and visualization of networks http://www.brainnetome.org/software.html, http://www.brainnetome.org/wiki DSI, diffusion spectrum imaging; DTI, diffusion tensor imaging; PASMRI, persistent angular structure MRI; QBI, Q-ball imaging; SD, spherical deconvolution. For the suggested steps on data processing, network construction and visualization, more details can be found at the wiki of the Brainnetome website (http://www. brainnetome.org/wiki).