Understanding the human brain remains the Holy Grail in biomedical science,and arguably in all of the sciences. Our brains represent the most complexsystems in the world (and some contend the universe) comprising nearly onehundred billion neurons with septillions of possible connections between them.The structure of these connections engenders an efficient hierarchical systemcapable of consciousness, as well as complex thoughts, feelings, and behaviors.Brain connectivity and network analyses have exploded over the last decade dueto their potential in helping us understand both normal and abnormal brainfunction. Functional connectivity (FC) analysis examines functionalassociations between time series pairs in specified brain voxels or regions.Brain network analysis serves as a distinct subfield of connectivity analysisin which associations are quantified for all time series pairs to create aninterconnected representation of the brain (a brain network), which allowsstudying its systemic properties. While connectivity analyses underlie networkanalyses, the subtle distinction between the two research areas has generallybeen overlooked in the literature, with them often being referred tosynonymously. However, developing more useful analytic methods and allowing formore precise biological interpretations requires distinguishing these twocomplementary domains.
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