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Brain Connect. 2016 Mar;6(2):95-8. doi: 10.1089/brain.2015.0361. Epub 2015 Oct 15.

Disentangling Brain Graphs: A Note on the Conflation of Network and Connectivity Analyses.

Author information

1
1 Department of Biostatistical Sciences, Wake Forest School of Medicine , Winston-Salem, North Carolina.
2
2 Laboratory for Complex Brain Networks, Wake Forest School of Medicine , Winston-Salem, North Carolina.
3
3 Department of Radiology, Wake Forest School of Medicine , Winston-Salem, North Carolina.

Abstract

Understanding the human brain remains the holy grail in biomedical science, and arguably in all of the sciences. Our brains represent the most complex systems in the world (and some contend the universe) comprising nearly 100 billion neurons with septillions of possible connections between them. The structure of these connections engenders an efficient hierarchical system capable of consciousness, as well as complex thoughts, feelings, and behaviors. Brain connectivity and network analyses have exploded over the last decade due to their potential in helping us understand both normal and abnormal brain function. Functional connectivity (FC) analysis examines functional associations between time series pairs in specified brain voxels or regions. Brain network analysis serves as a distinct subfield of connectivity analysis, in which associations are quantified for all time series pairs to create an interconnected representation of the brain (a brain network), which allows studying its systemic properties. While connectivity analyses underlie network analyses, the subtle distinction between the two research areas has generally been overlooked in the literature, with them often being referred to synonymously. However, developing more useful analytic methods and allowing for more precise biological interpretations require distinguishing these two complementary domains.

PMID:
26414952
PMCID:
PMC4779980
[Available on 2017-03-01]
DOI:
10.1089/brain.2015.0361
[Indexed for MEDLINE]
Free PMC Article

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