Negative edges and soft thresholding in complex network analysis of resting state functional connectivity data

Complex network analyses of functional connectivity have consistently revealed non-random (modular, small-world, scale-free-like) behavior of hard-thresholded networks constructed from the right-tail of the similarity histogram. In the present study we determined network properties resulting from ed...

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Bibliographic Details
Published in:NeuroImage (Orlando, Fla.) Fla.), 2011-04, Vol.55 (3), p.1132-1146
Main Authors: Schwarz, Adam J., McGonigle, John
Format: Article
Language:English
Subjects:
Adult
Algorithms
Cerebrospinal Fluid - physiology
Computer Simulation
Female
Functional connectivity
Graph theory
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Male
Middle Aged
Models, Neurological
Neural Networks (Computer)
Neural Pathways - physiology
Nonlinear Dynamics
Protein folding
Reproducibility
Reproducibility of Results
Resting state
Soft-thresholding
Weighted networks
Young Adult
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Summary:Complex network analyses of functional connectivity have consistently revealed non-random (modular, small-world, scale-free-like) behavior of hard-thresholded networks constructed from the right-tail of the similarity histogram. In the present study we determined network properties resulting from edges constrained to specific ranges across the full correlation histogram, in particular the left (negative-most) tail, and their dependence on the confound signal removal strategy employed. In the absence of global signal correction, left-tail networks comprised predominantly long range connections associated with weak correlations and were characterized by substantially reduced modularity and clustering, negative assortativity and γ
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2010.12.047