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Fractal analysis of resting state functional connectivity of the brain (2014)
| Content Provider | CiteSeerX |
|---|---|
| Author | You, Wonsang Achard, Sophie Stadler, Jörg Brückner, Bernd Seiffert, Udo |
| Abstract | A variety of resting state neuroimaging data tend to exhibit fractal behavior where their power spectrums follow power-law scaling. Resting state functional connectivity is significantly influenced by fractal behav-ior which may not directly originate from neuronal population activities of the brain. To describe the fractal behavior, we adopted the fraction-ally integrated process (FIP) model instead of the fractional Gaussian noise (FGN) since the FIP model covers more general aspects of fractal-ity than the FGN model. This model provides a theoretical basis for the dependence of resting state functional connectivity on fractal behavior. Inspired by this idea, we introduce a novel concept called the nonfractal connectivity which is defined as the correlation of short memory indepen-dent of fractal behavior, and compared it with the fractal connectivity which is an asymptotic wavelet correlation. We propose several wavelet-based estimators of fractal connectivity and nonfractal connectivity for a multivariate fractionally integrated noise (mFIN). These estimators were evaluated through simulation studies and applied to the analyses of resting state fMRI data of the rat brain. 1 |
| File Format | |
| Publisher Date | 2014-01-01 |
| Access Restriction | Open |
| Content Type | Text |
