Fractional Gaussian noise, functional MRI and Alzheimer's disease

By V. Maxim, Levent Sendur, Mohamed-Jalal Fadili, John Suckling, R. Gould, Robert J. Howard, E. Bullmore. NeuroImage, 2005

300 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/d2b3d25ceb2379709e1e8d616bab0be99457d1ce

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Citations in the corpus

Efficiency and Cost of Economical Brain Functional Networks (2007, methodology): “We used wavelets for estimation of functional connectivity in these data because of prior evidence indicating that cortical fMRI time series often have long memory in time (slowly decaying positive autocorrelation), or a 1/f power spectrum in the frequency domain [14,15].”
Altered functional connectivity in early Alzheimer's disease: A resting‐state fMRI study (2007, result): “With respect to AD, some studies have found that the pathophysiology of AD may be associated with abnormality in resting-state LFF [Grecius et al., 2004; Li et al., 2002; Maxim et al., 2005].”
Complex brain networks: graph theoretical analysis of structural and functional systems (2009, background): “This timescale invariance of wavelet correlations and the brain functional network parameters derived from them is a theoretically predictable corollary of the long-range autocorrelations of neurophysiological time serie”
Regional coherence changes in the early stages of Alzheimer's disease: A combined structural and resting-state functional MRI study (2007, background): “To our knowledge, only three prior studies have examined AD-related LFBF activity using resting-state fMRI (Li et al., 2002; Maxim et al., 2005; Wang et al., 2006).”
A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs (2006, methodology): “…well suited to analysis of signals that have fractal scaling or 1/f properties, as is typical of cortical fMRI time series in the resting state (Maxim et al., 2005) [see Bullmore et al. (2004) for a review of wavelet methods for fMRI data analysis and Percival and Walden (2000) for a general…”
On the use of correlation as a measure of network connectivity (2012, background): “5 has been suggested as a potential model for the functional-MRI BOLD signal (Maxim et al., 2005).”
The Oscillating Brain: Complex and Reliable (2009, background): “Furthermore, it is insensitive to non-stationary characteristics of LFO appreciated by previous work (Bullmore et al., 2004; Maxim et al., 2005; Wink et al., 2008).”
Broadband Criticality of Human Brain Network Synchronization (2009, background): “Power law scaling of human neurophysiological processes has been previously described in both functional MRI and MEG or electrophysiological datasets [14,15,43].”
Linking the multiple-demand cognitive control system to human electrophysiological activity (2025, unknown): “Aperiodic activity is ubiquitous across a wide range of modalities, including local field potentials (LFP), MEG/EEG, and fMRI blood oxygen level dependent (BOLD) signals including resting-state network dynamics (Bullmore et al., 2001; Fransson et al., 2013; He, 2011, 2014; Maxim et al., 2005).”