Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations
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9,700 citations
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...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...
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6,135 citations
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...This 1/f distribution has also been observed in studies of spontaneous electroencephalography (EEG...
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4,266 citations
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...(2002), Aks and Sprott (2003), for EEG measures, Linkenkaer-Hansen et al. (2001), Freeman et al. (2003), Leopold et al. (2003), Stam and de Bruin (2004). 49. Izhikevich et al. (2004). The embodiment of recent history is the temporal correlation represented by the 1/f memory of scale-free systems....
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...(2002), Aks and Sprott (2003), for EEG measures, Linkenkaer-Hansen et al. (2001), Freeman et al....
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...The exponent of the 1/fα relationship is somewhat different for gamma and theta power fluctuation (Linkenkaer-Hansen et al., 2001; Stam and de Bruin, 2004)....
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...The exponent of the 1/fα relationship is somewhat different for gamma and theta power fluctuation (Linkenkaer-Hansen et al., 2001; Stam and de Bruin, 2004). In agreement with these findings, Başar (1990) was among the first to suggest that EEG activity is best described as quasi-deterministic activity....
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...eyes closed) but is highly invariant across subjects (Linkenkaer-Hansen et al., 2001)....
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2,345 citations
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...Moreover, long period or very low-frequency coherent oscillations have been described recently in both monkey and human electrophysiological data (Linkenkaer-Hansen et al., 2001; Leopold et al., 2003)....
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References
12,803 citations
"Long-Range Temporal Correlations an..." refers methods in this paper
...The signals were filtered with a Morlet wavelet; the modulus of the complex-valued outcome, W(t,f) , represents the amplitude of the signal at a time range centered at t and in a frequency band centered at f (Torrence and Compo, 1998)....
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6,486 citations
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...Unlike deterministic approaches aimed at finding low-dimensional chaos, the SOC framework allows for a highdimensional character of the dynamics and for the presence of stochastic effects....
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...Neural networks host the common features of SOC systems, such as a large number of units (neurons), local and nonlinear interactions between neurons, externally imposed perturbations, a certain amount of stochastic variation of internal parameters, and ability to store information in spatial patterns....
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...After this stage, the dynamics of the system exhibit power-law scaling behavior, and the underlying process operates in a critical state, a phenomenon often termed self-organized criticality (SOC) (Bak et al., 1987, 1988)....
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...Since the first reports on self-organized criticality (Bak et al., 1987, 1988), ample evidence has indicated that several complex systems self-organize through local interactions to a critical state with long-range spatiotemporal correlations (Bak et al., 1989; Mantegna and Stanley, 1995; Boettcher…...
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...Based on the analogy with other SOC systems, one prediction is power-law statistics for the probability that a number of neurons, n, is recruited into an oscillatory event....
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4,365 citations
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...…fluctuation analysis has been developed for quantifying correlation properties in nonstationary signals, e.g., in physiological time series, because long-range correlations—revealed by an ACF analysis—can arise also as an artifact of the “patchiness” of nonstationary data (Peng et al., 1994, 1995)....
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3,891 citations
3,828 citations