Endogenous multifractal brain dynamics are modulated by age, cholinergic blockade and cognitive performance

Abstract

The intuitive notion that a healthy organism is characterised by regular, mechanistic function has been challenged by observations that a loss complexity is, in fact, indicative of ill-health. Monofractals succinctly describe complex processes, and are controlled by a single time-invariant scaling exponent, H, simply related to the fractal dimension. A previous analysis of resting fMRI time-series demonstrated that ageing and scopolamine administration were both associated with increases in H and that faster response in a prior encoding task was also associated with increased H. We revisit this experiment with a novel regional, multifractal approach in which fractal dynamics are assumed non-stationary and defined by a spectrum of local singularity exponents. Parameterisation of this spectrum was capable of refracting the effects of age, scopolamine and task performance as well as a refining a description of the associated signal changes. Using the same imaging data, we also explored turbulence as a possible mechanism underlying multifractal dynamics. Evidence is provided that Carstaing's model of turbulent information flow from high to low scales has only limited validity, and that invariance of energy dissipation is better explained by critical-phase phenomena, supporting the proposition that the brain maintains a state of self-organised criticality.

Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws

“…The oscillation amplitudes are directly correlated with these BOLD fluctuations (16)(17)(18)(19)(20) and exhibit interareal correlations that closely match those of BOLD signals (17,(21)(22)(23). Moreover, BOLD signals also exhibit scale-free temporal (24)(25)(26) and spatiotemporal correlations (27)(28)(29). The scaling laws of LRTCs thus are a unifying fundamental characteristic of spontaneous brain activity (1,30,31).…”

Bistability and Non-Gaussian Fluctuations in Spontaneous Cortical Activity

“…The detailed characterization of super-Gaussian empirical PDFs in the present study, particularly in the beta range, arguably provides strong support for this approach over standard ICA models. Another related study is that of Suckling et al (2008) who estimated the Hölder exponent, a measure of correlated fluctuations, from time series of the resting-state cortical BOLD signal. As with the present approach, they also analyzed timescale-specific activity via a multiscale wavelet decomposition.…”

The spatial pattern and drainage cell characteristics of a pockmark field, Nile Deep Sea Fan

“…Following its discovery (Bak et al, 1987), Self-Organised Criticality has been widely observed in slowly driven, non equilibrium systems where complexity could be generated as an emergent feature of extended systems with simple local interactions (Bak et al, 1987;Bak and Paczuski, 1995;Bak, 1996;Ball, 2004). Many examples of SOC have been identified in fields as diverse as ecology, evolutionary biology, astrophysics, astronomy, solar physics, geomorphology, natural hazards, neuroscience, economics and sociology (Georgoulis and Vlahos, 1998;Dendy et al, 1999;Ray et al, 2000;Allen et al, 2001;Watkins et al, 2001;Ormerod, 2002;Andergasssen et al, 2003;Fonstad and Marcus, 2003;Pueyo, 2007;Suckling et al, 2008;Krenn and Hergarten, 2009) but to date there is no known set of general characteristics that guarantee a system will display SOC (Ball, 2004). The pockmark distribution displays certain characteristics of Self-Organized Criticality when modelled using the equivalent of a minimum 10 m radius exclusion zone (referred to as an "avalanche" in SOC theory) (Fig.…”