Abstract
Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r(VO2), in the laboratory mouse Mus musculus, assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO2) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 102 s), either monofractal or weak multifractal dynamics are observed depending on whether Ta < 15 °C or Ta > 15 °C respectively. For larger time scales, r(VO2) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ(q), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b. We also show that the long-range correlation structure of r(VO2) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system.
Highlights
While an increasing number of authors have pointed out the complex nature of physiological processes (Burggren & Monticino, 2005; Spicer & Gaston, 1999), an emerging research question is what are the consequences and implications of physiological complexity for the homeostatic adaptive capability of animals, on a scenario of global climate change
Comparative experimental studies may help to untangle the relative importance of body size and taxonomic inertia in the emergence of multifractality
A related question is whether ectotherms do present any long-range correlation structure in their metabolic rate dynamics
Summary
Physiologic complexity is ubiquitous in all living organisms (Bassingthwaighte, Liebovitch & West, 1994; Glass, 2001; Goldberger et al, 2002; Burggren & Monticino, 2005). The application of analytic techniques from nonlinear dynamics and statistical physics to the study of different physiologic variables has led to the proposition of a general theory to account for the complexity of physiologic variables (Glass, 2001; Costa, Goldberger & Peng, 2002; Goldberger et al, 2002; Kantelhardt, 2011; Lipsitz, 2004) This theory states that, given certain parameter conditions, the state variables of healthy systems reveal complex variability associated with long-range (fractal) correlations, along with distinct classes of nonlinear interactions (Goldberger, 1996; Goldberger, Rigney & West, 1990; Goldberger et al, 2002). Over the last two decades, different studies have shown that the break down of this type of multi-scale, nonlinear complexity is a characteristic signature of disease and senescence, and as a result, the study of complexity in physiological variables has shown important promise in the efforts to understand and diagnose different pathologies (Costa et al, 2008; Delignières & Torre, 2009; Goldberger et al, 2002; Hausdorff et al, 2001; Hu et al, 2004; Ivanov et al, 2007; Lipsitz, 2004)
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