%0 Generic %A Mukli, Peter %A Nagy, Zoltan %A Racz, Frigyes S. %A Herman, Peter %A Eke, Andras %D 2018 %T Data_Sheet_1_Impact of Healthy Aging on Multifractal Hemodynamic Fluctuations in the Human Prefrontal Cortex.pdf %U https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Impact_of_Healthy_Aging_on_Multifractal_Hemodynamic_Fluctuations_in_the_Human_Prefrontal_Cortex_pdf/6955247 %R 10.3389/fphys.2018.01072.s001 %2 https://frontiersin.figshare.com/ndownloader/files/12754442 %K aging %K cerebral hemodynamics %K neurovascular coupling %K near-infrared spectroscopy (NIRS) %K correlation-based signal improvement %K multifractality %K multifractal analysis %K signal summation conversion %X

Fluctuations in resting-state cerebral hemodynamics show scale-free behavior over two distinct scaling ranges. Changes in such bimodal (multi) fractal pattern give insight to altered cerebrovascular or neural function. Our main goal was to assess the distribution of local scale-free properties characterizing cerebral hemodynamics and to disentangle the influence of aging on these multifractal parameters. To this end, we obtained extended resting-state records (N = 214) of oxyhemoglobin (HbO), deoxyhemoglobin (HbR) and total hemoglobin (HbT) concentration time series with continuous-wave near-infrared spectroscopy technology from the brain cortex. 52 healthy volunteers were enrolled in this study: 24 young (30.6 ± 8.2 years), and 28 elderly (60.5 ± 12.0 years) subjects. Using screening tests on power-law, multifractal noise, and shuffled data sets we evaluated the presence of true multifractal hemodynamics reflecting long-range correlation (LRC). Subsequently, scaling-range adaptive bimodal signal summation conversion (SSC) was performed based on standard deviation (σ) of signal windows across a range of temporal scales (s). Building on moments of different order (q) of the measure, σ(s), multifractal SSC yielded generalized Hurst exponent function, H(q), and singularity spectrum, D(h) separately for a fast and slow component (the latter dominating the highest temporal scales). Parameters were calculated reflecting the estimated measure at s = N (focus), degree of LRC [Hurst exponent, H(2) and maximal Hölder exponent, hmax] and measuring strength of multifractality [full-width-half-maximum of D(h) and ΔH15 = H(−15)−H(15)]. Correlation-based signal improvement (CBSI) enhanced our signal in terms of interpreting changes due to neural activity or local/systemic hemodynamic influences. We characterized the HbO-HbR relationship with the aid of fractal scale-wise correlation coefficient, rσ(s) and SSC-based multifractal covariance analysis. In the majority of subjects, cerebral hemodynamic fluctuations proved bimodal multifractal. In case of slow component of raw HbT, hmax, and Ĥ(2) were lower in the young group explained by a significantly increased rσ(s) among elderly at high temporal scales. Regarding the fast component of CBSI-pretreated HbT and that of HbO-HbR covariance, hmax, and focus were decreased in the elderly group. These observations suggest an attenuation of neurovascular coupling reflected by a decreased autocorrelation of the neuronal component concomitant with an accompanying increased autocorrelation of the non-neuronal component in the elderly group.

%I Frontiers