Mukli Peter, Nagy Zoltan, Racz Frigyes S, Herman Peter, Eke Andras
Institute of Clinical Experimental Research, Semmelweis University, Budapest, Hungary.
Department of Physiology, Semmelweis University, Budapest, Hungary.
Front Physiol. 2018 Aug 10;9:1072. doi: 10.3389/fphys.2018.01072. eCollection 2018.
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 ( = 2) 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 (). Building on moments of different order () of the measure, σ(), multifractal SSC yielded generalized Hurst exponent function, (), and singularity spectrum, () separately for a fast and slow component (the latter dominating the highest temporal scales). Parameters were calculated reflecting the estimated measure at = (focus), degree of LRC [Hurst exponent, (2) and maximal Hölder exponent, ] and measuring strength of multifractality [full-width-half-maximum of () and Δ = (-15)-(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, () 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, , and (2) were lower in the young group explained by a significantly increased () among elderly at high temporal scales. Regarding the fast component of CBSI-pretreated HbT and that of HbO-HbR covariance, , 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.
静息状态下脑血流动力学的波动在两个不同的标度范围内呈现出无标度行为。这种双峰（多）分形模式的变化有助于深入了解脑血管或神经功能的改变。我们的主要目标是评估表征脑血流动力学的局部无标度特性的分布，并厘清衰老对这些多重分形参数的影响。为此，我们使用连续波近红外光谱技术，从大脑皮层获取了氧合血红蛋白（HbO）、脱氧血红蛋白（HbR）和总血红蛋白（HbT）浓度时间序列的扩展静息状态记录（= 2）。本研究招募了52名健康志愿者：24名年轻人（30.6 ± 8.2岁）和28名老年人（60.5 ± 12.0岁）。通过对幂律、多重分形噪声和混洗数据集进行筛选测试，我们评估了反映长程相关性（LRC）的真正多重分形血流动力学的存在。随后，基于一系列时间尺度（）上信号窗口的标准差（σ），进行标度范围自适应双峰信号求和转换（SSC）。基于测量值σ（）的不同阶矩（），多重分形SSC分别为快速和慢速分量（后者主导最高时间尺度）生成广义赫斯特指数函数（）和奇异谱（）。计算参数以反映在 = （焦点）处的估计测量值、LRC程度[赫斯特指数，（2）和最大赫尔德指数，]以及测量多重分形性的强度[（）的半高全宽和Δ = （-15） - （15）]。基于相关性的信号改善（CBSI）在解释由于神经活动或局部/全身血流动力学影响引起的变化方面增强了我们的信号。我们借助分形尺度相关系数（）和基于SSC的多重分形协方差分析来表征HbO - HbR关系。在大多数受试者中，脑血流动力学波动被证明是双峰多重分形的。对于原始HbT的慢速分量，年轻人组中的、和（2）较低，这可以通过老年人在高时间尺度上显著增加的（）来解释。关于CBSI预处理后的HbT的快速分量以及HbO - HbR协方差的快速分量，老年人组中的、和焦点降低。这些观察结果表明，老年人组中神经血管耦合减弱，表现为神经元成分的自相关性降低，同时非神经元成分的自相关性增加。
