Eke Andras, Hermán Péter, Hajnal Márton
Institute of Human Physiology and Clinical Experimental Research, Semmelweis University, Budapest, Hungary.
J Cereb Blood Flow Metab. 2006 Jul;26(7):891-8. doi: 10.1038/sj.jcbfm.9600243. Epub 2005 Nov 16.
The complexity of spontaneous cerebral blood volume (CBV) fluctuations can emerge from random, fractal, or chaotic processes. Our aims were to define the contribution of these patterns to the observed complexity and to evaluate the effect of age and gender on it. The total hemoglobin content as the measure of CBV was monitored by near-infrared spectroscopy on volunteers (men n = 19, age = 20 to 78 years; women n = 23, age = 21 to 79 years). Random and fractal patterns were distinguished by the spectral index (beta). Chaos was identified by surrogate analysis of the correlation dimension (a static chaotic parameter, the dimension of the correlation integral) and the largest Lyapunov exponent (a dynamic chaotic parameter, the rate of exponential divergence of the system states from a perturbed initial condition over the chaotic attractor). In spontaneous CBV fluctuations, both fast random and slow fractal dynamics are present separately in their spectra by a cutoff frequency, f'. Below f' the pattern is fractal, in that power rises inversely with frequency as 1/f(beta). f' decreases with age in men and women alike (F1: up to 0.12+/-0.06 Hz versus F2: up to 0.05+/-0.04 Hz at P = 0.015, and M1: up to 0.16+/-0.05 Hz versus M2: up to 0.11+/-0.04 Hz at P = 0.044). Neither pre- nor postmenopausal age groups (1 and 2, respectively) showed a (low)beta gender difference. Surrogate analysis showed that CBV dynamics cannot be characterized on the grounds of deterministic chaos. Cerebral blood volume fluctuates in a complex, bimodal manner in humans, in that the fast dynamics has no structure, while the slow dynamics exhibits a self-similar, that is, fractal temporal structure. The range of fluctuation amplitudes produced by fractal dynamics is always larger than that of random fluctuations, and it shrinks with an altered structuring in aging women only.
自发性脑血容量(CBV)波动的复杂性可能源于随机、分形或混沌过程。我们的目的是确定这些模式对观察到的复杂性的贡献,并评估年龄和性别对其的影响。通过近红外光谱对志愿者(男性n = 19,年龄20至78岁;女性n = 23,年龄21至79岁)监测作为CBV测量指标的总血红蛋白含量。通过光谱指数(β)区分随机和分形模式。通过相关维数(一个静态混沌参数,相关积分的维数)和最大Lyapunov指数(一个动态混沌参数,系统状态在混沌吸引子上从扰动初始条件开始的指数发散率)的替代分析识别混沌。在自发性CBV波动中,快速随机动力学和缓慢分形动力学在其频谱中分别通过截止频率f'呈现。低于f'时模式为分形,即功率随频率以1/f(β)的形式反比上升。f'在男性和女性中均随年龄降低(F1:高达0.12±0.06Hz对比F2:高达0.05±0.04Hz,P = 0.015;M1:高达0.16±0.05Hz对比M2:高达0.11±0.04Hz,P = 0.044)。绝经前和绝经后年龄组(分别为1组和2组)均未显示出(低)β性别差异。替代分析表明,CBV动力学不能基于确定性混沌来表征。人类脑血容量以复杂的双峰方式波动,即快速动力学无结构,而缓慢动力学呈现自相似,即分形时间结构。分形动力学产生的波动幅度范围总是大于随机波动的幅度范围,且仅在老年女性中随着结构改变而缩小。