Arsac Laurent M
Université de Bordeaux, CNRS, Laboratoire IMS, UMR 5218, Talence, France.
Front Physiol. 2021 Apr 16;12:662076. doi: 10.3389/fphys.2021.662076. eCollection 2021.
There is some evidence that an improved understanding of executive control in the human movement system could be gained from explorations based on scale-free, fractal analysis of cyclic motor time series. Such analyses capture non-linear fractal dynamics in temporal fluctuations of motor instances that are believed to reflect how executive control enlist a coordination of multiple interactions across temporal scales between the brain, the body and the task environment, an essential architecture for adaptation. Here by recruiting elite rugby players with high motor skills and submitting them to the execution of rhythmic motor tasks involving legs and arms concurrently, the main attempt was to build on the multifractal formalism of movement control to show a marginal need of effective adaptation in concurrent tasks, and a preserved adaptability despite complexified motor execution. The present study applied a multifractal analytical approach to experimental time series and added surrogate data testing based on shuffled, ARFIMA, Davies&Harte and phase-randomized surrogates, for assessing scale-free behavior in repeated motor time series obtained while combining cycling with finger tapping and with circling. Single-tasking was analyzed comparatively. A focus-based multifractal-DFA approach provided Hurst exponents (H) of individual time series over a range of statistical moments H(), = [-15 15]. H(2) quantified monofractality and H(-15)-H(15) provided an index of multifractality. Despite concurrent tasking, participants showed great capacity to keep the target rhythm. Surrogate data testing showed reasonable reliability in using multifractal formalism to decipher movement control behavior. The global (i.e., monofractal) behavior in single-tasks did not change when adapting to dual-task. Multifractality dominated in cycling and did not change when cycling was challenged by upper limb movements. Likewise, tapping and circling behaviors were preserved despite concurrent cycling. It is concluded that the coordinated executive control when adapting to dual-motor tasking is not modified in people having developed great motor skills through physical training. Executive control likely emerged from multiplicative interactions across temporal scales which puts emphasis on multifractal approaches of the movement system to get critical cues on adaptation. Extending such analyses to less skilled people is appealing in the context of exploring healthy and diseased movement systems.
有证据表明,基于循环运动时间序列的无标度分形分析进行探索,可能有助于更好地理解人类运动系统中的执行控制。此类分析捕捉运动实例时间波动中的非线性分形动力学,这些波动被认为反映了执行控制如何促成大脑、身体和任务环境之间跨时间尺度的多重相互作用的协调,这是适应的基本架构。在此,通过招募具有高运动技能的精英橄榄球运动员,并让他们同时执行涉及腿部和手臂的有节奏运动任务,主要目的是基于运动控制的多重分形形式主义,来表明在并发任务中有效适应的边际需求,以及尽管运动执行变得复杂但仍保留的适应性。本研究将多重分形分析方法应用于实验时间序列,并基于洗牌、自回归分数整合移动平均(ARFIMA)、戴维斯&哈特(Davies&Harte)和相位随机化替代数据进行替代数据测试,以评估在将骑自行车与手指敲击和转圈相结合时获得的重复运动时间序列中的无标度行为。对单任务进行了比较分析。基于焦点的多重分形去趋势波动分析(DFA)方法提供了单个时间序列在一系列统计矩H(α)(α = [-15, 15])范围内的赫斯特指数(H)。H(2)量化了单分形性,H(-15)-H(15)提供了多重分形性指数。尽管是并发任务,参与者仍表现出很强的保持目标节奏的能力。替代数据测试表明,使用多重分形形式主义来解读运动控制行为具有合理的可靠性。单任务中的全局(即单分形)行为在适应双任务时没有改变。在骑自行车时多重分形性占主导,并且当骑自行车受到上肢运动挑战时也没有改变。同样,尽管同时骑自行车,敲击和转圈行为仍得以保留。得出的结论是,通过体育训练发展出高运动技能的人在适应双运动任务时的协调执行控制没有改变。执行控制可能源于跨时间尺度的乘法相互作用,这强调了运动系统的多重分形方法以获取关于适应的关键线索。在探索健康和患病运动系统的背景下,将此类分析扩展到技能较低的人群很有吸引力。