Free University Amsterdam, Department of Behavioral and Movement Sciences, Parnassia Academy, Parnassia Group, PsyQ, Department of Anxiety Disorders, Early Detection and Intervention Team (EDIT), Lijnbaan 4, 2512VA The Hague, the Netherlands.
Faculty of Social and Behavioral Sciences, Department of Cognitive Psychology, Pieter de la Courtgebouw, Postbus 9555, 2300 RB Leiden, the Netherlands.
Neurosci Biobehav Rev. 2023 Nov;154:105402. doi: 10.1016/j.neubiorev.2023.105402. Epub 2023 Sep 22.
Living systems are hierarchical control systems that display a small world network structure. In such structures, many smaller clusters are nested within fewer larger ones, producing a fractal-like structure with a 'power-law' cluster size distribution (a mereology). Just like their structure, the dynamics of living systems shows fractal-like qualities: the timeseries of inner message passing and overt behavior contain high frequencies or 'states' (treble) that are nested within lower frequencies or 'traits' (bass), producing a power-law frequency spectrum that is known as a 'state-trait continuum' in the behavioral sciences. Here, we argue that the power-law dynamics of living systems results from their power-law network structure: organisms 'vertically encode' the deep spatiotemporal structure of their (anticipated) environments, to the effect that many small clusters near the base of the hierarchy produce high frequency signal changes and fewer larger clusters at its top produce ultra-low frequencies. Such ultra-low frequencies exert a tonic regulatory pressure that produces morphological as well as behavioral traits (i.e., body plans and personalities). Nested-modular structure causes higher frequencies to be embedded within lower frequencies, producing a power-law state-trait continuum. At the heart of such dynamics lies the need for efficient energy dissipation through networks of coupled oscillators, which also governs the dynamics of non-living systems (e.q., earthquakes, stock market fluctuations). Since hierarchical structure produces hierarchical dynamics, the development and collapse of hierarchical structure (e.g., during maturation and disease) should leave specific traces in system dynamics (shifts in lower frequencies, i.e. morphological and behavioral traits) that may serve as early warning signs to system failure. The applications of this idea range from (bio)physics and phylogenesis to ontogenesis and clinical medicine.
生命系统是具有小世界网络结构的分层控制系统。在这种结构中,许多较小的簇嵌套在较少的较大簇中,形成一种分形结构,具有“整体论”的簇大小分布(部分整体关系)。就像它们的结构一样,生命系统的动力学表现出分形特征:内部信息传递和外在行为的时间序列包含高频或“状态”(高音),这些状态嵌套在低频或“特征”(低音)中,产生一种幂律频率谱,在行为科学中被称为“状态-特征连续体”。在这里,我们认为生命系统的幂律动力学源于其幂律网络结构:生物体“垂直编码”其(预期)环境的深度时空结构,以至于层次结构底部附近的许多小簇产生高频信号变化,而其顶部的少数较大簇产生超低频。这种超低频施加一种紧张的调节压力,产生形态和行为特征(即身体计划和个性)。嵌套模块结构导致高频嵌入低频,产生幂律状态-特征连续体。这种动力学的核心是通过耦合振荡器网络有效地耗散能量,这也控制着非生命系统的动力学(例如,地震、股票市场波动)。由于分层结构产生分层动力学,分层结构的发展和崩溃(例如,在成熟和疾病期间)应该在系统动力学中留下特定的痕迹(低频的变化,即形态和行为特征),这些特征可能作为系统故障的早期预警信号。这个想法的应用范围从(生物)物理学和系统发生学到个体发生学和临床医学。