Tognoli Emmanuelle, Zhang Mengsen, Fuchs Armin, Beetle Christopher, Kelso J A Scott
Human Brain and Behavior Laboratory, Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL, United States.
Department of Biological Sciences, Florida Atlantic University, Boca Raton, FL, United States.
Front Hum Neurosci. 2020 Aug 14;14:317. doi: 10.3389/fnhum.2020.00317. eCollection 2020.
Humans' interactions with each other or with socially competent machines exhibit lawful coordination patterns at multiple levels of description. According to Coordination Dynamics, such laws specify the flow of coordination states produced by functional synergies of elements (e.g., cells, body parts, brain areas, people…) that are temporarily organized as single, coherent units. These coordinative structures or synergies may be mathematically characterized as informationally coupled self-organizing dynamical systems (Coordination Dynamics). In this paper, we start from a simple foundation, an elemental model system for social interactions, whose behavior has been captured in the Haken-Kelso-Bunz (HKB) model. We follow a tried and tested scientific method that tightly interweaves experimental neurobehavioral studies and mathematical models. We use this method to further develop a body of empirical research that advances the theory toward more generalized forms. In concordance with this interdisciplinary spirit, the present paper is written both as an overview of relevant advances and as an introduction to its mathematical underpinnings. We demonstrate HKB's evolution in the context of social coordination along several directions, with its applicability growing to increasingly complex scenarios. In particular, we show that accommodating for symmetry breaking in intrinsic dynamics and coupling, multiscale generalization and adaptation are principal evolutions. We conclude that a general framework for social coordination dynamics is on the horizon, in which models support experiments with hypothesis generation and mechanistic insights.
人类彼此之间或与具备社交能力的机器之间的互动,在多个描述层面呈现出规律的协调模式。根据协调动力学,此类规律规定了由元素(例如细胞、身体部位、脑区、人……)的功能协同作用所产生的协调状态的流动,这些元素暂时组织成单一、连贯的单元。这些协调结构或协同作用在数学上可被表征为信息耦合的自组织动力系统(协调动力学)。在本文中,我们从一个简单的基础出发,即一个用于社会互动的基本模型系统,其行为已在哈肯-凯尔索-邦兹(HKB)模型中得以体现。我们遵循一种经过反复验证的科学方法,将实验神经行为研究与数学模型紧密交织在一起。我们运用这种方法进一步拓展了一系列实证研究,推动该理论朝着更具普遍性的形式发展。本着这种跨学科精神,本文既是相关进展的综述,也是其数学基础的介绍。我们展示了HKB模型在社会协调背景下沿几个方向的演变,其适用性扩展到日益复杂的场景。特别是,我们表明适应内在动力学和耦合中的对称性破缺、多尺度泛化和适应性是主要的演变方向。我们得出结论,一个社会协调动力学的通用框架即将出现,在这个框架中,模型支持带有假设生成和机制性见解的实验。