Turnbull Laura, Hütt Marc-Thorsten, Ioannides Andreas A, Kininmonth Stuart, Poeppl Ronald, Tockner Klement, Bracken Louise J, Keesstra Saskia, Liu Lichan, Masselink Rens, Parsons Anthony J
1Durham University, Durham, UK.
2Jacobs University, Bremen, Germany.
Appl Netw Sci. 2018;3(1):11. doi: 10.1007/s41109-018-0067-2. Epub 2018 Jun 18.
In recent years, parallel developments in disparate disciplines have focused on what has come to be termed ; a concept used in understanding and describing complex systems. Conceptualisations and operationalisations of connectivity have evolved largely within their disciplinary boundaries, yet similarities in this concept and its application among disciplines are evident. However, any implementation of the concept of connectivity carries with it both ontological and epistemological constraints, which leads us to ask if there is one type or set of approach(es) to connectivity that might be applied to all disciplines. In this review we explore four ontological and epistemological challenges in using connectivity to understand complex systems from the standpoint of widely different disciplines. These are: (i) defining the fundamental unit for the study of connectivity; (ii) separating structural connectivity from functional connectivity; (iii) understanding emergent behaviour; and (iv) measuring connectivity. We draw upon discipline-specific insights from Computational Neuroscience, Ecology, Geomorphology, Neuroscience, Social Network Science and Systems Biology to explore the use of connectivity among these disciplines. We evaluate how a connectivity-based approach has generated new understanding of structural-functional relationships that characterise complex systems and propose a 'common toolbox' underpinned by network-based approaches that can advance connectivity studies by overcoming existing constraints.
近年来，不同学科的平行发展聚焦于后来被称为“连通性”的概念；这一概念用于理解和描述复杂系统。连通性的概念化和操作化在很大程度上是在各学科界限内发展起来的，但这一概念及其在各学科间的应用存在明显的相似之处。然而，连通性概念的任何应用都伴随着本体论和认识论的限制，这促使我们思考是否存在一种或一组适用于所有学科的连通性研究方法。在这篇综述中，我们从广泛不同学科的角度探讨了使用连通性来理解复杂系统时面临的四个本体论和认识论挑战。它们分别是：（i）定义连通性研究的基本单元；（ii）区分结构连通性和功能连通性；（iii）理解涌现行为；以及（iv）测量连通性。我们借鉴了计算神经科学、生态学、地貌学、神经科学、社会网络科学和系统生物学等学科的特定见解，以探讨这些学科中连通性的应用。我们评估了基于连通性的方法如何产生了对表征复杂系统的结构 - 功能关系的新理解，并提出了一个以基于网络的方法为支撑的“通用工具箱”，该工具箱可以通过克服现有限制来推进连通性研究。
