Behavioural Biology Unit, University of Liège, Liège, Belgium.
Department of Psychology, Wilfrid Laurier University, Waterloo, Ontario, Canada.
Behav Res Methods. 2018 Aug;50(4):1673-1685. doi: 10.3758/s13428-018-1024-9.
Collective behaviors are observed throughout nature, from bacterial colonies to human societies. Important theoretical breakthroughs have recently been made in understanding why animals produce group behaviors and how they coordinate their activities, build collective structures, and make decisions. However, standardized experimental methods to test these findings have been lacking. Notably, easily and unambiguously determining the membership of a group and the responses of an individual within that group is still a challenge. The radial arm maze is presented here as a new standardized method to investigate collective exploration and decision-making in animal groups. This paradigm gives individuals within animal groups the opportunity to make choices among a set of discrete alternatives, and these choices can easily be tracked over long periods of time. We demonstrate the usefulness of this paradigm by performing a set of refuge-site selection experiments with groups of fish. Using an open-source, robust custom image-processing algorithm, we automatically counted the number of animals in each arm of the maze to identify the majority choice. We also propose a new index to quantify the degree of group cohesion in this context. The radial arm maze paradigm provides an easy way to categorize and quantify the choices made by animals. It makes it possible to readily apply the traditional uses of the radial arm maze with single animals to the study of animal groups. Moreover, it opens up the possibility of studying questions specifically related to collective behaviors.
集体行为在自然界中随处可见，从细菌菌落到人类社会。最近在理解动物产生群体行为的原因以及它们如何协调活动、构建集体结构和做出决策方面取得了重要的理论突破。然而，缺乏测试这些发现的标准化实验方法。值得注意的是，轻松、明确地确定群体的成员以及该群体中个体的反应仍然是一个挑战。本文提出了放射臂迷宫作为一种新的标准化方法，用于研究动物群体中的集体探索和决策。该范式为动物群体中的个体提供了在一组离散选择中做出选择的机会，并且这些选择可以很容易地在长时间内进行跟踪。我们通过使用一组鱼类进行避难所选择实验来证明该范式的有用性。使用开源、强大的自定义图像处理算法，我们自动计算迷宫每个臂中的动物数量，以确定多数选择。我们还提出了一个新的指数来量化这种情况下的群体凝聚力程度。放射臂迷宫范式提供了一种简单的方法来对动物的选择进行分类和量化。它使得可以很容易地将传统的单个动物使用放射臂迷宫的方法应用于动物群体的研究。此外，它还为研究与集体行为相关的特定问题提供了可能性。
