一个简单的认知模型解释了斑马鱼群游运动中的移动决策
A simple cognitive model explains movement decisions during schooling in zebrafish
AI总结：
本研究提出一个基于显式决策过程的二维认知模型，结合爆发-滑行游动模式，解释斑马鱼在虚拟现实环境中跟随同类时的空间分布和临界分叉现象，为群体运动建模提供基础。
摘要：
动物在移动过程中，无论独自行动还是处于群体中，都必须频繁地对未来的行进方向做出决策。本文以自然成群移动的斑马鱼（Danio rerio）为对象，研究这一过程。利用最先进的虚拟现实技术，我们研究了真实鱼如何跟随一个或多个移动的虚拟同类。这些数据被用于构建并测试一个包含显式决策过程的社会响应模型，在该模型中，鱼可以决定跟随哪一个虚拟同类，或者跟随某个平均方向。这种方法与以往基于连续计算（如方向平均）来确定运动方向的模型形成对比。在先前仅限于鱼运动一维投影的简化模型（Sridhar 等人，2021）的基础上，我们提出一个描述真实鱼在二维空间中自由游动的模型。受实验观察启发，该模型中的鱼游速度采用爆发-滑行（burst-and-coast）游动模式，其中爆发频率取决于鱼与所跟随的虚拟同类之间的距离。我们证明，该模型能够解释实验中真实鱼在虚拟同类后方的观测空间分布。特别地，当鱼决定只跟随一个虚拟同类而非将其作为平均群体跟随，该模型自然解释了自由游动鱼所观察到的临界分叉现象。该模型可为建立成群游动的鱼群模型提供基础，同时在个体层面显式描述其方向决策过程。
英文摘要：
While moving, animals must frequently make decisions about their future travel direction, whether they are alone or in a group. Here we investigate this process for zebrafish (Danio rerio), which naturally move in cohesive groups. Employing state-of-the-art virtual reality, we study how real fish follow one or several moving, virtual conspecifics. These data are used to inform, and test, a model of social response that includes a process of explicit decision-making, whereby the fish can decide which of the virtual conspecifics to follow, or to follow some average direction. This approach is in contrast with previous models where the direction of motion was based on a continuous computation, such as directional averaging. Building upon a simplified version of this model [Sridhar et al. 2021], which was limited to a one-dimensional projection of the fish motion, we present here a model that describes the motion of the real fish as it swims freely in two-dimensions. Motivated by experimental observations, the swim speed of the fish in this model uses a burst-and-coast swimming pattern, with the burst frequency being dependent on the distance of the fish from the followed conspecific(s). We demonstrate that this model is able to explain the observed spatial distribution of the real fish behind the virtual conspecifics in the experiments. In particular, the model naturally explains the observed critical bifurcations for a freely swimming fish, whenever the fish makes a decision to follow only one of the virtual conspecifics, instead of following them as an averaged group. This model can provide the foundation for modeling a cohesive shoal of swimming fish, while explicitly describing their directional decision-making process at the individual level
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
