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Probabilistic information transmission in a network of coupled oscillators reveals speed-accuracy trade-off in responding to threats

机译:耦合振荡器网络中的概率信息传输揭示了在应对威胁时速度精度的权衡

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摘要

Individuals in a group may obtain information from other group members about the environment, including the location of a food source or the presence of a predator. Here, we model how information spreads in a group using a susceptible-infected-removed epidemic model. We apply this model to a simulated shoal of fish using the motion dynamics of a coupled oscillator model, in order to test the biological hypothesis that polarized or aligned shoaling leads to faster and more accurate escape responses. The contributions of this study are the (i) application of a probabilistic model of epidemics to the study of collective animal behavior; (ii) testing the biological hypothesis that group cohesion improves predator escape; (iii) quantification of the effect of social cues on startle propagation; and (iv) investigation of the variation in response based on network connectivity. We find that when perfectly aligned individuals in a group are startled, there is a rapid escape by individuals that directly detect the threat, as well as by individuals responding to their neighbors. However, individuals that are not startled do not head away from the threat. In startled groups that are randomly oriented, there is a rapid, accurate response by individuals that directly detect the threat, followed by less accurate responses by individuals responding to neighbor cues. Over the simulation duration, however, even unstartled individuals head away from the threat. This study illustrates a potential speed-accuracy trade-off in the startle response of animal groups, in agreement with several previous experimental studies. Additionally, the model can be applied to a variety of group decision-making processes, including those involving higher-dimensional motion.
机译:团体中的个人可以从其他团体成员获取有关环境的信息,包括食物来源的位置或掠食者的存在。在这里,我们使用易感性感染去除流行模型对信息如何在一组中传播进行建模。我们使用耦合振荡器模型的运动动力学将此模型应用于模拟鱼群,以检验极化或对齐的鱼群导致更快,更准确的逃避响应的生物学假设。这项研究的贡献是:(i)将流行病的概率模型应用于动物集体行为的研究; (ii)检验群体凝聚力改善捕食者逃逸的生物学假设; (iii)量化社交线索对惊吓传播的影响; (iv)调查基于网络连接性的响应变化。我们发现,当一个小组中完全结盟的个人被吓到时,直接检测到威胁的个人以及对邻居做出反应的个人就会迅速逃脱。但是,没有被惊吓的人不会远离威胁。在随机定向的受惊群体中,直接检测到威胁的个人会做出快速,准确的响应,然后是对邻居线索做出响应的个人会做出较不准确的响应。但是,在整个仿真过程中,即使没有惊吓的人也远离威胁。这项研究表明,与先前的一些实验研究一致,动物群体在惊吓反应中可能存在速度准确性的折衷。此外,该模型可以应用于各种群体决策过程,包括那些涉及高维运动的过程。

著录项

  • 期刊名称 Chaos
  • 作者

    Amanda Chicoli; Derek A. Paley;

  • 作者单位
  • 年(卷),期 -1(26),11
  • 年度 -1
  • 页码 116311
  • 总页数 9
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

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