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使用信息论工具对集体通信进行解码。

Decoding collective communications using information theory tools.

机构信息

Environmental Laboratory, U.S. Army Engineer Research and Development Center (EL-ERDC), Vicksburg, MS, USA.

EL-ERDC, Newport, OR, USA.

出版信息

J R Soc Interface. 2020 Mar;17(164):20190563. doi: 10.1098/rsif.2019.0563. Epub 2020 Mar 18.

Abstract

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like , and , which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.

摘要

生物进化出了感觉机制,以便从环境中提取相关信息,从而能够评估自身处境并做出相应反应。对于像鱼群或鸟群这样集体活动的社交生物而言,信息共享可以进一步提高它们对环境的感知和反应速度。然而,关于社交协调的收益和成本的数据在很大程度上使我们对集体行为的进化原因的理解超过了我们对其产生机制的机械性认识。最近的研究开始通过对群体运动数据的精细分析来纠正这种不平衡。一种受到重新关注的方法是使用信息论(IT)工具,例如互信息、转移熵和延迟互信息,这些工具可以帮助识别出在生物体集体行动时经常出现的复杂动态模式中的因果相互作用。然而,关注集体行动的生态约束和解决方案的研究与展示 IT 工具在这一领域的应用前景的研究之间存在着沟通上的隔阂。我们试图通过一系列具有生态动机的例子来弥合这一分歧,这些例子旨在说明使用 IT 工具来深入了解群体动态的交互模式的好处和挑战。我们总结了目前在该领域中为克服现有挑战而采取的一些方法,并以乐观但谨慎的态度结束。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91a4/7115225/2c22f06185dd/rsif20190563-g1.jpg

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