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本文引用的文献

1
Inverse Square Lévy Walks are not Optimal Search Strategies for d≥2.在 d≥2 的情况下,平方反比 Lévy 漫步不是最优搜索策略。
Phys Rev Lett. 2020 Feb 28;124(8):080601. doi: 10.1103/PhysRevLett.124.080601.
2
Closer to critical resting-state neural dynamics in individuals with higher fluid intelligence.与具有较高流体智力的个体更接近的关键静息态神经动力学。
Commun Biol. 2020 Feb 3;3(1):52. doi: 10.1038/s42003-020-0774-y.
3
Optimal searching behaviour generated intrinsically by the central pattern generator for locomotion.由运动中央模式发生器产生的最佳搜索行为。
Elife. 2019 Nov 1;8:e50316. doi: 10.7554/eLife.50316.
4
Lévy-like movement patterns of metastatic cancer cells revealed in microfabricated systems and implicated in vivo.微制造系统中揭示的转移性癌细胞的 Lévy 样运动模式及其在体内的作用。
Nat Commun. 2018 Oct 31;9(1):4539. doi: 10.1038/s41467-018-06563-w.
5
Criticality Distinguishes the Ensemble of Biological Regulatory Networks.关键状态区分了生物调控网络的集合。
Phys Rev Lett. 2018 Sep 28;121(13):138102. doi: 10.1103/PhysRevLett.121.138102.
6
Lévy foraging patterns of rural humans.农村人类的 Lévy 觅食模式。
PLoS One. 2018 Jun 18;13(6):e0199099. doi: 10.1371/journal.pone.0199099. eCollection 2018.
7
Lévy flight movements prevent extinctions and maximize population abundances in fragile Lotka-Volterra systems.莱维飞行运动可防止脆弱的洛特卡-沃尔泰拉系统灭绝,并使种群丰度最大化。
Proc Natl Acad Sci U S A. 2018 Apr 10;115(15):3794-3799. doi: 10.1073/pnas.1719889115. Epub 2018 Mar 26.
8
Current status and future directions of Lévy walk research.莱维飞行研究的现状与未来方向。
Biol Open. 2018 Jan 11;7(1):bio030106. doi: 10.1242/bio.030106.
9
Emergence of Lévy Walks from Second-Order Stochastic Optimization.二阶随机优化中 Lévy 行走的出现。
Phys Rev Lett. 2017 Dec 22;119(25):250601. doi: 10.1103/PhysRevLett.119.250601. Epub 2017 Dec 18.
10
The evolutionary origins of Lévy walk foraging.莱维游走觅食的进化起源。
PLoS Comput Biol. 2017 Oct 3;13(10):e1005774. doi: 10.1371/journal.pcbi.1005774. eCollection 2017 Oct.

临界点附近 Lévy 游走的功能优势。

Functional advantages of Lévy walks emerging near a critical point.

机构信息

Center for Advanced Intelligence Project, RIKEN, Tokyo 103-0027, Japan

出版信息

Proc Natl Acad Sci U S A. 2020 Sep 29;117(39):24336-24344. doi: 10.1073/pnas.2001548117. Epub 2020 Sep 14.

DOI:10.1073/pnas.2001548117
PMID:32929032
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7533831/
Abstract

A special class of random walks, so-called Lévy walks, has been observed in a variety of organisms ranging from cells, insects, fishes, and birds to mammals, including humans. Although their prevalence is considered to be a consequence of natural selection for higher search efficiency, some findings suggest that Lévy walks might also be epiphenomena that arise from interactions with the environment. Therefore, why they are common in biological movements remains an open question. Based on some evidence that Lévy walks are spontaneously generated in the brain and the fact that power-law distributions in Lévy walks can emerge at a critical point, we hypothesized that the advantages of Lévy walks might be enhanced by criticality. However, the functional advantages of Lévy walks are poorly understood. Here, we modeled nonlinear systems for the generation of locomotion and showed that Lévy walks emerging near a critical point had optimal dynamic ranges for coding information. This discovery suggested that Lévy walks could change movement trajectories based on the magnitude of environmental stimuli. We then showed that the high flexibility of Lévy walks enabled switching exploitation/exploration based on the nature of external cues. Finally, we analyzed the movement trajectories of freely moving larvae and showed empirically that the Lévy walks may emerge near a critical point and have large dynamic range and high flexibility. Our results suggest that the commonly observed Lévy walks emerge near a critical point and could be explained on the basis of these functional advantages.

摘要

一类特殊的随机游走,即所谓的 Lévy 游走,在从细胞、昆虫、鱼类和鸟类到哺乳动物(包括人类)等各种生物体中都有观察到。尽管 Lévy 游走的普遍性被认为是为了提高搜索效率而进行自然选择的结果,但一些研究结果表明,Lévy 游走也可能是由与环境相互作用而产生的附带现象。因此,为什么它们在生物运动中如此普遍仍然是一个悬而未决的问题。基于一些证据表明 Lévy 游走是在大脑中自发产生的,以及 Lévy 游走中的幂律分布可以在临界点出现的事实,我们假设 Lévy 游走的优势可能会因临界点而增强。然而,对于 Lévy 游走的功能优势,我们还知之甚少。在这里,我们为运动生成建模了非线性系统,并表明在临界点附近出现的 Lévy 游走具有最佳的信息编码动态范围。这一发现表明,Lévy 游走可以根据环境刺激的大小来改变运动轨迹。然后,我们表明 Lévy 游走的高灵活性能够根据外部线索的性质进行开发/探索的切换。最后,我们分析了自由移动幼虫的运动轨迹,并从经验上表明,Lévy 游走可能在临界点附近出现,并且具有较大的动态范围和较高的灵活性。我们的研究结果表明,常见的 Lévy 游走是在临界点附近出现的,可以基于这些功能优势来解释。