Emergent Runaway into an Avoidance Area in a Swarm of Soldier Crabs

Murakami, Hisashi; Tomaru, Takenori; Nishiyama, Yuta; Moriyama, Tohru; Niizato, Takayuki; Gunji, Yukio Pegio

doi:10.1371/journal.pone.0097870

Cited by 34 publications

(28 citation statements)

References 31 publications

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“…Such behaviors are made possible through communication (e.g. quorum sensing [50]) and synchronization between the different elements (cells) of the system, only when a critical number (or density) of individuals in the population is reached [51][52][53]. In such cases, the LLN and CLT may not likely hold, as the average behavior of individual cells is expected to be different from the behavior of the whole population.…”

Section: Resultsmentioning

confidence: 99%

The reduction of gene expression variability from single cells to populations follows simple statistical laws

Piras¹,

Selvarajoo²

2015

Genomics

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Recent studies on single cells and population transcriptomics have revealed striking differences in global gene expression distributions. Single cells display highly variable expressions between cells, while cell populations present deterministic global patterns. The mechanisms governing the reduction of transcriptome-wide variability over cell ensemble size, however, remain largely unknown. To investigate transcriptome-wide variability of single cells to different sizes of cell populations, we examined RNA-Seq datasets of 6 mammalian cell types. Our statistical analyses show, for each cell type, increasing cell ensemble size reduces scatter in transcriptome-wide expressions and noise (variance over square mean) values, with corresponding increases in Pearson and Spearman correlations. Next, accounting for technical variability by the removal of lowly expressed transcripts, we demonstrate that transcriptome-wide variability reduces, approximating the law of large numbers. Subsequent analyses reveal that the entire gene expressions of cell populations and only the highly expressed portion of single cells are Gaussian distributed, following the central limit theorem.

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Section: Resultsmentioning

confidence: 99%

The reduction of gene expression variability from single cells to populations follows simple statistical laws

Piras¹,

Selvarajoo²

2015

Genomics

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“…In the present study, we show a local interaction named by mutual anticipation that is inspired the behavior of a swarm of soldier crabs3132333435. We previously proposed a model based both on the alignment and the mutual anticipation with asynchronous position updating3637.…”

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confidence: 80%

“…We found that this model of a swarm is more robust against external perturbations than previously considered models34. Moreover, we revealed that an emergent behavior of the soldier crabs could be explained by mutual anticipation31. In addition, we showed that a robust mobile swarm without collective order could be simulated using only on mutual anticipation without velocity matching and the randomly modified principal vector35.…”

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confidence: 87%

Emergence of a coherent and cohesive swarm based on mutual anticipation

Murakami

Niizato

Gunji

2017

Sci Rep

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Collective behavior emerging out of self-organization is one of the most striking properties of an animal group. Typically, it is hypothesized that each individual in an animal group tends to align its direction of motion with those of its neighbors. Most previous models for collective behavior assume an explicit alignment rule, by which an agent matches its velocity with that of neighbors in a certain neighborhood, to reproduce a collective order pattern by simple interactions. Recent empirical studies, however, suggest that there is no evidence for explicit matching of velocity, and that collective polarization arises from interactions other than those that follow the explicit alignment rule. We here propose a new lattice-based computational model that does not incorporate the explicit alignment rule but is based instead on mutual anticipation and asynchronous updating. Moreover, we show that this model can realize densely collective motion with high polarity. Furthermore, we focus on the behavior of a pair of individuals, and find that the turning response is drastically changed depending on the distance between two individuals rather than the relative heading, and is consistent with the empirical observations. Therefore, the present results suggest that our approach provides an alternative model for collective behavior.

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“…The swarm of the species has inherent noise that is individuals' different velocities in maintaining a densely and directed swarm [12]. Such an inherent noise has been found not only in the swarming of soldier crabs but also in other animal groups (e.g., [13,14]).…”

Section: Resultsmentioning

confidence: 99%