Noise-induced schooling of fish

Jhawar, Jitesh; Morris, Richard G.; Amith-Kumar, U. R.; M, Danny Raj; Rogers, Tim; Rajendran, Harikrishnan; Guttal, Vishwesha

doi:10.1038/s41567-020-0787-y

Cited by 106 publications

(99 citation statements)

References 48 publications

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“…The literature on noise-induced collective behaviour is relatively small and remains largely theoretical. Apart from a recent work which demonstrates that schooling in fish is a noiseinduced state [14], empirical work analysing stochasticity and its role in shaping collective behaviour remains at the margins of collective behaviour research [15][16][17][18][19]. Given that many animals live in small groups and that behavioural interactions are inherently stochastic, we assert that there is a vast scope for applying these intriguing theoretical ideas to empirical research on collective behaviour.…”

Section: Introductionmentioning

confidence: 92%

“…Let us now consider the dynamics of the collective state given by the stochastic differential equation [11,12,14],…”

Section: Noise-induced Collective Behaviour: a Brief Introductionmentioning

confidence: 99%

“…Despite the simplicity, the model can be applied to contexts of decision making and even collective motion-for example, a group moving in an annulus. Indeed, this model and its extensions have been applied in a wide range of contexts, such as marching locusts [18], fish schooling [14], decision making in animals [28,29] recruitment of cell signalling molecules [30] and even financial markets [31,32].…”

Section: Noise-induced Collective Behaviour: a Brief Introductionmentioning

confidence: 99%

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Noise-induced effects in collective dynamics and inferring local interactions from data

Jhawar

Guttal

2020

Phil. Trans. R. Soc. B

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In animal groups, individual decisions are best characterized by probabilistic rules. Furthermore, animals of many species live in small groups. Probabilistic interactions among small numbers of individuals lead to a so-called intrinsic noise at the group level. Theory predicts that the strength of intrinsic noise is not a constant but often depends on the collective state of the group; hence, it is also called a state-dependent noise or a multiplicative noise . Surprisingly, such noise may produce collective order. However, only a few empirical studies on collective behaviour have paid attention to such effects owing to the lack of methods that enable us to connect data with theory. Here, we demonstrate a method to characterize the role of stochasticity directly from high-resolution time-series data of collective dynamics. We do this by employing two well-studied individual-based toy models of collective behaviour. We argue that the group-level noise may encode important information about the underlying processes at the individual scale. In summary, we describe a method that enables us to establish connections between empirical data of animal (or cellular) collectives and the phenomenon of noise-induced states, a field that is otherwise largely limited to the theoretical literature. This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems’.

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Section: Introductionmentioning

confidence: 92%

“…Let us now consider the dynamics of the collective state given by the stochastic differential equation [11,12,14],…”

Section: Noise-induced Collective Behaviour: a Brief Introductionmentioning

confidence: 99%

Section: Noise-induced Collective Behaviour: a Brief Introductionmentioning

confidence: 99%

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Noise-induced effects in collective dynamics and inferring local interactions from data

Jhawar

Guttal

2020

Phil. Trans. R. Soc. B

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“…However, the fundamental mechanisms underlying our results such as self-sorting and the structure-dynamic feedback will not depend on a more complex, empirically derived, relative position dependence. Neither should alternative interaction mechanisms affect these findings [66][67][68][69].…”

Section: Discussionmentioning

confidence: 94%

Collective predator evasion: Putting the criticality hypothesis to the test

Klamser

Romanczuk

2021

PLoS Comput Biol

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According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the “criticality hypothesis”, appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the “criticality hypothesis”, but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality.

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“…A multistate NVM has been proposed to explain the emergence of flocking out from pairwise stochastic interactions [49][50][51]. Experimental evidence of these noisy voter-like interactions was found recently in groups of fish, where schooling is induced by the intrinsic noise that arises from the finite number of interacting individuals [52]. In all these cases, the external noise eliminates the absorbing (consensus) states, and, in the two-state NVM, the noise intensity induces a transition from a bistable phase characterized by a bimodal stationary distribution of opinion density to a monostable phase with a unimodal distribution [44].…”

Section: Introductionmentioning

confidence: 99%

Species exclusion and coexistence in a noisy voter model with a competition-colonization tradeoff

2021

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We introduce an asymmetric noisy voter model to study the joint effect of immigration and a competitiondispersal tradeoff in the dynamics of two species competing for space in regular lattices. Individuals of one species can invade a nearest-neighbor site in the lattice, while individuals of the other species are able to invade sites at any distance but are less competitive locally, i.e., they establish with a probability g 1. The model also accounts for immigration, modeled as an external noise that may spontaneously replace an individual at a lattice site by another individual of the other species. This combination of mechanisms gives rise to a rich variety of outcomes for species competition, including exclusion of either species, monostable coexistence of both species at different population proportions, and bistable coexistence with proportions of populations that depend on the initial condition. Remarkably, in the bistable phase, the system undergoes a discontinuous transition as the intensity of immigration overcomes a threshold, leading to a half loop dynamics associated to a cusp catastrophe, which causes the irreversible loss of the species with the shortest dispersal range.

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Noise-induced schooling of fish

Cited by 106 publications

References 48 publications

Noise-induced effects in collective dynamics and inferring local interactions from data

Noise-induced effects in collective dynamics and inferring local interactions from data

Collective predator evasion: Putting the criticality hypothesis to the test

Species exclusion and coexistence in a noisy voter model with a competition-colonization tradeoff

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