Collective motion patterns of self-propelled agents with both velocity alignment and aggregation interactions

2019 ◽  
Vol 99 (2) ◽  
Author(s):  
Bo Li ◽  
Zhi-Xi Wu ◽  
Jian-Yue Guan
Keyword(s):  
Collective Motion ◽  
Motion Patterns

scholarly journals Collective motion patterns of swarms with delay coupling: Theory and experiment

2016 ◽  
Vol 93 (3) ◽  
Author(s):  
Klementyna Szwaykowska ◽  
Ira B. Schwartz ◽  
Luis Mier-y-Teran Romero ◽  
Christoffer R. Heckman ◽  
Dan Mox ◽  
...  
Keyword(s):  
Collective Motion ◽  
Coupling Theory ◽  
Motion Patterns ◽  
Theory And Experiment

scholarly journals Computational and robotic modeling reveal parsimonious combinations of interactions between individuals in schooling fish

2019 ◽  
Author(s):  
Liu Lei ◽  
Ramón Escobedo ◽  
Clément Sire ◽  
Guy Theraulaz
Keyword(s):  
Nearest Neighbor ◽  
Collective Motion ◽  
Group Cohesion ◽  
Behavioral Model ◽  
Minimal Amount ◽  
Motion Patterns ◽  
Physical Constraints ◽  
Amount Of Information ◽  
The One ◽  
The Impact

AbstractCoordinated motion and collective decision-making in fish schools result from complex interactions by which individuals integrate information about the behavior of their neighbors. However, little is known about how individuals integrate this information to take decisions and control their movements. Here, we combine experiments with computational and robotic approaches to investigate the impact of different strategies for a fish to interact with its neighbors on collective swimming in groups of rummy-nose tetra (Hemigrammus rhodostomus). By means of a data-based agent model describing the interactions between pairs ofH. rhodostomus(Caloviet al., 2018), we show that the simple addition of the pairwise interactions with two neighbors quantitatively reproduces the collective behavior observed in groups of five fish. Increasing the number of interacting neighbors does not significantly improve the simulation results. Remarkably, we find that groups remain cohesive and polarized even when each agent only interacts with only one of its neighbors: the one that has the strongest contribution to the heading variation of the focal agent. However, group cohesion is lost when each agent only interacts with its nearest neighbor. We then investigate by means of a swarm robotic platform the collective motion in groups of five robots. Our platform combines the implementation of the fish behavioral model and an engineering-minded control system to deal with real-world physical constraints. We find that swarms of robots are able to reproduce the behavioral patterns observed in groups of five fish when each robot only interacts with its neighbor having the strongest effect on its heading variation, whereas increasing the number of interacting neighbors does not significantly improve the group coordination. Overall, our results suggest that fish have to acquire only a minimal amount of information about their environment to coordinate their movements when swimming in groups.Author SummaryHow do fish combine and integrate information from multiple neighbors when swimming in a school? What is the minimum amount of information about their environment needed to coordinate their motion? To answer these questions, we combine experiments with computational and robotic modeling to test several hypotheses about how individual fish could combine and integrate the information on the behavior of their neighbors when swimming in groups. Our research shows that, for both simulated agents and robots, using the information of two neighbors is sufficient to qualitatively reproduce the collective motion patterns observed in groups of fish. Remarkably, our results also show that it is possible to obtain group cohesion and coherent collective motion over long periods of time even when individuals only interact with their most influential neighbor, that is, the one that exerts the most important effect on their heading variation.

scholarly journals Confinement discerns swarmers from planktonic bacteria

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Weijie Chen ◽  
Neha Mani ◽  
Hamid Karani ◽  
Hao Li ◽  
Sridhar Mani ◽  
...  
Keyword(s):  
Collective Motion ◽  
Bacterial Species ◽  
Agar Plate ◽  
Soft Agar ◽  
Cell Alignment ◽  
Motion Pattern ◽  
Motion Patterns ◽  
Biological Phenotype ◽  
Bacterial Swarming

Powered by flagella, many bacterial species exhibit collective motion on a solid surface commonly known as swarming. As a natural example of active matter, swarming is also an essential biological phenotype associated with virulence, chemotaxis, and host pathogenesis. Physical changes like cell elongation and hyper flagellation have been shown to accompany the swarming phenotype. Less studied, however, are the contrasts of collective motion between the swarming cells and their counterpart planktonic cells of comparable cell density. Here, we show that confining bacterial movement in circular microwells allows distinguishing bacterial swarming from collective swimming. On a soft agar plate, a novel bacterial strain Enterobacter sp. SM3 in swarming and planktonic states exhibited different motion patterns when confined to circular microwells of a specific range of sizes. When the confinement diameter was between 40 μm and 90 μm, swarming SM3 formed a single swirl motion pattern in the microwells whereas planktonic SM3 formed multiple swirls. Similar differential behavior is observed across several other species of gram-negative bacteria. We also observed 'rafting behavior' of swarming bacteria upon dilution. We hypothesize that the rafting behavior might account for the motion pattern difference. We were able to predict these experimental features via numerical simulations where swarming cells are modeled with stronger cell-cell alignment interaction. Our experimental design using PDMS microchip disk arrays enabled us to observe bacterial swarming on murine intestinal surface suggesting a new method for characterizing bacterial swarming under complex environments, such as in polymicrobial niches, and for in vivo swarming exploration.

scholarly journals Oncostreams: Self-organization and dynamics determine spatial heterogeneity and malignant behavior in gliomas

2020 ◽  
Author(s):  
Andrea Comba ◽  
Sebastien Motsch ◽  
Patrick J. Dunn ◽  
Todd C. Hollon ◽  
Daniel B. Zamler ◽  
...  
Keyword(s):  
Tumor Heterogeneity ◽  
Collective Motion ◽  
Dynamic Heterogeneity ◽  
Human Gliomas ◽  
Dynamic Nature ◽  
Motion Patterns ◽  
Learning Analysis ◽  
Tumoral Cells ◽  
Malignant Behavior ◽  
Self Organizing

AbstractTumor heterogeneity is a hallmark of cancer and a determinant of malignant behavior. How tumor heterogeneity arises is thus of fundamental importance. Gliomas display oncostreams, self-organizing multicellular fascicles of elongated, aligned, collectively motile glioma cells, that establish dynamic heterogeneity throughout gliomas. Gliomas exhibit two collective motion patterns: streams, displaying bidirectional collective motion, and flocks, displaying unidirectional collective motion. Oncostreams function as highways to facilitate the intratumoral spread of tumoral and non-tumoral cells. Detailed quantitative and deep learning analysis of rodent and human gliomas uncovered that the density of oncostreams correlates positively with glioma aggressiveness. Our study establishes the self-organizing dynamic nature of gliomas, and its role in setting up dynamic tumor heterogeneity and consequently tumor malignant behavior.

scholarly journals Confinement Discerns Swarmers from Planktonic Bacteria

2020 ◽  
Author(s):  
Weijie Chen ◽  
Neha Mani ◽  
Hamid Karani ◽  
Hao Li ◽  
Sridhar Mani ◽  
...  
Keyword(s):  
Collective Motion ◽  
Bacterial Species ◽  
Agar Plate ◽  
Soft Agar ◽  
Motion Pattern ◽  
Motion Patterns ◽  
Differential Behavior ◽  
Biological Phenotype ◽  
Bacterial Swarming

AbstractPowered by flagella, many bacterial species exhibit collective motion on a solid surface commonly known as swarming. As a natural example of active matter, swarming is also an essential biological phenotype associated with virulence, chemotaxis, and host pathogenesis. Physical changes like cell elongation and hyper flagellation have been shown to accompany the swarming phenotype. However, less noticeable, are the contrasts of collective motion between the swarming cells and the planktonic cells of comparable cell density. Here, we show that confining bacterial movement in designed dimensions allows distinguishing bacterial swarming from collective swimming. We found that on a soft agar plate, a novel bacterial strain Enterobacter sp. SM3 exhibited different motion patterns in swarming and planktonic states when confined to circular microwells of a specific range of sizes. When the confinement diameter was between 40 μm and 90 μm, swarming SM3 formed a single swirl motion pattern in the microwells whereas planktonic SM3 showed multiple swirls. Similar differential behavior is observed across a range of randomly selected gram-negative bacteria. We hypothesize that the “rafting behavior” of the swarming bacteria upon dilution might account for the motion pattern difference. We verified our conjectures via numerical simulations where swarming cells are modeled with lower repulsion and more substantial alignment force. The novel technical approach enabled us to observe swarming on a non-agar tissue surface for the first time. Our work provides the basis for characterizing bacterial swarming under more sophisticated environments, such as polymicrobial swarmer detection, and in vivo swarming exploration.

Local interaction rules and collective motion in black neon tetra (Hyphessobrycon herbertaxelrodi) and zebrafish (Danio rerio).

2019 ◽  
Vol 133 (2) ◽  
pp. 143-155 ◽  
Author(s):  
Vicenç Quera ◽  
Elisabet Gimeno ◽  
Francesc S. Beltran ◽  
Ruth Dolado
Keyword(s):  
Danio Rerio ◽  
Collective Motion ◽  
Local Interaction

RELAXATION AND COLLECTIVE MOTION IN SUPERCONDUCTORS. A TWO-FLUID DESCRIPTION

1978 ◽  
Vol 39 (C6) ◽  
pp. C6-488-C6-489 ◽  
Author(s):  
C. J. Pethick ◽  
H. Smith
Keyword(s):  
Collective Motion ◽  
Two Fluid
Sign in / Sign up

Export Citation Format

Share Document