scholarly journals Larval zebrafish exhibit collective motion behaviors in constrained spaces

2021 ◽  
Author(s):  
Haider Zaki ◽  
Enkeleida Lushi ◽  
Kristen E Severi
Keyword(s):  
Social Interactions ◽  
Developmental Stage ◽  
Collective Behavior ◽  
Physical Environment ◽  
Collective Motion ◽  
Model System ◽  
Self Organization ◽  
Physical Mechanisms ◽  
Larval Zebrafish ◽  
Advance Knowledge

Collective behavior may be elicited or can spontaneously emerge by a combination of interactions with the physical environment and conspecifics moving within that environment. To investigate the relative contributions of these factors in a small millimeter-scale swimming organism, we observed larval zebrafish, interacting at varying densities under circular confinement. Our aim was to understand the biological and physical mechanisms acting on these larvae as they swim together inside circular confinements. If left undisturbed, larval zebrafish swim intermittently in a burst and coast manner and are socially independent at this developmental stage, before shoaling behavioral onset. We report here our analysis of a new observation for this well-studied species: in circular confinement and at sufficiently high densities, the larvae collectively circle rapidly alongside the boundary. This is a new physical example of self-organization of mesoscale living active matter driven by boundaries and environment geometry. We believe this is a step forward toward using a prominent biological model system in a new interdisciplinary context to advance knowledge of the physics of social interactions.

scholarly journals Larval Zebrafish Exhibit Collective Circulation in Confined Spaces

2021 ◽  
Vol 9 ◽  
Author(s):  
Haider Zaki ◽  
Enkeleida Lushi ◽  
Kristen E. Severi
Keyword(s):  
Social Interactions ◽  
Developmental Stage ◽  
Collective Behavior ◽  
Physical Environment ◽  
Model System ◽  
Biological Model ◽  
Self Organization ◽  
Confined Spaces ◽  
Larval Zebrafish ◽  
Advance Knowledge

Collective behavior may be elicited or can spontaneously emerge by a combination of interactions with the physical environment and conspecifics moving within that environment. To investigate the relative contributions of these factors in a small millimeter-scale swimming organism, we observed larval zebrafish, interacting at varying densities under circular confinement. If left undisturbed, larval zebrafish swim intermittently in a burst and coast manner and are socially independent at this developmental stage, before shoaling behavioral onset. Our aim was to explore the behavior these larvae as they swim together inside circular confinements. We report here our analysis of a new observation for this well-studied species: in circular confinement and at sufficiently high densities, the larvae collectively circle rapidly alongside the boundary. This is a new physical example of self-organization of mesoscale living active matter driven by boundaries and environment geometry. We believe this is a step forward toward using a prominent biological model system in a new interdisciplinary context to advance knowledge of the physics of social interactions.

scholarly journals Emergence of self-organized multivortex states in flocks of active rollers

2020 ◽  
Vol 117 (18) ◽  
pp. 9706-9711 ◽  
Author(s):  
Koohee Han ◽  
Gašper Kokot ◽  
Oleh Tovkach ◽  
Andreas Glatz ◽  
Igor S. Aranson ◽  
...  
Keyword(s):  
Computational Modeling ◽  
Collective Behavior ◽  
Rotational Motion ◽  
Collective Motion ◽  
Self Organization ◽  
Design Strategies ◽  
Vortex Phase ◽  
Active Elements ◽  
Self Organized ◽  
Dynamic Materials

Active matter, both synthetic and biological, demonstrates complex spatiotemporal self-organization and the emergence of collective behavior. A coherent rotational motion, the vortex phase, is of great interest because of its ability to orchestrate well-organized motion of self-propelled particles over large distances. However, its generation without geometrical confinement has been a challenge. Here, we show by experiments and computational modeling that concentrated magnetic rollers self-organize into multivortex states in an unconfined environment. We find that the neighboring vortices more likely occur with the opposite sense of rotation. Our studies provide insights into the mechanism for the emergence of coherent collective motion on the macroscale from the coupling between microscale rotation and translation of individual active elements. These results may stimulate design strategies for self-assembled dynamic materials and microrobotics.

scholarly journals Collective Motion in Human Crowds

2018 ◽  
Vol 27 (4) ◽  
pp. 232-240 ◽  
Author(s):  
William H. Warren
Keyword(s):  
Collective Behavior ◽  
Collective Motion ◽  
Local Level ◽  
Self Organization ◽  
Coherent Motion ◽  
Global Level ◽  
Crowd Behavior ◽  
Local Interactions ◽  
Fish Schools ◽  
Emergency Situations

The balletic motion of bird flocks, fish schools, and human crowds is believed to emerge from local interactions between individuals in a process of self-organization. The key to explaining such collective behavior thus lies in understanding these local interactions. After decades of theoretical modeling, experiments using virtual crowds and analysis of real crowd data are enabling us to decipher the “rules of engagement” governing these interactions. On the basis of such results, my students and I built a dynamical model of how a pedestrian aligns his or her motion with that of a neighbor and how these binary interactions are combined within a neighborhood of interaction. Computer simulations of the model generate coherent motion at the global level and reproduce individual trajectories at the local level. This approach has yielded the first experiment-driven, bottom-up model of collective motion, providing a basis for understanding more complex patterns of crowd behavior in both everyday and emergency situations.

scholarly journals Self-organization of collective escape in pigeon flocks

2022 ◽  
Vol 18 (1) ◽  
pp. e1009772
Author(s):  
Marina Papadopoulou ◽  
Hanno Hildenbrandt ◽  
Daniel W. E. Sankey ◽  
Steven J. Portugal ◽  
Charlotte K. Hemelrijk
Keyword(s):  
Collective Behavior ◽  
Computational Models ◽  
Collective Motion ◽  
Specific Model ◽  
Self Organization ◽  
Behavioral Rules ◽  
Bearing Angle ◽  
Gps Trajectories ◽  
Group Members ◽  
Species Specific

Bird flocks under predation demonstrate complex patterns of collective escape. These patterns may emerge by self-organization from local interactions among group-members. Computational models have been shown to be valuable for identifying what behavioral rules may govern such interactions among individuals during collective motion. However, our knowledge of such rules for collective escape is limited by the lack of quantitative data on bird flocks under predation in the field. In the present study, we analyze the first GPS trajectories of pigeons in airborne flocks attacked by a robotic falcon in order to build a species-specific model of collective escape. We use our model to examine a recently identified distance-dependent pattern of collective behavior: the closer the prey is to the predator, the higher the frequency with which flock members turn away from it. We first extract from the empirical data of pigeon flocks the characteristics of their shape and internal structure (bearing angle and distance to nearest neighbors). Combining these with information on their coordination from the literature, we build an agent-based model adjusted to pigeons’ collective escape. We show that the pattern of turning away from the predator with increased frequency when the predator is closer arises without prey prioritizing escape when the predator is near. Instead, it emerges through self-organization from a behavioral rule to avoid the predator independently of their distance to it. During this self-organization process, we show how flock members increase their consensus over which direction to escape and turn collectively as the predator gets closer. Our results suggest that coordination among flock members, combined with simple escape rules, reduces the cognitive costs of tracking the predator while flocking. Such escape rules that are independent of the distance to the predator can now be investigated in other species. Our study showcases the important role of computational models in the interpretation of empirical findings of collective behavior.

scholarly journals Self-organization of collective escape in pigeon flocks

2021 ◽  
Author(s):  
Marina Papadopoulou ◽  
Hanno Hildenbrandt ◽  
Daniel W.E. Sankey ◽  
Steven J. Portugal ◽  
Charlotte K. Hemelrijk
Keyword(s):  
Collective Behavior ◽  
Computational Models ◽  
Collective Motion ◽  
Specific Model ◽  
Self Organization ◽  
Predator Prey ◽  
Behavioral Rules ◽  
Bearing Angle ◽  
Species Specific

Bird flocks under predation demonstrate complex patterns of collective escape. These patterns may emerge by self-organization from simple interactions among group-members. Computational models have been shown to be valuable for identifying the behavioral rules that may govern these interactions among individuals during collective motion. However, our knowledge of such rules for collective escape is limited by the lack of quantitative data on bird flocks under predation in the field. In the present study, we analyze the first dataset of GPS trajectories of pigeons in airborne flocks attacked by a robotic falcon in order to build a species-specific model of collective escape. We use our model to examine a recently identified distance-dependent pattern of collective behavior that shows an increase in the escape frequency of pigeons when the predator is closer. We first extract from the empirical data the characteristics of pigeon flocks regarding their shape and internal structure (bearing angle and distance to nearest neighbours). Combining these with information on their coordination from the literature, we build an agent-based model tuned to pigeons' collective escape. We show that the pattern of increased escape frequency closer to the predator arises without flock-members prioritizing escape when the predator is near. Instead, it emerges through self-organization from an individual rule of predator-avoidance that is independent of predator-prey distance. During this self-organization process, we uncover a role of hysteresis and show that flock members increase their consensus over the escape direction and turn collectively as the predator gets closer. Our results suggest that coordination among flock-members, combined with simple escape rules, reduces the cognitive costs of tracking the predator. Such rules that are independent of predator-prey distance can now be examined in other species. Finally, we emphasize on the important role of computational models in the interpretation of empirical findings of collective behavior.

scholarly journals Rapid evolution of coordinated and collective movement in response to artificial selection

2020 ◽  
Author(s):  
Alexander Kotrschal ◽  
Alexander Szorkovszky ◽  
James Herbert-Read ◽  
Natasha I. Bloch ◽  
Maksym Romenskyy ◽  
...  
Keyword(s):  
Social Interaction ◽  
Social Interactions ◽  
Artificial Selection ◽  
Collective Behavior ◽  
Poecilia Reticulata ◽  
Collective Motion ◽  
Rapid Evolution ◽  
Social Contexts ◽  
Social Coordination ◽  
Social Decisions

AbstractCollective motion occurs when individuals use social interaction rules to respond to the movements and positions of their neighbors. How readily these social decisions are shaped by selection remains unknown. Through artificial selection on fish (guppies, Poecilia reticulata) for increased social coordination (group polarization), we demonstrate that social interaction rules can evolve remarkably fast. Within just three generations, groups of polarization selected females showed a 15% increase in polarization, coupled with increased cohesiveness, compared to fish from control lines. They did not differ in physical swimming ability or exploratory behavior. However, polarization selected fish adopted faster speeds, particularly in social contexts, and showed stronger alignment and attraction responses to multiple neighbors. Our results demonstrate that animals’ social interactions can rapidly evolve under strong selection, and reveal which social interaction rules change when collective behavior evolves.

scholarly journals Discrete modes of social information processing predict individual behavior of fish in a group

2017 ◽  
Vol 114 (38) ◽  
pp. 10149-10154 ◽  
Author(s):  
Roy Harpaz ◽  
Gašper Tkačik ◽  
Elad Schneidman
Keyword(s):  
Social Interactions ◽  
Social Information Processing ◽  
Collective Behavior ◽  
Single Mode ◽  
Group Behavior ◽  
Neural Correlates ◽  
Individual Behavior ◽  
Group Level ◽  
Adult Zebrafish ◽  
Passive Mode

Individual computations and social interactions underlying collective behavior in groups of animals are of great ethological, behavioral, and theoretical interest. While complex individual behaviors have successfully been parsed into small dictionaries of stereotyped behavioral modes, studies of collective behavior largely ignored these findings; instead, their focus was on inferring single, mode-independent social interaction rules that reproduced macroscopic and often qualitative features of group behavior. Here, we bring these two approaches together to predict individual swimming patterns of adult zebrafish in a group. We show that fish alternate between an “active” mode, in which they are sensitive to the swimming patterns of conspecifics, and a “passive” mode, where they ignore them. Using a model that accounts for these two modes explicitly, we predict behaviors of individual fish with high accuracy, outperforming previous approaches that assumed a single continuous computation by individuals and simple metric or topological weighing of neighbors’ behavior. At the group level, switching between active and passive modes is uncorrelated among fish, but correlated directional swimming behavior still emerges. Our quantitative approach for studying complex, multimodal individual behavior jointly with emergent group behavior is readily extensible to additional behavioral modes and their neural correlates as well as to other species.

Heat shock induces mini-Cajal bodies in the Xenopus germinal vesicle

2002 ◽  
Vol 115 (10) ◽  
pp. 2011-2020 ◽  
Author(s):  
Korie E. Handwerger ◽  
Zheng'an Wu ◽  
Christine Murphy ◽  
Joseph G. Gall
Keyword(s):  
Heat Shock ◽  
Germinal Vesicle ◽  
Model System ◽  
Cajal Body ◽  
Self Organization ◽  
Cajal Bodies ◽  
Oocyte Nucleus ◽  
Evolutionarily Conserved ◽  
And Behavior ◽  
Heat Shock Induction

Cajal bodies are evolutionarily conserved nuclear organelles that are believed to play a central role in assembly of RNA transcription and processing complexes. Although knowledge of Cajal body composition and behavior has greatly expanded in recent years, little is known about the molecules and mechanisms that lead to the formation of these organelles in the nucleus. The Xenopus oocyte nucleus or germinal vesicle is an excellent model system for the study of Cajal bodies, because it is easy to manipulate and it contains 50-100 Cajal bodies with diameters up to 10 μm. In this study we show that numerous mini-Cajal bodies (less than 2 μm in diameter) form in the germinal vesicle after oocytes recover from heat shock. The mechanism for heat shock induction of mini-Cajal bodies is independent of U7 snRNA and does not require transcription or import of newly translated proteins from the cytoplasm. We suggest that Cajal bodies originate by self-organization of preformed components, preferentially on the surface of B-snurposomes.

Sign in / Sign up

Export Citation Format

Share Document