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Guy Theraulaz - One of the best experts on this subject based on the ideXlab platform.
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collective response to perturbations in a data driven fish School Model
2015Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted by threats. However, a School's response to perturbations may be different depending on the nature of its collective state. Here we use a previously developed data-driven fish School Model to investigate how the School responds to perturbations depending on its different collective states, we measure its susceptibility to such perturbations, and exploit its relation with the intrinsic fluctuations in the School. In particular, we study how a single or a small number of perturbing individuals whose attraction and alignment parameters are different from those of the main population affect the long-term behaviour of a School. We find that the responsiveness of the School to the perturbations is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. It is also in this region that the susceptibility, and hence the fluctuations, of the polarization order parameter is maximal. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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collective response to perturbations in a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted to threats. However a School's response to perturbations may be different depending on its collective state. Here we use a previously developed data-driven fish School Model to investigate how a single or a small number of perturbing individuals affect the long-term behaviour of a School depending on its collective state. These perturbing fish are characterised by a set of attraction and alignment parameters different from those of the main population. We find that the responsiveness of the School to the perturbation is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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swarming Schooling milling phase diagram of a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy TheraulazAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais et al (2012 PLoS Comput. Biol. 8 e1002678), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioural transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittence between Schooling and milling for the same combination of individual parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais et al to be adaptive in the experimental conditions.
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swarming Schooling milling phase diagram of a data driven fish School Model
2013Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy Theraulaz, Sandrine NgoAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais etal (PLoS Comp. Biol. 8, e1002678 (2012)), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil}) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioral transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittency between Schooling and milling for the same combination of individuals parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais etal to be adaptive in the experimental conditions.
Daniel S Calovi - One of the best experts on this subject based on the ideXlab platform.
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collective response to perturbations in a data driven fish School Model
2015Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted by threats. However, a School's response to perturbations may be different depending on the nature of its collective state. Here we use a previously developed data-driven fish School Model to investigate how the School responds to perturbations depending on its different collective states, we measure its susceptibility to such perturbations, and exploit its relation with the intrinsic fluctuations in the School. In particular, we study how a single or a small number of perturbing individuals whose attraction and alignment parameters are different from those of the main population affect the long-term behaviour of a School. We find that the responsiveness of the School to the perturbations is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. It is also in this region that the susceptibility, and hence the fluctuations, of the polarization order parameter is maximal. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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collective response to perturbations in a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted to threats. However a School's response to perturbations may be different depending on its collective state. Here we use a previously developed data-driven fish School Model to investigate how a single or a small number of perturbing individuals affect the long-term behaviour of a School depending on its collective state. These perturbing fish are characterised by a set of attraction and alignment parameters different from those of the main population. We find that the responsiveness of the School to the perturbation is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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swarming Schooling milling phase diagram of a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy TheraulazAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais et al (2012 PLoS Comput. Biol. 8 e1002678), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioural transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittence between Schooling and milling for the same combination of individual parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais et al to be adaptive in the experimental conditions.
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swarming Schooling milling phase diagram of a data driven fish School Model
2013Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy Theraulaz, Sandrine NgoAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais etal (PLoS Comp. Biol. 8, e1002678 (2012)), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil}) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioral transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittency between Schooling and milling for the same combination of individuals parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais etal to be adaptive in the experimental conditions.
Clement Sire - One of the best experts on this subject based on the ideXlab platform.
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collective response to perturbations in a data driven fish School Model
2015Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted by threats. However, a School's response to perturbations may be different depending on the nature of its collective state. Here we use a previously developed data-driven fish School Model to investigate how the School responds to perturbations depending on its different collective states, we measure its susceptibility to such perturbations, and exploit its relation with the intrinsic fluctuations in the School. In particular, we study how a single or a small number of perturbing individuals whose attraction and alignment parameters are different from those of the main population affect the long-term behaviour of a School. We find that the responsiveness of the School to the perturbations is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. It is also in this region that the susceptibility, and hence the fluctuations, of the polarization order parameter is maximal. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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collective response to perturbations in a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted to threats. However a School's response to perturbations may be different depending on its collective state. Here we use a previously developed data-driven fish School Model to investigate how a single or a small number of perturbing individuals affect the long-term behaviour of a School depending on its collective state. These perturbing fish are characterised by a set of attraction and alignment parameters different from those of the main population. We find that the responsiveness of the School to the perturbation is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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swarming Schooling milling phase diagram of a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy TheraulazAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais et al (2012 PLoS Comput. Biol. 8 e1002678), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioural transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittence between Schooling and milling for the same combination of individual parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais et al to be adaptive in the experimental conditions.
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swarming Schooling milling phase diagram of a data driven fish School Model
2013Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy Theraulaz, Sandrine NgoAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais etal (PLoS Comp. Biol. 8, e1002678 (2012)), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil}) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioral transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittency between Schooling and milling for the same combination of individuals parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais etal to be adaptive in the experimental conditions.
Ugo Lopez - One of the best experts on this subject based on the ideXlab platform.
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collective response to perturbations in a data driven fish School Model
2015Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted by threats. However, a School's response to perturbations may be different depending on the nature of its collective state. Here we use a previously developed data-driven fish School Model to investigate how the School responds to perturbations depending on its different collective states, we measure its susceptibility to such perturbations, and exploit its relation with the intrinsic fluctuations in the School. In particular, we study how a single or a small number of perturbing individuals whose attraction and alignment parameters are different from those of the main population affect the long-term behaviour of a School. We find that the responsiveness of the School to the perturbations is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. It is also in this region that the susceptibility, and hence the fluctuations, of the polarization order parameter is maximal. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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collective response to perturbations in a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Paul Schuhmacher, Hugues Chate, Clement Sire, Guy TheraulazAbstract:Fish Schools are able to display a rich variety of collective states and behavioural responses when they are confronted to threats. However a School's response to perturbations may be different depending on its collective state. Here we use a previously developed data-driven fish School Model to investigate how a single or a small number of perturbing individuals affect the long-term behaviour of a School depending on its collective state. These perturbing fish are characterised by a set of attraction and alignment parameters different from those of the main population. We find that the responsiveness of the School to the perturbation is maximum near the transition region between milling and Schooling states where the School exhibits multistability and regularly shifts between these two states. We also find that a significant School's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
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swarming Schooling milling phase diagram of a data driven fish School Model
2014Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy TheraulazAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais et al (2012 PLoS Comput. Biol. 8 e1002678), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioural transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittence between Schooling and milling for the same combination of individual parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais et al to be adaptive in the experimental conditions.
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swarming Schooling milling phase diagram of a data driven fish School Model
2013Co-Authors: Daniel S Calovi, Ugo Lopez, Hugues Chate, Clement Sire, Guy Theraulaz, Sandrine NgoAbstract:We determine the basic phase diagram of the fish School Model derived from data by Gautrais etal (PLoS Comp. Biol. 8, e1002678 (2012)), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil}) swimming in a shallow tank. A modified Model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to Schooling induced by increasing the swimming speed, but also on the conditions under which a School can exhibit milling dynamics and the corresponding behavioral transitions. We show the existence of a transition region between milling and Schooling, in which the School exhibits multistability and intermittency between Schooling and milling for the same combination of individuals parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the Model and information propagation delays in the School, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais etal to be adaptive in the experimental conditions.
Heather A Mckay - One of the best experts on this subject based on the ideXlab platform.
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an active School Model to promote physical activity in elementary Schools action Schools bc
2008Co-Authors: Pattijean Naylor, Heather M Macdonald, Darren E R Warburton, Katherine E Reed, Heather A MckayAbstract:Objective: To assess the impact of an active School Model on children’s physical activity (PA). Design: 16-month cluster randomised controlled trial. Setting: 10 elementary Schools in Greater Vancouver, BC. Participants: 515 children aged 9–11 years. Intervention: Action Schools! BC (AS! BC) is an active School Model that provided Schools with training and resources to increase children’s PA. Schools implemented AS! BC with support from either external liaisons (liaison Schools, LS; four Schools) or internal champions (champion Schools, CS; three Schools). Outcomes were compared with usual practice (UP) Schools (three Schools). Main outcome measurements: PA was measured four times during the study using pedometers (step count, steps/day). Results: Boys in the LS group took 1175 more steps per day, on average, than boys in the UP group (95% CI: 97 to 2253). Boys in the CS group also tended to have a higher step count than boys in the UP group (+804 steps/day; 95% CI: 2341 to 1949). There was no difference in girls’ step counts across groups. Conclusions: The positive effect of the AS! BC Model on boys’ PA is important in light of the current global trend of decreased PA.
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lessons learned from action Schools bc an active School Model to promote physical activity in elementary Schools
2006Co-Authors: Pattijean Naylor, Heather M Macdonald, Katherine E Reed, Janelle A Zebedee, Heather A MckayAbstract:Summary The ‘active School’ Model offers promise for promoting School-based physical activity (PA); however, few intervention trials have evaluated its effectiveness. Thus, our purpose was to: (1) describe Action Schools! BC (AS! BC) and its implementation (fidelity and feasibility) and (2) evaluate the impact of AS! BC on School provision of PA. Ten elementary Schools were randomly assigned to one of the three conditions: Usual Practice (UP, three Schools), Liaison (LS, four Schools) or Champion (CS, three Schools). Teachers in LS and CS Schools received AS! BC training and resources but differed on the level of facilitation provided. UP Schools continued with regular PA. Delivery of PA during the 11-month intervention was assessed with weekly Activity Logs and intervention fidelity and feasibility were assessed using Action Plans, workshop evaluations, teacher surveys and focus groups with administrators, teachers, parents and students. Physical activity delivered was significantly greater in LS (+67.4 min/week; 95% CI: 18.7–116.1) and CS (+55.2 min/week; 95% CI: 26.4–83.9) Schools than UP Schools. Analysis of Action Plans and Activity Logs showed fidelity to the Model and moderate levels of compliance (75%). Teachers were highly satisfied with training and support. Benefits of AS! BC included positive changes in the children and School climate, including provision of resources, improved communication and program flexibility. These results support the use of the ‘active School’ Model to positively alter the School environment. The AS! BC Model was effective, providing more opportunities for “more children to be more active more often” and as such has the potential to provide health benefits to elementary School children.
