Collective motion in animal groups from a neurobiological perspective: The adaptive benefits of dynamic sensory loads and selective attention

Lemasson, Bertrand H.; Anderson, James J.; Goodwin, R. Andrew

doi:10.1016/j.jtbi.2009.08.013

Cited by 81 publications

(87 citation statements)

References 43 publications

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“…However, we are beginning to appreciate that even humans might rely on relatively simple rules to effectively navigate their environment (35). A model on retinal information processing shows that having a threshold mediated response plus sensitivity to particular information can allow individuals to filter out unimportant information from multiple neighbors while responding to strong directed motion of others (36). Such a mechanism is indeed compatible with our findings and may explain how individuals can disregard information from multiple neighbors.…”

Section: Discussionsupporting

confidence: 80%

Inferring the rules of interaction of shoaling fish

Herbert‐Read

Perna

Mann

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

501

550

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Collective motion, where large numbers of individuals move synchronously together, is achieved when individuals adopt interaction rules that determine how they respond to their neighbors' movements and positions. These rules determine how group-living animals move, make decisions, and transmit information between individuals. Nonetheless, few studies have explicitly determined these interaction rules in moving groups, and very little is known about the interaction rules of fish. Here, we identify three key rules for the social interactions of mosquitofish (Gambusia holbrooki): (i) Attraction forces are important in maintaining group cohesion, while we find only weak evidence that fish align with their neighbor's orientation; (ii) repulsion is mediated principally by changes in speed; (iii) although the positions and directions of all shoal members are highly correlated, individuals only respond to their single nearest neighbor. The last two of these rules are different from the classical models of collective animal motion, raising new questions about how fish and other animals self-organize on the move.collective animal behavior | fish shoals | group motion | self-propelled particles | self-organization C ollective motion of animal groups occurs when multiple individuals move synchronously, producing large scale "flocking" patterns (1-5). Numerous models have been developed to describe patterns of collective motion in terms of interactions between individuals (6-9). These simulation models usually assume that individuals move at a constant speed and their interactions are mediated through direction changes (1). Often these models use zonal rules, where individuals move away from neighbors at close distances and align and/or move toward neighbors at greater distances. Interactions can be with either all neighbors within some zone (7) or with a set of n nearest neighbors (10). These and other models have succeeded in reproducing qualitatively similar patterns to those seen in the collective motion of animal groups in nature.It remains unclear, however, whether the interaction rules implemented in models are the ones used by animals. Indeed, many collective motion patterns observed in nature can be simulated by models using very different interaction rules (1). We are only now beginning to accumulate evidence about which interaction rules are used. There has been recent identification of zones of repulsion and alignment in surf scoters (11). The structure of starling flocks is consistent with topological interactions between the birds (10). Homing pigeons appear to have hierarchical interactions such that birds with higher route-following fidelity act as leaders (12)(13)(14)(15). Partridge showed that lateral line and vision are both important in producing directional alignment in Gadid fish (16). Nonetheless, there remain a large number of open questions about the interactions of fish. For example, do fish adopt attraction and alignment within distinct zones as purported in most models? How many neighbors do fish ...

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Section: Discussionsupporting

confidence: 80%

Inferring the rules of interaction of shoaling fish

Herbert‐Read

Perna

Mann

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

501

550

View full text Add to dashboard Cite

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“…Here, individuals select influential neighbours based on one of two alternative mechanisms: the motion or number of apparent neighbours, as proposed by Lemasson et al [14] and Ballerini et al [6], respectively. Individuals reacting to motion cues direct their attention towards any apparent image(s) whose relative speed exceeds some proportion of their optic flow [14]: Alternatively, individuals reacting to a fixed number of neighbours limit their attention to their n-nearest apparent neighbours [6]:…”

Section: (B) Attention Mechanismsmentioning

confidence: 99%

“…Numerous models have explored how social individuals may integrate local information [6,8,10,[12][13][14][15]. These theoretical efforts are complemented by an equally diverse set of empirical findings supporting various alternatives [6,7,9,10,[15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Motion-guided attention promotes adaptive communications during social navigation

2013

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Animals are capable of enhanced decision making through cooperation, whereby accurate decisions can occur quickly through decentralized consensus. These interactions often depend upon reliable social cues, which can result in highly coordinated activities in uncertain environments. Yet information within a crowd may be lost in translation, generating confusion and enhancing individual risk. As quantitative data detailing animal social interactions accumulate, the mechanisms enabling individuals to rapidly and accurately process competing social cues remain unresolved. Here, we model how motion-guided attention influences the exchange of visual information during social navigation. We also compare the performance of this mechanism to the hypothesis that robust social coordination requires individuals to numerically limit their attention to a set of n-nearest neighbours. While we find that such numerically limited attention does not generate robust social navigation across ecological contexts, several notable qualities arise from selective attention to motion cues. First, individuals can instantly become a local information hub when startled into action, without requiring changes in neighbour attention level. Second, individuals can circumvent speed-accuracy trade-offs by tuning their motion thresholds. In turn, these properties enable groups to collectively dampen or amplify social information. Lastly, the minority required to sway a group's short-term directional decisions can change substantially with social context. Our findings suggest that motion-guided attention is a fundamental and efficient mechanism underlying collaborative decision making during social navigation.

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“…The neighbourhoods defined a priori in a modelling study can be justified by physical sensory arguments (e.g. range of vision through diffusive medium, rapid attenuation of pressure waves) or by neurobiological arguments as in the selective attention model [73]. But considering the tremendous effects of the chosen neighbourhood on the outputs of the simulations in terms of cohesiveness, structure and dynamics of a school, the ultimate test should be a confrontation with experiments, i.e.…”

Section: Determining Which Neighbours a Fish Is Interacting Withmentioning

confidence: 99%

From behavioural analyses to models of collective motion in fish schools

et al. 2012

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Fish schooling is a phenomenon of long-lasting interest in ethology and ecology, widely spread across taxa and ecological contexts, and has attracted much interest from statistical physics and theoretical biology as a case of self-organized behaviour. One topic of intense interest is the search of specific behavioural mechanisms at stake at the individual level and from which the school properties emerges. This is fundamental for understanding how selective pressure acting at the individual level promotes adaptive properties of schools and in trying to disambiguate functional properties from non-adaptive epiphenomena. Decades of studies on collective motion by means of individual-based modelling have allowed a qualitative understanding of the self-organization processes leading to collective properties at school level, and provided an insight into the behavioural mechanisms that result in coordinated motion. Here, we emphasize a set of paradigmatic modelling assumptions whose validity remains unclear, both from a behavioural point of view and in terms of quantitative agreement between model outcome and empirical data. We advocate for a specific and biologically oriented re-examination of these assumptions through experimental-based behavioural analysis and modelling.

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Collective motion in animal groups from a neurobiological perspective: The adaptive benefits of dynamic sensory loads and selective attention

Cited by 81 publications

References 43 publications

Inferring the rules of interaction of shoaling fish

Inferring the rules of interaction of shoaling fish

Motion-guided attention promotes adaptive communications during social navigation

From behavioural analyses to models of collective motion in fish schools

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