Visual attention and the acquisition of information in human crowds

Gallup, Andrew C.; Hale, Joseph J.; Sumpter, David J. T.; Garnier, Simon; Kacelnik, Alex; Krebs, John R.; Couzin, Iain D.

doi:10.1073/pnas.1116141109

Cited by 206 publications

(251 citation statements)

References 42 publications

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“…Interestingly, many previous approaches derive from the form P x = f ðxÞ=ðf ðxÞ + f ðyÞÞ (21,22,27,28), which is also a particular case of P x = f ðx; yÞ=ðf ðx; yÞ + f ðy; xÞÞ, and therefore compatible with probability matching. In other cases, the basic form P x = f ðxÞ=ðf ðxÞ + f ðyÞÞ has been modified by adding constant terms (29,30) or an extra function (25), as P x = f ðxÞ=ðf ðxÞ + f ðkÞÞ, with k a constant when animals have access to a single choice (31,32,34). Weber behavior can also be seen as a particular case.…”

Section: Discussionmentioning

confidence: 99%

“…Animals of different species have been observed to incorporate this extra information in their decisions in different ways. Some species make decisions that can be explained using the differences of the numbers of animals taking each option (21,22), others according to the relative differences (Weber's law) (23,24) or using other rules (25)(26)(27)(28)(29)(30)(31)(32)(33)(34). This diversity of decision schemes has translated into a diversity of models (21,22,(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34).…”

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confidence: 99%

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A common rule for decision making in animal collectives across species

Arganda

Pérez‐Escudero

Polavieja

2012

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

170

210

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A diversity of decision-making systems has been observed in animal collectives. In some species, choices depend on the differences of the numbers of animals that have chosen each of the available options, whereas in other species on the relative differences (a behavior known as Weber’s law), or follow more complex rules. We here show that this diversity of decision systems corresponds to a single rule of decision making in collectives. We first obtained a decision rule based on Bayesian estimation that uses the information provided by the behaviors of the other individuals to improve the estimation of the structure of the world. We then tested this rule in decision experiments using zebrafish ( Danio rerio ), and in existing rich datasets of argentine ants ( Linepithema humile ) and sticklebacks ( Gasterosteus aculeatus ), showing that a unified model across species can quantitatively explain the diversity of decision systems. Further, these results show that the different counting systems used by animals, including humans, can emerge from the common principle of using social information to make good decisions.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

A common rule for decision making in animal collectives across species

Arganda

Pérez‐Escudero

Polavieja

2012

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

170

210

View full text Add to dashboard Cite

show abstract

“…This exploration meaningfully extends existing research by measuring interactional outcomes that are nonobservable to individual social actors. Research on information propagation (22), imitation (24), and social influence (25) study large-scale dynamics by focusing on behavior manifested in a social context (e.g., observed, interpreted, and acted on); however, this excludes a large class of situations that involve unobservable cognitive consequences of social interactions, such as mnemonic reinforcement and retrieval-induced forgetting effects. In this study, we fill this gap and provide a framework for investigating the emergent properties of individual cognition at a social level.…”

Section: Discussionmentioning

confidence: 99%

Mnemonic convergence in social networks: The emergent properties of cognition at a collective level

Coman

Momennejad

Drach

et al. 2016

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

102

111

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The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members' memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.mnemonic reinforcement effect | socially-shared retrieval-induced forgetting | social networks | collective memories | emergent phenomena

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“…In humans or animals, collective behaviors are suggested to increase sensory range (Couzin, 2009), and may serve visual attention. However collective behavior can prove difficult to relate to individual behavior (Gallup et al, 2012). Here is further food for thoughts coming from the study of brain networks dynamics.…”

Section: Synchrony Is a Process And A Solutionmentioning

confidence: 99%

Challenges for the understanding of the dynamics of social coordination

Lagarde

2013

Front. Neurorobot.

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The way people interact can be examined by looking at the way they move relative to each other. Seeking the principles behind those interactions have consequences potentially related to any type of interpersonal function, far beyond the so-called “motor” processes typically associated with the study of movements, be it perceptive, cognitive, affective, pragmatic, or epistemic. Here, we present the way the framework of coordination dynamics define and addresses the interactive actions in a dyad. We first introduce the basics of pattern formation as the roots of the theoretical approach of coordination dynamics, and then the way this framework may contribute to establish a solution to classify behaviors. Thereafter we review promising empirical results on the dynamics of interpersonal coordination, and finally discuss were to go next to decipher the way the coordination between two people and the way each individual contribute may be disentangled.

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Visual attention and the acquisition of information in human crowds

Cited by 206 publications

References 42 publications

A common rule for decision making in animal collectives across species

A common rule for decision making in animal collectives across species

Mnemonic convergence in social networks: The emergent properties of cognition at a collective level

Challenges for the understanding of the dynamics of social coordination

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