Social Foraging
Follow
Find
60.9K views | +0 today
Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
Your new post is loading...
Your new post is loading...
Scooped by Ashish Umre
Scoop.it!

Artifacts Shed Light on Social Networks of the Past

Artifacts Shed Light on Social Networks of the Past | Social Foraging | Scoop.it

The advent of social networking sites like Facebook and Twitter have made us all more connected, but long-distance social networks existed long before the Internet.

 

An article published this week in the Proceedings of the National Academy of Sciences sheds light on the transformation of social networks in the late pre-Hispanic American Southwest and shows that people of that period were able to maintain surprisingly long-distance relationships with nothing more than their feet to connect them.

 

Led by University of Arizona anthropologist Barbara Mills, the study is based on analysis of more than 800,000 painted ceramic and more than 4,800 obsidian artifacts dating from A.D. 1200-1450, uncovered from more than 700 sites in the western Southwest, in what is now Arizona and western New Mexico.

 

With funding from the National Science Foundation, Mills, director of the UA School of Anthropology, worked with collaborators at Archeology Southwest in Tucson to compile a database of more than 4.3 million ceramic artifacts and more than 4,800 obsidian artifacts, from which they drew for the study.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Banks: From Bubbles & Nuclear Winters To Golden Eras

Banks: From Bubbles & Nuclear Winters To Golden Eras | Social Foraging | Scoop.it

On November 15, 1971, an advertisement appeared in Electronic News in Santa Clara, California for a new electronic device. It was called the 4004. It was the first commercially available microprocessor that could make calculations on a silicon chip. It cost sixty dollars.

 

Although practically no one realized it at the time, this was “the big bang of a new universe of all-pervasive computing and digital communications”. The chips were powerful and cheap. They opened innumerable technological and business possibilities. They would transform the way people lived and worked around the world.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

The Evolutionary Dynamics of Protein-Protein Interaction Networks Inferred from the Reconstruction of Ancient Networks

The Evolutionary Dynamics of Protein-Protein Interaction Networks Inferred from the Reconstruction of Ancient Networks | Social Foraging | Scoop.it

Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. A number of theoretical models have been developed to explain both the network formation and the current structure. Favored are models based on duplication and divergence of genes, as they most closely represent the biological foundation of network evolution. However, studies are often based on simulated instead of empirical data or they cover only single organisms. Methodological improvements now allow the analysis of PPI networks of multiple organisms simultaneously as well as the direct modeling of ancestral networks. This provides the opportunity to challenge existing assumptions on network evolution. We utilized present-day PPI networks from integrated datasets of seven model organisms and developed a theoretical and bioinformatic framework for studying the evolutionary dynamics of PPI networks. A novel filtering approach using percolation analysis was developed to remove low confidence interactions based on topological constraints. We then reconstructed the ancient PPI networks of different ancestors, for which the ancestral proteomes, as well as the ancestral interactions, were inferred. Ancestral proteins were reconstructed using orthologous groups on different evolutionary levels. A stochastic approach, using the duplication-divergence model, was developed for estimating the probabilities of ancient interactions from today's PPI networks. The growth rates for nodes, edges, sizes and modularities of the networks indicate multiplicative growth and are consistent with the results from independent static analysis. Our results support the duplication-divergence model of evolution and indicate fractality and multiplicative growth as general properties of the PPI network structure and dynamics.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

A “Bat” Is Easier to Learn than a “Tab”: Effects of Relative Phonotactic Frequency on Infant Word Learning

A “Bat” Is Easier to Learn than a “Tab”: Effects of Relative Phonotactic Frequency on Infant Word Learning | Social Foraging | Scoop.it

Many studies have shown that during the first year of life infants start learning the prosodic, phonetic and phonotactic properties of their native language. In parallel, infants start associating sound sequences with semantic representations. However, the question of how these two processes interact remains largely unknown. The current study explores whether (and when) the relative phonotactic probability of a sound sequence in the native language has an impact on infants’ word learning. We exploit the fact that Labial-Coronal (LC) words are more frequent than Coronal-Labial (CL) words in French, and that French-learning infants prefer LC over CL sequences at 10 months of age, to explore the possibility that LC structures might be learned more easily and thus at an earlier age than CL structures. Eye movements of French-learning 14- and 16-month-olds were recorded while they watched animated cartoons in a word learning task. The experiment involved four trials testing LC sequences and four trials testing CL sequences. Our data reveal that 16-month-olds were able to learn the LC and CL words, while14-month-olds were only able to learn the LC words, which are the words with the more frequent phonotactic pattern. The present results provide evidence that infants’ knowledge of their native language phonotactic patterns influences their word learning: Words with a frequent phonotactic structure could be acquired at an earlier age than those with a lower probability. Developmental changes are discussed and integrated with previous findings.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Limiting Factors for Mapping Corpus-Based Semantic Representations to Brain Activity

Limiting Factors for Mapping Corpus-Based Semantic Representations to Brain Activity | Social Foraging | Scoop.it

To help understand how semantic information is represented in the human brain, a number of previous studies have explored how a linear mapping from corpus derived semantic representations to corresponding patterns of fMRI brain activations can be learned. They have demonstrated that such a mapping for concrete nouns is able to predict brain activations with accuracy levels significantly above chance, but the more recent elaborations have achieved relatively little performance improvement over the original study. In fact, the absolute accuracies of all these models are still currently rather limited, and it is not clear which aspects of the approach need improving in order to achieve performance levels that might lead to better accounts of human capabilities. This paper presents a systematic series of computational experiments designed to identify the limiting factors of the approach. Two distinct series of artificial brain activation vectors with varying levels of noise are introduced to characterize how the brain activation data restricts performance, and improved corpus based semantic vectors are developed to determine how the word set and model inputs affect the results. These experiments lead to the conclusion that the current state-of-the-art input semantic representations are already operating nearly perfectly (at least for non-ambiguous concrete nouns), and that it is primarily the quality of the fMRI data that is limiting what can be achieved with this approach. The results allow the study to end with empirically informed suggestions about the best directions for future research in this area.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Information-Theoretic Analysis of the Dynamics of an Executable Biological Model

Information-Theoretic Analysis of the Dynamics of an Executable Biological Model | Social Foraging | Scoop.it

To facilitate analysis and understanding of biological systems, large-scale data are often integrated into models using a variety of mathematical and computational approaches. Such models describe the dynamics of the biological system and can be used to study the changes in the state of the system over time. For many model classes, such as discrete or continuous dynamical systems, there exist appropriate frameworks and tools for analyzing system dynamics. However, the heterogeneous information that encodes and bridges molecular and cellular dynamics, inherent to fine-grained molecular simulation models, presents significant challenges to the study of system dynamics. In this paper, we present an algorithmic information theory based approach for the analysis and interpretation of the dynamics of such executable models of biological systems. We apply a normalized compression distance (NCD) analysis to the state representations of a model that simulates the immune decision making and immune cell behavior. We show that this analysis successfully captures the essential information in the dynamics of the system, which results from a variety of events including proliferation, differentiation, or perturbations such as gene knock-outs. We demonstrate that this approach can be used for the analysis of executable models, regardless of the modeling framework, and for making experimentally quantifiable predictions.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Drawing from Memory: Hand-Eye Coordination at Multiple Scales

Drawing from Memory: Hand-Eye Coordination at Multiple Scales | Social Foraging | Scoop.it

Eyes move to gather visual information for the purpose of guiding behavior. This guidance takes the form of perceptual-motor interactions on short timescales for behaviors like locomotion and hand-eye coordination. More complex behaviors require perceptual-motor interactions on longer timescales mediated by memory, such as navigation, or designing and building artifacts. In the present study, the task of sketching images of natural scenes from memory was used to examine and compare perceptual-motor interactions on shorter and longer timescales. Eye and pen trajectories were found to be coordinated in time on shorter timescales during drawing, and also on longer timescales spanning study and drawing periods. The latter type of coordination was found by developing a purely spatial analysis that yielded measures of similarity between images, eye trajectories, and pen trajectories. These results challenge the notion that coordination only unfolds on short timescales. Rather, the task of drawing from memory evokes perceptual-motor encodings of visual images that preserve coarse-grained spatial information over relatively long timescales as well.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Here Today, Gone Tomorrow – Adaptation to Change in Memory-Guided Visual Search

Here Today, Gone Tomorrow – Adaptation to Change in Memory-Guided Visual Search | Social Foraging | Scoop.it

Visual search for a target object can be facilitated by the repeated presentation of an invariant configuration of nontargets (‘contextual cueing’). Here, we tested adaptation of learned contextual associations after a sudden, but permanent, relocation of the target. After an initial learning phase targets were relocated within their invariant contexts and repeatedly presented at new locations, before they returned to the initial locations. Contextual cueing for relocated targets was neither observed after numerous presentations nor after insertion of an overnight break. Further experiments investigated whether learning of additional, previously unseen context-target configurations is comparable to adaptation of existing contextual associations to change. In contrast to the lack of adaptation to changed target locations, contextual cueing developed for additional invariant configurations under identical training conditions. Moreover, across all experiments, presenting relocated targets or additional contexts did not interfere with contextual cueing of initially learned invariant configurations. Overall, the adaptation of contextual memory to changed target locations was severely constrained and unsuccessful in comparison to learning of an additional set of contexts, which suggests that contextual cueing facilitates search for only one repeated target location.

more...
No comment yet.
Rescooped by Ashish Umre from Papers
Scoop.it!

Smart Rewiring for Network Robustness

While new forms of attacks are developed every day to compromise essential infrastructures, service providers are also expected to develop strategies to mitigate the risk of extreme failures. In this context, tools of Network Science have been used to evaluate network robustness and propose resilient topologies against attacks. We present here a new rewiring method to modify the network topology improving its robustness, based on the evolution of the network largest component during a sequence of targeted attacks. In comparison to previous strategies, our method lowers by several orders of magnitude the computational effort necessary to improve robustness. 

 

Smart Rewiring for Network Robustness

V.H.P. Louzada, F. Daolio, H.J. Herrmann, M. Tomassini

http://arxiv.org/abs/1303.5269


Via Complexity Digest
more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Angiogenesis: An Adaptive Dynamic Biological Patterning Problem

Angiogenesis: An Adaptive Dynamic Biological Patterning Problem | Social Foraging | Scoop.it

Formation of functionally adequate vascular networks by angiogenesis presents a problem in biological patterning. Generated without predetermined spatial patterns, networks must develop hierarchical tree-like structures for efficient convective transport over large distances, combined with dense space-filling meshes for short diffusion distances to every point in the tissue. Moreover, networks must be capable of restructuring in response to changing functional demands without interruption of blood flow. Here, theoretical simulations based on experimental data are used to demonstrate that this patterning problem can be solved through over-abundant stochastic generation of vessels in response to a growth factor generated in hypoxic tissue regions, in parallel with refinement by structural adaptation and pruning. Essential biological mechanisms for generation of adequate and efficient vascular patterns are identified and impairments in vascular properties resulting from defects in these mechanisms are predicted. The results provide a framework for understanding vascular network formation in normal or pathological conditions and for predicting effects of therapies targeting angiogenesis.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

The Virus That Learns

The Virus That Learns | Social Foraging | Scoop.it

If you don’t have an immune system, you don’t last long in this parasite-riddled world. Your body receives a steady stream of invaders–viruses, bacteria, and other pathogens–which it has to recognize and fight. In many cases, it’s a brutal battle with an ultimate goal of eradication. In other cases, the immune system simply keeps strangers in check, preventing them from spreading. As many as a third of all humans have cysts in their brains containing a single-celled parasite called Toxoplasma. As long as the parasite stays in its cyst, the immune system lets it be. If Toxoplasma breaks out and starts to multiply, however, the immune system picks off the new cells. And if people lose their immune system–due to HIV infection, for example–Toxoplasma runs rampant and causes devastating brain damage.

 

more...
No comment yet.
Rescooped by Ashish Umre from Papers
Scoop.it!

Predicting and controlling infectious disease epidemics using temporal networks

Predicting and controlling infectious disease epidemics using temporal networks | Social Foraging | Scoop.it

Infectious diseases can be considered to spread over social networks of people or animals. Mainly owing to the development of data recording and analysis techniques, an increasing amount of social contact data with time stamps has been collected in the last decade. Such temporal data capture the dynamics of social networks on a timescale relevant to epidemic spreading and can potentially lead to better ways to analyze, forecast, and prevent epidemics. However, they also call for extended analysis tools for network epidemiology, which has, to date, mostly viewed networks as static entities. We review recent results of network epidemiology for such temporal network data and discuss future developments.

 

Predicting and controlling infectious disease epidemics using temporal networks

Naoki Masuda and Petter Holme

F1000Prime Rep2013, 5:6 (doi: 10.12703/P5-6)

http://f1000.com/prime/reports/b/5/6


Via Complexity Digest
more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Using Bayesian networks to discover relations between genes, environment, and disease

We review the applicability of Bayesian networks (BNs) for discovering relations between genes, environment, and disease. By translating probabilistic dependencies among variables into graphical models and vice versa, BNs provide a comprehensible and modular framework for representing complex systems.

We first describe the Bayesian network approach and its applicability to understanding the genetic and environmental basis of disease. We then describe a variety of algorithms for learning the structure of a network from observational data.

Because of their relevance to real-world applications, the topics of missing data and causal interpretation are emphasized. The BN approach is then exemplified through application to data from a population-based study of bladder cancer in New Hampshire, USA.
more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Bacteria to become 'bio-batteries': Bacteria power 'bio-battery' breakthrough

Bacteria to become 'bio-batteries': Bacteria power 'bio-battery' breakthrough | Social Foraging | Scoop.it
Bacteria could soon be acting as microscopic "bio-batteries" thanks to a joint UK-US research effort.

 

The team of scientists has laid bare the power-generating mechanism used by well-known marine bacteria.

 

Before now it was not clear whether the bacteria generated an electrical charge themselves or used something else to do it.

 

Unpicking the process opens the door to using the bacteria as an in-situ robust power source.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

I Should but I Won’t: Why Young Children Endorse Norms of Fair Sharing but Do Not Follow Them

I Should but I Won’t: Why Young Children Endorse Norms of Fair Sharing but Do Not Follow Them | Social Foraging | Scoop.it

Young children endorse fairness norms related to sharing, but often act in contradiction to those norms when given a chance to share. This phenomenon has rarely been explored in the context of a single study. Using a novel approach, the research presented here offers clear evidence of this discrepancy and goes on to examine possible explanations for its diminution with age. In Study 1, 3–8-year-old children readily stated that they themselves should share equally, asserted that others should as well, and predicted that others had shared equally with them. Nevertheless, children failed to engage in equal sharing until ages 7–8. In Study 2, 7–8-year-olds correctly predicted that they would share equally, and 3–6-year-olds correctly predicted that they would favor themselves, ruling out a failure-of-willpower explanation for younger children's behavior. Similarly, a test of inhibitory control in Study 1 also failed to explain the shift with age toward adherence to the endorsed norm. The data suggest that, although 3-year-olds know the norm of equal sharing, the weight that children attach to this norm increases with age when sharing involves a cost to the self.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

The Co-Evolution of Fairness Preferences and Costly Punishment

The Co-Evolution of Fairness Preferences and Costly Punishment | Social Foraging | Scoop.it

We study the co-evolutionary emergence of fairness preferences in the form of other-regarding behavior and its effect on the origination of costly punishment behavior in public good games. Our approach closely combines empirical results from three experiments with an evolutionary simulation model. In this way, we try to fill a gap between the evolutionary theoretical literature on cooperation and punishment on the one hand and the empirical findings from experimental economics on the other hand. As a principal result, we show that the evolution among interacting agents inevitably favors a sense for fairness in the form of “disadvantageous inequity aversion”. The evolutionary dominance and stability of disadvantageous inequity aversion is demonstrated by enabling agents to co-evolve with different self- and other-regarding preferences in a competitive environment with limited resources. Disadvantageous inequity aversion leads to the emergence of costly (“altruistic”) punishment behavior and quantitatively explains the level of punishment observed in contemporary lab experiments performed on subjects with a western culture. Our findings corroborate, complement, and interlink the experimental and theoretical literature that has shown the importance of other-regarding behavior in various decision settings.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

A Comparison of the Spatial Linear Model to Nearest Neighbor (k-NN) Methods for Forestry Applications

Forest surveys provide critical information for many diverse interests. Data are often collected from samples, and from these samples, maps of resources and estimates of aerial totals or averages are required. In this paper, two approaches for mapping and estimating totals; the spatial linear model (SLM) and k-NN (k-Nearest Neighbor) are compared, theoretically, through simulations, and as applied to real forestry data. While both methods have desirable properties, a review shows that the SLM has prediction optimality properties, and can be quite robust. Simulations of artificial populations and resamplings of real forestry data show that the SLM has smaller empirical root-mean-squared prediction errors (RMSPE) for a wide variety of data types, with generally less bias and better interval coverage than k-NN. These patterns held for both point predictions and for population totals or averages, with the SLM reducing RMSPE from 9% to 67% over some popular k-NN methods, with SLM also more robust to spatially imbalanced sampling. Estimating prediction standard errors remains a problem for k-NN predictors, despite recent attempts using model-based methods. Our conclusions are that the SLM should generally be used rather than k-NN if the goal is accurate mapping or estimation of population totals or averages.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

A Computational Model for Collective Cellular Motion in Three Dimensions: General Framework and Case Study for Cell Pair Dynamics

A Computational Model for Collective Cellular Motion in Three Dimensions: General Framework and Case Study for Cell Pair Dynamics | Social Foraging | Scoop.it

Cell migration in healthy and diseased systems is a combination of single and collective cell motion. While single cell motion has received considerable attention, our understanding of collective cell motion remains elusive. A new computational framework for the migration of groups of cells in three dimensions is presented, which focuses on the forces acting at the microscopic scale and the interactions between cells and their extracellular matrix (ECM) environment. Cell-cell adhesion, resistance due to the ECM and the factors regulating the propulsion of each cell through the matrix are considered. In particular, our approach emphasizes the role of receptors that mediate cell-cell and cell-matrix interactions, and examines how variation in their properties induces changes in cellular motion. As an important case study, we analyze two interacting cells. Our results show that the dynamics of cell pairs depends on the magnitude and the stochastic nature of the forces. Stronger intercellular stability is generally promoted by surface receptors that move. We also demonstrate that matrix resistance, cellular stiffness and intensity of adhesion contribute to migration behaviors in different ways, with memory effects present that can alter pair motility. If adhesion weakens with time, our findings show that cell pair break-up depends strongly on the way cells interact with the matrix. Finally, the motility for cells in a larger cluster (size 50 cells) is examined to illustrate the full capabilities of the model and to stress the role of cellular pairs in complex cellular structures. Overall, our framework shows how properties of cells and their environment influence the stability and motility of cellular assemblies. This is an important step in the advancement of the understanding of collective motility, and can contribute to knowledge of complex biological processes involving migration, aggregation and detachment of cells in healthy and diseased systems.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Agent-Based Models of Strategies for the Emergence and Evolution of Grammatical Agreement

Agent-Based Models of Strategies for the Emergence and Evolution of Grammatical Agreement | Social Foraging | Scoop.it

Grammatical agreement means that features associated with one linguistic unit (for example number or gender) become associated with another unit and then possibly overtly expressed, typically with morphological markers. It is one of the key mechanisms used in many languages to show that certain linguistic units within an utterance grammatically depend on each other. Agreement systems are puzzling because they can be highly complex in terms of what features they use and how they are expressed. Moreover, agreement systems have undergone considerable change in the historical evolution of languages. This article presents language game models with populations of agents in order to find out for what reasons and by what cultural processes and cognitive strategies agreement systems arise. It demonstrates that agreement systems are motivated by the need to minimize combinatorial search and semantic ambiguity, and it shows, for the first time, that once a population of agents adopts a strategy to invent, acquire and coordinate meaningful markers through social learning, linguistic self-organization leads to the spontaneous emergence and cultural transmission of an agreement system. The article also demonstrates how attested grammaticalization phenomena, such as phonetic reduction and conventionalized use of agreement markers, happens as a side effect of additional economizing principles, in particular minimization of articulatory effort and reduction of the marker inventory. More generally, the article illustrates a novel approach for studying how key features of human languages might emerge.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Attractor Metabolic Networks

Attractor Metabolic Networks | Social Foraging | Scoop.it

The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Long-term evolutionary outcomes are constrained, surprisingly predictable

Long-term evolutionary outcomes are constrained, surprisingly predictable | Social Foraging | Scoop.it

A new study co-authored by SFI External Professor and Science Board co-chair Marcus Feldman demonstrates that not only is long-term evolution possible, but long-term evolutionary outcomes can be surprisingly predictable.

 

In recent years, some scientists have argued that natural selection occurs not just at the individual organism level, but also between lineages over the course of many generations.

 

The Stanford group set up a computer simulation in which 128 lineages of proteins continuously folded into new shapes, competing to bind with other molecules, called ligands, in each new configuration. The better each protein could attach itself to the ligands, the more ligands it would scoop up, and the higher its fitness – that is, its average number of "offspring" – would be. The simulation was run for 10,000 generations.

 

Although the chaos of 128 lineages – a total of more than 16,000 individual proteins – mutating over thousands of generations might seem unpredictable, and that it would be nearly impossible for the same thing to happen twice, it's actually the opposite, the researchers say.

 

"Even though things look complicated, the possible evolutionary trajectories are quite constrained," said lead author Michael Palmer, a computational biologist at Stanford. "There are only a few viable mutations at any point, which makes the dynamics predictable and repeatable, even over the long term."

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Multi-scale Inference of Interaction Rules in Animal Groups Using Bayesian Model Selection

Multi-scale Inference of Interaction Rules in Animal Groups Using Bayesian Model Selection | Social Foraging | Scoop.it

Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis). We show that these exhibit a stereotypical ‘phase transition’, whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have ‘memory’ of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture the observed locality of interactions. Traditional self-propelled particle models fail to capture the fine scale dynamics of the system. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics, while maintaining a biologically plausible perceptual range. We conclude that prawns’ movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Bees can sense—and learn from—the electric fields of flowers

Bees can sense—and learn from—the electric fields of flowers | Social Foraging | Scoop.it

Flowers offer all sorts of cues to their pollinators—colors, patterns, shapes, and scents all help plants communicate with butterflies, bats, birds, and bees. But recent research suggests that another type of information—electrical fields—may work in concert with these other cues to provide extremely nuanced details about pollination status. This week in the journal Science, researchers show that this may play an important role in the extremely close-knit relationship between flowers and their pollinators.

 

As they travel through the air, bumblebees lose electrons, accumulating a small positive electrical charge. Flowers, meanwhile, are generally negatively charged at the top, thanks to a slight positive charge in the air around them. As a bee approaches a flower, a tiny electric field is created between plant and pollinator.

 

In the past, scientists have suggested that these differing charges encourage the transfer of pollen between flower and bee, helping the tiny pollen grains “jump” onto the pollinator. However, the new study showed that the bee’s landing actually influences the flower’s electrical charge—increasing it slightly—for a short period of time. The study's authors hypothesize that this change may signal to the next bee that the flower has just been visited and that its nectar stash is depleted. Other cues, such as a flower’s shape or color, sometimes change in response to a bee’s visit, but these changes can take hours. The electrical field, on the other hand, changes almost instantaneously, providing a nearly immediate signal to incoming bees.

 

In order for this process to work, bees must be able to sense the electrical fields of flowers. To test this ability, the researchers created a field of fake flowers that they could manipulate. Half the flowers were positively charged, and these flowers held a tiny bit of sugar solution as a reward for the bees. The remaining flowers had no charge and held a bitter quinine drink. After just 40 visits, the bees had learned that the positively charged flowers were rewarding, and they visited them more than 80 percent of the time. Once the charges were turned off, the visitation rate to the sugar-laden flowers decreased to random chance, since the bees no longer could use the electric field as a cue.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Nature inspired adaptive strategies for information sharing

Nature inspired adaptive strategies for information sharing | Social Foraging | Scoop.it

Social learning is an e ffective way to reduce uncertainty about the environment, helping individuals to adopt adaptive behaviour cheaply. Although this is evident for learning about temporally stable targets, such as acquisition of an avoidance of toxic foods, the utility of social learning in a temporally unstable environment is less clear, since knowledge acquired by social learning may be outdated. An individual can either depend entirely on its own foraging information (individual forager) or that provided by the environment or shared by other agents. We are interested in scenarios where individual foraging might be a useful and effective strategy and how the topology and distribution of resources in the network/environment might a ffect this.

more...
No comment yet.
Scooped by Ashish Umre
Scoop.it!

Brain mapping reveals neurological basis of decision-making in rats

Brain mapping reveals neurological basis of decision-making in rats | Social Foraging | Scoop.it
Scientists at UC San Francisco have discovered how memory recall is linked to decision-making in rats, showing that measurable activity in one part of the brain occurs when rats in a maze are playing out memories that help them decide which way to turn. The more they play out these memories, the more likely they are to find their way correctly to the end of the maze.
more...
No comment yet.