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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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Reasons for Using Social Networks Professionally - The Influence of User Diversity on Usage Motivation

Reasons for Using Social Networks Professionally - The Influence of User Diversity on Usage Motivation | Social Foraging | Scoop.it

Since the success of social media in private usage settings, social media applications spread rapidly in the working context. In business internal contexts these applications seem useful as a measure for strategic knowledge management. Social media in this context promises to offer adequate facilities to support a systematic storage of knowledge as well as a support of knowledge exchange and communication in enterprises. But since social media is only successful when used, the usage motivation of employees is one central key for their success. Therefore this paper focusses on the motivation to use social media professionally. To achieve this we are investigating the influence of user diversity factors such as age, gender, and social media expertise on aspects of usage motivation. In a study with N=84 the employees of an enterprise were asked which reasons for using social media are relevant to them. Findings show that both factors age and gender reveal a relatively low influence on the factors evaluation of usage motives, tools (as a measure for motivation), and incentives/reinforcements for social network usage. In contrast both expertise with social media and achievement motivation revealed many correlations with both usage motives and tools as well as incentives and reinforcements.

 
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Practical Eye Tracking of the Ecommerce Website User Experience

Practical Eye Tracking of the Ecommerce Website User Experience | Social Foraging | Scoop.it

Eye tracking is a productive tool in researching the user experience of ecommerce websites. Because information throughout the online path to purchase is communicated visually, gaze behavior is among the most effective and informative means of testing the extent to which a given ecommerce site facilitates a smooth transaction. The process of analysis typically involves examining the characteristics and patterns of visual attention during the online shopping process. Eye-tracking metrics are used in conjunction with data-based visualizations and traditional usability techniques to answer a variety of questions about the online shopping process. Principles of appropriate design, execution and analysis of an ecommerce eye-tracking study are discussed, along with relevant case examples.

 
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Sparrows and Owls: Characterisation of Expert Behaviour in StackOverflow

Sparrows and Owls: Characterisation of Expert Behaviour in StackOverflow | Social Foraging | Scoop.it

Question Answering platforms are becoming an important repository of crowd-generated knowledge. In these systems a relatively small subset of users is responsible for the majority of the contributions, and ultimately, for the success of the Q/A system itself. However, due to built-in incentivization mechanisms, standard expert identification methods often misclassify very active users for knowledgable ones, and misjudge activeness for expertise. This paper contributes a novel metric for expert identification, which provides a better characterisation of users’ expertise by focusing on the quality of their contributions. We identify two classes of relevant users, namelysparrows and owls, and we describe several behavioural properties in the context of theStackOverflow Q/A system. Our results contribute new insights to the study of expert behaviour in Q/A platforms, that are relevant to a variety of contexts and applications.

 
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The Magic Barrier of Recommender Systems – No Magic, Just Ratings

The Magic Barrier of Recommender Systems – No Magic, Just Ratings | Social Foraging | Scoop.it

Recommender Systems need to deal with different types of users who represent their preferences in various ways. This difference in user behaviour has a deep impact on the final performance of the recommender system, where some users may receive either better or worse recommendations depending, mostly, on the quantity and the quality of the information the system knows about the user. Specifically, the inconsistencies of the user impose a lower bound on the error the system may achieve when predicting ratings for that particular user.

 

In this work, we analyse how the consistency of user ratings (coherence) may predict the performance of recommendation methods. More specifically, our results show that our definition of coherence is correlated with the so-called magic barrier of recommender systems, and thus, it could be used to discriminate between easy users (those with a low magic barrier) and difficult ones (those with a high magic barrier). We report experiments where the rating prediction error for the more coherent users is lower than that of the less coherent ones. We further validate these results by using a public dataset, where the magic barrier is not available, in which we obtain similar performance improvements.

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Data Design for Personalization: Current Challenges and Emerging Opportunities | eBay Research Labs

Data Design for Personalization: Current Challenges and Emerging Opportunities | eBay Research Labs | Social Foraging | Scoop.it

Personalization is central to most Internet experiences. Personalization is a data-driven process, whether the data are explicitly gathered (e.g., by asking people to fill out forms) or implicitly (e.g. through analysis of behavioral data). It is clear that designing for effective personalization poses interesting engineering and computer science challenges. However, personalization is also a user experience issue. We believe that encouraging dialogue and collaboration between data mining experts, content providers, and user-focused researchers will offer gains in the area of personalization for search and for other domains. This workshop is part of a larger effort we are developing: D2D: Data to Design - Design to Data. Our vision is to provide a forum for researchers and practitioners in computer and systems sciences, data sciences, machine learning, information retrieval, interaction and interface design, and human computer interaction to interact. Our goal is to explore issues surrounding content and presentation personalization across different devices, and to set an agenda for cross-discipline, collaborative engagement.

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On Welsh Corgis, Computer Vision, and the Power of Deep Learning - Microsoft's Project Adam

On Welsh Corgis, Computer Vision, and the Power of Deep Learning - Microsoft's Project Adam | Social Foraging | Scoop.it

Can you tell the difference between the two breeds of corgis? If you’re like many, you probably are barely even aware that such dogs exist, let alone the fact that there are two—and only two—kinds of corgis. Add the detail that those two breeds are both named after Welsh counties—the Pembroke Welsh corgi and the Cardigan Welsh corgi—and it’s safe to say that the people who could correctly identify one from the other are few and far between..

 

But Project Adam can.

 

Project Adam, an initiative by Microsoft researchers and engineers, aims to demonstrate that large-scale, commodity distributed systems can train huge deep neural networks effectively. For proof, the researchers created the world’s best photograph classifier, using 14 million images from ImageNet, an image database divided into 22,000 categories.

 

Included in the vast array of categories are some that pertain to dogs. Project Adam knows dogs. It can identify dogs in images. It can identify kinds of dogs. It can even identify particular breeds, such as whether a corgi is a Pembroke or a Cardigan.

Now, if this all sounds vaguely familiar, that’s because it is—vaguely. A couple of years ago, The New York Times wrote a story about Google using a network of 16,000 computers to teach itself to identify images of cats. That is a difficult task for computers, and it was an impressive achievement.

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Friendship and natural selection

Friendship and natural selection | Social Foraging | Scoop.it

More than any other species, humans form social ties to individuals who are neither kin nor mates, and these ties tend to be with similar people. Here, we show that this similarity extends to genotypes. Across the whole genome, friends’ genotypes at the single nucleotide polymorphism level tend to be positively correlated (homophilic). In fact, the increase in similarity relative to strangers is at the level of fourth cousins. However, certain genotypes are also negatively correlated (heterophilic) in friends. And the degree of correlation in genotypes can be used to create a “friendship score” that predicts the existence of friendship ties in a hold-out sample. A focused gene-set analysis indicates that some of the overall correlation in genotypes can be explained by specific systems; for example, an olfactory gene set is homophilic and an immune system gene set is heterophilic, suggesting that these systems may play a role in the formation or maintenance of friendship ties. Friends may be a kind of “functional kin.” Finally, homophilic genotypes exhibit significantly higher measures of positive selection, suggesting that, on average, they may yield a synergistic fitness advantage that has been helping to drive recent human evolution.

 
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Generalize or Personalize - Do Dogs Transfer an Acquired Rule to Novel Situations and Persons?

Generalize or Personalize - Do Dogs Transfer an Acquired Rule to Novel Situations and Persons? | Social Foraging | Scoop.it

Recent studies have raised the question of whether dogs, like human infants, comprehend an established rule as generalizable, normative knowledge or rather as episodic information, existing only in the immediate situation. In the current study we tested whether dogs disobeyed a prohibition to take a treat (i) in the presence of the communicator of the ban, (ii) after a temporary absence of the communicator, and (iii) in the presence of a novel person. Dogs disobeyed the rule significantly more often when the communicator left the room for a moment or when they were faced with a new person, than when she stayed present in the room. These results indicate that dogs “forget” a rule as soon as the immediate human context becomes disrupted.

 
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Seventh International Workshop on Guided Self-Organization

The workshop will bring together researchers from a richly diverse background who share interest in understanding and designing self-organising systems. Of particular interest are well-founded, but general methods for characterizing such systems in a principled way with the view of ultimately allowing them to be guided toward prespecified goals. Information theory, nonlinear dynamics and graph theory are core to many of these methods, and quantifying complexity and its sources is a common theme.

This year, the workshop is organised in collaboration with the BrainLinks-BrainTools cluster of excellence at University of Freiburg ( https://www.brainlinks-braintools.uni-freiburg.de/ ), and one focus theme will be guided self-organisation in neural systems.

 

Seventh International Workshop on Guided Self-Organisation (GSO-2014) to be held from December 16-18, 2014 in Freiburg, Germany.

http://ml.informatik.uni-freiburg.de/events/gso14/index


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KPMG and Imperial College London form £20 million partnership to transform UK into global leader in big data analytics

KPMG and Imperial College London today announce the launch of a major new partnership to create the ‘KPMG Centre for Advanced Business Analytics’. KPMG will invest over £20m, with the aim of putting the UK at the forefront of data science. 

The project will focus on five key areas - analysis of business capital, growth opportunities, people, operations and resilience.  Each area has been selected to help UK businesses gain a competitive edge by launching products and services ahead of international competitors.  The new KPMG Centre will also develop innovative approaches, analytical methods and tools for using big data, giving UK businesses the opportunity to solve complex issues, such as enabling banks to predict fraud or helping retailers better understand consumer behaviour. 

The eight year project will see a joint team working together, with the ambition of completing 15-20 projects per year.

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Inside the Artificial Brain That’s Remaking the Google Empire

Inside the Artificial Brain That’s Remaking the Google Empire | Social Foraging | Scoop.it

It was one of the most tedious jobs on the internet. A team of Googlers would spend day after day staring at computer screens, scrutinizing tiny snippets of street photographs, asking themselves the same question over and over again: “Am I looking at an address or not?’ Click. Yes. Click. Yes. Click. No.

 

This was a critical part of building the company’s Google Maps service. Knowing the precise address of a building is really helpful information for mapmakers. But that didn’t make life any easier for those poor Googlers who had to figure out whether a string of numbers captured by Google’s roving Street View cars was a phone number, a graffiti tag, or a legitimate address.

 

Then, a few months ago, they were relieved of their agony, after some Google engineers trained the company’s machines to handle this thankless task. Traditionally, computers have muffed this advanced kind of image recognition, and Google finally cracked the problem with its new artificial intelligence system, known as Google Brain. With Brain, Google can now transcribe all of the addresses that Street View has captured in France in less than an hour.

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Three-dimensionally printed biological machines powered by skeletal muscle

Three-dimensionally printed biological machines powered by skeletal muscle | Social Foraging | Scoop.it

Combining biological components, such as cells and tissues, with soft robotics can enable the fabrication of biological machines with the ability to sense, process signals, and produce force. An intuitive demonstration of a biological machine is one that can produce motion in response to controllable external signaling. Whereas cardiac cell-driven biological actuators have been demonstrated, the requirements of these machines to respond to stimuli and exhibit controlled movement merit the use of skeletal muscle, the primary generator of actuation in animals, as a contractile power source. Here, we report the development of 3D printed hydrogel “bio-bots” with an asymmetric physical design and powered by the actuation of an engineered mammalian skeletal muscle strip to result in net locomotion of the bio-bot. Geometric design and material properties of the hydrogel bio-bots were optimized using stereolithographic 3D printing, and the effect of collagen I and fibrin extracellular matrix proteins and insulin-like growth factor 1 on the force production of engineered skeletal muscle was characterized. Electrical stimulation triggered contraction of cells in the muscle strip and net locomotion of the bio-bot with a maximum velocity of ∼156 μm s−1, which is over 1.5 body lengths per min. Modeling and simulation were used to understand both the effect of different design parameters on the bio-bot and the mechanism of motion. This demonstration advances the goal of realizing forward-engineered integrated cellular machines and systems, which can have a myriad array of applications in drug screening, programmable tissue engineering, drug delivery, and biomimetic machine design.

 
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Miro Svetlik's curator insight, July 16, 2014 6:47 AM

Biological robots might even surpass their mechanical counterparts mainly due to replicating abilities and principles taken from the nature. In any case it opens a huge new possibilities to augment and support human body.

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Realized niche shift during a global biological invasion

Realized niche shift during a global biological invasion | Social Foraging | Scoop.it

Accurate forecasts of biological invasions are crucial for managing invasion risk but are hampered by niche shifts resulting from evolved environmental tolerances (fundamental niche shifts) or the presence of novel biotic and abiotic conditions in the invaded range (realized niche shifts). Distinguishing between these kinds of niche shifts is impossible with traditional, correlative approaches to invasion forecasts, which exclusively consider the realized niche. Here we overcome this challenge by combining a physiologically mechanistic model of the fundamental niche with correlative models based on the realized niche to study the global invasion of the cane toad Rhinella marina. We find strong evidence that the success of R. marina in Australia reflects a shift in the species’ realized niche, as opposed to evolutionary shifts in range-limiting traits. Our results demonstrate that R. marina does not fill its fundamental niche in its native South American range and that areas of niche unfilling coincide with the presence of a closely related species with which R. marina hybridizes. Conversely, in Australia, where coevolved taxa are absent, R. marina largely fills its fundamental niche in areas behind the invasion front. The general approach taken here of contrasting fundamental and realized niche models provides key insights into the role of biotic interactions in shaping range limits and can inform effective management strategies not only for invasive species but also for assisted colonization under climate change.

 
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Cultural Divergence in Website Interaction Spanish vs. English

Cultural Divergence in Website Interaction Spanish vs. English | Social Foraging | Scoop.it

Our perception of the world around us is based on our knowledge and experiences. Web design has used this concept to improve websites by matching expectations derived from the knowledge and experience to design concepts. Understanding the role culture plays in perception of websites needs to be better understood. This paper uses eye-tracking gaze patterns (ETMAP) in conjunction with a cultural identification survey (ARSMA-II) to explore divergences between American and Latino-Americans. Our results suggest a relationship between sequential reading and scanning behaviors with acculturation scores. While these results demonstrate that the methodology has potential, the findings need to be confirmed in future studies.

 
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Towards Personalized Multilingual Information Access - Exploring the Browsing and Search Behavior of Multilingual Users

Towards Personalized Multilingual Information Access - Exploring the Browsing and Search Behavior of Multilingual Users | Social Foraging | Scoop.it

The shift from the originally English-language-dominated web towards a truly global world wide web has generated a pressing need to develop novel solutions that address multilingual user diversity. In particular, many web users today are polyglots, i.e. they are proficient in more than one language. However, little is known about the browsing and search habits of such users, and even less about how to best assist their multilingual behaviors through appropriate systems and tools. In order to gain a better understanding, this paper presents a survey of 385 polyglot web users, focusing specifically on the relationship between multiple language proficiency and browsing/search language choice. Results from the survey indicate that polyglot users make significant use of multiple languages during their daily browsing and searching, and that contextual factors such as language proficiency, usage purpose, and topic domain have a significant influence on their language choice and frequency. The paper provides a detailed analysis regarding each of these factors, and offers insights about how to support multilingual users through novelPersonalized Multilingual Information Access systems.

 
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Time-Sensitive User Profile for Optimizing Search Personlization

Time-Sensitive User Profile for Optimizing Search Personlization | Social Foraging | Scoop.it

Thanks to social Web services, Web search engines have the opportunity to afford personalized search results that better fit the user’s information needs and interests. To achieve this goal, many personalized search approaches explore user’s social Web interactions to extract his preferences and interests, and use them to model his profile. In our approach, the user profile is implicitly represented as a vector of weighted terms which correspond to the user’s interests extracted from his online social activities. As the user interests may change over time, we propose to weight profiles terms not only according to the content of these activities but also by considering the freshness. More precisely, the weights are adjusted with a temporal feature. In order to evaluate our approach, we model the user profile according to data collected from Twitter. Then, we rerank initial search results accurately to the user profile. Moreover, we proved the significance of adding a temporal feature by comparing our method with baselines models that does not consider the user profile dynamics.

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A computational model for mood recognition

In an ambience designed to adapt to the user’s affective state, per-vasive technology should be able to decipher unobtrusively his underlying mood. Great effort has been devoted to automatic punctual emotion recognition from visual input. Conversely, little has been done to recognize longer-lasting affective states, such as mood. Taking for granted the effectiveness of emotion recognition algorithms, we go one step further and propose a model for estimating the mood of an affective episode from a known sequence of punctual emotions. To validate our model experimentally, we rely on the human annotations of the well-established HUMAINE database. Our analysis indicates that we can approximate fairly accurately the human process of summarizing the emotional content of a video in a mood estimation. A moving average function with exponential discount of the past emotions achieves mood prediction accuracy above 60%.
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▶ Global Brain: Web as Self-organizing Distributed Intelligence - Francis Heylighen

Distributed intelligence is an ability to solve problems and process information that is not localized inside a single person or computer, but that emerges from the coordinated interactions between a large number of people and their technological extensions. The Internet and in particular the World-Wide Web form a nearly ideal substrate for the emergence of a distributed intelligence that spans the planet, integrating the knowledge, skills and intuitions of billions of people supported by billions of information-processing devices. This intelligence becomes increasingly powerful through a process of self-organization in which people and devices selectively reinforce useful links, while rejecting useless ones. This process can be modeled mathematically and computationally by representing individuals and devices as agents, connected by a weighted directed network along which "challenges" propagate. Challenges represent problems, opportunities or questions that must be processed by the agents to extract benefits and avoid penalties. Link weights are increased whenever agents extract benefit from the challenges propagated along it. My research group is developing such a large-scale simulation environment in order to better understand how the web may boost our collective intelligence. The anticipated outcome of that process is a "global brain", i.e. a nervous system for the planet that would be able to tackle both global and personal problems.

 

Summer School in cognitive Science: Web Science and the Mind Institut des sciences cognitives, UQAM, Montréal, Canada http://www.summer14.isc.uqam.ca/

http://www.isc.uqam.ca/ ;

FRANCIS HEYLIGHEN, Vrije Universiteit Brussel, ECCO - Evolution, Complexity and Cognition research group

Towards a Global Brain: the Web as a Self-organizing, Distributed Intelligence

http://youtu.be/w2sznrVtiLg


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Tom Cockburn's curator insight, July 17, 2014 4:06 AM

Apart from outraging some religious groups and upsetting some neo- luddites,this sounds interesting,provided we have some checks and balances/ failsafe options too

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Multilayer networks

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such ‘multilayer’ features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize ‘traditional’ network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other and provide a thorough discussion that compares, contrasts and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks and many others. We also survey and discuss existing data sets that can be represented as multilayer networks. We review attempts to generalize single-layer-network diagnostics to multilayer networks. We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions and various types of dynamical processes on multilayer networks. We conclude with a summary and an outlook.

 
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Crowdsourcing for Cognitive Science – The Utility of Smartphones

Crowdsourcing for Cognitive Science – The Utility of Smartphones | Social Foraging | Scoop.it

By 2015, there will be an estimated two billion smartphone users worldwide. This technology presents exciting opportunities for cognitive science as a medium for rapid, large-scale experimentation and data collection. At present, cost and logistics limit most study populations to small samples, restricting the experimental questions that can be addressed. In this study we investigated whether the mass collection of experimental data using smartphone technology is valid, given the variability of data collection outside of a laboratory setting. We presented four classic experimental paradigms as short games, available as a free app and over the first month 20,800 users submitted data. We found that the large sample size vastly outweighed the noise inherent in collecting data outside a controlled laboratory setting, and show that for all four games canonical results were reproduced. For the first time, we provide experimental validation for the use of smartphones for data collection in cognitive science, which can lead to the collection of richer data sets and a significant cost reduction as well as provide an opportunity for efficient phenotypic screening of large populations.

 
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NetSci-X 2015: International School and Conference on Network Science, Rio de Janeiro

The NetSci-X is the first Network Science Conference outside the USA-Europe axis. It will bring together leading researchers and practitioners working in the emerging area of network science.
The conference fosters interdisciplinary communication and collaboration, with focus on novel directions in network research within the biological and environmental sciences, computer and information sciences, social sciences, finance and business, among others.
The NetSci-X Conference will be held in January 2015 in Rio de Janeiro, Brazil, at the Getulio Vargas Foundation—one of the main Think Tanks in the world and leading educational and research institution in Brazil.

 

http://www.netsci-x2015.net


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Glass Brain: Virtual Reality Meets Neuroscience

Glass Brain: Virtual Reality Meets Neuroscience | Social Foraging | Scoop.it
Bridging the worlds of neuroscience and high-tech virtual realty, the Glass Brain, a project of the new Neuroscape Lab at the University of California San Francisco may open up new insights into the complicated mechanisms of the brain.

 

Researchers have developed a new way to explore the human brain through virtual reality. The system, called Glass Brain, initiated by Philip Rosedale, creator of the famous game Second Life, and Adam Gazzaley, a neuroscientist at the University of California San Francisco, combines brain scanning, brain recording and virtual reality to allow a user to journey through a person’s brain in real-time.

 For a recent demonstration at the South by Southwest (SXSW) Interactive festival in Austin, Texas, Rosedale made his wife a cap studded with electroencephalogram (EEG) electrodes that measure differences in electric potential in order to record brain activity, while he wore a virtual reality headset to explore her brain in 3D, as flashes of light displayed her brain activity from the EEG.

The Glass Brain didn’t actually show what Rosedale’s wife was thinking, but Gazzaley’s team ultimately hopes to get closer to decoding brain signals and displaying them using the virtual reality system.


This is an anatomically-realistic 3D brain visualization depicting real-time source-localized activity (power and "effective" connectivity) from EEG (electroencephalographic) signals. Each color represents source power and connectivity in a different frequency band (theta, alpha, beta, gamma) and the golden lines are white matter anatomical fiber tracts. Estimated information transfer between brain regions is visualized as pulses of light flowing along the fiber tracts connecting the regions.


The modeling pipeline includes MRI (Magnetic Resonance Imaging) brain scanning to generate a high-resolution 3D model of an individual's brain, skull, and scalp tissue, DTI (Diffusion Tensor Imaging) for reconstructing white matter tracts, and BCILAB (http://sccn.ucsd.edu/wiki/BCILAB) / SIFT (http://sccn.ucsd.edu/wiki/SIFT) to remove artifacts and statistically reconstruct the locations and dynamics (amplitude and multivariate Granger-causal (http://www.scholarpedia.org/article/G...) interactions) of multiple sources of activity inside the brain from signals measured at electrodes on the scalp (in this demo, a 64-channel "wet" mobile system by Cognionics/BrainVision (http://www.cognionics.com)).

The final visualization is done in Unity and allows the user to fly around and through the brain with a gamepad while seeing real-time live brain activity from someone wearing an EEG cap.


Via Dr. Stefan Gruenwald
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Culture influences strategy in online coordination game

Culture influences strategy in online coordination game | Social Foraging | Scoop.it

We examine different populations’ play in coordination games in online experiments with over 1,000 study participants. Study participants played a two-player coordination game that had multiple equilibria: two equilibria with highly asymmetric payoffs and another equilibrium with symmetric payoffs but a slightly lower total payoff. Study participants were predominantly from India and the United States. Study participants residing in India played the strategies leading to asymmetric payoffs significantly more frequently than study participants residing in the United States who showed a greater play of the strategy leading to the symmetric payoffs. In addition, when prompted to play asymmetrically, the population from India responded even more significantly than those from the United States. Overall, study participants’ predictions of how others would play were more accurate when the other player was from their own populations, and they coordinated significantly more frequently and earned significantly higher payoffs when matched with other study participants from their own population than when matched across populations.

 
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Early Warning Signs in Social-Ecological Networks

Early Warning Signs in Social-Ecological Networks | Social Foraging | Scoop.it

A number of social-ecological systems exhibit complex behaviour associated with nonlinearities, bifurcations, and interaction with stochastic drivers. These systems are often prone to abrupt and unexpected instabilities and state shifts that emerge as a discontinuous response to gradual changes in environmental drivers. Predicting such behaviours is crucial to the prevention of or preparation for unwanted regime shifts. Recent research in ecology has investigated early warning signs that anticipate the divergence of univariate ecosystem dynamics from a stable attractor. To date, leading indicators of instability in systems with multiple interacting components have remained poorly investigated. This is a major limitation in the understanding of the dynamics of complex social-ecological networks. Here, we develop a theoretical framework to demonstrate that rising variance—measured, for example, by the maximum element of the covariance matrix of the network—is an effective leading indicator of network instability. We show that its reliability and robustness depend more on the sign of the interactions within the network than the network structure or noise intensity. Mutualistic, scale free and small world networks are less stable than their antagonistic or random counterparts but their instability is more reliably predicted by this leading indicator. These results provide new advances in multidimensional early warning analysis and offer a framework to evaluate the resilience of social-ecological networks.

 
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Information-based fitness and the emergence of criticality in living systems

Information-based fitness and the emergence of criticality in living systems | Social Foraging | Scoop.it

Empirical evidence suggesting that living systems might operate in the vicinity of critical points, at the borderline between order and disorder, has proliferated in recent years, with examples ranging from spontaneous brain activity to flock dynamics. However, a well-founded theory for understanding how and why interacting living systems could dynamically tune themselves to be poised in the vicinity of a critical point is lacking. Here we use tools from statistical mechanics and information theory to show that complex adaptive or evolutionary systems can be much more efficient in coping with diverse heterogeneous environmental conditions when operating at criticality. Analytical as well as computational evolutionary and adaptive models vividly illustrate that a community of such systems dynamically self-tunes close to a critical state as the complexity of the environment increases while they remain noncritical for simple and predictable environments. A more robust convergence to criticality emerges in coevolutionary and coadaptive setups in which individuals aim to represent other agents in the community with fidelity, thereby creating a collective critical ensemble and providing the best possible tradeoff between accuracy and flexibility. Our approach provides a parsimonious and general mechanism for the emergence of critical-like behavior in living systems needing to cope with complex environments or trying to efficiently coordinate themselves as an ensemble.

 
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