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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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Strategy Diversity Stabilizes Mutualism through Investment Cycles, Phase Polymorphism, and Spatial Bubbles

Strategy Diversity Stabilizes Mutualism through Investment Cycles, Phase Polymorphism, and Spatial Bubbles | Social Foraging | Scoop.it

There is continuing interest in understanding factors that facilitate the evolution and stability of cooperation within and between species. Such interactions will often involve plasticity in investment behavior, in response to the interacting partner's investments. Our aim here is to investigate the evolution and stability of reciprocal investment behavior in interspecific interactions, a key phenomenon strongly supported by experimental observations. In particular, we present a comprehensive analysis of a continuous reciprocal investment game between mutualists, both in well-mixed and spatially structured populations, and we demonstrate a series of novel mechanisms for maintaining interspecific mutualism. We demonstrate that mutualistic partners invariably follow investment cycles, during which mutualism first increases, before both partners eventually reduce their investments to zero, so that these cycles always conclude with full defection. We show that the key mechanism for stabilizing mutualism is phase polymorphism along the investment cycle.

 

Although mutualistic partners perpetually change their strategies, the community-level distribution of investment levels becomes stationary. In spatially structured populations, the maintenance of polymorphism is further facilitated by dynamic mosaic structures, in which mutualistic partners form expanding and collapsing spatial bubbles or clusters. Additionally, we reveal strategy-diversity thresholds, both for well-mixed and spatially structured mutualistic communities, and discuss factors for meeting these thresholds, and thus maintaining mutualism. Our results demonstrate that interspecific mutualism, when considered as plastic investment behavior, can be unstable, and, in agreement with empirical observations, may involve a polymorphism of investment levels, varying both in space and in time. Identifying the mechanisms maintaining such polymorphism, and hence mutualism in natural communities, provides a significant step towards understanding the coevolution and population dynamics of mutualistic interactions.

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Natural Selection, Not Mutation: Recombination in Drosophila Increases Diversity

Natural Selection, Not Mutation: Recombination in Drosophila Increases Diversity | Social Foraging | Scoop.it

Plants do it. Animals do it. People do it, too. During meiosis—the cell division that creates eggs and sperm—all these organisms mix the genetic material inherited from their mother and father. This mixing is called recombination, and it results from crossover events, where pairs of chromosomes swap genetic material. Evolutionary biologists have long known that recombination seems to increase genetic diversity. That is, high rates of recombination in a species are correlated with high rates of genetic diversity between individuals in that species.

 

What has been less clear is how recombination leads to increased diversity. Do crossover events predominantly cause mutations, or is their primary effect to break up linkage between genes? Genes that are linked—near each other on the same chromosome—are more likely to be inherited together. By breaking up linkage, recombination makes it easier for natural selection to target individual genes while avoiding the potentially disadvantageous effect of simultaneously reducing diversity at neighboring genes (a phenomenon known as “Hill-Robertson interference”).

 

To assess whether recombination causes mutations, researchers have previously looked at recombination rates at certain points on the same chromosome of closely related species and assessed whether there was increased genetic divergence—genetic variation between species—at those points. They found no increase in divergence, leading to the conclusion that the association between diversity and recombination was not predominantly caused by mutations. However, these analyses suffered from the implicit assumption that recombination rates were the same in related species. Recently, a number of studies have found that this is not always the case; even in closely related species, local recombination rates can vary greatly, raising questions about work that has not taken this variability into account and leaving room for the mutation hypothesis to resurface.

 

In this issue of PLOS Biology, Suzanne McGaugh, Mohamed Noor, and colleagues at Duke University and the University of Wisconsin-Madison settle the question, at least for fruit flies. Using relatives of the well-known Drosophila melanogaster, the researchers compared the local genetic variation within and between species (i.e., diversity and divergence, respectively) at regions of the flies' chromosomes that they knew to have similar recombination rates.

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When Is My Tweet's Prime of Life? (A brief statistical interlude.)

When Is My Tweet's Prime of Life? (A brief statistical interlude.) | Social Foraging | Scoop.it

We use many tools to tailor our Twitter use, but how can we accurately measure the lifespan of a tweet? Peter Bray digs into the data and uses retweets (i.e. the currency of Twitter) to predict just how long your tweet's prime of life will be.

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Location based Social Network Users Through a Lense: Examining Temporal User Patterns

There has been a rapid proliferation of location-based social networks (LBSNs) during the last years. The spatial component of these systems provides a rich source of information that can be exploited by a number of novel services. However, to better design such services, it is important to understand the way people make use of these platforms and how this usage changes over time. While there exist studies that examine the motivations of people for adopting the usage of LBSNs and the temporal dynamics of these motivations, they are based on interviews and are mostly qualitative. Motivations can further only indirectly reveal or help us infer user behavior. In this paper, we analyze data from two commercial LBSNs to examine the temporal evolution of usage patterns to see what the data on their own reveal. We find that users of two social networks that we examined increase their level of activity as they use the system. However, depending on the main purpose of the underlying LBSN, users may exhibit different behaviors over time. We believe that our findings can open new directions and stimulate further research on areas such as location prediction and its applications (e.g., urban and transportation planning and location-based advertisment).

 

PDF Copy: http://www.aaai.org/ocs/index.php/FSS/FSS12/paper/viewFile/5555/5898

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Will Diet Pepper, Pepsi, and Big Data Determine the Outcome of Tomorrow's Election?

Will Diet Pepper, Pepsi, and Big Data Determine the Outcome of Tomorrow's Election? | Social Foraging | Scoop.it

If your favorite soda is Diet Dr. Pepper, the chances are that you’ll be supporting Mitt Romney tomorrow. Pepsi drinker? You’re most likely voting for Barack Obama. If you drink Mountain Dew, you probably don’t care either way.

 

These types of conclusions may seem simplistic and superficial, but both campaigns are betting that they will be the key to deciding who the next President of the United States is.

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The Visualizing Global Marathon 2012 - Nov 9th-11th

The Visualizing Global Marathon 2012 - Nov 9th-11th | Social Foraging | Scoop.it

The Visualizing Marathon is the world's largest student data visualization competition. This year, we're bringing the global student design community together for one weekend to tackle real world issues with data and design.

 

Dive into data visualization alongside students from around the world. At the start of the marathon we'll unveil the data set and challenge you to design and build a project that creatively visualizes the data. You can work individually or in teams, participating online or at one of our in-person meetups. We'll be broadcasting workshops by data viz rockstars throughout the weekend. There will also be games, mini-challenges and more ways to connect with other students. Upload your finished project by the deadline, and then get to see what everyone else has been working on!

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Predicting Hurricane Sandy

Predicting Hurricane Sandy | Social Foraging | Scoop.it

In 2009, the U.S. National Weather Service set ambitious goals—to improve the accuracy of forecasts of hurricane tracks and intensity by 20 percent by 2014 and by 50 percent by 2019. Last year for the first time, in modeling Hurricane Irene, the National Weather Service was able to incorporate data from flying planes through the storm directly into the simulations of the storm’s progress. Adding that detailed data from inside the storm, and other advances, meant that the 48-hour forecast of Hurricane Irenewas just as accurate as a 24-hour forecast had been a decade earlier.And the advance forecast of Hurricane Sandy, now heading for the east coast of the United States, should be even more accurate, thanks to a couple of advances in modeling that earlier this year moved from the research laboratories into operational use as part of the U.S. Global Forecast System (GFS). (Other countries run their own models; for example, Europe has a model called the ECMWF Model and the United Kingdom has UKMET Office Model.)

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A defeasible reasoning model of inductive concept learning from examples and communication

This paper introduces a logical model of inductive generalization, and specifically of the machine learning task of inductive concept learning (ICL). We argue that some inductive processes, like ICL, can be seen as a form of defeasible reasoning. We define a consequence relation characterizing which hypotheses can be induced from given sets of examples, and study its properties, showing they correspond to a rather well-behaved non-monotonic logic. We will also show that with the addition of a preference relation on inductive theories we can characterize the inductive bias of ICL algorithms. The second part of the paper shows how this logical characterization of inductive generalization can be integrated with another form of non-monotonic reasoning (argumentation), to define a model of multiagent ICL. This integration allows two or more agents to learn, in a consistent way, both from induction and from arguments used in the communication between them. We show that the inductive theories achieved by multiagent induction plus argumentation are sound, i.e. they are precisely the same as the inductive theories built by a single agent with all data.

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BabelNet: A very large multilingual semantic network

BabelNet: A very large multilingual semantic network | Social Foraging | Scoop.it

BabelNet, a very large multilingual semantic networkwith millions of concepts obtained from:

 

1. an integration of WordNet and Wikipedia based on an automatic mapping algorithm

 

2. translations of the concepts (i.e. English Wikipedia pages and WordNet synsets) based on Wikipedia cross-language links and the output of a machine translation system

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Algorithmic Typography, Crafted Entirely With Computer Code

Algorithmic Typography, Crafted Entirely With Computer Code | Social Foraging | Scoop.it

Even the most serious typographers realize their work is in some ways a means to an end: While individual letters may be beautiful, they exist ultimately to form words. Yeohyun Ahn is a designer who has a different fate in mind for typography. She uses computer code compiled in the visual programming language Processing to algorithmically craft letters as individual pieces of software. The collection of 10 typefaces is called TYPE+CODE II, and it reimagines letters as complex, visually varied creations that, while not quite sentient or interactive, don’t utilize any of the traditional tools in a typical typographer’s arsenal.

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Slime mold uses an externalized spatial “memory” to navigate in complex environments

Spatial memory enhances an organism’s navigational ability. Memory typically resides within the brain, but what if an organism has no brain? We show that the brainless slime mold Physarum polycephalum constructs a form of spatial memory by avoiding areas it has previously explored. This mechanism allows the slime mold to solve the U-shaped trap problem—a classic test of autonomous navigational ability commonly used in robotics—requiring the slime mold to reach a chemoattractive goal behind a U-shaped barrier. Drawn into the trap, the organism must rely on other methods than gradient-following to escape and reach the goal. Our data show that spatial memory enhances the organism’s ability to navigate in complex environments. We provide a unique demonstration of a spatial memory system in a nonneuronal organism, supporting the theory that an externalized spatial memory may be the functional precursor to the internal memory of higher organisms.

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Precisely targeted electrical brain stimulation alters perception of faces, study finds

Precisely targeted electrical brain stimulation alters perception of faces, study finds | Social Foraging | Scoop.it

In a painless clinical procedure performed on a patient with electrodes temporarily implanted in his brain, Stanford University doctors pinpointed two nerve clusters that are critical for face perception. The findings could have practical value in treating people with prosopagnosia -- the inability to distinguish one face from another -- as well in gaining an understanding of why some of us are so much better than others at recognizing and remembering faces.

 

In a study published Oct. 24 in the Journal of Neuroscience, the scientists showed that mild electrical stimulation of two nerve clusters spaced a half-inch apart in a brain structure called the fusiform gyrus caused the subject's perception of faces to instantly become distorted while leaving his perception of other body parts and inanimate objects unchanged.

 

The surprised reaction of the subject, Ron Blackwell of Santa Clara, Calif., is captured in a video made during the procedure. "You just turned into somebody else. Your face metamorphosed," he tells the researcher in the video.

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Algorithmic Architecture

This short film is intended to encourage a creative audience to seek out Kevin Slavin’s talk Those Algorithms Which Govern Our Lives. It employs an effect which takes place in Google Earth when its 3D street photography and 2D satellite imagery don’t register correctly. This glitch is applied as a metaphor for the way that our 21st century supercities are physically changing to suit the needs of computer algorithms rather than human employees.

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Social Networks And Group Formation: Theoretical Concepts to Leverage

Humans suffer from information overload; there’s much more information on any given subject than a person is able to access. As a result, people are forced to depend upon each other for knowledge. Know-who information rather than know-what, know-how or know-why information has become most crucial. It involves knowing who has the needed information and being able to reach that person (Johnson et al. 2000).

 

In this context, understanding the formation, evolution and utilization of online social networks becomes important. A social network is “a set of people (or organizations or other social entities) connected by a set of social relationships, such as friendship, co-working or information exchange.” (Garton et al., 1997) While the Internet contributes to the information overload, it also provides useful tools to effectively manage one’s social networks and through them gain access to the right pieces of information.

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New technology can improve public WiFi connections by 700 per cent

New technology can improve public WiFi connections by 700 per cent | Social Foraging | Scoop.it

Could this spell the end for frustratingly slow internet connections in coffee shops, libraries and airports? Scientists have developed a new system which can improve WiFi connections by 700 per cent.

 

The new software can be added to existing network setups, the researchers said. Existing systems work by transferring data through a single channel. But they can become clogged when too many requests are sent by users all attempting to access the WiFi network at once.

 

They can attempt to prioritise data to be sent back to users – which are needed in order to display services such as websites – but that, in turn, slows down new requests by other users, often meaning that pages become slow or even impossible to load.

 

But the programme developed by the researchers at North Carolina State University solves that by monitoring the amount of traffic passing through a WiFi connection and sorting and prioritising it where a backlog is detected. In doing so, the software - called WiFox – smooths the flow back and forth of traffic, speeding up the connection for more people.

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Math takes center stage as experts predict storms, elections and more

Math takes center stage as experts predict storms, elections and more | Social Foraging | Scoop.it

Forget political pundits, gut instincts, and psychics. The mightier-than-ever silicon chip seems to reveal the future.In just two weeks this fall, computer models displayed an impressive prediction prowess.

 

It started when the first computer model alerted meteorologists to the pre-Halloween disaster headed for the Northeast from a bunch of clouds in the Caribbean. Nearly a week later, that weather system became Hurricane Sandy and grew into a superstorm after taking a once-in-a-century sharp turn into New Jersey.

 

Then, statistician and blogger Nate Silver correctly forecast on his beat-up laptop how all 50 states would vote for president. He even predicted a tie in Florida and projected it eventually would tip to President Barack Obama, which is the equivalent of predicting a coin landing on its side. He did it by taking polling data, weighing it for past accuracy and running 40,000 computer simulations at a time.

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New form of brain plasticity: How social isolation disrupts myelin production

Animals that are socially isolated for prolonged periods make less myelin in the region of the brain responsible for complex emotional and cognitive behavior, researchers at the University at Buffalo and Mt. Sinai School of Medicine report in Nature Neuroscienceonline.

 

The research sheds new light on brain plasticity, the brain's ability to adapt to environmental changes. It reveals that neurons aren't the only brain structures that undergo changes in response to an individual's environment and experience, according to one of the paper's lead authors, Karen Dietz, PhD, research scientist in the Department of Pharmacology and Toxicology in the UB School of Medicine and Biomedical Sciences.

 

Dietz did the work while a postdoctoral researcher at Mt. Sinai School of Medicine; Jia Liu, PhD, a Mt. Sinai postdoctoral researcher, is the other lead author.

 

The paper notes that changes in the brain's white matter, or myelin, have been seen before in psychiatric disorders, and demyelinating disorders have also had an association with depression. Recently, myelin changes were also seen in very young animals or adolescents responding to environmental changes.

 

"This research reveals for the first time a role for myelin in adult psychiatric disorders," Dietz says. "It demonstrates that plasticity in the brain is not restricted to neurons, but actively occurs in glial cells, such as the oligodendrocytes, which produce myelin."

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Evolution of Associative Learning in Chemical Networks

Evolution of Associative Learning in Chemical Networks | Social Foraging | Scoop.it

Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ‘memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells.

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Duncan Watts: From Sociology to Social Network

Everything changed for an Ivy League professor when he reinvestigated the “six degrees of separation”...
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What Do Animals Want?

What Do Animals Want? | Social Foraging | Scoop.it

Whatever anybody says, I feel that the hard problem of consciousness is still very hard, and to try and rest your ethical case on proving something that has baffled people for years seems to me to be not good for animals. Much, much better to say let's go for something tangible, something we can measure. Are the animals healthy, do they have what they want? Then if you can show that, then that's a much, much better basis for making your decisions.

 

MARIAN STAMP DAWKINS is professor of animal behaviour at the University of Oxford, where she heads the Animal Behaviour Research Group. She is the author of Why Animals Matter.


Via Complexity Digest
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An Efficient and Versatile Approach to Trust and Reputation using Hierarchical Bayesian Modelling

In many dynamic open systems, autonomous agents must interact with one another to achieve their goals. Such agents may be self-interested and, when trusted to perform an action, may betray that trust by not performing the action as required. Due to the scale and dynamism of these systems, agents will often need to interact with other agents with which they have little or no past experience. Each agent must therefore be capable of assessing and identifying reliable interaction partners, even if it has no personal experience with them. To this end, we present HABIT, a Hierarchical And Bayesian Inferred Trust model for assessing how much an agent should trust its peers based on direct and third party information.

 

This model is robust in environments in which third party information is malicious, noisy, or otherwise inaccurate. Although existing approaches claim to achieve this, most rely on heuristics with little theoretical foundation. In contrast, HABIT is based exclusively on principled statistical techniques: it can cope with multiple discrete or continuous aspects of trustee behaviour; it does not restrict agents to using a single shared representation of behaviour; it can improve assessment by using any observed correlation between the behaviour of similar trustees or information sources; and it provides a pragmatic solution to the whitewasher problem (in which unreliable agents assume a new identity to avoid bad reputation). In this paper, we describe the theoretical aspects of HABIT, and present experimental results that demonstrate its ability to predict agent behaviour in both a simulated environment, and one based on data from a real-world webserver domain. In particular, these experiments show that HABIT can predict trustee performance based on multiple representations of behaviour, and is up to twice as accurate as BLADE, an existing state-of-the-art trust model that is both statistically principled and has been previously shown to outperform a number of other probabilistic trust models.

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Civil and Environmental Engineering: From bacteria to bridges, CEE researchers tackle natural and built environments.

Civil and Environmental Engineering: From bacteria to bridges, CEE researchers tackle natural and built environments. | Social Foraging | Scoop.it

This is a department with a very long history,” says Andrew Whittle, the head of MIT’s Department of Civil and Environmental Engineering (CEE). That history, dating back to the Institute’s founding, is reflected in the department’s designation as Course 1 (of the many courses of study available to MIT students). But CEE is also a department that has changed significantly over time, as reflected in its renaming 20 years ago, when environmental engineering was added to its name.

 

That expansion is not so unusual: Many other civil engineering departments have added an environmental component in recent years. And in a way, the addition of the environment as a specific focus in the department was not such a great change from its traditional purview, Whittle says. Water supply and sewage systems, for example, always a strong component of civil engineering, necessarily involve a close understanding of the links between large manmade structures and their ecosystems. These have “always been a big issue in the civil engineering world,” says Whittle, the Edmund K. Turner Professor of Civil and Environmental Engineering, who has been teaching at MIT for three decades.

 

But MIT’s approach to civil and environmental engineering, he says, is exceptionally well integrated between studies at the very largest and the very smallest scales: bridges and buildings at one end, and microbial ecosystems at the other. Unlike its peer departments elsewhere, Whittle says, CEE requires all its students to spend a year in an intensive course that tightly integrates the civil and environmental sides of the discipline.

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Ryan Dolack's curator insight, March 5, 2013 7:50 AM

The combination of civil engineering and other engineering fields

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Did bacteria spark evolution of multicellular life?

Did bacteria spark evolution of multicellular life? | Social Foraging | Scoop.it

A new study now suggests that bacteria may also have helped kick off one of the key events in evolution: the leap from one-celled organisms to many-celled organisms, a development that eventually led to all animals, including humans.

 

Published this month in the inaugural edition of the new online journal eLife, the study by University of California, Berkeley, and Harvard Medical School scientists involves choanoflagellates (aka "choanos"), the closest living relatives of animals. These microscopic, one-celled organisms sport a long tail or flagellum, tentacles for grabbing food and are members of the ocean's plankton community. As our closest living relative, choanos offer critical insights into the biology of their last common ancestor with animals, a unicellular or colonial organism that lived and died over 650 million years ago.

 

"Choanoflagellates evolved not long before the origin of animals and may help reveal how animals first evolved," said senior author Nicole King, UC Berkeley associate professor of molecular and cell biology.

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Probing the Neural Basis of Perceptual Phenomenology with the Touch-Induced Visual Illusion

Probing the Neural Basis of Perceptual Phenomenology with the Touch-Induced Visual Illusion | Social Foraging | Scoop.it

Using the touch-induced visual illusion we examine whether the brain regions involved in coding sensory information are dissociable from those that contain decision information. Activity in the intraparietal sulcus, as measured by functional magnetic resonance imaging, was associated with the illusion suggesting a sensory coding role whereas activity in the middle occipital gyrus differentially modulated activity according to the decisions made by subjects consistent with their reported perceptual phenomenology.

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Exercise the body to keep the brain healthy, study suggests

Exercise the body to keep the brain healthy, study suggests | Social Foraging | Scoop.it

People who exercise later in life may better protect their brain from age-related changes than those who do not, a study suggests.Researchers found that people over 70 who took regular exercise showed less brain shrinkage over a three-year period than those who did little exercise.

 

Psychologists and Neuroimaging experts, based at the University of Edinburgh, did not find there to be any benefit to brain health for older people from participation in social or mentally stimulating activities.

 

Greater brain shrinkage is linked to problems with memory and thinking and the researchers say their findings suggest that exercise is potentially one important pathway to maintaining a healthy brain both in terms of size and reducing damage.

 

The researchers also examined the brain's white matter - the wiring that transmits messages round the brain. They found that people over 70 who were more physically active had fewer 'damaged' areas - visible as abnormal areas on scanning - in the white matter than those who did little exercise.

 

Additionally, the researchers from the University of Edinburgh found that the over-70s taking regular exercise had more grey matter - the parts of the brain with nerve cell bodies.

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