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Similar neural responses predict friendship | Nature Communications

Two of the “Big Five” personality traits—extraversion11,12 and openness to experience12—appear to be more similar among friends than among individuals who are not friends with one another. However, the remaining Big Five traits do not predict friendship formation well13. Similarities in conscientiousness and neuroticism are not associated with friendship formation12, and evidence for more similar levels of trait agreeableness among friends has been found in some studies12, but not in others11.

The Network Effects Manual: 13 Different Network Effects (and counting)

The direct network effect was the first ever to be noticed, back in 1908. The Chairman of AT&T at the time, Theodore Vail, noticed how hard it was for other phone companies to compete with AT&T once they had more customers in a given locale. He pointed this out in his annual report to shareholders, writing that: “Two exchange systems in the same community, cannot be… a permanency. No one has use for two telephone connections if he can reach all with whom he desires connection through one.” Vail noticed that the value of AT&T was mostly based on their network, not their phone technology. At the time, it was a revolutionary insight. It showed that even if a new telephone was clearly superior to their old phone on a technical level, no one would want the new telephone if they couldn’t use it to call their friends and family.

Smart people have better connected brains: In intelligent persons, some brain regions interact more closely, while others de-couple themselves -- ScienceDaily

The study shows that in more intelligent persons certain brain regions are clearly more strongly involved in the exchange of information between different sub-networks of the brain in order for important information to be communicated quickly and efficiently. On the other hand, the research team also identified brain regions that are more strongly 'de-coupled' from the rest of the network in more intelligent people. This may result in better protection against distracting and irrelevant inputs. "We assume that network properties we have found in more intelligent persons help us to focus mentally and to ignore or suppress irrelevant, potentially distracting inputs," says Basten. The causes of these associations remain an open question at present. "It is possible that due to their biological predispositions, some individuals develop brain networks that favor intelligent behaviors or more challenging cognitive tasks. However, it is equally as likely that the frequent use of the brain for cognitively challenging tasks may positively influence the development of brain networks. Given what we currently know about intelligence, an interplay of both processes seems most likely."

Your brain does not process information and it is not a computer | Aeon Essays

Worse still, even if we had the ability to take a snapshot of all of the brain’s 86 billion neurons and then to simulate the state of those neurons in a computer, that vast pattern would mean nothing outside the body of the brain that produced it. This is perhaps the most egregious way in which the IP metaphor has distorted our thinking about human functioning. Whereas computers do store exact copies of data – copies that can persist unchanged for long periods of time, even if the power has been turned off – the brain maintains our intellect only as long as it remains alive. There is no on-off switch. Either the brain keeps functioning, or we disappear. What’s more, as the neurobiologist Steven Rose pointed out in The Future of the Brain (2005), a snapshot of the brain’s current state might also be meaningless unless we knew the entire life history of that brain’s owner – perhaps even about the social context in which he or she was raised.

outsiders see the big picture

One of the interesting "side effects" of this project was the discovery of the great connectedness of the yellow nodes -- the outside contractors -- in this project. They were better integrated in the knowledge flows of this project than any other group -- they reached more people, over shorter paths. Of course, the bad news is that these contractors will all leave at the end of the project, and the company will no longer have access to their knowledge. The company did not want to lose key knowledge from, and about, the project. They set up regular knowledge-sharing sessions where key network nodes would share their wisdom, experience and learning about the project. This allowed the knowledge to flow from the well-connected contractors back into the regular organization.

Runners' brains may be more connected, research shows | EurekAlert! Science News

University of Arizona researchers compared brain scans of young adult cross country runners to young adults who don't engage in regular physical activity. The runners, overall, showed greater functional connectivity -- or connections between distinct brain regions -- within several areas of the brain, including the frontal cortex, which is important for cognitive functions such as planning, decision-making and the ability to switch attention between tasks.

A friend of a friend is ... a dense network | EurekAlert! Science News

In their recent paper published in Physical Review Letters, the researchers constructed a general network evolution in which every new node links to one target node already in the network, as well as to each of the neighbors of the target (that is, friends of friends), with copying probability p. The likelihood of each of these "copying" steps turns out to be the crucial factor in how the network evolves. If copying is unlikely, the network evolves into a sparse, skeleton-like framework. But when the copying probability is greater than 1/2, the network becomes dense, with the number of links growing faster than the network itself. This "densifying" behavior has been observed in real world data, such as research paper citation lists, internet router maps, and other networks.

How many friends can you have?

The Dunbar number is actually a series of them. The best known, a hundred and fifty, is the number of people we call casual friends—the people, say, you’d invite to a large party. (In reality, it’s a range: a hundred at the low end and two hundred for the more social of us.) From there, through qualitative interviews coupled with analysis of experimental and survey data, Dunbar discovered that the number grows and decreases according to a precise formula, roughly a “rule of three.” The next step down, fifty, is the number of people we call close friends—perhaps the people you’d invite to a group dinner. You see them often, but not so much that you consider them to be true intimates. Then there’s the circle of fifteen: the friends that you can turn to for sympathy when you need it, the ones you can confide in about most things. The most intimate Dunbar number, five, is your close support group. These are your best friends (and often family members). On the flipside, groups can extend to five hundred, the acquaintance level, and to fifteen hundred, the absolute limit—the people for whom you can put a name to a face.

Pain tolerance predicts human social network size : Scientific Reports

Mapping social space in the hippocampus

Participants played the lead role in a “choose-your-own-adventure” game, in which they interacted with cartoon characters. We found that a geometric model of social relationships, in a “social space” framed by power and affiliation, predicted hippocampal activity. Moreover, participants who reported better social skills showed stronger covariance between hippocampal activity and “movement” through “social space.” These results suggest that the hippocampus is critical for social cognition, and imply that beyond framing physical locations, the hippocampus computes a more abstract, multidimensional cognitive map. Importantly, these neural representations of social space may be relevant for psychological wellbeing. Here we report new evidence on how this model can be predictive of social behavior and cognition. We found that a number of geometric variables, extracted from participants’ behavior in the game, correlated robustly with trait scores: participants with higher social anxiety tended to give less power to the game’s characters; and participants who reported less social avoidance and higher self-efficacy showed increased exploration of the social space. Additionally, we found that lower hippocampal volumes predicted lower fidelity tracking of social distance in the posterior cingulate cortex.

The Law School with the Most Influence Will Surprise You

For the Ravel Influence Score, we developed a measure that looks at both quantity and quality of work. Using data from Ravel’s platform we weighed the number of rulings a judge wrote and the number of times those decisions were cited in other opinions. In short, this is an approach that judges judges by way of other judges.

German Forest Ranger Finds That Trees Have Social Networks, Too

trees in the forest are social beings. They can count, learn and remember; nurse sick neighbors; warn each other of danger by sending electrical signals across a fungal network known as the “Wood Wide Web”; and, for reasons unknown, keep the ancient stumps of long-felled companions alive for centuries by feeding them a sugar solution through their roots.

Despite poaching, elephants' social networks hold steady -- ScienceDaily

the structure of the Kenyan elephants' social network was maintained over time, despite a 70 percent turnover of individuals. Generally speaking, the oldest and most experienced remaining individuals stepped up to fill socially central "hubs" in the network. The researchers also found that they could predict the social positions of daughters after a disruption based on that of their mothers in the years before. That ability of daughters to fill the social network roles of their mothers drove the observed network resilience. In extreme situations where families had lost most of the mature adults, elephants created new networks from previously distant connections.

The network's the thing — Remains of the Day

Software may be eating the world, but I posit that networks are going to eat an outsized share because they capitalize disproportionately on the internet. Journalism, advertising, video, music, publishing, transportation, finance, retail, and more—networks are going to enter those spaces faster than those industries can turn themselves into networks. That some of our first generation online social networks have begun self-actualizing is just the beginning of that movement.

Clustered Networks Spread Behavior Change Faster | WIRED

To do the experiment, he created an internet-based health community and invited people already participating in other online health forums to join. Over 1,500 people signed up to participate, and they were placed anonymously in one of two different kinds of networks: a random network with many distant ties (above left), or a clustered network with many overlapping connections (above right). Users in both networks had the same number of assigned “health buddies.” They couldn’t contact their buddies directly, but they could see how their buddies rated content on the site, and could receive e-mails informing them of their buddies activities. […]In the clustered network, 54 percent of the people signed up for the forum, compared to 38 percent in the random network, and almost four times as fast. Not surprisingly, Centola also found the more friends people had that also signed up, the more likely they were to return to the forum to participate.

Friends at Work? Not So Much

In 1985, about half of Americans said they had a close friend at work; by 2004, this was true for only 30 percent. And in nationally representative surveys of American high school seniors, the proportion who said it was very important to find a job where they could make friends dropped from 54 percent in 1976, to 48 percent in 1991, to 41 percent in 2006.

Clustered Networks Spread Behavior Change Faster | WIRED

In the clustered network, 54 percent of the people signed up for the forum, compared to 38 percent in the random network, and almost four times as fast.

Neurons as adventurous voyagers

Each neuron is imprisoned in your brain. I now think of these as cells within cells, as cells within prison cells. Realize that every neuron in your brain, every human cell in your body (leaving aside all the symbionts), is a direct descendent of eukaryotic cells that lived and fended for themselves for about a billion years as free-swimming, free-living little agents. They fended for themselves, and they survived.              They had to develop an awful lot of know-how, a lot of talent, a lot of self-protective talent to do that. When they joined forces into multi-cellular creatures, they gave up a lot of that. They became, in effect, domesticated. They became part of larger, more monolithic organizations. My hunch is that that's true in general. We don't have to worry about our muscle cells rebelling against us, or anything like that. When they do, we call it cancer, but in the brain I think that (and this is my wild idea) maybe only in one species, us, and maybe only in the obviously more volatile parts of the brain, the cortical areas, some little switch has been thrown in the genetics that, in effect, makes our neurons a little bit feral, a little bit like what happens when you let sheep or pigs go feral, and they recover their wild talents very fast. Maybe a lot of the neurons in our brains are not just capable but, if you like, motivated to be more adventurous, more exploratory or risky in the way they comport themselves, in the way they live their lives. They're struggling amongst themselves with each other for influence, just for staying alive, and there's competition going on between individual neurons. As soon as that happens, you have room for cooperation to create alliances, and I suspect that a more free-wheeling, anarchic organization is the secret of our greater capacities of creativity, imagination, thinking outside the box and all that, and the price we pay for it is our susceptibility to obsessions, mental illnesses, delusions and smaller problems.

What Happens When Your Brain Says You Don't Exist : Shots - Health News : NPR

What seems to be happening is that there is a network in the brain that is responsible for internal awareness, awareness of our own body, awareness of our emotions, awareness of our self-related thoughts, and in Cotard's, it seems like that particular network is tamped down. In some sense, their own experience of their body, in all its vividness, in experience of their own emotions in all its vividness, that's compromised very severely. In some sense they're not feeling themselves vividly. It's as simple as that. But, then there's something else that's happening in the brain. It seems like parts of the brain that are responsible for rational thought are also damaged. First of all, what might be happening is a perception that arises in their brain saying that they are dead because they're not literally perceiving their own body and body states and emotions vividly and then that perception — irrational though it is — is not being shot down.

How Complex Networks Explode with Growth | Quanta Magazine

Dimitris Achlioptas, a computer scientist at the University of California, Santa Cruz, proposed a possible means for delaying a phase transition into a densely connected network, by merging the traditional notion of percolation with an optimization strategy known as the power of two choices. Instead of just letting two random nodes connect (or not), you consider two pairs of random nodes, and decide which pair you prefer to connect. Your choice is based on predetermined criteria — for instance, you might select whichever pair has the fewest pre-existing connections to other nodes. Because a random system would normally favor those nodes with the most pre-existing connections, this forced choice introduces a bias into the network — an intervention that alters its typical behavior. In 2009, Achlioptas, Raissa D’Souza, a physicist at the University of California, Davis, and Joel Spencer, a mathematician at New York University’s Courant Institute of Mathematical Sciences, found that tweaking the traditional percolation model in this way dramatically changes the nature of the resulting phase transition. Instead of arising from a slow, steady continuous march toward greater and greater connectivity, connections emerge globally all at once throughout the system in a kind of explosion — hence the moniker “explosive percolation.”

How Complex Networks Explode with Growth

Public relations professionals often ask how D’Souza’s work might help their products go viral. She typically responds by pointing out that her models actually suppress viral behavior, at least in the short term. “Do you want to eke out all the gains as quickly as you can, or do you want to suppress [growth] so when it does happen, more people learn about it right away?” she said. The same holds true for political campaigns, according to Ziff. Following this model, they would spend much of their time early in the campaign on grassroots local efforts, building up localized clusters of connections and suppressing the emergence of long-range connections until the campaign was ready to go national with a big media splash.

How Complex Networks Explode with Growth

They have uncovered many other percolation models that do yield truly abrupt transitions. […] In traditional percolation, nodes and pairs of nodes are chosen at random to form connections, but the likelihood of two clusters merging is proportional to their size. Once a large cluster has formed, it dominates the system, absorbing any smaller clusters that might otherwise merge and grow. However, in the explosive models, the network grows, but the growth of the large cluster is suppressed. This allows many large but disconnected clusters to grow, until the system hits the critical threshold where adding just one or two extra links triggers an instantaneous switch to über-connectivity. All the large clusters combine at once in a single violent merger.

Does gentrification lead to generification?

In the longer term, high commercial rents also damage what made neighborhoods like the West Village attractive and appealing to buyers and renters in the first place. One usually pays for distinction, and there is nothing distinct about a neighborhood where new businesses are national chains or safe, high-margin operations. The preservationist Jeremiah Moss, the author of the Vanishing New York blog, points out that Greenwich Village has been a bohemian center since the eighteen-fifties, but, since the rise in rents, it “no longer drives the culture,” and instead is becoming what James Howard Kunstler termed “a geography of nowhere.”

Unlocking the organization with simple network mapping

Our client asked us to map cooperation in their organization because they had the feeling something might not be quite right.When together we looked at the network map, our client immediately recognized the bottleneck:the Head of Customer Services. This manager’s centrality was constraining the speed, spread and quality of information flow, creating a major HR risk. If this person were occupied, then the exchange of information between the Customer Service department and the rest of the organization would be seriously impaired. And on top of all of this, given that all information in the organization flowed through this same person, all information had the same “imprint” and was colored by the values and opinions of this person.

When networking works

Sleep from 4-8PM every day. “I nap every day in Davos sometime between the hours of 4-8pm. It’s the most efficient time to catch up on sleep so I can be fresh when the time is opportune. The opportune moments happen while dancing at one of the nightcaps or at a chateau where only a select group of people is invited. The conversations there can go on until the early morning hours.”

In Venture Capital, Birds of a Feather Lose Money Together (Success Defined as IPO)

They found that the probability of success decreased by 17 percent if two co-investors had previously worked at the same company—even if they hadn't worked there at the same time. In cases where investors had attended the same undergraduate school, the success rate dropped by 19 percent. And, overall, investors who were members of the same ethnic minority were 20 percent less successful than investors with different ethnic backgrounds.