Ralf Schmälzlea,b, Matthew Brook O’Donnellb , Javier O. Garciac , Christopher N. Casciob , Joseph Bayerd , Danielle S. Bassette,f, Jean M. Vettelc,e,g, and Emily B. Falkb,1 a Department of Communication, Michigan State University, East Lansing, MI 48824; b Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104; c Human Research and Engineering Directorate, US Army Research Laboratory, Aberdeen Proving Ground, MD 21005; d School of Communication, The Ohio State University, Columbus, OH 43210; e Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104; f Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104; and g Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106

Social ties are crucial for humans. Disruption of ties through social exclusion has a marked effect on our thoughts and feelings; however, such effects can be tempered by broader social network resources. Here, we use fMRI data acquired from 80 male adolescents to investigate how social exclusion modulates functional connectivity within and across brain networks involved in social pain and understanding the mental states of others (i.e., mentalizing). Furthermore, using objectively logged friendship network data, we examine how individual variability in brain reactivity to social exclusion relates to the density of participants’ friendship networks, an important aspect of social network structure. We find increased connectivity within a set of regions previously identified as a mentalizing system during exclusion relative to inclusion. These results are consistent across the regions of interest as well as a whole-brain analysis. Next, examining how social network characteristics are associated with task-based connectivity dynamics, we find that participants who showed greater changes in connectivity within the mentalizing system when socially excluded by peers had less dense friendship networks. This work provides insight to understand how distributed brain systems respond to social and emotional challenges and how such brain dynamics might vary based on broader social network characteristics.

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by Anna Gorman

Lynn Whittaker stood in the hallway of her home looking at the framed photos on the wall. In one, her son Andrew is playing high school water polo. In another, he’s holding a trombone. The images show no hint of his life today: the seizures that leave him temporarily paralyzed, the weakness that makes him fall over, his labored speech, his scrambled thoughts. Andrew, 28, can no longer feed himself or walk on his own. The past nine years have been a blur of doctor appointments, hospital visits, and medical tests that have failed to produce answers.

“You name it, he doesn’t have it,” his mother said.

Andrew has never had a clear diagnosis. He and his family are in a torturous state of suspense, hanging their hopes on every new exam and evaluation. Recently, they have sought help from the Undiagnosed Diseases Network, a federally funded coalition of universities, clinicians, hospitals, and researchers dedicated to solving the nation’s toughest medical mysteries. The doctors and scientists in the network harness advances in genetic science to identify rare, sometimes unknown, illnesses.

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by Alfredo J. Morales, Vaibhav Vavilala, Rosa M. Benito, Yaneer Bar-Yam

Social media are transforming global communication and coordination and provide unprecedented opportunities for studying socio-technical domains. Here we study global dynamical patterns of communication on Twitter across many scales. Underlying the observed patterns is both the diurnal rotation of the Earth, day and night, and the synchrony required for contingency of actions between individuals. We find that urban areas show a cyclic contraction and expansion that resembles heartbeats linked to social rather than natural cycles. Different urban areas have characteristic signatures of daily collective activities. We show that the differences detected are consistent with a new emergent global synchrony that couples behaviour in distant regions across the world. Although local synchrony is the major force that shapes the collective behaviour in cities, a larger-scale synchronization is beginning to occur.

Social networks may be the most valuable and durable types of businesses powered by “network effects,” the phenomenon of products or services becoming more powerful the more people use them.

The social-networking companies in our recently launched Network Effect Index — a group of current and formerly public consumer-Web companies valued at $1 billion or more — outperformed the S&P by over 170 percent in the last five years, the most of any business category in the index.

This is one reason the imminent IPO of social/mobile app Snap, which thrives on network effects, is being so closely watched. Another is that Snap — the parent of the ragingly popular Snapchat service, and a company expected to be valued at roughly $20 billion at its offering — represents the first credible threat to the Facebook social-networking colossus. Interestingly, Snap has grown by following a path very different than Facebook’s — so much so that we believe Snap ultimately could be valued less like a traditional social network and more like a hardware-software company, like Apple, or a media business, like Comcast.

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The work could lead to a new approach to the study of what is possible, and how it follows from what already exists.

Innovation is one of the driving forces in our world. The constant creation of new ideas and their transformation into technologies and products forms a powerful cornerstone for 21st century society. Indeed, many universities and institutes, along with regions such as Silicon Valley, cultivate this process.

And yet the process of innovation is something of a mystery. A wide range of researchers have studied it, ranging from economists and anthropologists to evolutionary biologists and engineers. Their goal is to understand how innovation happens and the factors that drive it so that they can optimize conditions for future innovation.

This approach has had limited success, however. The rate at which innovations appear and disappear has been carefully measured. It follows a set of well-characterized patterns that scientists observe in many different circumstances. And yet, nobody has been able to explain how this pattern arises or why it governs innovation.

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You can see the published paper here.

Study finds a stronger correlation for women between success and being central to a network

Being well connected is more important for women who want to get ahead in science than men, a study suggests.

By analyzing how patterns of research collaboration relate to scientific outcomes, US statisticians found that highly cited female scientists at top US universities tended to be very prominent within their research networks.

However, the same was not true for highly cited male scientists, who are generally less central to the larger academic networks they participated in, according to the paper by Charisse Madlock-Brown, from the University of Tennessee Health Science Center, and David Eichmann, from the University of Iowa. The article, “The Scientometrics of Successful Women in Science”, was published recently online by the Institute of Electrical and Electronics Engineers.

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Friendship isn’t always as serendipitous as it might feel. Are you a “tight-knitter”, a “compartmentalizer,” or a “sampler”? According to Dartmouth sociology professor Janice McCabe, whose study of the effects of social connections on academic performance was published this month in the journal Contexts, when forming new friendships, people tend to follow one of these three patterns. McCabe used mathematical models to examine the friendship structures of 67 students on a Midwestern college campus, aiming to figure out how those structures influenced success in the classroom.

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Complex networks form the backbone of modern society: the Internet, the aviation network, the pattern of connections between individuals. And more complex examples are constantly emerging—the way genes interact in cells, how information flows through the banking system and the ecosystem.

The more complex the system, the harder it is to control. Nevertheless, computer scientists, doctors, economists and the like exercise a modicum of control over many of these networks.

And that raises an interesting question: is it possible to exercise the same kind of control over the most complex network we know of: the human brain?

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