Monthly Archives: January 2010

Self-Control

By Chris Fariss

I found the following post at Chris Blattman‘s blog; however, the original post is from yet another blog, The Frontal Cortex.  Is this cross-blogging or blog-crossing?  Anyway, I think the experiments will be of interest to our group.  Enjoy.

For the most part, self-control is seen as an individual trait, a measure of personal discipline. If you lack self-control, then it’s your own fault, a character flaw built into the brain.

However, according to a new study by Michelle vanDellen, a psychologist at the University of Georgia, self-control contains a large social component; the ability to resist temptation is contagious. The paper consists of five clever studies, each of which demonstrates the influence of our peer group on our self-control decisions.

For instance, in one study 71 undergraduates watched a stranger exert self-control by choosing a carrot instead of a cookie, while others watched people eat the cookie instead of the carrot. That’s all that happened: the volunteers had no other interaction with the eaters. Nevertheless, the performance of the subjects was significantly altered on a subsequent test of self-control. People who watched the carrot-eaters had more discipline than those who watched the cookie-eaters.


Be sure to check out the many other interesting posts at Chris Blattman‘s blog.  As for The Frontal Cortex, this was my first visit to the site but it might be worth exploring a bit more.

Slime Mold Leaves Urban Planners Unemployed

By Chris Fariss

The abstract of a recently published report in Science:

Transport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. Furthermore, they develop without centralized control and may represent a readily scalable solution for growing networks in general. We show that the slime mold Physarum polycephalum forms networks with comparable efficiency, fault tolerance, and cost to those of real-world infrastructure networks—in this case, the Tokyo rail system. The core mechanisms needed for adaptive network formation can be captured in a biologically inspired mathematical model that may be useful to guide network construction in other domains.

Atsushi Tero, Seiji Takagi, Tetsu Saigusa, Kentaro Ito, Dan P. Bebber, Mark D. Fricker, Kenji Yumiki, Ryo Kobayashi, Toshiyuki Nakagaki. 2010. “Rules for Biologically Inspired Adaptive Network DesignScience Vol. 327. no. 5964, pp. 439 – 442 DOI: 10.1126/science.1177894

Human Rights as a Latent Variable

By Chris Fariss

Keith Schnakenberg and I are working on a paper in which we measure the unobservable level of respect for human rights.  We use the same Bayesian model that Shawn Treier and Simon Jackman use to measure the latent level of democracy in their 2008 paper that was published in the American Journal of Political Science.   As with the construction of GRE scores, the ordinal item-response (IRT) model explicitly models the measurement error that results when different component indicators are aggregated together.

Posterior densities for item discrimination parameters for individual physical integrity rights (300 draws). The item discrimination parameter represent the degree to which the item discriminates between states' along the latent human rights variable. Greater values along the x-axis signify greater discrimination by the item.

The data we use to estimate the IRT model is available from the CIRI Human Rights Data Project.  The model allows us to generate point estimates and credible intervals for the latent variable of interest.

Latent variables estimates for all 192 countries in the CIRI dataset in the year 2007. Blue dots are point estimates (posterior means) and red lines are 95% credible intervals.

For those interested, Simon Jackman has posted several slide-shows on his website that demonstrate the IRT model in action.  In our paper we also demonstrate a simple way to include the uncertainty from the estimates in models that include such a measure as an independent variable.  You can download a copy of our paper at SSRN (we will upload the paper soon).  For now, here is the current version of our abstract:

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Recent Abstracts

By Darren Schreiber

In this set of abstracts, we get some interesting evidence on why high sensation seekers might be drawn to scary movies (1) and a series of methodological innovations that demonstrate how new advances are going to improve our ability to get useful insights from MRI data (2, 5, 7, 8, 9, 114). We also have some new work illuminating the role of stereotyped racial judgments (which rely on the amgydala) and individuate judgments which use a broad network of regions connected with mentalizing (3). Another article shows that there is variation in the deactivations of some regions of the default mode network in particular types tasks (4). We also learn that the default mode network contains the most heavily functionally connected brain regions, with the posterior cingulate being particular well connected to the rest of the brain (10).

Another article melds structural and functional connectivity data to provide an exciting methodological innovation (11). I have long hoped that brain imaging statistical analysis would start to do better at accounting for our priors about how the brain is organized, specifically that techniques would be developed to take advantage of our knowledge of structure while we try to understand function. This paper is a great step in this direction and I know that the developers of the FSL package are also making strides towards this goal.

On the topic of connectivity, we have a study that used a structural connectivity technique to demonstrate that the amgydala appears to have at least three distinct subregions (5). The amgydala is also shown to vary in size in non-medicated bi-polar patients, controls, and medicated bipolar patients (6).

Rounding out the remainder, we have a nice paper that provides a possible explanation for why the anterior cingulate appears to be active in reward activity in non-human primates, but seems to be mostly involved in error prediction in humans (12). Another paper demonstrates an important lesson for economists about the distinction between monetary and social rewards (13). While we may anticipate them using the same region (striatum), consumption of those rewards implicates distinct regions. We also have some insight into mental fatigue that confirms the importance of rest and perhaps provides a way of understanding why we feel so depleted after a hard day of academic brain busting (14). The next to last paper tries to synthesize two literatures suggesting alternative functions for the anterior temporal lobe, suggesting that perhaps it is our attempt to integrate conceptual understanding of our social tasks that is activating the region (15). And finally, we’ve got a paper looking at a potential genetic role for face recognition and a demonstration that it is independent of general intelligence (16).

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Reporting the News Using Only Twitter and Facebook as Sources

By Jason J. Jones

Five journalists have volunteered to be locked in a house with no access to the outside world except Facebook and Twitter. Their task will be to report the day’s news as best they can using only these sources.

The Washington Post and Ars Technica are optimistic.  Personally, I wouldn’t be surprised if the stories they report end up a little garbled.

Altruism: Reciprocity v. Kinship

by Jaime Settle

A Nature News article highlights the recent finding that reciprocity explains more of the variance in grooming behaviors between primate species than does kinship:

Deriving Social Networks from Mobile Phone Data: Benefits and Challenges

By Jaime Settle

I’m going to present two articles at our meeting next week that both generate social network structure and interaction using data collected from mobile phones.

The Onnela et al. 2007 paper uses the call records from over 4,000,000 people to create a network which includes about 20% of a country’s entire population. The authors explore the relationship between local and global network topology and teh spread of information through the network, concluding that:

“Taken together, weak ties appear to be crucial for maintaining the network’s structural integrity, but strong ties play an important role in maintaining local communities. Both weak and strong ties are ineffective, however, when it comes to information transfer, given that most news in the real simulations reaches an individual for the first time through ties of intermediate strength” (p. 7336)

The Eagle, Pentland and Lazer 2009 paper uses proximity data generated from software embedded in cell phones to track the behavior of 94 students and faculty at a research university. They find that the observational data on proximity can better predict job satisfaction and friendship formation than respondent self-report.

Both articles represent major advances in our ability to collect data on social networks, however, they also raise interesting questions about what we are actually measuring as links between the nodes. I hope our discussion of the contributions and drawbacks of these two approaches will help us think through the operationalization of our own network research.