Containing misinformation: Modeling spatial games of fake news.

The spread of fake news on social media is a pressing issue. Here, we develop a mathematical model on social networks in which news sharing is modeled as a coordination game. We use this model to study the effect of adding designated individuals who sanction fake news sharers (representing, for example, correction of false claims or public shaming of those who share such claims).

Evolutionary Kuramoto dynamics.

Biological systems have a variety of time-keeping mechanisms ranging from molecular clocks within cells to a complex interconnected unit across an entire organism. The suprachiasmatic nucleus, comprising interconnected oscillatory neurons, serves as a master-clock in mammals. The ubiquity of such systems indicates an evolutionary benefit that outweighs the cost of establishing and maintaining them, but little is known about the process of evolutionary development.

The dual problems of coordination and anti-coordination on random bipartite graphs.

In some scenarios ("anti-coordination games"), individuals are better off choosing different actions than their neighbors while in other scenarios ("coordination games"), it is beneficial for individuals to choose the same strategy as their neighbors. Despite having different incentives and resulting population dynamics, it is largely unknown which collective outcome, anti-coordination or coordination, is easier to achieve. To address this issue, we focus on the distributed graph coloring problem on bipartite graphs.

Random choices facilitate solutions to collective network coloring problems by artificial agents.

Global coordination is required to solve a wide variety of challenging collective action problems from network colorings to the tragedy of the commons. Recent empirical study shows that the presence of a few noisy autonomous agents can greatly improve collective performance of humans in solving networked color coordination games. To provide analytical insights into the role of behavioral randomness, here we study myopic artificial agents attempting to solve similar network coloring problems using decision update rules that are only based on local information but allow random choices at various stages of their heuristic reasonings.

Encoding seasonal information in a two-oscillator model of the multi-oscillator circadian clock.

The suprachiasmatic nucleus (SCN) is a collection of about 10 000 neurons, each of which functions as a circadian clock with slightly different periods and phases, that work in concert with form and maintain the master circadian clock for the organism. The diversity among neurons confers on the SCN the ability to robustly encode both the 24-h light pattern as well as the seasonal time. Cluster synchronization brings the different neurons into line and reduces the large population to essentially two oscillators, coordinated by a macroscopic network motif of asymmetric repulsive-attractive coupling.

Deconstructing Circadian Rhythmicity with Models and Manipulations.

A master brain clock, localized to the hypothalamic suprachiasmatic nucleus (SCN), coordinates daily rhythms of physiology and behavior. Within the SCN, interconnected individual neurons are oscillators that, as an ensemble, function to send a coherent timing signal to the brain and body. However, individually, these neurons display different amplitudes, periods, and phases of oscillation.

Seeking and receiving social support on Facebook for surgery.

Social networking sites such as Facebook provide a new way to seek and receive social support, a factor widely recognized as important for one's health. However, few studies have used actual conversations from social networking sites to study social support for health related matters. We studied 3,899 Facebook users, among a sample of 33,326 monitored adults, who initiated a conversation that referred to surgery on their Facebook Wall during a six-month period.

Measures of centrality based on the spectrum of the Laplacian.

We introduce a family of new centralities, the k-spectral centralities. k-spectral centrality is a measurement of importance with respect to the deformation of the graph Laplacian associated with the graph. Due to this connection, k-spectral centralities have various interpretations in terms of spectrally determined information.

Cortical feature maps via geometric models.

We present a new model for feature map formation in the primary visual cortex, building on dimension reduction/wire length minimization techniques. We create a model space of feature parameters, endowed with various geometries picked to reflect physical or experimental data and search for a map from the parameter space to the cortical sheet which minimizes distortions. Upon simulating these maps, we find a family of Riemannian and sub-Riemannian geometries which give rise to feature maps which reflect known experimental data concerning (1) the qualitative arrangement of orientation maps and (2) the distribution of connections.