Mood and reward dynamics in human adolescent brain electrophysiology

Despite the frequency of mood disorders in the population our understanding of neuronal markers of mood remains elusive which stalls the development of targeted brain-based treatments for these problems. Computational models can help identifying likely parameters affecting self-reported mood during mood induction tasks. Here we test if our previously proposed computational model dynamics of self-reported mood during monetary gambling can be used to identify trial-by-trial variations in neuronal activity. To this end we shifted mood in healthy (N=24) and depressed (N=30) adolescents by delivering individually tailored reward prediction errors whilst recording magnetoencephalography (MEG) data. Following a pre-registered analysis we hypothesize that expectation (defined by previous reward outcomes) would be predictive of beta-gamma oscillatory power (25-40Hz), a frequency shown to modulate to reward feedback. We also hypothesize that trial variations in the evoked response to the presentation of gambling options and in source localized responses to reward feedback. Through our multilevel statistical analysis we found confirmatory evidence that beta-gamma power is positively related to reward expectation during mood shifts, with possible localized sources in the posterior cingulate cortex. We also confirmed reward prediction error to be predictive of trial-level variations in the response of the paracentral lobule and expectation to have an effect on the cerebellum after presentation of gambling options. To our knowledge, this is the first study to relate fluctuations in mood on a minute time-scale to variations in neural oscillations with non-invasive electrophysiology.

Mapping Social Distress: A Computational Approach to Spatiotemporal Distribution of Anxiety

Anxiety is a pervasive emotional state that tends to arise in situations involving uncertainty due partly to social and contextual issues including competition, economic disparity, and social insecurity. Thus, distribution of aggregate emotions, such as in anxiety, may reveal an important picture of otherwise invisible social processes in which individuals interact with local and global opportunities, constraints, and potential threats. The aim of this study is to present a computational approach to the dynamic distribution of anxiety extracted from natural language expressions of users of Twitter, a popular global social media platform. We develop an unsupervised machine learning procedure based on a naive Bayes model to classify contents of anxiety, estimate the degree of anxiety, and construct a geographic map of spatiotemporal distribution of anxiety. To validate our mapping results, a multilevel statistical analysis was performed to examine how anxiety distribution is correlated with other district-level sociodemographic statistics such as rates of birth and early divorce. Implications for further research and extension are discussed.

Stress and telomere shortening among central Indian conservation refugees

Research links psychosocial stress to premature telomere shortening and accelerated human aging; however, this association has only been demonstrated in so-called “WEIRD” societies (Western, educated, industrialized, rich, and democratic), where stress is typically lower and life expectancies longer. By contrast, we examine stress and telomere shortening in a non-Western setting among a highly stressed population with overall lower life expectancies: poor indigenous people—the Sahariya—who were displaced (between 1998 and 2002) from their ancestral homes in a central Indian wildlife sanctuary. In this setting, we examined adult populations in two representative villages, one relocated to accommodate the introduction of Asiatic lions into the sanctuary (n = 24 individuals), and the other newly isolated in the sanctuary buffer zone after their previous neighbors were moved (n = 22). Our research strategy combined physical stress measures via the salivary analytes cortisol and α-amylase with self-assessments of psychosomatic stress, ethnographic observations, and telomere length assessment [telomere–fluorescence in situ hybridization (TEL-FISH) coupled with 3D imaging of buccal cell nuclei], providing high-resolution data amenable to multilevel statistical analysis. Consistent with expectations, we found significant associations between each of our stress measures—the two salivary analytes and the psychosomatic symptom survey—and telomere length, after adjusting for relevant behavioral, health, and demographic traits. As the first study (to our knowledge) to link stress to telomere length in a non-WEIRD population, our research strengthens the case for stress-induced telomere shortening as a pancultural biomarker of compromised health and aging.

Charmed by China? Popular Perceptions of Chinese Influence in Asia

Chinese influence in Asia is complicated by many factors. There are those who argue that China's growing military and economic power make this influence an automatic threat, while others maintain that China's recent attempts at a ‘charm offensive’ mute this threat and have succeeded in creating a positive image for many of its regional neighbors. Drawing on survey data collected across 23 countries, we enter this debate by asking what individuals in and across Asia think about Chinese influence. Do they see this influence as positive or negative? What factors at the individual and national levels most clearly shape their perceptions? Using multilevel statistical analysis, we find that Asian opinions of Chinese influence are on the whole quite positive and are influenced by a range of factors, including foreign policy interest, national identification, foreign contact, and recent military conflict.

Elite Competition, Religiosity, and Anti-Americanism in the Islamic World

The battle for public opinion in the Islamic world is an ongoing priority for U.S. diplomacy. The current debate over why many Muslims hold anti-American views revolves around whether they dislike fundamental aspects of American culture and government, or what Americans do in international affairs. We argue, instead, that Muslim anti-Americanism is predominantly a domestic, elite-led phenomenon that intensifies when there is greater competition between Islamist and secular-nationalist political factions within a country. Although more observant Muslims tend to be more anti-American, paradoxically the most anti-American countries are those in which Muslim populations are less religious overall, and thus more divided on the religious–secular issue dimension. We provide case study evidence consistent with this explanation, as well as a multilevel statistical analysis of public opinion data from nearly 13,000 Muslim respondents in 21 countries.