Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.social status | fMRI | social network | popularity | social cognition

Little is known about whether emotion regulation can have lasting effects on the ability of a stimulus to continue eliciting affective responses in the future. To address this issue, participants cognitively reappraised negative images once or four times. One week later they passively viewed old and new images to identify lasting effects of prior reappraisal. As in prior work, active reappraisal increased prefrontal responses while decreasing amygdala responses and self-reported emotion. At one week, amygdala responses remained attenuated for images that had been repeatedly reappraised compared to images reappraised once, new control images, and control images seen as many times but were never reappraised. Prefrontal activation was not selectively elevated for repeatedly reappraised images and was not related to long-term amygdala attenuation. These results suggest that reappraisal can exert long-lasting “dose-dependent” effects on amygdala response that may cause lasting changes in the neural representation of an unpleasant event's emotional value.

This article identifies significant high-risk clusters of autism based on residence at birth in California for children born from 1993 through 2001. These clusters are geographically stable. Children born in a primary cluster are at four times greater risk for autism than children living in other parts of the state. This is comparable to the difference between males and females and twice the risk estimated for maternal age over 40. In every year roughly 3% of the new caseload of autism in California arises from the primary cluster we identify -a small zone 20km by 50km. We identify a set of secondary clusters that support the existence of the primary clusters. The identification of robust spatial clusters indicates that autism does not arise from a global treatment and indicates that important drivers of increased autism prevalence are located at the local level.

Descartes famously argued that the mind is both everlasting and indivisible (Descartes, 1988). If he was right about the first part, he is probably pretty impressed with the advance of human knowledge on the second. Although Descartes' position on the indivisibility of the mind has been echoed at times in the history of psychology and neuroscience (Flourens & Meigs, 1846;Lashley, 1929;Uttal, 2003), the modern field has made steady progress in demonstrating that subjective mental life can be understood as the product of distinct functional systems. Today, largely because of the success of cognitive neuroscience models, researchers understand that people's intellectual faculties emerge from the operation of core systems that are instantiated by particular brain networks (Gazzaniga, 2009;Shallice, 1988). From this perspective, the brain consists of a set of distinct but interacting information processing systems that carry out cognitive functions of perception, attention, decision making, memory, executive control, and so forth. Without a doubt, the breadth of these models is impressive, but until relatively recently they have been incomplete in an important way. Namely, researchers in this tradition had placed scant emphasis on the social and emotional abilities that account for much of what makes human experience such a complex and fascinating target of scientific explanation. SOCIAL COGNITIVE NEUROSCIENCE APPROACHIn the past decade, the field of social cognitive neuroscience (SCN) has attempted to fill this gap, integrating the theories and methods of two parent disciplines: social psychology and cognitive neuroscience. Stressing the interdependence of brain, mind, and social context, SCN seeks to explain psychological phenomena at three levels of analysis: the neural level of brain systems, the cognitive level of information processing mechanisms, and the social level of the experiences and actions of social agents (Ochsner & Lieberman, 2001). In contrast to scientific approaches that grant near exclusive focus to a single level of analysis (e.g., behaviorism, artificial intelligence, eliminative materialism), SCN researchers develop theories that leverage data from each of these three levels, regarding them as complementary sources of information that enrich and mutually constrain the understanding of mental function (Cacioppo & Berntson, 1992;Ochsner, 2007). Accordingly, SCN experiments typically involve manipulating and measuring variables at the social and neural levels and attempting to draw inferences about intervening psychological processes. In service of this goal, SCN research makes use of a wide array of tools, including complex social paradigms meant to model aspects of everyday social phenomena, tightly controlled cognitive tasks, and neuroimaging as well as other biological measures.Bruce P. Doré and Noam Zerubavel contributed equally to this chapter.

Parental age at child's birth--which has increased for U.S. children in the 1992-2000 birth cohorts--is strongly associated with an increased risk of autism. By turning a social demographic lens on the historical patterning of concordance among twin pairs, we identify a central mechanism for this association: de novo mutations, which are deletions, insertions, and duplications of DNA in the germ cells that are not present in the parents' DNA. Along the way, we show that a demographic eye on the rising prevalence of autism leads to three major discoveries. First, the estimated heritability of autism has been dramatically overstated. Second, heritability estimates can change over remarkably short periods of time because of increases in germ cell mutations. Third, social demographic change can yield genetic changes that, at the population level, combine to contribute to the increased prevalence of autism.