Amygdala volume and social network size in humans

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Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender's and receiver's temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.fMRI | hyperscanning | joint attention H uman social interactions have likely shaped brain evolution and are critical for development, health, and society. Defining their neural underpinnings is a key goal of social neuroscience. Interacting dyads, the simplest and fundamental form of human interaction, have been examined with behavioral setups that used real movement interactions during communication in real time as a proxy (1-4), providing mathematical models representing human interaction, goal sharing, mutual engagement, and coordination. To identify the neural systems supporting these behaviors, neuroimaging would be the tool of choice, but studying dyadic interactions with this method is both experimentally and analytically challenging. Consequently, the neural processes underlying human social interactions remain incompletely understood.Experimentally, studying dyads with neuroimaging technology that allows only one participant per scanner provides challenges that have been addressed in the literature in one of two ways. First, the audiovisual experiences of human social contact have been simulated using stimuli such as photographs, recorded videos, or computerized avatars in the absence of human interaction (5-7), or, recently, immersive audiovisual linkups have been used with one of the two participants being scanned (8, 9). Secondly, pioneering neuroimaging experiments have coupled two scanner sites over the Internet, a setup called hyperscanning, enabling subjects to observe higher-level behavioral responses such as choices made to accept or reject an offer in real time while in the scanners (10, 11). In the current study, we aimed to combine the advantages of these experimental approaches by enabling two humans to see (and possibly hear) each other in a hyperscanning framework, enabling an immersive social interaction while both participant's brains are imaged. To do so, we implemented a setup with delay-free data transmission and precisely synchronized data acquisitio...

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 97%

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

Bilek¹,

Ruf

Schäfer³

et al. 2015

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124

“…3) have reported that individuals' social network size and complexity correlated with gray matter in the vmPFC (45,46), amygdala (47,48), and lTPJ (45). Moreover, individual macaques' gray matter in the mPFC and regions approximating human TPJ covary with both social network size (which was experimentally assigned) and social status (49,50).…”

Section: Discussionmentioning

confidence: 98%

Neural mechanisms tracking popularity in real-world social networks

Zerubavel

Bearman

Weber

et al. 2015

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

“…For structural analyses, estimates of NAcc volumes were extracted for each individual subject using FreeSurfer (20). Left hippocampal volumes were additionally extracted and used as a control region for comparison, similar to previous studies (41).…”

Section: Methodsmentioning

confidence: 99%

Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues

Rapuano

Zieselman

Kelley

et al. 2016

Obesity is a major public health concern that involves an interaction between genetic susceptibility and exposure to environmental cues (e.g., food marketing); however, the mechanisms that link these factors and contribute to unhealthy eating are unclear. Using a well-known obesity risk polymorphism (FTO rs9939609) in a sample of 78 children (ages 9-12 y), we observed that children at risk for obesity exhibited stronger responses to food commercials in the nucleus accumbens (NAcc) than children not at risk. Similarly, children at a higher genetic risk for obesity demonstrated larger NAcc volumes. Although a recessive model of this polymorphism best predicted body mass and adiposity, a dominant model was most predictive of NAcc size and responsivity to food cues. These findings suggest that children genetically at risk for obesity are predisposed to represent reward signals more strongly, which, in turn, may contribute to unhealthy eating behaviors later in life.T he relationship between genes and sensitivity to environmental cues is elusive, yet it is paramount to understanding the development of potentially maladaptive human behaviors. The rising prevalence of obesity is a major public health concern that has been attributed to various factors, such as genetic susceptibility (1), and increases in the availability and marketing of calorie-dense foods (2). However, little is known about how genetic predisposition to obesity influences sensitivity to real-world food cues and contributes to the development of unhealthy eating behaviors.Previous neuroimaging studies have demonstrated that responses to food cues in reward-related regions of the brain, such as the nucleus accumbens (NAcc), predict weight gain in adulthood (3) and giving in to food temptations in daily life (4). Furthermore, structural differences in NAcc volume have been positively associated with body mass index (BMI) in adults (5, 6). Because the development of the NAcc precedes the development of prefrontal control systems (7), this structure is suggested to play a key role in motivating and establishing unhealthy eating behaviors early in the lifespan. Importantly, genetic factors are a known contributor to brain development (8) and may influence risky behaviors during childhood and adolescence by biasing the early development of anatomical structures underlying reward-related brain function.In addition, the notion that genes contribute to obesity has recently gained much attention. More specifically, the fat-mass and obesity-associated (FTO) rs9939609 polymorphism has been strongly related to increased BMI and adiposity across the lifespan, and is suggested to influence food intake and food choice, rather than energy expenditure (9-11). Those with two high-risk "A" alleles (AA) are at an enhanced risk for obesity compared with those with two low-risk "T" alleles (TT) or those who are heterozygous (AT) for the FTO rs9939609 polymorphism. Although the FTO gene is highly expressed in the brain (1), the mechanism by which this gene promotes unhealthy...