Caroline F. Zink

Know your place: neural processing of social hierarchy in humans.

Social hierarchies guide behavior in many species, including humans, where status also has an enormous impact on motivation and health. However, little is known about the underlying neural representation of social hierarchies in humans. In the present study, we identify dissociable neural responses to perceived social rank using functional magnetic resonance imaging (fMRI) in an interactive, simulated social context. In both stable and unstable social hierarchies, viewing a superior individual differentially engaged perceptual-attentional, saliency, and cognitive systems, notably dorsolateral prefrontal cortex. In the unstable hierarchy setting, additional regions related to emotional processing (amygdala), social cognition (medial prefrontal cortex), and behavioral readiness were recruited. Furthermore, social hierarchical consequences of performance were neurally dissociable and of comparable salience to monetary reward, providing a neural basis for the high motivational value of status. Our results identify neural mechanisms that may mediate the enormous influence of social status on human behavior and health.

A validated network of effective amygdala connectivity

Regulatory interactions with the amygdala are thought to be critical for emotional processing in the extended limbic system. Structural equation modeling (path analysis) is a widely used method to quantify interactions among brain regions based on connectivity models, but is often limited by lack of precise anatomical and functional constraints. To address this issue, we developed an automated elaborative path analysis procedure guided by known anatomical connectivity in the macaque. We applied this technique to a large human fMRI data set acquired during perceptual processing of angry or fearful facial stimuli. The derived models were inferentially validated using a bootstrapping split-half approach in pairs of 500 independent groups. Significant paths across the groups were used to form a rigorously validated and consistent path model. We confirm and extend previous observations of amygdala regulation by an extended prefrontal network encompassing cingulate, orbitofrontal, insular, and dorsolateral prefrontal cortex, as well as strong interactions between amygdala and parahippocampal gyrus. This validated model can be used to study neurocognitive correlates as well as genotype or disease-related alterations of functional interactions in the limbic system.

Vasopressin Modulates Medial Prefrontal Cortex–Amygdala Circuitry during Emotion Processing in Humans

The neuropeptide vasopressin is a modulator of mammalian social behavior and emotion, particularly fear, aggression, and anxiety. In humans, the neural circuitry underlying behavioral effects of vasopressin is unknown. Using a double-blind crossover administration of 40 IU of vasopressin or placebo and functional MRI during processing of facial emotions in healthy male volunteers, we show that vasopressin specifically reduces differential activation in the subgenual cingulate cortex. Structural equation modeling of a previously evaluated circuit between amygdala, subgenual cingulate, and supragenual cingulate revealed altered effective connectivity between subgenual and supragenual cingulate under vasopressin. Our data demonstrate an impact of vasopressin on activity and connectivity in the cortical component of a medial prefrontal cortex–amygdala circuit implicated in emotional regulation, providing the first data on the neural basis for the effects of vasopressin on social behavior in humans with potential therapeutic significance for mood and anxiety disorders.

Subjective Socioeconomic Status Predicts Human Ventral Striatal Responses to Social Status Information

The enormous influence of hierarchical rank on social interactions [1] suggests that neural mechanisms exist to process status-related information [2] and ascribe value to it. The ventral striatum is prominently implicated in processing value and salience, independent of hedonic properties [3, 4], and a functional magnetic resonance imaging (fMRI) study of social status perception in humans demonstrated that viewing higher-ranked compared to lower-ranked individuals evokes a ventral striatal response [5], indicative of a greater assignment of value/salience to higher status. Consistent with this interpretation, nonhuman primates value information associated with higher-ranked conspecifics more than lower-ranked, as illustrated using a choice paradigm in which monkeys preferentially take the opportunity to view high-status monkeys [6]. Interestingly, this status-related value assignment in nonhuman primates is influenced by ones own hierarchical rank: high-status monkeys preferentially attend to conspecifics of high status, whereas low-status monkeys will also attend to other low-status monkeys [7]. Complementary to these findings, using fMRI and a social status judgment task in humans, we suggest a neurobiological mechanism by which ones own relative hierarchical rank influences the value attributed to particular social status information by demonstrating that ones subjective socioeconomic status differentially influences ventral striatal activity during processing of status-related information.

Vasopressin modulates social recognition-related activity in the left temporoparietal junction in humans

The neuropeptide vasopressin is a key molecular mediator of social behavior in animals and humans, implicated in anxiety and autism. Social recognition, the ability to assess the familiarity of others, is essential for appropriate social interactions and enhanced by vasopressin; however, the neural mechanisms mediating this effect in humans are unknown. Using functional magnetic resonance imaging (fMRI) and an implicit social recognition matching task, we employed a double-blinded procedure in which 20 healthy male volunteers self-administered 40 UI of vasopressin or placebo intranasally, 45 min before performing the matching task in the scanner. In a random-effects fMRI analysis, we show that vasopressin induces a regionally specific alteration in a key node of the theory of mind network, the left temporoparietal junction, identifying a neurobiological mechanism for prosocial neuropeptide effects in humans that suggests novel treatment strategies.

Using Expectancy Theory to quantitatively dissociate the neural representation of motivation from its influential factors in the human brain: An fMRI study

Abstract Researchers have yet to apply a formal operationalized theory of motivation to neurobiology that would more accurately and precisely define neural activity underlying motivation. We overcome this challenge with the novel application of the Expectancy Theory of Motivation to human fMRI to identify brain activity that explicitly reflects motivation. Expectancy Theory quantitatively describes how individual constructs determine motivation by defining motivation force as the product of three variables: expectancy – belief that effort will better performance; instrumentality – belief that successful performance leads to particular outcome, and valence – outcome desirability. Here, we manipulated information conveyed by reward‐predicting cues such that relative cue‐evoked activity patterns could be statistically mapped to individual Expectancy Theory variables. The variable associated with activity in any voxel is only reported if it replicated between two groups of healthy participants. We found signals in midbrain, ventral striatum, sensorimotor cortex, and visual cortex that specifically map to motivation itself, rather than other factors. This is important because, for the first time, it empirically clarifies approach motivation neural signals during reward anticipation. It also highlights the effectiveness of the application of Expectancy Theory to neurobiology to more precisely and accurately probe motivation neural correlates than has been achievable previously. HighlightsExpectancy Theory provides a formal operational definition of motivation.For the first time, we apply Expectancy Theory to fMRI to study motivation signals precisely.With Expectancy Theory, motivation fMRI signals are isolated from reward and other processes.Signals in ventral striatum, midbrain, sensorimotor, and visual cortex scale specifically with evoked motivation.This highlights the effectiveness of applying Expectancy Theory to probe motivation neurobiology.