Major depression is one of the most common psychiatric disorders in the United States, afflicting an estimated 20 million people in the United States in 2013. The statistics for anxiety disorders are even more staggering, with twice the prevalence of depression and an average onset estimated at 11 years of age. Though these disorders, characterized by a negativity bias, are both widespread and debilitating, their neurobiological bases and risk factors remain poorly understood. This project will address these gaps by examining the mechanisms underlying the extent of an individual's negativity bias and regulatory strategies that override this negativity. Images of emotional facial expressions are a useful tool for examining negativity bias and its regulation. For instance, some expressions provide clear information about the emotions and intentions of others (e.g., happy or angry) whereas others are ambiguous (e.g., surprise) because they signal both positive (e.g., a surprise party) and negative outcomes (e.g., witnessing an accident). When experienced without a clarifying context, surprised expressions provide insight into an individual's disposition: they are stably interpreted as positive by some people and as negative by others. The PI's prior work demonstrated that the ?initial, automatic? interpretation is negative (i.e., even for people who eventually interpret the expression as positive). Positive interpretations may then require an additional regulatory process in the brain that overrides this initial negativity ? one that only some individuals adopt naturally. Interestingly, children show a stronger negativity bias than adults, which is likely attributable to weaker regulatory mechanisms in children. The goal of the proposed research is to use state-of-the-art brain imaging and analysis techniques to advance the understanding of the biological mechanisms of the valence bias (i.e., the tendency for an individual to interpret surprise as positive or negative). By identifying the mechanisms underlying this bias, this project will support the broad, long-term objective of developing new approaches to predict, prevent, and treat the negativity bias associated with mood disorders such as depression and anxiety. The three aims are: 1) Determine extent to which resting-state functional connectivity (RSFC) in the amygdala and cingulo- opercular network (CO) networks predicts positive valence bias in adults. fMRI data will be collected from adults to determine if greater functional connectivity in regulatory networks is associated with positive bias. 2) Determine extent to which RSFC in the amygdala and CO networks is responsible for the developmental transition from a negative valence bias in childhood to individual differences in adulthood. Similar data will be collected in children/adolescents to characterize the transition away from the negative bias in childhood. 3) Identify the role of regional brain reactivity and explicit emotion regulation in valence bias. fMRI data will be collected from participants of all ages while they passively view facial expressions of emotion and in a task that requires regulating the natural emotional response in order to examine these effects on valence bias.
The proposed project will offer information on the regulatory brain networks that may explain individual differences in the bias to interpret an ambiguous social signal as either positive or negative (i.e., valence bias). This information is crucial because valence bias can serve as a continuous measure of both negativity bias, which has been thought to underpin the development and persistence of mood and anxiety conditions, and emotion regulation ability. This project aims to understand the mechanisms underlying the valence bias, including the naturally enhanced negative bias in a healthy population of subjects (children) in order to lay the groundwork for tools and clinical approaches to address relevant psychopathologies (e.g., depression and anxiety).
