Maital Neta - US grants

PROJECT SUMMARY/ABSTRACT 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.

Many significant social decisions are made in situations of high uncertainty. A person?s ability to resolve such uncertainty can have profound implications for outcomes ranging from health to work performance. Past research has shown that people exhibit reliable tendencies to respond to uncertainty with either positive or negative emotions. These personal biases play a significant role in responding well or poorly to high uncertainty. This project leverages the urgent opportunity presented by the COVID-19 pandemic to advance the understanding of individual-level biases in the context of a societal-level stressor. Very little is currently known about the effects of societal-level stressors, such as a global pandemic, on individual-level trait-like biases. The negative thoughts and feelings some individuals experience in response to extreme societal uncertainty can have deleterious outcomes on health, work performance, and relationships. This project lays the foundation for developing interventions to disrupt these maladaptive processes in favor of more productive responses.

An online study includes three distinct measures of valence bias (the tendency to ascribe uncertainty with a negative meaning). Measures of mood/temperament, resilience, and social factors likely affected by the COVID-19 pandemic (e.g., loneliness) are collected. A subset of participants in the study completed the valence bias tasks before the pandemic (Wave 1). In a longitudinal design, these same participants will be re-assessed at the height of the pandemic (Wave 2) and again after the pandemic ends (Wave 3). By following people over time, it is possible to gauge the effects associated with a greater increase in negativity as a function of the global pandemic, as well as greater recovery after it ends. A new group of participants will be added at Waves 2 and 3 to provide additional data for a cross-sectional exploration of the mechanisms that predict individual differences in valence bias at each time point. Age-related effects will also be explored at each wave. The research considers how people can learn to "do it better" to increase well-being and resilience in response to societal threats and uncertainty. The findings will shed light on how some individuals are able to override stress-related increases in negativity and instead resolve uncertainty in a positive light.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.