Abstract
Anhedonia, a reduced ability to experience positive affect and seek rewards, is present across many psychiatric disorders, notably among individuals who experienced trauma. Within the social domain, anhedonia manifests as an altered sense of belonging and social isolation and is associated with poorer clinical outcomes. Yet, mechanistic operationalizations of social anhedonia are lacking, limiting our understanding of the relationship between these mechanisms and affective symptoms. To address these questions, we developed a social reward exploration task which was administered to a transdiagnostic sample of trauma-exposed Veterans (N = 33) while they underwent functional magnetic resonance imaging. The goal was to maximize compliments from two unknown partners, as participants were told these partners selected compliments based on seeing their picture. A Bayesian reinforcement learning modeling approach was used to extract cognitive and neural markers of compliment (reward) exploration. To address these questions, we developed a social reward exploration task which was administered to a transdiagnostic sample of trauma-exposed Veterans (N = 33) while they underwent functional magnetic resonance imaging. The goal was to maximize compliments from two unknown partners, as participants were told these partners selected compliments based on seeing their picture. A Bayesian reinforcement learning modeling approach was used to extract cognitive and neural markers of compliment (reward) exploration. Higher social connectedness (β = 0.51; 95 % CI=[0.11,0.94]) and anxiety (β = 0.57; 95 % CI=[0.13,1.00]) were independently associated with more model-based choices of the partner they anticipated to be most complimenting. In the dorsal anterior cingulate cortex (ACC; z = 3.89, p .001) and left inferior parietal lobule (z = 3.96, p .001), neural responses to reward prediction errors (RPE) were more positive in response to compliment relative to non-compliment outcomes. Greater positive RPE ACC activation was associated with lower anxiety (β = -0.51; 95 % CI=[-0.99,-0.10]. Computational approaches to social reinforcement learning can help identify important neurocognitive differences in social reward sensitivity among individuals with complex affective profiles, such as trauma-exposed individuals. Understanding these differences may help develop new prediction and treatment tools for social anhedonia.