Abstract

BackgroundEarly adverse experiences are assumed to affect fundamental processes of reward learning and decision-making. However, computational neuroimaging studies investigating these circuits in the context of adversity are sparse and limited to studies conducted in adolescent samples, leaving the long-term effects unexplored. MethodsUsing data from a longitudinal birth cohort study (n=156, 87 females), we investigated associations between adversities and computational markers of reward learning (i.e., expected value (EV), prediction errors). At the age of 33 years, all participants completed an fMRI-based passive avoidance task. Psychopathology measures were collected at the time of fMRI investigation and during the COVID-19 pandemic. We applied a principal component analysis to capture common variation across seven adversity measures. The resulting adversity factors (factor-1: postnatal psychosocial adversities and prenatal maternal smoking, factor-2: prenatal maternal stress and obstetric adversity, and factor-3: lower maternal stimulation) were linked with psychopathology and neural responses in the core reward network using multiple regression analysis. ResultsWe found that the adversity dimension primarily informed by lower maternal stimulation was linked to lower EV representation in the right putamen, right nucleus accumbens (NAcc), and anterior cingulate cortex. EV encoding in the right NAcc further mediated the relationship between this adversity dimension and psychopathology and predicted higher withdrawn symptoms during the COVID-19 pandemic. ConclusionsOur results suggested that early adverse experiences in caregiver context might have a long-term disruptive effect on reward learning in reward-related brain regions, which can be associated with suboptimal decision-making and thereby may increase the vulnerability of developing psychopathology.

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