A specific computational role for early-life unpredictability, and not lifelong traumatic experience, in decision-making under uncertainty

It has been shown that early-life adversity (ELA) shapes how individuals learn, remember, and make decisions, yet the precise computations altered by these experiences remain unclear. Here, we combine a structured foraging task with computational modeling to test a recently developed theory for how a particular kind of ELA, early-life unpredictability (ELU), specifically influences choice under uncertainty. Adult participants (N=297) performed a sequential foraging task requiring continuous trade-offs between exploiting depleting resources and exploring alternatives. Subsets also completed assessments of early-life unpredictability (QUIC) and for trauma symptoms arising from lifelong stressors (PCL). We fit participants’ behavior with a Bayesian learning-and-planning model in which uncertainty modulates the valuation of leaving a current resource patch. Critically, the subjective influence of local uncertainty was allowed to vary freely between participants. Consistent with theoretical proposals, computational model fits and mediation analyses revealed a robust indirect pathway: ELU predicted increased discounting in the face of uncertainty, which in turn predicted greater overharvesting. This pattern was consistent across environmental conditions, indicating that early-life unpredictability primarily influences behavior through a general influence on uncertainty processing. Importantly, although PCL scores were also correlated with uncertainty adaptation, these effects were fully accounted for by shared variance with ELU, offering a clear dissociation between developmental unpredictability and lifelong traumatic experience. Together, our results show that early-life unpredictability causes long-lasting changes in decision-making by amplifying the subjective experience of uncertainty.