A drift-diffusion modeling approach reveals differences in decision-making dynamics across species and ages

Inferential decision-making is the ability to deduce new relations (e.g., A>C) from known ones (A>B, B>C). It emerges in childhood and is shared by several animal species. However, it remains unclear whether different species and age groups rely on similar computational strategies. Computational approaches based on the Drift Diffusion Model (DDM) are used to uncover hidden variables in decision-making strategies. DDM models decisions as a process of accumulating evidence toward a threshold. Fast decisions may depend on either faster accumulation or lower thresholds, reflecting different cognitive strategies. We tested 83 adults, 98 children, and 2 monkeys using a six-item transitive inference task (A>B>C>D>E>F), requiring judgments about all item pairs. While performance was comparable across groups, DDM captured distinct parameters underlying mechanisms. In adults, decision performance primarily affected the rate of accumulation of evidence. In children and monkeys, changes in accumulation rate were coupled with a progressive lowering of the decision threshold over time. These results evidenced greater urgency and reduced caution in individuals with less developed cognitive control. Overall, our findings indicate that similar behavioral outcomes may arise from different decision-making dynamics shaped by developmental and evolutionary factors.