Applying drift diffusion models to rat gambling task data reveals divergent cognitive mechanisms underlying risky choice

The rat gambling task (rGT) has been widely used to investigate the neural mechanisms underlying risky choice and motor impulsivity. Here, rats sample between four options (P1-P4) that vary in the size and probability of reward and time-out penalties. The optimal strategy is to avoid risky options that may yield higher per-trial gains, but deliver longer and more frequent time-outs. Previous reports suggest pairing wins with salient audiovisual cues increases risky decision making, but behavioural variation is high, and it is unclear whether motor impulsivity is also affected. Here we leveraged rGT data from over 750 rats to characterize behavioural performance across sex and cue condition. We compared different methods of classifying rats as optimal or risk-preferring, using either a unitary decision score variable or specific P-choice preference, and applied drift diffusion modeling (DDM) to explore whether divergent cognitive mechanisms underlie risky decision making across subgroups. We confirmed that risky choice is higher on the cued rGT, partly due to a greater proportion of risk-preferring rats, but also because net optimal decision-makers chose the risky options more often. Risk-preferring rats made more impulsive, premature responses regardless of cue condition, as did males. Optimal decision-makers made more premature responses when cues were present, such that premature response rates were higher overall on the cued rGT. DDM and response latency data suggest divergent cognitive processes underpinning risky decisions across sex. Wider decision boundaries were associated with both highly optimal and highly risky choice patterns, indicating risky choices are made deliberatively by highly risk-preferring individuals. Similar results were obtained regardless of classification method.