Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion modeling
Fig 1
A schematic of the two-stage task (panel A) and an example of a random walk used to generate the true expected value for each of the four bandits at the task second-stage (panel B). At the first-stage participants choose between two options (represented by abstract fractal images) that determined the presentation of the second-stage via fixed transition probabilities of 70% (‘common’) or 30% (‘rare’). At the second-stage, participants again choose between two bandits that led to receipt of reward (£0 or £1 play pounds). Note the second-stage included two pairs of bandits where the composition of each pair was fixed, but where the value of each bandit drifted slowly and independently. More specifically the reward associated with the second-stage bandits were subjected to random walks and thus had to be constantly learned by participants.