The Drift Diffusion Model can account for the accuracy and reaction time of value-based choices under high and low time pressure

An important open problem is how values are compared to make simple choices. a natural hypothesis is that the brain carries out the computations associated with the value comparisons in a manner consistent with the drift diffusion model (ddm),since this model has been able to account for a large amount of data in other domains. we investigated the ability of four different versions of the ddm to explain the data in a real binary food choice task under conditions of high and low time pressure. we found that a seven-parameter version of the ddm can account for the choice and reaction time data with high-accuracy,in both the high and low time pressure conditions. the changes associated with the introduction of time pressure could be traced to changes in two key model parameters: the barrier height and the noise in the slope of the drift process.