A parallel accumulator model accounts for decision randomness when deciding on risky prospects with different expected value

In decision-making situations individuals rarely have complete information available to select the best option and often show decisional randomness, i.e. given the same amount of knowledge individuals choose different options at different times.  Dysfunctional processes resulting in altered decisional randomness can be considered a target process for psychiatric disorders, yet these processes remain poorly understood.  Advances in computational modeling of decision-making offer a potential explanation for decisional randomness by positing that decisions are implemented in the brain through accumulation of noisy evidence, causing a generally less preferred option to be chosen at times by chance.  One such model, the linear ballistic accumulator (LBA), assumes that individuals accumulate information for each option independently over time and that the first option to reach a threshold will be selected.  To investigate the mechanisms of decisional randomness, we applied the LBA to a decisi...