The neural computation of human goal-directed behavior in complex motivational states

Because the motives behind goal-directed behaviors are often complex, most behaviors result from the interplay between different motives. However, it is unclear how this interplay between multiple motives affects the neural computation of goal-directed behaviors. Using a combination of drift-diffusion modeling and fMRI, we show that the interplay between different social motives changes initial preferences for prosocial behavior before a person makes a behavioral choice. This increase in preferences for the prosocial choice option was tracked by neural responses in the bilateral dorsal striatum, which in turn lowered the amount of information necessary for choosing prosocial behavior. We obtained these results using a paradigm in which each participant performed the same behavior based on different, simultaneously activated motives, or based on each of the motives separately. Thus, our findings provide a model of behavioral choice computation in complex motivational states, i.e., the motivational setting that drives most goal-directed human behaviors.