Adolescence is a developmental period associated with an increase in impulsivity. Impulsivity is a multidimensional construct, and in this study we focus on one of the underlying components: impatience. Impatience can result from (i) disregard of future outcomes and/or (ii) oversensitivity to immediate rewards, but it is not known which of these evaluative processes underlie developmental changes. To distinguish between these two causes, we investigated developmental changes in the structural and functional connectivity of different frontostriatal tracts. We report that adolescents were more impatient on an intertemporal choice task and reported less future orientation, but not more present hedonism, than young adults. Developmental increases in structural connectivity strength in the right dorsolateral prefrontal tract were related to increased negative functional coupling with the striatum and an age-related decrease in discount rates. Our results suggest that mainly increased control, and the integration of future-oriented thought, drives the reduction in impatience across adolescence.adolescence | connectivity | impatience | delay discounting | DTI

Large individual differences exist in the ability to delay gratification for the sake of satisfying longer-term goals. These individual differences are commonly assayed by studying intertemporal preferences, as revealed by choices between immediate and delayed rewards. In the brain, reward-based and goal-oriented decisions are believed to rely on the striatum and its interactions with other cortical and subcortical networks. However, it remains unknown which specific cortical-striatal tracts are involved in intertemporal decision making. We use connectivity analyses in both structural and functional MRI to further our understanding of the relationship between distinct corticostriatal networks and intertemporal preferences in humans. Our results revealed distinct striatal pathways that are differentially related to delay discounting. Structural and functional connectivity between striatum and lateral prefrontal cortex was associated with increased patience, whereas connectivity between subcortical areas and striatum was associated with increased impulsivity. These findings provide novel insights into how the anatomy and functioning of striatal circuits mediate individual differences in intertemporal choice.

Two separate cognitive processes are involved in choosing between rewards available at different points in time. The first is temporal discounting, which consists of combining information about the size and delay of prospective rewards to represent subjective values. The second involves a comparison of available rewards to enable an eventual choice on the basis of these subjective values. While several mathematical models of temporal discounting have been developed, the reward selection process has been largely unexplored. To address this limitation, we evaluated the applicability of the Linear Ballistic Accumulator (LBA) model as a theory of the selection process in intertemporal choice. The LBA model formalizes the selection process as a sequential sampling algorithm in which information about different choice options is integrated until a decision criterion is reached. We compared several versions of the LBA model to demonstrate that choice outcomes and response times in intertemporal choice are well captured by the LBA process. The relationship between choice outcomes and response times that derives from the LBA model cannot be explained by temporal discounting alone. Moreover, the drift rates that drive evidence accumulation in the best-fitting LBA model are related to independently estimated subjective values derived from various temporal discounting models. These findings provide a quantitative framework for predicting dynamics of choice-related activity during the reward selection process in intertemporal choice and link intertemporal choice to other classes of decisions in which the LBA model has been applied.

The need to test a growing number of theories in cognitive science has led to increased interest in inferential methods that integrate multiple data modalities. In this manuscript, we show how a method for integrating three data modalities within a single framework provides (1) more detailed descriptions of cognitive processes and (2) more accurate predictions of unobserved data than less integrative methods. Specifically, we show how combining either EEG and fMRI with a behavioral model can perform substantially better than a behavioral-data-only model in both generative and predictive modeling analyses. We then show how a trivariate model - a model including EEG, fMRI, and behavioral data - outperforms bivariate models in both generative and predictive modeling analyses. Together, these results suggest that within an appropriate modeling framework, more data can be used to better constrain cognitive theory, and to generate more accurate predictions for behavioral and neural data.

Intertemporal choice requires a dynamic interaction between valuation and deliberation processes. While evidence identifying candidate brain areas for each of these processes is well established, the precise mechanistic role carried out by each brain region is still debated. In this article, we present a computational model that clarifies the unique contribution of frontoparietal cortex regions to intertemporal decision making. The model we develop samples reward and delay information stochastically on a moment-by-moment basis. As preference for the choice alternatives evolves, dynamic inhibitory processes are executed by way of asymmetric lateral inhibition. We find that it is these lateral inhibition processes that best explain the contribution of frontoparietal regions to intertemporal decision making exhibited in our data.