Abstract
Individual differences in delay discounting—how much we discount future compared to immediate rewards—are associated with general life outcomes, psychopathology, and obesity. Here, we use machine learning on fMRI activity during an intertemporal choice task to develop a functional brain marker of these individual differences in human adults. Training and cross-validating the marker in one data set (Study 1, N = 110 male adults) resulted in a significant prediction-outcome correlation (r = 0.49), generalized to predict individual differences in a completely independent data set (Study 2, N = 145 male and female adults, r = 0.45), and predicted discounting several weeks later. Out-of-sample responses of the functional brain marker, but not discounting behavior itself, differed significantly between overweight and lean individuals in both studies, and predicted fasting state blood levels of insulin, c-peptide, and leptin in Study 1. Significant predictive weights of the marker were found in cingulate, insula, and frontoparietal areas, among others, suggesting an interplay among regions associated with valuation, conflict processing, and cognitive control. This new functional brain marker is a step towards a generalizable brain model of individual differences in delay discounting. Future studies can evaluate it as a potential transdiagnostic marker of altered decision-making in different clinical and developmental populations.
Significance statement:
People differ substantially in how much they prefer smaller sooner or larger later rewards such as spending money now versus saving it for retirement. These individual differences are generally stable over time and have been related to differences in mental and bodily health. What is their neurobiological basis? We applied machine-learning to brain imaging data to identify a novel brain activity pattern that accurately predicts how much people prefer sooner versus later rewards, and which can be used as a new brain-based measure of intertemporal decision-making in future studies. The resulting functional brain marker also predicts overweight and metabolism-related blood markers, providing new insight into the possible links between metabolism and the cognitive and brain processes involved in intertemporal decision-making.
Footnotes
The authors declare no financial interests or conflict of interests.
We received funding from the ANR (Tremplin-ERC grant “Brain Gut Decision” to HP), Campus France (Marie-Sklodowska-Curie co-fund fellowship PRESTIGE-2018-2-0023 to LK), French federal funding (program ‘Investissements d’avenir’, ANR-10-IAIHU-06), the Federal Ministry of Education and Research Germany (Diet-Body-Brain grant 01EA1809B to BW and 01EA1707 to MCS), the National Cancer Institute (R35CA197461 [CL] and R01CA170297 [JK and CL]), and the AE Foundation (to JK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank P. Trautner for help with the programming of the task (Study 1); A. Simonetti, M. Boerth, J. Tholen, A.-A. Ortner, A. Koehlmoos, S. Winkler, L. Bernardo, A. M. Burke, M. K. Caulfield, N. Cooper, G. Donnay, M. Falcone, J. Jorgensen, R. Kazinka, J. Luery, M. McConnell, R. Miglin, D. Mukherjee, T. Parthasarathi, S. Price, M. Schlussel, R. Sharp, H. J. Sohn, D. Spence, and K. Terilli for help with data acquisition; and T. D. Wager for the Canlab toolbox and helpful discussion.