An fMRI-Based Brain Marker of Individual Differences in Delay Discounting.

Leonie Koban, Sangil Lee, Daniela S Schelski, Marie-Christine Simon, Caryn Lerman, Bernd Weber, Joseph W Kable, Hilke Plassmann

Journal: The Journal of neuroscience : the official journal of the Society for Neuroscience 2023;43(9):1600-1613

PMID: 36657973

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 dataset (Study 1,  = 110 male adults) resulted in a significant prediction-outcome correlation ( = 0.49), generalized to predict individual differences in a completely independent dataset (Study 2:  = 145 male and female adults,  = 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 toward 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. People differ substantially in how much they prefer smaller sooner rewards 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.

Copyright © 2023 the authors.

Address: Marketing Area, INSEAD, F-77300 Fontainebleau, France [email protected].; Control-Interoception-Attention Team, Paris Brain Institute (ICM), INSERM U1127, CNRS UMR7225, Sorbonne University, 75013 Paris, France.; CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, Université Claude Bernard Lyon 1, 69500 Bron, France.; Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6018.; Center for Economics and Neuroscience, University of Bonn, 53113 Bonn, Germany.; Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, 53113 Bonn, Germany.; Institute for Nutrition and Food Science, Nutrition and Microbiota, University of Bonn, 53113 Bonn, Germany.; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California 90033.; Marketing Area, INSEAD, F-77300 Fontainebleau, France.
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