Marketing Area, INSEAD, F-77300 Fontainebleau, France
Control-Interoception-Attention Team, Paris Brain Institute (ICM), INSERM U1127, CNRS UMR7225, Sorbonne University, 75013 Paris, France.
J Neurosci. 2023 Mar 1;43(9):1600-1613. doi: 10.1523/JNEUROSCI.1343-22.2022. Epub 2023 Jan 19.
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.
个体在延迟折扣方面的差异——即我们对即时奖励与未来奖励的偏好程度差异——与一般生活结果、精神病理学和肥胖有关。在这里，我们使用功能磁共振成像（fMRI）活动在跨时间选择任务中的机器学习，为人类成年人的这些个体差异开发一种功能性大脑标记物。在一个数据集（研究 1，= 110 名男性成年人）中训练和交叉验证标记物导致了显著的预测结果相关性（= 0.49），并推广到预测另一个完全独立数据集（研究 2：= 145 名男性和女性成年人，= 0.45）的个体差异，并且预测了数周后的折扣。在两个研究中，功能大脑标记物的样本外反应（而不是折扣行为本身）在超重和正常体重个体之间有显著差异，并且预测了研究 1 中空腹状态下胰岛素、C 肽和瘦素的水平。在扣带、脑岛和额顶叶等区域发现了标记物的显著预测权重，这表明与估值、冲突处理和认知控制相关的区域之间存在相互作用。这种新的功能性大脑标记物是朝着延迟折扣个体差异的可推广大脑模型迈出的一步。未来的研究可以评估它作为不同临床和发展人群改变决策的潜在跨诊断标记物。人们在更喜欢较小的即时奖励还是更大的延迟奖励方面存在很大差异，例如现在花钱与为退休存钱。这些个体差异在时间上通常是稳定的，并且与精神和身体健康的差异有关。它们的神经生物学基础是什么？我们应用机器学习对大脑成像数据进行分析，以识别一种新的大脑活动模式，该模式可以准确预测人们更喜欢即时奖励还是延迟奖励，并且可以作为未来研究中跨时间决策的新的基于大脑的测量方法。由此产生的功能性大脑标记物还可以预测超重和与代谢相关的血液标志物，为代谢与涉及跨时间决策的认知和大脑过程之间的可能联系提供了新的见解。
