Barakat Arthur, Brochard Jules, Pessiglione Mathias, Godin Jean-Philippe, Cuenoud Bernard, Xin Lijing, Clairis Nicolas, Sandi Carmen
Laboratory of Behavioral Genetics (LGC), Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Transdisciplinary Research Areas, Life and Health, University of Bonn, Bonn, Germany.
Transl Psychiatry. 2025 Sep 29;15(1):344. doi: 10.1038/s41398-025-03554-6.
Motivation drives individuals to overcome costs to achieve desired outcomes, such as rewards or avoidance of punishment, with significant variability across individuals. The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) and anterior insula are key brain regions implicated in effort-based decision-making. Here, we utilized proton magnetic resonance spectroscopy (H-MRS) at 7 Tesla on 69 healthy participants in these brain regions to uncover the neurometabolic factors that influence these differences. We designed and applied an effort-based decision-making task requiring mental and physical effort to probe motivated behavior, complemented by computational modeling to extract key behavioral parameters. Gradient boosting machine learning was applied to explore the predictive role of specific metabolites in motivated behavior. Our results reveal that a model established on dmPFC/dACC metabolites explains decisions to exert high mental effort and sensitivity to mental effort. In particular, glutamate, aspartate, and lactate in dmPFC/dACC, three metabolites linked through the tricarboxylic acid cycle and glycolysis, were identified as key discriminative metabolites in the dmPFC/dACC, predictive of mental effort choices, underpinning energy supply and cognitive processes. Anterior insula metabolites did not significantly relate to effort-related decisions. Notably, glutamine and lactate levels between the periphery (plasma) and the dmPFC/dACC were correlated, suggesting a metabolic link between peripheral and central biomarkers of effort. Our findings provide novel insights into the neurometabolic underpinnings of motivated behavior and propose novel biomarkers for mental effort-based decision-making. Importantly, our study highlights the relevance of multivariable approaches in elucidating complex cognitive functions.
动机驱使个体克服代价以实现期望的结果，如奖励或避免惩罚，个体之间存在显著差异。背内侧前额叶皮质/背侧前扣带回皮质（dmPFC/dACC）和前岛叶是参与基于努力的决策的关键脑区。在此，我们利用7特斯拉的质子磁共振波谱（H-MRS）对69名健康参与者的这些脑区进行研究，以揭示影响这些差异的神经代谢因素。我们设计并应用了一项需要精神和体力努力的基于努力的决策任务来探究动机行为，并辅以计算建模来提取关键行为参数。应用梯度提升机器学习来探索特定代谢物在动机行为中的预测作用。我们的结果表明，基于dmPFC/dACC代谢物建立的模型能够解释做出高精神努力的决策以及对精神努力的敏感性。特别是，dmPFC/dACC中的谷氨酸、天冬氨酸和乳酸这三种通过三羧酸循环和糖酵解联系在一起的代谢物，被确定为dmPFC/dACC中的关键判别代谢物，可预测精神努力选择，支撑能量供应和认知过程。前岛叶代谢物与努力相关决策无显著关联。值得注意的是，外周（血浆）与dmPFC/dACC之间的谷氨酰胺和乳酸水平相关，表明外周和中枢努力生物标志物之间存在代谢联系。我们的研究结果为动机行为的神经代谢基础提供了新的见解，并提出了基于精神努力的决策的新生物标志物。重要的是，我们的研究强调了多变量方法在阐明复杂认知功能方面的相关性。
