Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedial prefrontal cortex/dorsal anterior cingulate (dmPFC/dACC) cortex and anterior insula (AI), along with other brain regions, are part of the decision-making circuitry. Moreover, recent evidence suggests that the neurometabolism of specific brain regions can affect decision-making. Therefore, this Thesis explores the neurobiological and metabolic underpinnings of inter-individual differences in motivated behavior in the dmPFC/dACC and AI. We combine proton magnetic resonance spectroscopy, functional magnetic resonance imaging, an effort-based decision-making task, as well as computational modeling to explore the neurobiological foundations and metabolic basis of motivation in healthy individuals. Additionally, we employ mass spectrometry coupled with liquid chromatography to measure plasma metabolite concentrations. The behavioral task is designed to computationally model and extract motivational parameters, encompassing sensitivity to reward and punishment, mental and physical effort, bias, physical fatigue, and mental facilitation Using machine learning, we underscore that a combination of three metabolites - glutamate, aspartate, and lactate - in the dmPFC/dACC, can effectively predict the amount of mental effort participants are willing to exert. Additionally, aspartate and lactate in the dmPFC/dACC emerge as primary predictors of mental effort sensitivity. These findings are specific to the dmPFC/dACC and are not replicated with metabolites in the AI. Furthermore, a similar analysis yielded borderline predictions regarding the amount of physical effort participants are willing to undertake. In our path analysis, we demonstrate that plasma lactate concentration influences dmPFC/dACC lactate level, which, in turn, negatively correlates with the extent of physical effort participants are willing to exert. This effect between dmPFC/dACC lactate concentration and motivation is mediated by the negative correlation of dmPFC/dACC lactate on the BOLD activity. A parallel path analysis is conducted using physical effort sensitivity, demonstrating that the dmPFC/dACC lactate concentration correlates positively with the perception of physical effort, an effect also mediated by the BOLD activity. Importantly, these results are specific to physical effort and dmPFC/dACC metabolism, as a similar mediation could not be obtained for mental effort or taking into consideration AI metabolites. Our approach provides a deeper understanding of the underlying connections between dmPFC/dACC activity, metabolism, and motivated behavior. In summary, this Thesis addresses a gap in the literature by examining the connection between the neurometabolism of the dmPFC/dACC, the BOLD activity in these regions, and motivated behavior. Our findings pave the way for future studies to explore the causal role of glutamate, aspartate, and lactate in physical and mental effort-based decision-making. A deeper understanding of the neurobiological foundations of motivation opens up new possibilities for targeting novel biomarkers in motivation, providing intervention opportunities to empower individuals to maximize their potential.