Apathy is highly prevalent across almost all psychiatric and neurological disorders. Even in otherwise healthy people, there is a large inter-individual variability in apathy, with some individuals exhibiting high apathy scores, though below the clinical threshold, indicative of what is known as subclinical apathy. Despite its significance, the neural underpinnings of individual differences in subclinical apathy and effort-based decision making remain elusive. In this project, we address this gap in healthy human subjects through comprehensive neuropsychological assessments of apathy, depression and anhedonia, as well as computational modeling of behavior in an effort-based decision-making task, enabling quantification of subjective effort and reward valuation in each individual. We combine these behavioral data with a multimodal quantification of brain morphometry using magnetic resonance imaging (MRI), structural connectivity using diffusion-weighted imaging (DWI) and effective connectivity using dual-site transcranial magnetic stimulation (dsTMS).