We present a publicly available dataset of 227 healthy participants comprising a young (N=153, 25.1±3.1 years, range 20–35 years, 45 female) and an elderly group (N=74, 67.6±4.7 years, range 59–77 years, 37 female) acquired cross-sectionally in Leipzig, Germany, between 2013 and 2015 to study mind-body-emotion interactions. During a two-day assessment, participants completed MRI at 3 Tesla (resting-state fMRI, quantitative T1 (MP2RAGE), T2-weighted, FLAIR, SWI/QSM, DWI) and a 62-channel EEG experiment at rest. During task-free resting-state fMRI, cardiovascular measures (blood pressure, heart rate, pulse, respiration) were continuously acquired. Anthropometrics, blood samples, and urine drug tests were obtained. Psychiatric symptoms were identified with Standardized Clinical Interview for DSM IV (SCID-I), Hamilton Depression Scale, and Borderline Symptoms List. Psychological assessment comprised 6 cognitive tests as well as 21 questionnaires related to emotional behavior, personality traits and tendencies, eating behavior, and addictive behavior. We provide information on study design, methods, and details of the data. This dataset is part of the larger MPI Leipzig Mind-Brain-Body database.

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We investigated whether greed would predict risky decision-making and recorded neural responses during a monetary gambling task using the electroencephalogram. We found that individuals high in trait-greed took higher risks to maximize monetary outcome. Furthermore, this relation was moderated by state-greed; specifically, trait-greed had a stronger impact on risky decision-making when activated by situational characteristics. On the neural level, greedy individuals showed a specific response to favorable and unfavorable outcomes. Specifically, they had a reduced feedback-related negativity-difference score to these events, indicating that they might have difficulty in learning from experience, especially from mistakes and negative feedback. It is concluded that greed may explain risky and reckless behavior in diverse settings, such as investment banking, and may account for phenomena such as stock market bubbles.