Great progress has been made in understanding how people make financial decisions. However, there is little research on how people make health and treatment choices. Our study aimed to examine how participants weigh benefits (reduction in disease progression) and probability of risk (medications’ side effects) when making hypothetical treatment decisions, and to identify the neural networks implicated in this process. Fourteen healthy participants were recruited to perform a treatment decision probability discounting task using MRI. Behavioral responses and skin conductance responses (SCRs) were measured. A whole brain analysis were performed to compare activity changes between “mild” and “severe” medications’ side effects conditions. Then, orbitofrontal cortex (OFC), ventral striatum (VS), amygdala and insula were chosen for effective connectivity analysis. Behavioral data showed that participants are more likely to refuse medication when side effects are high and efficacy is low. SCRs values were significantly higher when people made medication decisions in the severe compared to mild condition. Functionally, OFC and VS were activated in the mild condition and were associated with increased likehood of choosing to take medication (higher area under the curve “AUC” side effects/efficacy). These regions also demonstrated an increased effective connectivity when participants valued treatment benefits. By contrast, the OFC, insula and amygdala were activated in the severe condition and were associated with and increased likelihood to refuse treatment. These regions showed enhanced effective connectivity when participants were confronted with increased side effects severity. This is the first study to examine the behavioral and neural bases of medical decision making.
- % BOLD signal change
- Behavioral economic model
- fMRI treatment decision probability discounting
- Psychophysiological interaction
- Treatment decision making