Sensation seeking and risk adjustment: the role of reward sensitivity in dynamic risky decisions.

Objective: The primary objective of our research is to delve into the relationships between sensation seeking (SS), reward sensitivity (RS), and risk adjustment (RA) within the context of dynamic risk-taking behaviors. By integrating the reinforcement learning model and neural measures obtained from dynamic risk-taking tasks, we aim to explore how these personality traits influence individual decision-making processes and engagement in risk-related activities. We aim to dissect the neural and cognitive mechanisms underlying this interplay, thereby shedding light on the stable brain-based characteristics contributing to the observed variability in risk-taking and decision-making behaviors. Understanding these links could significantly enhance our ability to predict individual differences in risk preferences and develop targeted interventions for managing risky behaviors across different contexts. Method: We developed a task to measure RA through a structured yet uncertain environment modeled after the Balloon Analog Risk Task. We enlisted 80 young adults to perform this task, and of these, 40 were subjected to electroencephalography (EEG) to assess neural correlates of RS. Subsequently, we analyzed event-related potentials and spectral perturbations to discern neural distinctions related to RS. We compared these distinctions concerning RA among participants exhibiting different levels of SS. Results: Individuals exhibiting higher levels of SS (HSS) in the study displayed a tendency to disregard past risks, potentially resulting in diminished behavioral adaptability. EEG results indicated that individuals with HSS exhibited reduced neural responses to feedback compared to those with low SS, potentially affecting their feedback processing and decision-making. Moreover, the comparison of effects underscores the significant impact of RS and SS on shaping RA during dynamic decision-making scenarios. Conclusion: This study has advanced the understanding of how SS and RS influence RA, revealing that RS prompts RA, while individuals with HSS often exhibit blunted RS, leading to worse RA. Future research should focus on the specific aspects of HSS and their implications for decision-making across different risk contexts. Employing advanced neuroimaging and cognitive modeling techniques will be pivotal in unraveling the neural mechanisms driving these individual differences in risky behavior.