Neuroeconomics combines classical economics and neuroscience to deepen our understanding about the role played by human brain in economic decision-making. Several theoretical models have recognized that decisions made by individuals are widely affected by three factors: the characteristics of the decision, circumstantial-situational factors, and individual differences. Mixed Reality Interfaces (MRET) makes it possible to simulate an environment with better ecological validity and control than previously possible for brain research. The ESR will make use measures of subconscious brain processes through the use of mixed reality technologies (MRET) and advanced biometric signals processing (EEG, fNIRS, GSR, HV, ET, Voice Analysis and Body Postures) to improve the knowledge that contextual factors have in human decision-making. The adopted methodology is two-fold. On one hand, It will evaluate the influence that contextual information has on decision making modulating different perceptual channels (vision, sound, and odor) in virtual environments. On the other hand,  it will analyze how different elements present only in “artificial” realities, like navigation and interaction metaphors, will influence decision making. Finally, it will compare virtual immersive reality interfaces vs mixed reality interfaces by designing and conducting experiments in healthy subjects.

Planned secondments: UPISA (2 months) to study the application of machine learning techniques to psychophysiological signals; AMS (2 months) to study fNIRS technologies and UVEG (2 months) to study consumer behaviour models.