ESR4: UKB

Increasing predictive validity of human decisions under risk situations using fMRI measurements and mixed reality technology (WP2)

Neuroeconomics tries to improve our understanding of human decision making by combining models and theories from economics, neuroscience and psychology. Most behavioral and survey-based measures to characterize individuals show only moderate transfer into more complex, real-life decisions. The ESR will develop a broader range of fMRI based tasks on risk-taking and analyse individual differences in reactions to different levels of risk. The goal is to create (together with UPV) VR-based, more ecologically valid and domain specific risk-taking tasks and relate individual difference measures in fMRI to behaviour measured in VR-experiments and perform longitudinal (questionnaire-based) assessments of real-life risk taking behaviours.

Planned secondments: UPV (2 months) to study VR/MR technologies; NEUR (2 months) to apply technologies to neuro-business models.

Diana Shih

Biography:  

I have completed my Bachelor’s degree in psychology at St. Mary’s University, Twickenham, London, which peaked my research interest in cognitive neuroscience. I furthered my education and completed my Postgraduate degree in brain and cognition at Erasmus University Rotterdam in Rotterdam, Netherlands. Upon my graduation, I had taken a job to become a research assistant at the institute of cognitive neuroscience, National Central University of Taiwan. My main research interest currently is to explore the neural mechanisms of consumer food choices in organic food products. I have experience in fMRI, EEG, MEG, eye-tracking technology and TMS. 

Host

Secondment

MY PROJECT

Increasing predictive validity of human decisions under risk situations using fMRI measurements and mixed reality technology (WP2)

EXPECTED RESULTS

  • The ESR will provide VR-based domain-specific risk-taking tasks in relation to monetary risks, health-risks and social risks. Additionally, the ESR will show how individual heterogeneity in neurophysiological measures predict differences in behaviour and real life risk taking.