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How do we make snap decisions under pressure? How do we choose to cheat in a game?
This research line uses the possibilities of virtual reality and brain imaging to model human decision-making in difficult conditions
Can personality predict decision-making?
Uijong Ju has started a series of experiments, in which we are trying to link personality aspects to decision-making during accident situations in driving. Since it is impossible to conduct controlled experiments in real life on how people react during accident situations, we are using virtual reality to create accident situations, observing how people decide and then trying to predict their decision from a variety of personality-related measures. An initial pilot study published in IEEE VR 2016 has shown that it is possible to predict decision-making in a sudden, unexpected accident situation from aspects such as psychopathy and empathy to some degree (Ju et al., 2016).
Can personality predict decision-making across two different cultures - and to what degree does it predict self-sacrifical decisions??
This was expanded in two follow-up studies, one using two large population samples in Germany and Korea (Ju et al., 2019, where he showed that psychopathy was a significant predictor of the decision-making process), and another using a sacrificing-decision similar to the famous trolley problem (Ju et al., 2019b, in which impulsivity and psychopathy turned out to be predictive factors).
Can we decode risk-taking from EEG signatures?
Peoples' risk-taking behavior varies from timid and careful, low-risk individuals to bold and careless, high-risk individuals. Can we use EEG to predict who is who? In a study by Yiyu Chen, the balloon analogue risk task (BART) is used in an EEG experiment in order to find out potential correlates in the EEG signal that allow us to distinguish high risk-takers from low risk-takers. Specifically, we examine the feedback-related negativity components (FRN) in the EEG spectrum and ERP components as potential candidates for such a distinction. Using a sample of 17 participants, we find a reliable, larger FRN for risk avoiders as well as increased delta and theta power in several central electrode sites. These results represent the first step towards robust bio-markers of risk-taking behavior.
Can we decode the ability to remember a word during vocabulary learning from EEG data?
Uijong Ju has started a series of experiments, in which we are trying to link personality aspects to decision-making during accident situations in driving. Since it is impossible to conduct controlled experiments in real life on how people react during accident situations, we are using virtual reality to create accident situations, observing how people decide and then trying to predict their decision from a variety of personality-related measures. An initial pilot study published in IEEE VR 2016 has shown that it is possible to predict decision-making in a sudden, unexpected accident situation from aspects such as psychopathy and empathy to some degree (Ju et al., 2016).
Can we decode deceit from EEG data in a two-player game?
In another set of experiments, Yiyu Chen is looking at using EEG to investigate higher-level decision-making in a game situation. For this, we have implemented a two-person setup, in which both players’ brain activity is simultaneously measured using two synchronized EEG systems. The data for this highly challenging set of experiments is publicly available to benchmark decoding algorithms!