| Title | EEG-Based Neural Correlates of Trust in Human-Autonomy Interaction |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Wang, M., Hussein, A., Rojas, R. F., Shafi, K., Abbass, H. A. |
| Conference Name | 2018 IEEE Symposium Series on Computational Intelligence (SSCI) |
| Keywords | autonomous systems, brain, Brain modeling, Computational modeling, eeg, electroencephalography, electroencephalography signals, feature extraction, fourier analysis, Games, Human Behavior, human factor, human trust, human-autonomy interaction, Investment, medical signal processing, Mixed model analysis, neurophysiology, power spectrum, pubcrawl, Trust |
| Abstract | This paper aims at identifying the neural correlates of human trust in autonomous systems using electroencephalography (EEG) signals. Quantifying the relationship between trust and brain activities allows for real-time assessment of human trust in automation. This line of effort contributes to the design of trusted autonomous systems, and more generally, modeling the interaction in human-autonomy interaction. To study the correlates of trust, we use an investment game in which artificial agents with different levels of trustworthiness are employed. We collected EEG signals from 10 human subjects while they are playing the game; then computed three types of features from these signals considering the signal time-dependency, complexity and power spectrum using an autoregressive model (AR), sample entropy and Fourier analysis, respectively. Results of a mixed model analysis showed significant correlation between human trust and EEG features from certain electrodes. The frontal and the occipital area are identified as the predominant brain areas correlated with trust. |
| DOI | 10.1109/SSCI.2018.8628649 |
| Citation Key | wang_eeg-based_2018 |
EEG-Based Neural Correlates of Trust in Human-Autonomy Interaction