Our current research directions:
1) Social cognition and affective neuroscience: the multi-modal representation of negative emotional experiences (anxiety, fear, helpless) and its neurocomputation; the learning and representation of social information (social distance, emotional variability, affiliation) and its influence on social relationship; the neurocomputation of mentalizing and social decision-making (dishonesty decisions); the effect of pharmaceutical modulation (oxytocin) and neuromodulation (TMS&TDCS) on social cognition and behaviors.
2) Computational neuroscience: we mainly leverage Bayesian modeling, Reinforcement learning, Drift-diffusion model to quantify human social learning and adaptive social decision-making.
3) Artificial intelligence (AI) and Human-AI interaction: e.g., how AI facilitates empathy and interaction between human-AI and even between human-human, how human perceive and inference the affect of AI.
We are supported by the following grants: