Yaqiong Xiao Lab

1. Multimodal representation of cognition: We investigate how cognitive and social information is represented and dynamically organized across neural,physiological, and behavioral systems. By integrating EEG, fNIRS, eye tracking, pupillometry, and behavioral measures, we characterize multimodal signatures of cognitive and social processes.

2. Dynamic cognition in naturalistic contexts: We use neural representation analysis, inter-subject neural synchrony, multivariate methods, and computational approaches to examine how cognitive and neural dynamics vary across individuals, contexts, and developmental stages. A particular focus is understanding the organization of cognition in naturalistic settings and its links to behavioral and developmental outcomes.

3. Adaptive neurofeedback and cognitive-state estimation: An emerging direction explores adaptive, closed-loop approaches to cognitive-state estimation and regulation. We investigate how multimodal signals, including EEG, eye movements, pupillometry, and peripheral physiological measures, can be integrated to track dynamic cognitive and affective states in real time and to guide individualized feedback. Building on multimodal approaches to characterize cognitive dynamics, this work aims to establish reliable state-estimation frameworks and ultimately develop personalized closed-loop interventions for cognitive and emotional regulation.