Understanding individuals' internal cognitive states during group interactions is crucial for enhancing group dynamics and communication. This study investigated internal states by analyzing physiological data—EEG, electrocardiography, and pupil size—collected from high school students during group discussions. Using a data-driven clustering method, we identified four distinct internal states, each corresponding to the different power distributions in the four frequency bands of EEG activity, heart rate variability, and pupil size. These states were not only associated with verbal behavior such as “speaking”, they were also associated with nonverbal cues such as “gazing at faces” and other body languages. We also examined the influence of environmental factors on internal states, including the presence of a facilitator and the group size. The presence of a facilitator significantly increased the probability of participants remaining in the high alpha-power state, possibly reflecting a relaxed or moderately aroused state. This study provides insights into the physiological underpinnings of group interactions, which can be leveraged to improve educational settings and other group-based activities.

Classical and recent evidence has suggested that alpha oscillations play a critical role in temporally discriminating or binding successively presented items. Challenging this view, Buergers and Noppeney [Buergers, S., & Noppeney, U. The role of alpha oscillations in temporal binding within and across the senses. Nature Human Behaviour , 6 , 732–742, 2022] found that by combining EEG, psychophysics, and signal detection theory, neither prestimulus nor resting-state alpha frequency influences perceptual sensitivity and bias in the temporal binding task. We propose the following four points that should be considered when interpreting the role of alpha oscillations, and especially their frequency, on perceptual temporal binding: (1) Multiple alpha components can be contaminated in conventional EEG analysis; (2) the effect of alpha frequency on perception will interact with alpha power; (3) prestimulus and resting-state alpha frequency can be different from poststimulus alpha frequency, which is the frequency during temporal binding and should be more directly related to temporal binding; and (4) when applying signal detection theory under the assumption of equal variance, the assumption is often incomplete and can be problematic (e.g., the magnitude relationships between individuals in parametric sensitivity may change when converted into nonparametric sensitivity). Future directions, including solutions to each of the issues, are discussed.