Researchers have developed a method to combine brain activity data from EEG with environmental information to predict affective states. They used a dataset of 42 participants and combined it with environmental representations derived from various sources such as air quality, satellite imagery, and street maps. The study found that the multimodal model achieved higher accuracy in predicting affective states compared to using EEG alone. However, the results do not establish a causal relationship between environmental exposure and affective states. --- Why it matters: This research matters because it demonstrates the technical feasibility of combining brain activity data with environmental information to better understand human behavior and emotions. This could have implications for developing more accurate models for predicting affective states in various applications such as mental health diagnosis and personalized recommendations. Source: https://arxiv.org/abs/2608.20807