A chill brain-music interface for enhancing music chills with personalized playlists

Music chills are physical sensations, such as goosebumps, linked to intense pleasure and engage the brain's reward system. However, individual differences in music preferences and neural responses make it difficult to enhance these experiences consistently. To address this issue, we developed the chill brain-music interface (C-BMI), a neurofeedback system that uses an in-ear electroencephalogram (EEG) to create personalized playlists. For each participant, we built two regression models: one predicting pleasure from acoustic features, and another decoding pleasure from EEG data. Using these models, four playlists were generated: two designed to enhance pleasure and two to reduce it. In each pair, one playlist incorporated real-time EEG-based updates, whereas the other relied solely on acoustic features. The EEG-updated pleasure-enhancing playlist elicited more subjective chills and higher pleasure ratings than the pleasure-reducing playlists, suggesting that adapting music selection to individual neural activities can amplify chills and emotional engagement with music.