This literature review examines the intricate relationship between music prediction and its emotional influence on depression. Drawing on theoretical frameworks such as predictive coding and empirical evidence from neuroimaging, psychophysiological studies, and clinical trials, the review explores how the brain's anticipation and processing of musical cues evoke emotional responses. Foundational work and recent advances underscore the role of hierarchical predictive networks in modulating emotional experiences during music listening. In healthy individuals, the balance between predictability and surprise—especially as influenced by rhythmic complexity and cultural learning—creates a rich palette of emotional reactions. In contrast, individuals with depression often exhibit distorted predictive processes, characterized by overly rigid and negatively biased expectations, which may reinforce depressive cognitions and emotional dysregulation. Music-based interventions, as evidenced by systematic reviews, have shown promise in alleviating depressive symptoms by engaging both psychological and physiological pathways. However, gaps remain—particularly regarding the impact of violated musical predictions on emotional processing in depression. Future research integrating neuroimaging and psychophysiological measures is essential to better understand these mechanisms and to optimize music-based therapeutic strategies. This review thus highlights both the potential and current limitations of leveraging music’s predictive properties for improving mental health outcomes in depression.
Research Article
Open Access