![]() ![]() This review posits that several global brain theories may be unified by the free-energy principle. The free-energy principle: a unified brain theory? Nat. Rhythmic complexity and predictive coding: a novel approach to modeling rhythm and meter perception in music. In this review, the author shows how music engages phylogenetically old reward networks in the brain to evoke emotions, and not merely subjective feelings. Brain correlates of music-evoked emotions. Action-based effects on music perception. Toward a neural basis of music perception–a review and updated model. ![]() A seminal review of auditory–motor coupling in music. When the brain plays music: auditory–motor interactions in music perception and production. ![]() These recent advances shed new light on what makes music meaningful from a neuroscientific perspective. This in turn has important implications for human creativity as evinced by music improvisation. This Review elucidates how this formulation of music perception and expertise in individuals can be extended to account for the dynamics and underlying brain mechanisms of collective music making. We show that music perception, action, emotion and learning all rest on the human brain’s fundamental capacity for prediction - as formulated by the predictive coding of music model. Here we review the cognitive neuroscience literature of music perception. This enactive aspect has led to a more comprehensive understanding of music processing involving brain structures implicated in action, emotion and learning. However, when listening to music, we actively generate predictions about what is likely to happen next. Music processing in the brain - namely, the perception of melody, harmony and rhythm - has traditionally been studied as an auditory phenomenon using passive listening paradigms. Music is ubiquitous across human cultures - as a source of affective and pleasurable experience, moving us both physically and emotionally - and learning to play music shapes both brain structure and brain function. ![]()
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