We suggest that music perception is an active act of listening, providing an irresistible epistemic offering. When listening to music we constantly generate plausible hypotheses about what could happen next, while actively attending to music resolves the ensuing uncertainty. Within the predictive coding framework, we present a novel formulation of precision filtering and attentional selection, which explains why some lower-level auditory, and even higher-level music-syntactic processes elicited by irregular events are relatively exempt from top-down predictive processes. We review findings providing unique evidence for the attentional selection of salient auditory features. This formulation suggests that 'listening' is a more active process than traditionally conceived in models of perception. In recent years, predictive processes have been recognized as an integral part of both perception and action [1, 2] . Predictive coding (PC) furnishes a compelling framework for understanding such processes in audition and language comprehension [3] [4] [5] [6] . According to the PC framework, backward predictions are passed down cortical hierarchies to resolve or 'explain away' prediction errors (see Glossary) at lower levels (i.e., sensory information that does not match a prediction) ( Figure 1 , Key Figure) . These prediction errors then ascend the hierarchy to evince better predictions [7] . With regard to auditory perception, the levels of this hierarchy could comprise the auditory brainstem and thalamus, primary auditory cortex, auditory association cortex, and frontal cortex. This distributed system is part of a hierarchy that ultimately subsumes other systems such as sensorimotor, visceromotor (autonomic), and memory systems. By formulating motor and autonomic reflexes as the resolution of prediction errors, one arrives at active inference; namely, an enactive generalization of PC. This generalization means that perceptual processes are not just passive and bottom-up but are constructive, where perception is actively driven by top-down processes. Thus, active inference implies that cognitive processes on the one hand (e.g., prediction, planning, action, learning, and the like), and perceptual processes on the other, are not serial or separable, but intertwined in a hierarchical cascade of prediction error reducing dynamics. Music offers a most illuminating paradigm to understand the fundaments of the predictive brain, largely because every type of music is based on predictable regularities (e.g., temporal, melodic, and, depending on the musical culture or musical tradition, harmonic, timbral, and textural structure) [8] . In contrast to an unpredictable (e.g., random) sensory stream, musical structure affords competing hypotheses or predictions about possible outcomes [9] and then dispels uncertainty by confirming a particular prediction, given a particular musical tradition or culture. We will first consider the most straightforward example of musical predictions, namely predictions of musical events in time (i.e., predictions about when musical events occur). We then turn to the conundrum that acoustically irregular events, as well as irregular harmonies, Music provides a remarkable 'epistemic offering': it continuously satisfies our need to resolve uncertainty, thereby underwriting its rewarding nature. Within the predictive coding framework, there are (first-order) predictions of perceptual content and (secondorder) predictions of the precision (i. e., confidence or certainty) that are ascribed to first-order predictions. The capacity to update beliefs about precision endows us with the ability to attend selectively to uncertainty resolving, epistemically rewarding streams of information, as exemplified in actively listening to music. We consider the evidence for 'active listening' in terms of increased rates of evidence accumulation (i.e., reduced latencies of the early right anterior negativity), when subjects are informed about impending music-syntactic violations. This enactive take on music perception fits comfortably with the notion that our predictions of music are based on how we would generate it ourselves; thereby accounting for the phenomenon of 'musical groove'.
Koelsch et al. REF proposed the Predictive Coding (PC) framework, also pointing to the involvement of transmodal neural circuits in both prediction and prediction error resolution of musical content.
Predictive Processes and the Peculiar Case of Music
Trends in cognitive sciences
Trends in cognitive sciences
Psychology Medicine