Abstract
Theories of predictive processing propose that prediction error responses are modulated by precision. While there is some evidence for this phenomenon in the visual and, to some extent, the auditory domain, little is known about whether and how it happens in the complex auditory contexts of daily life. Here, we looked at the precision-weighting of prediction error in a common, structurally rich and more ecologically valid context such as music. We created musical tone sequences with different degrees of entropy to manipulate the precision of participants’ auditory expectations. Magnetoencephalography (MEG) was used to measure the magnetic counterpart of the mismatch negativity (MMNm) as a neural marker of prediction error in a multi-feature paradigm. Pitch, slide, intensity, and timbre deviants were included. We compared high-entropy stimuli, consisting of a set of non-repetitive melodies, with low-entropy stimuli consisting of a simpler and more predictable pitch pattern. Entropy was estimated with an information-theoretic model of auditory expectation. We found a strong reduction in pitch and slide MMNm amplitudes in the high-entropy as compared to the low-entropy context. No significant differences were found for intensity and timbre MMNm amplitudes. Furthermore, in a separate behavioral experiment investigating deviance detection, similar decreases were found for accuracy and confidence measures in response to more subtle increases in stimulus entropy. Our results indicate that precision modulates musical prediction error and suggest that this effect is specific to features that depend on the manipulated auditory dimension—pitch information, in this case. We thus provide evidence consistent with a precision-weighting mechanism in the auditory domain.