• The mismatch negativity (MMNm) is reduced in musical contexts with high pitch uncertainty • The MMNm reduction is restricted to pitch-related features • Accuracy during deviance detection is reduced in contexts with higher uncertainty • The results suggest a feature-selective precision modulation of prediction error Materials, data and scripts can be found in the Open Science Framework repository: http://bit.ly/music_entropy_MMN
This paper introduces active listening, as a unified framework for synthesising and recognising speech. The notion of active listening inherits from active inference, which considers perception and action under one universal imperative: to maximise the evidence for our (generative) models of the world. First, we describe a generative model of spoken words that simulates (i) how discrete lexical, prosodic, and speaker attributes give rise to continuous acoustic signals; and conversely (ii) how continuous acoustic signals are recognised as words. The ‘active’ aspect involves (covertly) segmenting spoken sentences and borrows ideas from active vision. It casts speech segmentation as the selection of internal actions, corresponding to the placement of word boundaries. Practically, word boundaries are selected that maximise the evidence for an internal model of how individual words are generated. We establish face validity by simulating speech recognition and showing how the inferred content of a sentence depends on prior beliefs and background noise. Finally, we consider predictive validity by associating neuronal or physiological responses, such as the mismatch negativity and P300, with belief updating under active listening, which is greatest in the absence of accurate prior beliefs about what will be heard next.
Auditory prediction error responses elicited by surprising sounds can be reliably recorded with musical stimuli that are more complex and realistic than those typically employed in EEG or MEG oddball paradigms. However, these responses are reduced as the predictive uncertainty of the stimuli increases. In this study, we investigate whether this effect is modulated by musical expertise. Magnetic mismatch negativity (MMNm) responses were recorded from 26 musicians and 24 non‐musicians while they listened to low‐ and high‐uncertainty melodic sequences in a musical multi‐feature paradigm that included pitch, slide, intensity and timbre deviants. When compared to non‐musicians, musically trained participants had significantly larger pitch and slide MMNm responses. However, both groups showed comparable reductions in pitch and slide MMNm amplitudes in the high‐uncertainty condition compared with the low‐uncertainty condition. In a separate, behavioural deviance detection experiment, musicians were more accurate and confident about their responses than non‐musicians, but deviance detection in both groups was similarly affected by the uncertainty of the melodies. In both experiments, the interaction between uncertainty and expertise was not significant, suggesting that the effect is comparable in both groups. Consequently, our results replicate the modulatory effect of predictive uncertainty on prediction error; show that it is present across different types of listeners; and suggest that expertise‐related and stimulus‐driven modulations of predictive precision are dissociable and independent.
Highlights:• The mismatch negativity (MMNm) is reduced in musical contexts with high pitch uncertainty • The MMNm reduction is restricted to pitch-related features • Accuracy during deviance detection is reduced in contexts with higher uncertainty • The results suggest a feature-selective precision modulation of prediction error Materials, data and scripts can be found in the Open Science Framework repository: AbstractTheories of predictive processing propose that prediction error responses are modulated by the certainty of the predictive model or precision. While there is some evidence for this phenomenon in the visual and, to a lesser extent, the auditory modality, little is known about whether it operates in the complex auditory contexts of daily life. Here, we examined how prediction error responses behave in a more complex and ecologically valid auditory context than those typically studied. We created musical tone sequences with different degrees of pitch uncertainty to manipulate the precision of participants' auditory expectations. Magnetoencephalography 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 simple, repetitive pitch pattern. Pitch entropy was quantitatively assessed with an information-theoretic model of auditory expectation. We found a 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 the detection of pitch deviants, similar decreases were found for accuracy measures in response to more fine-grained increases in pitch entropy. Our results are consistent with a precision modulation of auditory prediction error in a musical context, and suggest that this effect is specific to features that depend on the manipulated dimension-pitch information, in this case.
In typical listeners, the perceptual salience of a surprising auditory event depends on the uncertainty of its context. For example, in melodies, pitch deviants are more easily detected and generate larger neural responses when the context is highly predictable than when it is less so. However, it is not known whether amusic listeners with abnormal pitch processing are sensitive to the degree of uncertainty of pitch sequences and, if so, whether they are to a different extent than typical listeners. To answer this question, we manipulated the uncertainty of short melodies while participants with and without congenital amusia underwent EEG recordings in a passive listening task. Uncertainty was manipulated by presenting melodies with different levels of complexity and familiarity, under the assumption that simpler and more familiar patterns would enhance pitch predictability. We recorded mismatch negativity (MMN) responses to pitch, intensity, timbre, location, and rhythm deviants as a measure of auditory surprise. We found reduced MMN amplitudes and longer peak latencies for all sound features with increasing levels of complexity, and putative familiarity effects only for intensity deviants. No significant group-by-complexity or group-byfamiliarity interactions were detected. However, in amusics, pitch MMN responses peaked later and were disrupted in high complexity and unfamiliar melodies. Our results indicate that amusics are sensitive to the uncertainty of melodic sequences and hint at pitch-specific impairments in this population when uncertainty is high. As previous research has linked amusia with abnormal frontotemporal connectivity, our findings potentially suggest that processing pitch under high uncertainty conditions requires an intact frontotemporal loop.
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