Dissociating Prediction Failure: Considerations from Music Perception

Ross, Sherman; Hansen, Niels Chr.

doi:10.1523/jneurosci.0053-16.2016

Cited by 22 publications

(21 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite these limitations, our work provides further evidence for the effect of uncertainty-or precisionon prediction error, which is consistent with an increasing number of empirical findings (Garrido et al, 2013;Hsu et al, 2015;Lumaca et al, 2019;Sedley et al, 2016;Sohoglu & Chait, 2016;Southwell & Chait, 2018), theories of predictive processing and models of music perception (Clark, 2016;Feldman & Friston, 2010;Hohwy, 2013;Ross & Hansen, 2016;Vuust et al, 2018). Furthermore, our findings confirm that MMNm responses can be reliably recorded in realistic paradigms where sounds constantly change, which constitutes a methodological improvement on existing approaches.…”

Section: Limitations and Future Directionssupporting

confidence: 88%

“…Interestingly, even though MMNm responses were reliable, their amplitudes were reduced in the HE context compared to the LE context, for pitch and slide deviants. This is consistent with predictive processing theories which propose that prediction error responses are reduced in contexts with high as compared to low uncertainty or, equivalently, low as compared to high precision (Clark, 2016;Feldman & Friston, 2010;Hohwy, 2013;Ross & Hansen, 2016;Vuust, Dietz, Witek, & Kringelbach, 2018). The ensuing precision-weighted prediction error would ensure that primarily reliable sensory signals drive learning and behavior.…”

Section: Introductionsupporting

confidence: 85%

See 1 more Smart Citation

Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians

Quiroga-Martinez¹,

Hansen

Højlund

et al. 2019

Preprint

View full text Add to dashboard Cite

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 of pitch and slide MMNm amplitudes in the high-uncertainty condition compared to the lowuncertainty condition. In a separate, behavioral 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.

show abstract

Section: Limitations and Future Directionssupporting

confidence: 88%

Section: Introductionsupporting

confidence: 85%

Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians

Quiroga-Martinez¹,

Hansen

Højlund

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Conversely, encoding of interval information requires more intensive training and long retention intervals (Dowling and Bartlett, 1981) . In the current experiment, the use of the Bohlen-Pierce scale ensures that there is no contamination of prior knowledge from earlier music life exposure (Ross and Hansen, 2016) . The fact that a tonal hierarchy is not readily available to the participants may have hindered the detection of interval changes.…”

Section: Discussionmentioning

confidence: 99%

Learning of complex auditory patterns changes intrinsic and feedforward effective connectivity between Heschl’s gyrus and planum temporale

Lumaca

Dietz

Quiroga-Martinez

et al. 2019

Preprint

View full text Add to dashboard Cite

Learning of complex auditory sequences such as language and music can be thought of as the continuous optimisation of internal predictive representations of sound-pattern regularities, driven by prediction errors. In predictive coding (PC), this occurs through changes in the intrinsic and extrinsic connectivity of the relevant cortical networks, whereby minimization of precision-weighted prediction error signals improves the accuracy of future predictions. Here, we employed Dynamic Causal Modelling (DCM) on functional magnetic resonance (fMRI) data acquired during the presentation of complex auditory patterns. In an oddball paradigm, we presented 52 volunteers (non-musicians) with isochronous 5-tone melodic patterns (standards), randomly interleaved with rare novel patterns comprising contour or pitch interval changes (deviants). Here, listeners must update their standard melodic models whenever they encounter unexpected deviant stimuli. Contour deviants induced an increased BOLD response, as compared to standards, in primary (Heschl's gyrus, HG) and secondary auditory cortices (planum temporale, PT). Within this network, we found a left-lateralized increase in feedforward connectivity from HG to PT for deviant responses and a concomitant disinhibition within left HG. Consistent with PC, our results suggest that model updating in auditory pattern perception and learning is associated with specific changes in the excitatory feedforward connections encoding prediction errors and in the intrinsic connections that encode the precision of these errors and modulate their gain. Significance statementThe learning of complex auditory stimuli such as music and speech can be thought of as the continuous optimisation of brain predictive models driven by prediction errors.Using dynamic causal modelling on fMRI data acquired during a melodic oddball paradigm, we here show that brain responses to unexpected sounds were best explained by an increase in excitation within Heschl's gyrus and an increase in forward connections from Heschl's gyrus to planum temporale. Our results are consistent with a predictive coding account of sensory learning, whereby prediction error responses to new sounds drive model adjustments via feedforward connections and intrinsic connections encode the confidence of these prediction errors.

show abstract

“…Carrus, Pearce, & Bhattacharya, 2013;Koelsch, Gunter, Friederici, & Schröger, 2000;Vuust et al, 2005). Interestingly, precision has been suggested to modulate musical prediction error and play an important role in the perceptual, aesthetic and emotional dimensions of musical experience (Hansen, Dietz, & Vuust, 2017;Ross & Hansen, 2016;Vuust, Witek, Dietz, & Kringelbach, 2018). Bringing empirical support to these claims, two behavioral studies have shown that listeners estimate the precision of musical expectations and that low-probability tones are judged as more unexpected in contexts with low as compared to high uncertainty (Hansen & Pearce, 2014;Hansen, Vuust, & Pearce, 2016).…”

Section: Introductionmentioning

confidence: 99%

Reduced prediction error responses in high- as compared to low-uncertainty musical contexts

Quiroga-Martinez

Hansen

Hoejlund

et al. 2018

Preprint

View full text Add to dashboard Cite

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.

show abstract

Dissociating Prediction Failure: Considerations from Music Perception

Cited by 22 publications

References 14 publications

Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians

Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians

Learning of complex auditory patterns changes intrinsic and feedforward effective connectivity between Heschl’s gyrus and planum temporale

Reduced prediction error responses in high- as compared to low-uncertainty musical contexts

Contact Info

Product

Resources

About