Biology subjects

Hansen, N. C.

Publications and source records attributed to Hansen, N. C..

7 recordsLinked to original sources

bioRxiv2021

Musicianship and melodic predictability enhance neural gain in auditory cortex during pitch deviance detection

When listening to music, pitch deviations are more salient and elicit stronger prediction error responses when the melodic context is predictable and when the listener is a musician. Yet, the neuronal dynamics and changes in synaptic efficacy underlying such effects remain unclear. Here, we employed dynamic causal modeling (DCM) to investigate whether the magnetic mismatch negativity response (MMNm)--and its modulation by context predictability and musical expertise--are associated with enhanced neural gain of auditory areas, as a plausible mechanism for encoding precision-weighted prediction errors. Using Bayesian model comparison, we asked whether models with intrinsic connections within primary auditory cortex (A1) and superior temporal gyrus (STG)--typically related to gain control--or extrinsic connections between A1 and STG--typically related to propagation of prediction and error signals--better explained magnetoencephalography (MEG) responses. We found that, compared to regular sounds, out-of-tune pitch deviations were associated with lower intrinsic (inhibitory) connectivity in A1 and STG, and lower backward (inhibitory) connectivity from STG to A1, consistent with disinhibition and enhanced neural gain in these auditory areas. More predictable melodies were associated with disinhibition in right A1, while musicianship was associated with disinhibition in left A1 and reduced connectivity from STG to left A1. These results indicate that musicianship and melodic predictability, as well as pitch deviations themselves, enhance neural gain in auditory cortex during deviance detection. Our findings are consistent with predictive processing theories suggesting that precise and informative error signals are selected by the brain for subsequent hierarchical processing. Significance statementIn complex auditory contexts, being able to identify informative signals is of paramount importance. Such is the case of music listening, where surprising sounds play a fundamental role in its perceptual, aesthetical, and emotional experience. Crucially, surprising sounds in the pitch dimension are more easily detected and generate stronger cortical responses when melodies are predictable and when the listener is a musician. Using Dynamic Causal Modelling, here we show that such effects arise from a local increase in neural gain within auditory areas, rather than from passing of prediction and error signals between brain regions. Consistent with predictive processing theories, this suggests that the enhanced precision of auditory predictive models--through melodic predictability and musical training--up-regulates the processing of informative error signals in the brain.

neuroscience↗

bioRxiv2019

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

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 (Heschls 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 Heschls gyrus and an increase in forward connections from Heschls 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.

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bioRxiv2019

Decomposing neural responses to melodic surprise in musicians and non-musicians: evidence for a hierarchy of predictions in the auditory system

Neural responses to auditory surprise are typically studied with highly unexpected, disruptive sounds. Consequently, little is known about auditory prediction in everyday contexts that are characterized by fine-grained, non-disruptive fluctuations of auditory surprise. To address this issue, we used IDyOM, a computational model of auditory expectation, to obtain continuous surprise estimates for a set of newly composed melodies. Our main goal was to assess whether the neural correlates of non-disruptive surprising sounds in a musical context are affected by musical expertise. Using magnetoencephalography (MEG), auditory responses were recorded from musicians and non-musicians while they listened to the melodies. Consistent with a previous study, the amplitude of the N1m component increased with higher levels of computationally estimated surprise. This effect, however, was not different between the two groups. Further analyses offered an explanation for this finding: Pitch interval size itself, rather than probabilistic prediction, was responsible for the modulation of the N1m, thus pointing to low-level sensory adaptation as the underlying mechanism. In turn, the formation of auditory regularities and proper probabilistic prediction were reflected in later components: the mismatch negativity (MMNm) and the P3am, respectively. Overall, our findings reveal a hierarchy of expectations in the auditory system and highlight the need to properly account for sensory adaptation in research addressing statistical learning. Highlights- In melodies, sound expectedness (modeled with IDyOM) is associated with the amplitude of the N1m. - This effect is not different between musicians and non-musicians. - Sensory adaptation related to melodic pitch intervals explains better the N1m effect. - Auditory regularities and the expectations captured by IDyOM are reflected in the MMNm and P3am. - Evidence for a hierarchy of auditory predictions during melodic listening.

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bioRxiv2019

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

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 low-uncertainty 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.

neuroscience↗

bioRxiv2019

Poorer auditory sensitivity is related to stronger visual enhancement of the human auditory mismatch negativity (MMNm)

Multisensory processing facilitates perception of our everyday environment and becomes particularly important when sensory information is degraded or close to the discrimination threshold. Here, we used magnetoencephalography and an audiovisual oddball paradigm to assess the complementary role of visual information in subtle pitch discrimination at the neural level of participants with varying levels of pitch discrimination abilities, i.e., musicians and nonmusicians. The amplitude of the auditory mismatch negativity (MMNm) served as an index of sensitivity. The gain in amplitude resulting from compatible audiovisual information was larger in participants whose MMNm amplitude was smaller in the condition deviating only in the auditory dimension, in accordance with the multisensory principle of inverse effectiveness. These findings show that discrimination of even a sensory-specific feature as pitch is facilitated by multisensory information at a pre-attentive level, and they highlight the importance of considering inter-individual differences in uni-sensory abilities when assessing multisensory processing.

neuroscience↗

bioRxiv2019

Domain-relevant auditory expertise modulates the additivity of neural mismatch responses in humans

It is unknown whether domain-relevant expertise is associated with more independent or more dependent predictive processing of acoustic features. Here, mismatch negativity (MMNm) was recorded with magnetoencephalography (MEG) from 25 musicians and 25 non-musicians, exposed to complex musical multi-feature and simple oddball control paradigms. Deviants differed in frequency (F), intensity (I), perceived location (L), or any combination of these (FI, IL, LF, FIL). Neural processing overlap was assessed through MMNm additivity by comparing double- and triple-deviant MMNms ("empirical") to summed constituent single-deviant MMNms ("modelled"). Significantly greater subadditivity was present in musicians compared to non-musicians, specifically for frequency-related deviants in complex contexts. Despite using identical sounds, expertise effects were absent from the simple paradigm. This novel finding supports the dependent processing hypothesis whereby experts recruit overlapping neural resources facilitating more integrative representations of domain-relevant stimuli. Such specialized predictive processing may enable experts such as musicians to capitalise on complex acoustic cues.

neuroscience↗

bioRxiv2018

Precision weighting of musical prediction error: converging neurophysiological and behavioral evidence

Theories 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.\n\nHighlightsO_LIThe mismatch negativity (MMNm) is reduced in musical contexts with high pitch uncertainty\nC_LIO_LIThe MMNm reduction is restricted to pitch-related features\nC_LIO_LIAccuracy during deviance detection is reduced in contexts with higher uncertainty\nC_LIO_LIThe results suggest a feature-selective precision modulation of prediction error\nC_LI\n\nMaterials, data and scripts can be found in the Open Science Framework repository: http://bit.ly/music_entropy_MMN\n\nDOI: 10.17605/OSF.IO/MY6TE

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