Fractionating auditory priors: A neural dissociation between active and passive experience of musical sounds

Abstract

Learning, attention and action play a crucial role in determining how stimulus predictions are formed, stored, and updated. Years-long experience with the specific repertoires of sounds of one or more musical styles is what characterizes professional musicians. Here we contrasted active experience with sounds, namely long-lasting motor practice, theoretical study and engaged listening to the acoustic features characterizing a musical style of choice in professional musicians with mainly passive experience of sounds in laypersons. We hypothesized that long-term active experience of sounds would influence the neural predictions of the stylistic features in professional musicians in a distinct way from the mainly passive experience of sounds in laypersons. Participants with different musical backgrounds were recruited: professional jazz and classical musicians, amateur musicians and non-musicians. They were presented with a musical multi-feature paradigm eliciting mismatch negativity (MMN), a prediction error signal to changes in six sound features for only 12 minutes of electroencephalography (EEG) and magnetoencephalography (MEG) recordings. We observed a generally larger MMN amplitudes–indicative of stronger automatic neural signals to violated priors–in jazz musicians (but not in classical musicians) as compared to non-musicians and amateurs. The specific MMN enhancements were found for spectral features (timbre, pitch, slide) and sound intensity. In participants who were not musicians, the higher preference for jazz music was associated with reduced MMN to pitch slide (a feature common in jazz music style). Our results suggest that long-lasting, active experience of a musical style is associated with accurate neural priors for the sound features of the preferred style, in contrast to passive listening.

BDNF Val66Met polymorphism as putative genetic substrate of music-induced plasticity in auditory prediction

“…Consistent with former findings about experience-dependent plasticity in musicians, we found enhanced auditory ERPs in musicians compared to non-musicians, with greater magnitude of both MMN components (Herholz and Zatorre, 2012;Kraus and Chandrasekaran, 2010;Lappe et al, 2008;Shahin et al, 2003;Vuust et al, 2011Vuust et al, , 2012bVuust et al, , 2012a. Nonetheless, since the main focus of the study was on the role played by BDNF in neuroplastic changes induced by training, and since the differences between musicians and non-musicians have been widely described by former studies (Brattico et al, 2001;Kliuchko et al, 2019b;Schlaug, 2015;Steele et al, 2013;Vuust et al, 2005;Vuust et al, 2012b) we did not focus on this detail. Instead, we mainly focused on the differences between musicians in relation to their genotype.…”

“…In accordance with our hypothesis, we observed an effect of the Val66Met polymorphism on were generally modest in size, between-group differences were consistently found within 100-200ms from the onset of the deviant stimulus, with the sole exception of rhythm, for which the difference was greatest around 300ms. Nonetheless, previous studies using the same paradigm as the one used here (Bonetti et al, 2017;Kliuchko et al, 2019b) reported a later MMN component for the rhythm deviant compared to the other musical features. Thus, it is plausible to assume that the observed modulatory effect of the polymorphism affected a subset of the physiological processes involved in MMN generation.…”

“…First, we computed the neural responses to deviants to visually inspect the quality of the data and to control the clarity of the isolated MMN and P3a peaks. Coherently with the previous literature that used the same paradigm as the one used in this study (Bonetti et al, 2017(Bonetti et al, , 2018(Bonetti et al, , 2021Kliuchko et al 2016Kliuchko et al , 2019a, we assessed that such peaks were stronger for musicians compared to non-musicians. In agreement with what reported in those studies, we observed that the clearest MMN and P3a peaks occurred for localization, slide and timbre .…”

“…The continuous learning process updating the accuracy of auditory predictions is well exemplified by professional musicians, whose auditory predictive abilities are enhanced as a result of their years-long music training (Brattico et al, 2001(Brattico et al, , 2009Herdener et al, 2010;Jäncke, 2009;Kliuchko et al, 2019a;Kraus & Chandrasekaran, 2010;Vuust et al, 2012b).…”

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

“…Crucially, deviants are more easily detected and the amplitude of the MMN becomes larger, when melodies are predictable and when the listener is a musician (Quiroga-Martinez et al, 2019a). Yet, despite the growing empirical evidence (Garrido et al, 2013; Hsu et al, 2015; Kliuchko et al, 2019; Southwell & Chait, 2018; Tervaniemi et al, 2014), little is known about the fluctuations in effective connectivity and neuronal dynamics that mediate these phenomena.…”