Sustained Pupil Responses Are Modulated by Predictability of Auditory Sequences

Milne, Alice E.; Zhao, Sijia; Tampakaki, Christina; Bury, Gabriela; Chait, Maria

doi:10.1523/jneurosci.2879-20.2021

Cited by 16 publications

(26 citation statements)

References 62 publications

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“…The human auditory system exhibits a remarkable sensitivity to detect and learn statistical regularities in sound ( Saffran et al, 1999 ; Skerritt-Davis and Elhilali, 2018 ). This capacity has been corroborated in statistical learning paradigms using behavioral ( Barascud et al, 2016 ; Bianco et al, 2020 ), eye-tracking ( Milne et al, 2021 ; Zhao et al, 2019 ), and neuroimaging techniques ( Barascud et al, 2016 ; Moldwin et al, 2017 ; Pesnot Lerousseau and Schön, 2021 ). Furthermore, humans have extraordinary implicit memory for auditory patterns ( Agres et al, 2018 ; Bianco et al, 2020 ).…”

Section: Discussionmentioning

confidence: 81%

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience

Kern

Heilbron

Lange

et al. 2022

eLife

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Expectations shape our experience of music. However, the internal model upon which listeners form melodic expectations is still debated. Do expectations stem from Gestalt-like principles or statistical learning? If the latter, does long-term experience play an important role, or are short-term regularities sufficient? And finally, what length of context informs contextual expectations? To answer these questions, we presented human listeners with diverse naturalistic compositions from Western classical music, while recording neural activity using MEG. We quantified note-level melodic surprise and uncertainty using various computational models of music, including a state-of-the-art transformer neural network. A time-resolved regression analysis revealed that neural activity over fronto-temporal sensors tracked melodic surprise particularly around 200 ms and 300–500 ms after note onset. This neural surprise response was dissociated from sensory-acoustic and adaptation effects. Neural surprise was best predicted by computational models that incorporated long-term statistical learning – rather than by simple, Gestalt-like principles. Yet, intriguingly, the surprise reflected primarily short-range musical contexts of less than ten notes. We present a full replication of our novel MEG results in an openly available EEG dataset. Together, these results elucidate the internal model that shapes melodic predictions during naturalistic music listening.

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Section: Discussionmentioning

confidence: 81%

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience

Kern

Heilbron

Lange

et al. 2022

eLife

View full text Add to dashboard Cite

show abstract

“…The human auditory system exhibits a remarkable sensitivity to detect and learn statistical regularities in sound (Saffran et al, 1999;Skerritt-Davis & Elhilali, 2018). This capacity has been corroborated in statistical learning paradigms using behavioural (Barascud et al, 2016;Bianco et al, 2020), eye-tracking (Milne et al, 2021;Zhao et al, 2019), and neuroimaging techniques (Barascud et al, 2016;Moldwin et al, 2017;Pesnot Lerousseau & Schön, 2021). Furthermore, humans have extraordinary implicit memory for auditory patterns (Agres et al, 2018;Bianco et al, 2020).…”

Section: Discussionmentioning

confidence: 88%

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience

Kern

Heilbron

Lange

et al. 2022

Preprint

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Expectations shape our experience of music. However, the internal model upon which listeners form melodic expectations is still debated. Do expectations stem from Gestalt-like principles or statistical learning? If the latter, does long-term experience play an important role, or are short-term regularities sufficient? And finally, what length of context informs contextual expectations? To answer these questions, we presented human listeners with diverse naturalistic compositions from Western classical music, while recording neural activity using MEG. We quantified note-level melodic surprise and uncertainty using various computational models of music, including a state-of-the-art transformer neural network. A time-resolved regression analysis revealed that neural activity over fronto-temporal areas tracked melodic surprise particularly around 200 ms and 300-500 ms after note onset. This neural surprise response was dissociated from sensory-acoustic and adaptation effects. Neural surprise was best predicted by computational models that incorporated long-term statistical learning - rather than by simple, Gestalt-like principles. Yet, intriguingly, the surprise reflected primarily short-range musical contexts of less than ten notes. We present a full replication of our novel MEG results in an openly available EEG dataset. Together, these results elucidate the internal model that shapes melodic predictions during naturalistic music listening.

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“…Borghini and Hazan (2020) replicated this interaction of findings, and further demonstrated that the effect of semantic context was indeed limited to native listeners and did not extend to nonnative listeners, suggesting a difference in real-time processing effort rather than mere differences in success after a sentence was already spoken. The impact of predictability on real-time effort extends beyond speech as well; Milne et al (2021) observed reduction of pupil dilation at the onset of coherent structure in an auditory stimulus consisting of tone pips. Each of these studies demonstrates that pupillometry can be used to interpret whether effort is engaged more rapidly or slowly across time.…”

Section: Dilations During Listeningmentioning

confidence: 99%

Time Scales and Moments of Listening Effort Revealed in Pupillometry

Winn

2023

Semin Hear

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This article offers a collection of observations that highlight the value of time course data in pupillometry and points out ways in which these observations create deeper understanding of listening effort. The main message is that listening effort should be considered on a moment-to-moment basis rather than as a singular amount. A review of various studies and the reanalysis of data reveal distinct signatures of effort before a stimulus, during a stimulus, in the moments after a stimulus, and changes over whole experimental testing sessions. Collectively these observations motivate questions that extend beyond the “amount” of effort, toward understanding how long the effort lasts, and how precisely someone can allocate effort at specific points in time or reduce effort at other times. Apparent disagreements between studies are reconsidered as informative lessons about stimulus selection and the nature of pupil dilation as a reflection of decision making rather than the difficulty of sensory encoding.

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Sustained Pupil Responses Are Modulated by Predictability of Auditory Sequences

Cited by 16 publications

References 62 publications

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience

Time Scales and Moments of Listening Effort Revealed in Pupillometry

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