Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge

Moser, Julia; Batterink, Laura; Hegner, Yiwen Li; Schleger, Franziska; Braun, Christoph; Paller, Ken A.; Preißl, Hubert

doi:10.1101/2020.07.30.228130

Cited by 6 publications

(7 citation statements)

References 68 publications

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“…Interestingly, the ITPC differences between conditions (temporally-local vs. global) emerged during the experiment in chunk-rate peaks, but not in telement-rate peaks, suggesting that rapid learning could modulate neural entrainment to auditory sequences with different regularities at the chunk-rate level. Similarly, a previous study (Moser et al, 2021) found significant differences in non-linguistic triplet-rate ITPC peaks between structured and random conditions, occurring during early exposure. This ITPC difference suggests a fine shift in sequence encoding, with different regularities from single elements to integrated chunks.…”

Section: Discussionsupporting

confidence: 69%

“What” and “when” predictions modulate auditory processing in a contextually specific manner

Cappotto

Luo

Lai

et al. 2022

Preprint

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Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli (i.e., what it is) and their timing (i.e., when it will occur), both of which are known to interactively modulate sensory processing. In real-world stimulus streams, regularities also occur contextually - e.g. predictions of individual notes vs. melodic contour in music. However, it is unknown whether the brain integrates predictions in a contextually congruent manner (e.g., if slower when predictions selectively interact with complex what predictions), and whether integrating predictions of simple vs. complex features rely on dissociable neural correlates. To address these questions, our study employed what and when violations at different levels - single tones (elements) vs. tone pairs (chunks) - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N=20) performing a repetition detection task. Our results reveal that what and when predictions interactively modulated stimulus-evoked response amplitude in a contextually congruent manner, but that these modulations were shared between contexts in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of what and when prediction selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network. Taken together, these results suggest that the brain integrates different predictions with a high degree of contextual specificity, but in a shared and distributed cortical network.

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Section: Discussionsupporting

confidence: 69%

“What” and “when” predictions modulate auditory processing in a contextually specific manner

Cappotto

Luo

Lai

et al. 2022

Preprint

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“…The processing of different auditory features is thought to be lateralized (e.g., Tervaniemi & Hugdahl, 2003): left for temporal features and right for spectral features (Zatorre & Belin, 2001), which seems to be the case also for newborns (DeCasper & Prescott, 2009). Entrainment to a structured sequence in a statistical learning task showed similar lateralization of brain activity to the current one compared to a non-structured sequence in adults with better performance (Moser et al, 2021). This brings up the possibility of an interaction between entrainment and statistical learning, as we have proposed above.…”

Section: Discussionmentioning

confidence: 92%

Beat processing in newborn infants cannot be explained by statistical learning based on transition probabilities

Háden

Bouwer

Honing

et al. 2022

Preprint

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Newborn infants have been shown to extract temporal regularities from sound sequences, both in the form of learning regular sequential properties, and extracting periodicity in the input, commonly referred to as a beat. However, these two types of regularities are often indistinguishable in isochronous sequences, as both statistical learning and beat perception can be elicited by the regular alternation of accented and unaccented sounds. Here, we manipulated the isochrony of sound sequences in order to disentangle statistical learning from beat perception in sleeping newborn infants in an EEG experiment, as previously done in adults and macaque monkeys. We used a binary accented sequence that induces a beat when presented with isochronous timing, but not when presented with randomly jittered timing. We compared mismatch responses to infrequent deviants falling on either accented or unaccented (i.e., odd and even) positions. Results showed a clear difference between metrical positions in the isochronous sequence, but not in the equivalent jittered sequence. This suggests that beat processing is present in newborns. However, the current paradigm did not show effects of statistical learning, despite previous evidence for this ability in newborns. These results show that statistical learning does not explain beat processing in newborn infants.

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“…One possibility is that in the present study the concurrent speech motor task specifically disrupted early-level auditory-motor processing of speech sounds, which impaired participants' ability to learn statistical regularities in speech streams. During processing of structured auditory streams, neural oscillations are entrained to their repeating statistical structures as well as their elements, either syllables or tones (Batterink et al, 2015b(Batterink et al, , 2019Batterink & Paller, 2017;Bogaerts et al, 2020;Doelling & Assaneo, 2021;Moser et al, 2021). The prevalent hypothesis is that neural oscillations reflect phases of high and low excitability of the neurons involved (Giraud & Poeppel, 2012;Lakatos et al, 2005;Ten Oever & Martin, 2021).…”

Section: Further Speculation and Interpretation Of The Main Findingsmentioning

confidence: 99%

“…Does the speech motor system play a domain-general role in auditory SL or does the speech motor system play a specific role in acquiring patterns and regularities from sequences of speech sounds specifically? Intriguingly, SL of patterns in tone sequences has also been shown to engage frontal motor regions in the left hemisphere (Moser et al, 2021;Farthouat et al, 2017). This has led to a proposal that the left-lateralized motor system could contribute to auditory SL in a domaingeneral manner.…”

mentioning

confidence: 99%

Specificity of Motor Contributions to Auditory Statistical Learning

Boeve,

Möttönen,

Smalle

2024

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Statistical learning is the ability to extract patterned information from continuous sensory signals. Recent evidence suggests that auditory-motor mechanisms play an important role in auditory statistical learning from speech signals. The question remains whether auditory-motor mechanisms support such learning generally or in a domain-specific manner. In Experiment 1, we tested the specificity of motor processes contributing to learning patterns from speech sequences. Participants either whispered or clapped their hands while listening to structured speech. In Experiment 2, we focused on auditory specificity, testing whether whispering equally affects learning patterns from speech and non-speech sequences. Finally, in Experiment 3, we examined whether learning patterns from speech and non-speech sequences are correlated. Whispering had a stronger effect than clapping on learning patterns from speech sequences in Experiment 1. Moreover, whispering impaired statistical learning more strongly from speech than non-speech sequences in Experiment 2. Interestingly, while participants in the non-speech tasks spontaneously synchronized their motor movements with the auditory stream more than participants in the speech tasks, the effect of the motor movements on learning was stronger in the speech domain. Finally, no correlation between speech and non-speech learning was observed. Overall, our findings support the idea that learning statistical patterns from speech versus non-speech relies on segregated mechanisms, and that the speech motor system contributes to auditory statistical learning in a highly specific manner.

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Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge

Cited by 6 publications

References 68 publications

“What” and “when” predictions modulate auditory processing in a contextually specific manner

“What” and “when” predictions modulate auditory processing in a contextually specific manner

Beat processing in newborn infants cannot be explained by statistical learning based on transition probabilities

Specificity of Motor Contributions to Auditory Statistical Learning

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