Biology subjects

Schon, D.

Publications and source records attributed to Schon, D..

9 recordsLinked to original sources

bioRxiv2026

Cortical encoding of probabilistic temporal predictions during speech perception

The temporal structure of speech has traditionally been characterized by the rhythmicity of its canonical linguistic units (phonemes, syllables, words), each summarized by a mean occurrence rate. While valid, this view overlooks whether speech carries a finer, context-dependent and probabilistic temporal structure that could support temporal predictive coding during listening. Using large French and English speech corpora, we trained models of increasing complexity to predict the onsets of linguistic units. Recurrent neural networks (RNNs) outperform mean-rate and hazard-rate models, showing that the variability around these rates is not noise but a temporal structure shaped by local context, statistically predictable across phonemes, syllables and words. Recording from 7,698 intracerebral electrodes in 53 neurosurgical patients listening to natural speech, we next show that the models' output), the continuous probability of an upcoming onset (when), explains neural activity beyond acoustic and linguistic content (what) features, with markedly stronger effects for RNNs than for mean- or hazard-rate models. This dynamic neural prediction of when an onset will occur is dissociable from the encoding of linguistic content, relying on largely distinct channel populations. Temporal predictions engage a distributed cortical network extending from bilateral temporal cortex into left frontal and sensorimotor regions. Together, these results establish temporal prediction in speech as a dynamic, context-dependent and probabilistic process in its own right.

neuroscience↗

bioRxiv2024

Bridging verbal coordination and neural dynamics

AbstractOur use of language, which is profoundly social in nature, essentially takes place in interactive contexts and is shaped by precise coordination dynamics that interlocutors must observe. Thus, language interaction is highly demanding on fast adjustment of speech production. Here, we developed a real-time coupled-oscillators virtual partner that allows - by changing the coupling strength parameters - to modulate the ability to synchronise speech with a virtual speaker. Then, we recorded the intracranial brain activity of 16 patients with drug-resistant epilepsy while they performed a verbal coordination task with the virtual partner (VP). More precisely, patients had to repeat short sentences synchronously with the VP. This synchronous speech task is efficient to highlight both the dorsal and ventral language pathways. Importantly, combining time-resolved verbal coordination and neural activity shows more spatially differentiated patterns and different types of neural sensitivity along the dorsal pathway. More precisely, high-frequency activity in left secondary auditory regions is highly sensitive to verbal coordinative dynamics, while primary regions are not. Finally, while bilateral engagement was observed in the high-frequency activity of the IFG BA44--which seems to index online coordinative adjustments that are continuously required to compensate deviation from synchronisation-- interpretation of right hemisphere involvement should be approached cautiously due to relatively sparse electrode coverage. These findings illustrate the possibility and value of using a fully dynamic, adaptive and interactive language task to gather deeper understanding of the subtending neural dynamics involved in speech perception, production as well as their interaction.

neuroscience↗

bioRxiv2023

Neuronal Avalanches in Naturalistic Speech and Music Listening

Neuronal avalanches are cascade-like events ubiquitously observed across imaging modalities and scales. Aperiodic timing and topographic distribution of these events have been related to the systemic physiology of brain states. However, it is still unknown whether neuronal avalanches are correlates of cognition, or purely reflect physiological properties. In this work, we investigate this question by analyzing intracranial recordings of epileptic participants during rest and passive listening of naturalistic speech and music stimuli. During speech or music listening, but not rest, participants brains "tick" together, as the timing of neuronal avalanches is stimulus-driven and hence correlated across participants. Auditory regions are strongly participating in coordinated neuronal avalanches, but also associative regions, indicating both the specificity and distributivity of cognitive processing. The subnetworks where such processing takes place during speech and music largely overlap, especially in auditory regions, but also diverge in associative cortical sites. Finally, differential pathways of avalanche propagation across auditory and non-auditory regions differentiate brain network dynamics during speech, music and rest. Overall, these results highlight the potential of neuronal avalanches as a neural index of cognition. Authors summaryNeuronal avalanches consist of collective network events propagating across the brain in short-lived and aperiodic instances. These salient events have garnered a great interest for studying the physics of cortical dynamics, and bear potential for studying brain data also in purely neuroscientific contexts. In this work we investigated neuronal avalanches to index cognition, analyzing an intracranial stereo electroencephalography (iEEG) dataset during speech, music listening and resting state in epileptic patients. We show that neuronal avalanches are consistently driven by music and speech stimuli: avalanches co-occur in participants listening to the same auditory stimulus; avalanche topography differs from resting state, presenting partial similarities during speech and music; avalanche propagation changes during speech, music, and rest conditions, especially along the pathways between auditory and non auditory regions. Our work underlines the distributed nature of auditory stimulus processing, supporting neuronal avalanches as a valuable and computationally advantageous framework for the study of cognition in humans.

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bioRxiv2023

Perception of Speech Turn Dynamics is preserved in Congenitally Deaf children with Cochlear Implants

Perceptual and speech production abilities of children with cochlear implants (CI) are usually tested by word and sentence repetition or naming tests. However, in their daily life they show very heterogeneous language skills. Here, we describe a way of increasing the ecological validity of language assessment, promoting the use of close to real-life listening situations. The setup consists in watching the audio-visual conversation of two individuals. Childrens gaze-switches from one speaker to the other serve as a proxy of their prediction abilities. Moreover, to better understand the basis and the impact of anticipatory behaviour, we also measured childrens ability to understand the dialogue content, their speech perception and memory skills as well as their rhythmic skills. Importantly, we compared children with CI performances with those of an age-matched group of children with NH. While children with CI revealed poorer speech perception and verbal working memory abilities than NH children, there was no difference in gaze anticipatory behaviour. Interestingly, in children with CI only, we found a significant correlation between dialogue comprehension, perceptive skills and gaze anticipatory behaviour. Our results confirm and extend to a conversational context previous findings showing an absence of predictive deficits in children with CI. The current design seems an interesting avenue to provide an accurate and objective estimate of anticipatory language behaviour in a rather ecological conversational context also with young children.

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bioRxiv2023

Neural dynamics of predictive timing and motor engagement in music listening

Why do humans spontaneously dance to music? To test the hypothesis that motor dynamics reflect predictive timing during music listening, we built melodies with varying degrees of rhythmic predictability. Magnetoencephalography data showed that while auditory regions track the rhythm of melodies, intrinsic neural dynamics at delta (1.4 Hz) and beta (20-30 Hz) rates in the dorsal auditory pathway embody the experience of groove. Critically, neural dynamics are organized along this pathway in a spectral gradient, with the left sensorimotor cortex acting as a hub coordinating groove-related delta and beta activity. Combined with predictions of a neurodynamic model, this indicate that spontaneous motor engagement during music listening is a manifestation of predictive timing effected by interaction of neural dynamics along the dorsal auditory pathway. One-Sentence SummaryInteracting neural dynamics along the dorsal auditory pathway effect the experience of groove during music listening.

neuroscience↗

bioRxiv2022

Speech and music recruit frequency-specific distributed and overlapping cortical networks

To what extent does speech and music processing rely on domain-specific and domain-general neural networks? Using whole-brain intracranial EEG recordings in 18 epilepsy patients listening to natural, continuous speech or music, we investigated the presence of frequency-specific and network-level brain activity. We combined it with a statistical approach in which a clear operational distinction is made between shared, preferred, and domain-selective neural responses. We show that the majority of focal and network-level neural activity is shared between speech and music processing. Our data also reveal an absence of anatomical regional selectivity. Instead, domain-selective neural responses are restricted to distributed and frequency-specific coherent oscillations, typical of spectral fingerprints. Our work highlights the importance of considering natural stimuli and brain dynamics in their full complexity to map cognitive and brain functions.

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bioRxiv2022

Attentional inhibition ability predicts neural representation during challenging auditory streaming

Focusing on a single source within a complex auditory scene is challenging. M/EEG-based auditory attention detection allows to detect which stream, within a set of multiple concurrent streams, an individual is attending to. The high inter-individual variability in the AAD performance is most often attributed to physiological factors and signal to noise ratio of neural data. Here we address the hypothesis that cognitive factors and in particular sustained attention, WM and attentional inhibition, may also partly explain the variability in AAD performance, because they support the cognitive processes required when listening to complex auditory scenes. Here, we chose a particularly challenging auditory scene, by presenting dichotically polyphonic classical piano excerpts lasting one minute each. Two different excerpts were presented simultaneously in each ear. Forty-one participants, with different degrees of musical expertise, listened to these complex auditory scenes focussing on one ear while we recorded the EEG. Participants also completed several tasks assessing executive functions. As expected, attended stimuli were better decoded than unattended stimuli. Importantly, attentional inhibition ability did explain around 10% of the reconstruction accuracy and around 8% of the classification accuracy. No other cognitive function was a significant predictor of reconstruction or of classification accuracies. No clear effect of musical expertise was found on reconstruction and classification performances. In conclusion, cognitive factors seem to impact the robustness of the auditory representation and hence the performance of neural based decoding approaches. Taking advantage of this relation could be useful to improve next-generation hearing aids.

neuroscience↗

bioRxiv2020

Musical expertise is associated with improved neural statistical learning.

It is poorly known whether musical training leads to improvements in general cognitive abilities, such as statistical learning (SL). In standard SL paradigms, musicians have better performances than non-musicians. However, these better performances could be due to an improved ability to process sensory information, as opposed to an improved ability to learn sequence statistics. Unfortunately, these very different explanations make similar predictions on the performances averaged over multiple trials. To solve this controversy, we developed a Bayesian model and recorded electroencephalography (EEG) to study trial-by-trial responses. Our results confirm that musicians perform ~15% better than non-musicians at predicting items in auditory sequences that embed either simple or complex statistics. This higher performance is explained in the Bayesian model by parameters governing SL, as opposed to parameters governing sensory information processing. EEG recordings reveal a neural underpinning of the musicians advantage: the P300 amplitude correlates with the Bayesian model surprise elicited by each item, and so, more strongly for musicians than non-musicians. Finally, early EEG components correlate with the Bayesian model surprise elicited by simple statistics, as opposed to late EEG components that correlate with Bayesian model surprise elicited by complex statistics surprise, and so more strongly for musicians than non-musicians. Overall, our results prove that musical expertise is associated with improved neural SL, and support music-based intervention to fine tune general cognitive abilities.

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bioRxiv2019

Persistent neural entrainment in the human cortex is frequency selective

Cortical oscillations have been proposed to play a functional role in speech and music perception, attentional selection and working memory, via the mechanism of neural entrainment. One of the most compelling arguments for neural entrainment is that its modulatory effect on ongoing oscillations outlasts rhythmic stimulation. We tested the existence of this phenomenon by studying cortical neural oscillations during and after presentation of melodic stimuli in a passive perception paradigm. Melodies were composed of [~]60 and [~]80 Hz tones embedded in a 2.5 Hz stream. Using intracranial and surface recordings in humans, we reveal consistent neural response properties throughout the cortex, well beyond the auditory regions. Persistent oscillatory activity in the high-gamma band was observed in response to the tones. By contrast, in response to the 2.5 Hz stream, no persistent activity in any frequency band was observed. We further show that our data are well-captured by a model of damped harmonic oscillator and can be classified into three classes of neural dynamics, with distinct damping properties and eigenfrequencies. This model provides a mechanistic and quantitative explanation of the frequency selectivity of auditory neural entrainment in the human cortex. Significance statementIt has been proposed that the functional role of cortical oscillations is subtended by a mechanism of entrainment, the synchronisation in phase or amplitude of neural oscillations to a periodic stimulation. We tested whether the modulatory effect on ongoing oscillations outlasts the rhythmic stimulation, a phenomenon considered to be one of the most compelling arguments for entrainment. Using intracranial and surface recordings of human listening to rhythmic auditory stimuli, we reveal consistent oscillatory responses throughout the cortex, with persistent activity of high-gamma oscillations. On the contrary, neural oscillations do not outlast low-frequency acoustic dynamics. We interpret our results as reflecting harmonic oscillator properties - a model ubiquitous in physics but rarely used in neuroscience.

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