Biology subjects

Arnal, L. H.

Publications and source records attributed to Arnal, L. H..

7 recordsLinked to original sources

bioRxiv2024

Multi-stream predictions in human auditory cortex during natural music listening

Musical expectations shape how we perceive and process music, yet current computational models are limited to monophonic or simplified stimuli. The study of the neural processes underlying musical expectations in real-world music therefore requires significant advances in our statistical modeling of these stimuli. We present PolyRNN, a recurrent neural network designed to model expectations in naturalistic, polyphonic music. We recorded neurophysiological activity non invasively (MEG) and within the human brain (intracranial EEG) while participants listened to naturally expressive piano recordings. The musical expectations estimated by the model are encoded in evoked P2- and P3-like components in auditory regions. Comparing PolyRNN to a state-of-the-art generative music model, we show that piano roll representations are best suited to represent expectations in polyphonic contexts. Overall, our approach provides a new way to capture the musical expectations emerging from natural music listening, and enables the study of predictive processes in more ecologically valid settings.

neuroscience↗

bioRxiv2023

Predictable sequential structure enhances auditory sensitivity in clinical audiograms

Human hearing is highly sensitive and allows us to detect acoustic events at low levels. However, sensitivity is not only a function of the integrity of cochlear transduction mechanisms, but also constrained by central processes such as attention and expectation. While the effects of distraction and attentional orienting are generally acknowledged, the extent to which probabilistic expectations influence sensitivity at threshold is not clear. Classical audiometric tests, commonly used to assess hearing thresholds, do not distinguish between bottom-up sensitivity and top-down processes. In this study, we aim to decipher the influence of various types of expectations on hearing thresholds and how this information can be used to improve the assessment of hearing sensitivity. Our results raise important questions regarding the conventional assessment of hearing thresholds, both in fundamental research and in audiological clinical assessment.

animal behavior and cognition↗

bioRxiv2022

Adaptive oscillators provide a hard-coded Bayesian mechanism for rhythmic inference

Bayesian theories of perception suggest that the human brain internalizes a model of environmental patterns to reduce sensory noise and improve stimulus processing. The internalization of external regularities is particularly manifest in the time domain: humans excel at predictively synchronizing their behavior with external rhythms, as in dance or music performance. The neural processes underlying rhythmic inferences are debated: whether predictive perception relies on high-level generative models or whether it can readily be implemented locally by hard-coded intrinsic oscillators synchronizing to rhythmic input remains unclear. Here, we propose that these seemingly antagonistic accounts can be conceptually reconciled. In this view, neural oscillators may constitute hard-coded physiological priors - in a Bayesian sense - that reduce temporal uncertainty and facilitate the predictive processing of noisy rhythms. To test this, we asked human participants to track pseudo-rhythmic tone sequences and assess whether the final tone was early or late. Using a Bayesian model, we account for various aspects of participants performance and demonstrate that the classical distinction between absolute and relative mechanisms can be unified under this framework. Next, using a dynamical systems perspective, we successfully model this behavior using an adaptive frequency oscillator which adjusts its spontaneous frequency based on the rate of stimuli. This model better reflects human behavior than a canonical nonlinear oscillator and a predictive ramping model, both widely used for temporal estimation and prediction. Our findings suggest that an oscillator may be considered useful as a potential heuristic for a rhythmic prior in the Bayesian sense. Together, the results show that adaptive oscillators provide an elegant and biologically plausible means to subserve (bayesian) rhythmic inference, thereby reconciling numerous empirical observations and a priori incompatible frameworks for temporal inferential processes.

neuroscience↗

bioRxiv2022

Salient 40 Hz sounds probe affective aversion and neural excitability

The human auditory system is not equally reactive to all frequencies of the audible spectrum. Emotional and behavioral reactions to loud or aversive acoustic features can vary from one individual to another, to the point that some exhibit exaggerated or even pathological responses to certain sounds. The neural mechanisms underlying these interindividual differences remain unclear. Whether distinct aversion profiles map onto neural excitability at the individual level needs to be tested. Here, we measured behavioral and EEG responses to click trains (from 10 to 250 Hz, spanning the roughness and pitch perceptual ranges) to test the hypothesis that interindividual variability in aversion to rough sounds is reflected in neural response differences between participants. Linking subjective aversion to 40 Hz steady-state EEG responses, we demonstrate that participants experiencing enhanced aversion to roughness also show stronger neural responses to this attribute. Interestingly, this pattern also correlates with inter-individual anxiety levels, suggesting that this personality trait might interact with subjective sensitivity and neural excitability to these sounds. These results support the idea that 40 Hz sounds can probe the excitability of non-canonical auditory systems involved in exogenous salience processing and aversive responses at the individual level. By linking subjective aversion to neural excitability, 40 Hz sounds provide neuromarkers relevant to a variety of pathological conditions, such as those featuring enhanced emotional sensitivity (hyperacusis, anxiety) or aberrant neural responses at 40 Hz (autism, schizophrenia).

neuroscience↗

bioRxiv2021

Imagined speech can be decoded from low- and cross-frequency features in perceptual space

Reconstructing intended speech from neural activity using brain-computer interfaces (BCIs) holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech have met limited success, mainly because the associated neural signals are weak and variable hence difficult to decode by learning algorithms. Using three electrocorticography datasets totalizing 1444 electrodes from 13 patients who performed overt and imagined speech production tasks, and based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future BCIs, and assessed their performance to discriminate speech items in articulatory, phonetic, vocalic, and semantic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to successful imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings demonstrate that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding, and that exploring perceptual spaces offers a promising avenue for future imagined speech BCIs.

neuroscience↗

bioRxiv2020

Premature commitment to uncertain beliefs during human NMDA receptor hypofunction

In uncertain environments, accurate decision-making requires integrating ambiguous or conflicting signals - a cognitive inference process thought to require n-methyl-d-aspartate (NMDA) synaptic receptors. Here we characterized the causal impact of human NMDA receptor hypofunction on cognitive inference using placebo-controlled infusions of ketamine in a visual cue combination task. Participants tested under ketamine showed elevated uncertainty, together with impaired cognitive inference despite intact visual processing. This behavioral effect of ketamine was associated in patterns of electrical brain activity with degraded and unbalanced coding of presented cues in associative cortex, followed by premature response preparation in motor cortex. Through quantitative simulations, we propose that these cognitive alterations reflect an urge to explain away the elevated uncertainty triggered by ketamine. This compensatory mechanism may cause the emergence of psychotic symptoms observed under chronic NMDA receptor dysfunction, but also forge unusually strong beliefs when confronted with uncertainty in everyday life.

neuroscience↗

bioRxiv2020

Selective enhancement of low-gamma activity by tACS improves phonemic processing and reading accuracy in dyslexia

The phonological deficit in dyslexia is associated with altered low-gamma oscillatory function in left auditory cortex, but a causal relationship between oscillatory function and phonemic processing has never been established. After confirming a deficit at 30 Hz with electroencephalography (EEG), we applied 20 minutes of transcranial alternating current stimulation (tACS) to transiently restore this activity in adults with dyslexia. The intervention significantly improved phonological processing and reading accuracy as measured immediately after tACS. The effect was selective to 30 Hz stimulation, and proportional to dyslexia severity. Importantly, we observed that the focal intervention on the left auditory cortex also decreased 30 Hz activity in the right superior temporal cortex, resulting in reinstating a left dominance for the oscillatory response, as present in controls. These findings formally establish a causal role of neural oscillations in phonological processing, and offer solid neurophysiological grounds for a potential correction of low-gamma anomalies, and for alleviating of the phonological deficit in dyslexia.

neuroscience↗