Biology subjects

Aucouturier, J.-J.

Publications and source records attributed to Aucouturier, J.-J..

10 recordsLinked to original sources

bioRxiv2026

Human primary auditory cortex and insula encode perceptual decisions, not stimulus features

The traditional view of perceptual decision-making assumes a largely feedforward cortical hierarchy, in which sensory regions encode stimulus features that are progressively integrated with top-down signals in higher order associative areas to guide decisions. However, recent work has cast doubt on whether stimulus-and decision-related signals actually follow such a predicted spatiotemporal organization, especially in naturalistic situations where sensory cues are subtle and decisions more strongly driven by internal strategies. Leveraging the unique spatiotemporal precision of human intracerebral recordings, we map here how stimulus and decision variables are represented along the auditory cortical hierarchy as patients engage in a social voice decision task with realistic, low-salience cues. Contrary to feedforward predictions, we found no clear spatial or temporal gradient separating stimulus- and decision-related effects; rather, decision effects emerged early during stimulus exposure and, strikingly, flowed back all the way to the most primary regions of the superior temporal gyrus. In addition, the direction of these early and primary decision signals closely reflected the variability in patients specific decision criteria. Taken together, these results strongly challenge the traditional feedforward model, supporting a view in which the activity of early auditory regions does not reflect subtle stimulus categories but is instead dynamically configured by task-dependent priors and response strategies. Significant StatementThis work studies an ecological social-cognitive decision task based on subtle but natural vocal cues. Contrary to expectations, it shows that early and primary auditory activity in human intracerebral recordings does not reflect stimulus categories but instead patients decisions and decision criteria. These results are significant because they provide rare human intracerebral evidence that sensory regions are not static repositories of stimulus representations but rather dynamic, task-dependent filters that are configured by priors and decision criteria.

neuroscience↗

bioRxiv2025

Learning the bistable cortical dynamics of the sleep-onset period

Humans just dont fall asleep like a log - or step-function. Rather, the sleep-onset period (SOP) exhibits dynamic and non-monotonous changes of electroencephalogram (EEG) with high, and so far poorly understood, intra- and inter-individual variability. Computational models of the sleep regulation network have suggested that the transition to sleep can be viewed as a noisy bifurcation at a saddle point which is determined by an underlying control signal or "sleep drive". However, such models do not describe how internal control signals in the SOP can produce rapid switches between stable wake and sleep states, nor how these state-space changes are translated in the macroscopic EEG. Here, we propose a minimally-parameterized stochastic dynamical model, in which one slowly-varying control parameter drives the wake-to-sleep transition while exhibiting noise-driven bistability. We provide a procedure for estimating the parameters of the model given single observations of experimental sleep EEG data, and show that it can reproduce a wide variety of SOP phenomenology. Using the model to analyze a pre-existing sleep EEG dataset, we find that the estimated model parameters correlate with subjective sleepiness reports. These results suggest that the bistable characteristics of the SOP can serve as biomarkers for tracking intra- and inter-individual variability of sleep-onset disorders. Author summaryRecent neuroscience research has showed a growing interest in understanding the complexity of how we fall asleep. Electroencephalographic (EEG) recordings of the sleep onset period show all the hallmarks of a noise-driven bistable system, but there currently exists no computational model that can be fitted on experimental data to understand this behavior. In this paper, we propose a minimally-parameterized model, which dynamics corresponds to the motion of an noisy overdamped particle in a slowly tilting bistable landscape, as well as a way to fit it to an individuals sleep-onset EEG. We show that the fitted parameters of individual participants correlate with their subjective reports of sleepiness, suggesting that the model can capture important aspects of inter-individual variability, as well as provide potential biomarkers for sleep-onset disorders.

neuroscience↗

bioRxiv2023

The implicit influence of pitch contours and emotional timbre on P300 components in an own-name oddball paradigm

ObjectivePrevious evidence has suggested that paralinguistic features of speech stimuli may influence the characteristics of P300 components when used in clinical evaluation of consciousness. However, it remains unknown what exact acoustic components of speech are influential in such tasks, and whether they are capable of interacting with attentional deployment (as indexed by P300) in an implicit manner. MethodTo study this question, we adapted here an auditory oddball-paradigm used in clinical practice (the "own-name" paradigm), and tested whether systematic transformations of pitch contours (i.e. rising or falling intonation) and emotional timbre (i.e. smiling or rough voices) on the participants names influenced P300 responses in 24 healthy participants. ResultsP300 responses to rising pitch contours were smaller than to falling pitch contours, possibly reflecting an interference of the rising contours with participant attention in the deviant-counting task. No such difference was observed with emotional timbre variations. Conclusion and SignificanceThese results suggest that the cognitive resources involved in pitch contour processing overlap more strongly than timbre with the resources required to count own-name deviants, and that rising pitch contours should be tested prospectively as a way to increase the saliency of consciousness evaluation in unconscious patients.

neuroscience↗

bioRxiv2023

Cortical responses to looming sources are explained away by the auditory periphery

A wealth of behavioral evidence indicate that sounds with increasing intensity (i.e. appear to be looming towards the listener) are processed with increased attentional and physiological resources compared to receding sounds. However, the neurophysiological mechanism responsible for such cognitive amplification remains elusive. Here, we show that the large differences seen between cortical responses to looming and receding sounds are in fact almost entirely explained away by nonlinear encoding at the level of the auditory periphery. We collected EEG mismatch negativity (MMN) data in response to deviant stimuli with both dynamic (looming and receding) and constant level (flat) differences to the standard in the same participants. We then combined a computational model of the auditory periphery with generative EEG methods (temporal response functions, TRFs) to model the single-participant MMN responses to flat deviants, and used them to predict the effect of the same mechanism on looming and receding stimuli. The flat model explained a remarkable 45% variance of the looming response, and 33% of the receding response. This provide striking evidence that MMN responses to looming and receding sounds result from the same cortical mechanism that generate MMN to constant-level deviants: all such differences are the sole consequence of their particular physical morphology getting amplified and integrated by peripheral auditory mechanisms. Thus, not all effects seen cortically proceed from top-down modulations by high-level decision variables, but can rather be performed early and efficiently by feed-forward peripheral mechanisms that evolved precisely to sparing subsequent networks with the necessity to implement such mechanisms.

neuroscience↗

bioRxiv2020

Sound context modulates perceived vocal emotion

Many animal vocalizations contain nonlinear acoustic phenomena as a consequence of physiological arousal. In humans, nonlinear features are processed early in the auditory system, and are used to efficiently detect alarm calls and other urgent signals. Yet, high-level emotional and semantic contextual factors likely guide the perception and evaluation of roughness features in vocal sounds. Here we examined the relationship between perceived vocal arousal and auditory context. We presented listeners with nonverbal vocalizations (yells of a single vowel) at varying levels of portrayed vocal arousal, in two musical contexts (clean guitar, distorted guitar) and one non-musical context (modulated noise). As predicted, vocalizations with higher levels of portrayed vocal arousal were judged as more negative and more emotionally aroused than the same voices produced with low vocal arousal. Moreover, both the perceived valence and emotional arousal of vocalizations were significantly affected by both musical and non-musical contexts. These results show the importance of auditory context in judging emotional arousal and valence in voices and music, and suggest that nonlinear features in music are processed similarly to communicative vocal signals.

animal behavior and cognition↗

bioRxiv2019

A language-familiarity effect on the recognition of computer-transformed vocal emotional cues

People are more accurate in voice identification and emotion recognition in their native language than in other languages, a phenomenon known as the language familiarity effect (LFE). Previous work on cross-cultural inferences of emotional prosody has left it difficult to determine whether these native-language advantages arise from a true enhancement of the auditory capacity to extract socially relevant cues in familiar speech signals or, more simply, from cultural differences in how these emotions are expressed. In order to rule out such production differences, this work employed algorithmic voice transformations to create pairs of stimuli in the French and Japanese language which differed by exactly the same amount of prosodic expression. Even though the cues were strictly identical in both languages, they were better recognized when participants processed them in their native language. This advantage persisted in three types of stimulus degradation (jabberwocky, shuffled and reversed sentences). These results provide univocal evidence that production differences are not the sole drivers of LFEs in cross-cultural emotion perception, and suggest that it is the listeners lack of familiarity with the individual speech sounds of the other language, and not e.g. with their syntax or semantics, which impairs their processing of higher-level emotional cues.

neuroscience↗

bioRxiv2019

Happy you, happy me: expressive changes on a stranger’s voice recruit faster implicit processes than self-produced expressions

In social interactions, people have to pay attention both to the what and who. In particular, expressive changes heard on speech signals have to be integrated with speaker identity, differentiating e.g. self- and other-produced signals. While previous research has shown that self-related visual information processing is facilitated compared to non-self stimuli, evidence in the auditory modality remains mixed. Here, we compared electroencephalography (EEG) responses to expressive changes in sequence of self- or other-produced speech sounds, using a mismatch negativity (MMN) passive oddball paradigm. Critically, to control for speaker differences, we used programmable acoustic transformations to create voice deviants which differed from standards in exactly the same manner, making EEG responses to such deviations comparable between sequences. Our results indicate that expressive changes on a strangers voice are highly prioritized in auditory processing compared to identical changes on the self-voice. Other-voice deviants generate earlier MMN onset responses and involve stronger cortical activations in a left motor and somatosensory network suggestive of an increased recruitment of resources for less internally predictable, and therefore perhaps more socially relevant, signals.

neuroscience↗

bioRxiv2019

Influence of Vocal Feedback on Emotions Provides Causal Evidence for the Self-Perception Theory

Emotional reactions are usually accompanied by vocalizations whose acoustic features are largely impacted by the physiological state of the body. While many theoretical frameworks emphasize the role played by the perception of bodily changes in the emergence of emotional feelings, few attempts have been made to assess the impact of vocal self-perception in this process. Here, we address this question by asking participants to deliberate out loud about how they would feel in various imaginary situations while we covertly manipulate their voices in order to make them sound emotional. Perceiving these artificial expressive cues in their own voice altered participants inferences about how they would feel. Crucially, this effect of vocal self-perception on felt emotions was abolished when participants detected our manipulation either explicitly or implicitly. Beyond demonstrating that vocal self-perception plays a role in the emergence of emotions, these results provide causal evidence for self-perception theories.

neuroscience↗

bioRxiv2019

Enjoy The Violence: Is appreciation for extreme music the result of cognitive control over the threat response system?

Traditional neurobiological theories of musical emotions explain well why extreme music such as punk, hardcore or metal, whose vocal and instrumental characteristics share much similarity with acoustic threat signals, should evoke unpleasant feelings for a large proportion of listeners. Why it doesnt for metal music fans, however, remains a theoretical challenge: metal fans may differ from non-fans in how they process acoustic threat signals at the sub-cortical level, showing deactivated or reconditioned responses that differ from controls. Alternatively, it is also possible that appreciation for metal depends on the inhibition by cortical circuits of a normal low-order response to auditory threat. In a series of three experiments, we show here that, at a sensory level, metal fans actually react equally negatively, equally fast and even more accurately to cues of auditory threat in vocal and instrumental contexts than non-fans. Conversely, cognitive load somewhat appears to reduce fans appreciation of metal to the level reported by non-fans. Taken together, these results are not compatible with the idea that extreme music lovers do so because of a different low-level response to threat, but rather, highlight a critical contribution of higher-order cognition to the aesthetic experience. These results are discussed in the light of recent higher-order theories of emotional consciousness, which we argue should be generalized to the emotional experience of music across musical genres.

neuroscience↗

bioRxiv2018

CLEESE: An open-source audio-transformation toolbox for data-driven experiments in speech and music cognition

Over the past few years, the field of visual social cognition and face processing has been dramatically impacted by a series of data-driven studies employing computer-graphics tools to synthesize arbitrary meaningful facial expressions. In the auditory modality, reverse correlation is traditionally used to characterize sensory processing at the level of spectral or spectro-temporal stimulus properties, but not higher-level cognitive processing of e.g. words, sentences or music, by lack of tools able to manipulate the stimulus dimensions that are relevant for these processes. Here, we present an open-source audio-transformation toolbox, called CLEESE, able to systematically randomize the prosody/melody of existing speech and music recordings. CLEESE works by cutting recordings in small successive time segments (e.g. every successive 100 milliseconds in a spoken utterance), and applying a random parametric transformation of each segments pitch, duration or amplitude, using a new Python-language implementation of the phase-vocoder digital audio technique. We present here two applications of the tool to generate stimuli for studying intonation processing of interrogative vs declarative speech, and rhythm processing of sung melodies.

neuroscience↗