Biology subjects

Pesnot Lerousseau, J.

Publications and source records attributed to Pesnot Lerousseau, J..

5 recordsLinked to original sources

bioRxiv2021

The channel capacity of multilevel linguistic features constrains speech comprehension

Humans are expert at processing speech but how this feat is accomplished remains a major question in cognitive neuroscience. Capitalizing on the concept of channel capacity, we developed a unified measurement framework to investigate the respective influence of seven acoustic and linguistic features on speech comprehension, encompassing acoustic, sub-lexical, lexical and supra-lexical levels of description. We show that comprehension is independently impacted by all these features, but at varying degrees and with a clear dominance of the syllabic rate. Comparing comprehension of French words and sentences further reveals that when supra-lexical contextual information is present, the impact of all other features is dramatically reduced. Finally, we estimated the channel capacity associated with each linguistic feature and compared them with their generic distribution in natural speech. Our data point towards supra-lexical contextual information as the feature limiting the flow of natural speech. Overall, this study reveals how multilevel linguistic features constrain speech comprehension.

neuroscience↗

bioRxiv2021

Multisensory correlation computations in the human brain uncovered by a time-resolved encoding model

Neural mechanisms that arbitrate between integrating and segregating multisensory information are essential for complex scene analysis and for the resolution of the multisensory correspondence problem. However, these mechanisms and their dynamics remain largely unknown, partly because classical models of multisensory integration are static. Here, we used the Multisensory Correlation Detector, a model that provides a good explanatory power for human behavior while incorporating dynamic computations. Participants judged whether sequences of auditory and visual signals originated from the same source (causal inference) or whether one modality was leading the other (temporal order), while being recorded with magnetoencephalography. To test the match between the Multisensory Correlation Detector dynamics and the magnetoencephalographic recordings, we developed a novel dynamic encoding-model approach of electrophysiological activity, which relied on temporal response functions. First, we confirm that the Multisensory Correlation Detector explains causal inference and temporal order patterns well. Second, we found strong fits of brain activity to the two outputs of the Multisensory Correlation Detector in temporo-parietal cortices, a region with known multisensory integrative properties. Finally, we report an asymmetry in the goodness of the fits, which were more reliable during the causal inference than during the temporal order judgment task. Overall, our results suggest the plausible existence of multisensory correlation detectors in the human brain, which explain why and how causal inference is strongly driven by the temporal correlation of multisensory signals.

neuroscience↗

bioRxiv2021

Visualizing sounds: training-induced plasticity with a visual-to-auditory conversion device

Sensory substitution devices aim at restoring visual functions by converting visual information into auditory or tactile stimuli. Although these devices show promises in the range of behavioral abilities they allow, the processes underlying their use remains underspecified. In particular, while an initial debate focused on the visual versus auditory or tactile nature of sensory substitution, since over a decade, the idea that it reflects a mixture of both has emerged. In order to investigate behaviorally the extent to which visual and auditory processes are involved, participants completed a Stroop-like crossmodal interference paradigm before and after being trained with a conversion device which translates visual images into sounds. In addition, participants auditory abilities and their phenomenologies were measured. Our study revealed that, after training, when asked to identify sounds, processes shared with vision were involved, as participants performance in sound identification was influenced by the simultaneously presented visual distractors. In addition, participants performance during training and their associated phenomenology depended on their auditory abilities, revealing that processing finds its roots in the input sensory modality. Our results pave the way for improving the design and learning of these devices by taking into account inter-individual differences in auditory and visual perceptual strategies. HighlightsO_LITrained people spontaneously use processes shared with vision when hearing sounds from the device C_LIO_LIProcesses with conversion devices find roots both in vision and audition C_LIO_LITraining with a visual-to-auditory conversion device induces perceptual plasticity C_LI

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.

neuroscience↗

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.

neuroscience↗