Biology subjects

Joucla, C.

Publications and source records attributed to Joucla, C..

5 recordsLinked to original sources

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↗

bioRxiv2021

Three simple steps to improve the interpretability of EEG-SVM studies

Research in machine-learning classification of electroencephalography (EEG) data offers important perspectives for the diagnosis and prognosis of a wide variety of neurological and psychiatric conditions, but the clinical adoption of such systems remains low. We propose here that much of the difficulties translating EEG-machine learning research to the clinic result from consistent inaccuracies in their technical reporting, which severely impair the interpretability of their often-high claims of performance. Taking example from a major class of machine-learning algorithms used in EEG research, the support-vector machine (SVM), we highlight three important aspects of model development (normalization, hyperparameter optimization and cross-validation) and show that, while these 3 aspects can make or break the performance of the system, they are left entirely undocumented in a shockingly vast majority of the research literature. Providing a more systematic description of these aspects of model development constitute three simple steps to improve the interpretability of EEG-SVM research and, in fine, its clinical adoption.

neuroscience↗

bioRxiv2019

An artistic approach to neurofeedback for emotion regulation

Neurofeedback has been shown to be a promising tool for learning to regulate ones own emotions in healthy populations and in neuropsychiatric disorders. While it has been suggested that neurofeedback performance improves when sensory feedback is related to the pathology under consideration, it is still difficult to represent in real time a proper feedback representative of our emotional state. Since emotion is a central part of peoples dealings with artworks, we have initiated a collaboration between neuroscientists and artists to develop a visual representation of emotions that can be used in neurofeedback experiences. As a result of this collaboration, emotions were represented as particles, moving in a white sphere according to valence and arousal levels. In this study, several possibilities for particle control were explored: direction of particles, their concentration in a specific place, or their gravity. 107 participants evaluated these performances, either in laboratory condition or at various scientific and artistic events. At the end of the experiment, questionnaires were distributed to participants who were asked to indicate on scales ranging from 0 to 5 how artistic the different representations were and could be used as a clinical activity, whether they thought they had successfully controlled the particles during the neurofeedback exercise, and whether they had appreciated the experience. We found that influing on the direction and concentration of particles was considered the most artistic with an average score around 3/5. 47% of the participants considered the concentration of particles as artistic. In addition, although this is not the purpose of this study, we found that participants could significantly control the direction of particles during this session. These encouraging results constitute a first step before evaluating the effectiveness of our emotional neurofeedback over several sessions in healthy, then pathological populations.

neuroscience↗

bioRxiv2019

Modeling decision-making under uncertainty: a direct comparison study between human and mouse gambling data

Decision-making is a conserved evolutionary process enabling to choose one option among several alternatives, and relying on reward and cognitive control systems. The Iowa Gambling Task allows to assess human decision-making under uncertainty by presenting four cards decks with various cost-benefit probabilities. Participants seek to maximize their monetary gains by developing long-term optimal choice strategies. Animal versions have been adapted with nutritional rewards but interspecies data comparisons are still scarce. Our study directly compared physiological decision-making performances between humans and wild-type C57BL/6 mice. Human subjects fulfilled an electronic Iowa Gambling Task version while mice performed a maze-based adaptation with four arms baited in a probabilistic way. Our data show closely matching performances among species with similar patterns of choice behaviors. Moreover, both populations clustered into good, intermediate, and poor decision-making categories with similar proportions. Remarkably, mice good decision-makers behaved as humans of the same category, but slight differences among species have been evidenced for the other two subpopulations. Overall, our direct comparative study confirms the good face validity of the rodent gambling task. Extended behavioral characterization and pathological animal models should help strengthen its construct validity and disentangle determinants of decision-making in animals and humans.

neuroscience↗