Recent news

Jules Cauzinille

Jules Cauzinille was awarded a 2022 ILCB PhD grant to conduct a project under the supervision of Benoît Favre (LIS), in collaboration with Arnaud Rey (LPC), Thierry Legou (LPL), and Ricard Marxer (Université de Toulon). Jules obtained a bachelor’s degree in computational linguistics and a master’s degree in natural language processing at Université Paris Cité. He has a particular interest in speech and para-linguistics, and on the development of machine learning and computational models for the automatic processing of human communication. He has previously explored the annotation of affective behaviors in political speech and the automatic recognition of vocal expressiveness, under the supervision of Marc Evrard and Albert Rilliard (LISN – CNRS). In his PhD, Jules will further explore non-textual speech processing in both human and primate vocalizations. The aims are to build self-supervised acoustic representation learning models and to conduct a set of probing experiments including data-based vocal synthesis of primate soundscapes.

MIA: An open-source toolbox for Multi-patient Intracranial EEG Analysis

Intracranial EEG (iEEG) performed during the pre-surgical evaluation of refractory epilepsy provides a great opportunity to investigate the neurophysiology of human cognitive functions with exceptional spatial and temporal precisions. A difficulty of the iEEG approach for cognitive neuroscience, however, is the potential variability across patients in the anatomical location of implantations and in the functional responses that are therein recorded. In this context, we designed, implemented, and tested a user-friendly and efficient open-source toolbox for Multi-Patient Intracranial data Analysis (MIA), which can be used as standalone program or as a Brainstorm plugin.

Dubarry, A.-S., Liégeois-Chauvel, C., Trébuchon, A., Bénar, C. & Alario, F.-X. Neuroimage 257, 119251 (2022)@HAL

Bissera Ivanova

Bissera Ivanova was awarded a 2022 ILCB PhD grant to conduct a project under the supervision of Kristof Strijkers (LPL), Benjamin Morillon (INS), and Liina Pylkkänen  from New York University (NYU), to explore the spatio-temporal dynamics of syntax processing between the production and perception modalities. Bissera studied in the UK, completing a BA in Linguistics and a MSc in Cogntive Science, and working as a research assistant on a project on the development of pragmatic skills in children. Bissera then came to Aix-Marseille to work with Dr Strijkers on the neural dynamics of single word processing. Of course, language exists in its naturalistic environment as words interwoven in complex structures. Bissera was thus very interested in exploring the neural dynamics supporting syntactic structure processing. It is fantastic that Prof Pylkkänen has joined the supervisor’s team, as she is an leading expert on the dynamics of syntax and semantics processing.

Does auditory deprivation impair statistical learning in the auditory modality?

Jacques Pesnot Lerousseau, Céline Hidalgo, Stéphane Roman, & Daniele Schön

Early sensory deprivation allows assessing the extent of reorganisation of cognitive functions, well beyond sensory processing. As such, it is a good model to explore the links between sensory experience and cognitive functions. One of these functions, statistical learning – the ability to extract and use regularities present in the environment – is suspected to be impaired in prelingually deaf children with a cochlear implant. However, empirical evidence supporting this claim is very scarce and studies have reported contradictory results. This might be because previous studies have tested statistical learning only in the visual modality and did not make clear distinctions between multiple types of statistical regularities. To overcome these problems, we designed a modified serial reaction time task where cochlear implanted children and normal hearing children had to react to auditory sequences that embed multiple statistical regularities, namely transition probabilities of 0th, 1st or 2nd order. We compared the reaction times of the children with the output of a simple computational model that learns transition probabilities. First, 6–12 years old children were able to learn 0th and 1st order transition probabilities but not 2nd order ones. Second, there were no differences between cochlear implanted children and their normal hearing peers. These results indicate that auditory statistical learning is preserved in congenitally deaf children with cochlear implants. This suggests in turn that early auditory deprivation might not be crucially detrimental for the normal development of statistical learning.

The Role of Motor Inhibition During Covert Speech Production

Ladislas Nalborczyk, Ursula Debarnot, Marieke Longcamp, Aymeric Guillot, & F.-Xavier Alario

Front. Hum. Neurosci. 16:804832@HAL

Covert speech is accompanied by a subjective multisensory experience with auditory and kinaesthetic components. An influential hypothesis states that these sensory percepts result from a simulation of the corresponding motor action that relies on the same internal models recruited for the control of overt speech. This simulationist view raises the question of how it is possible to imagine speech without executing it. In this perspective, we discuss the possible role(s) played by motor inhibition during covert speech production. We suggest that considering covert speech as an inhibited form of overt speech maps naturally to the purported progressive internalization of overt speech during childhood. We further argue that the role of motor inhibition may differ widely across different forms of covert speech (e.g., condensed vs. expanded covert speech) and that considering this variety helps reconciling seemingly contradictory findings from the neuroimaging literature.

Challenges and new perspectives of developmental cognitive EEG studies

Estelle Hervé, Giovanni Mento, Béatrice Desnous, & Clément François

Despite shared procedures with adults, electroencephalography (EEG) in early development presents many specificities that need to be considered for good quality data collection. In this paper, we provide an overview of the most representative early cognitive developmental EEG studies focusing on the specificities of this neuroimaging technique in young participants, such as attrition and artifacts. We also summarize the most representative results in developmental EEG research obtained in the time and time-frequency domains and use more advanced signal processing methods. Finally, we briefly introduce three recent standardized pipelines that will help promote replicability and comparability across experiments and ages. While this paper does not claim to be exhaustive, it aims to give a sufficiently large overview of the challenges and solutions available to conduct robust cognitive developmental EEG studies.

When words collide: Bayesian meta-analyses of distractor and target properties in the picture-word interference paradigm

Audrey Bürki-Foschini, F.-Xavier Alario, & Shravan Vasishth

In the picture-word interference paradigm, participants name pictures while ignoring a written or spoken distractor word. Naming times to the pictures are slowed down by the presence of the distractor word. The present study investigates in detail the impact of distractor and target word properties on picture naming times, building on the seminal study by Miozzo and Caramazza (2003) “When more is less: A counterintuitive effect of distractor frequency in the picture-word interference paradigm. Journal of Experimental Psychology. General.” We report the results of several Bayesian meta-analyses, based on 26 datasets. These analyses provide estimates of effect sizes and their precision for several variables and their interactions. They show the reliability of the distractor frequency effect on picture naming latencies (latencies decrease as the frequency of the distractor increases) and demonstrate for the first time the impact of distractor length, with longer naming latencies for trials with longer distractors. Moreover, distractor frequency interacts with target word frequency to predict picture naming latencies. The methodological and theoretical implications of these findings are discussed.

Detecting non-adjacent dependencies is the exception rather than the rule

Laure Tosatto, Guillem Bonafos, Jean-Baptiste Melmi, & Arnaud Rey

Statistical learning refers to our sensitivity to the distributional properties of our environment. Humans have been shown to readily detect the dependency relationship of events that occur adjacently in a stream of stimuli but processing non-adjacent dependencies (NADs) appears more challenging. In the present study, we tested the ability of human participants to detect NADs in a new Hebb-naming task that has been proposed recently to study regularity detection in a noisy environment. In three experiments, we found that most participants did not manage to extract NADs. These results suggest that the ability to learn NADs in noise is the exception rather than the rule. They provide new information about the limits of statistical learning mechanisms.

On the role of interference in sequence learning in Guinea baboons (Papio Papio)

Laura Ordonez Magro, Joël Fagot, Jonathan Grainger, & Arnaud Rey

Learn Behav (2022) @HAL

It is nowadays well-established that decay and interference are two main causes of forgetting. In the present study, we specifically focus on the impact of interference on memory forgetting. To do so, we tested Guinea baboons (Papio papio) on a visuo-motor adaptation of the Serial Reaction Time task in which a target sequence is repeated, and a random sequence is interposed between repetitions, a similar situation as the one used in the Hebb repetition paradigm. In this task, one three-item sequence, the repeated sequence, was presented every second trial and interleaved with random sequences. Interference was implemented by using random sequences containing one item that was also part of the repeated sequence. In a first condition, the overlapping item was located at the same position as the repeated sequence. In a second condition, the overlapping item was located at one of the two other positions. In a third condition, there was no overlap between repeated and random sequences. Contrary to previous findings, our results reveal similar learning slopes across all three conditions, suggesting that interference did not affect sequence learning in the conditions tested. Findings are discussed in the light of previous research on sequence learning and current models of memory and statistical learning.