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Liliane Sprenger-Charolles (1946-2026)

The Institute of Language, Communication and the Brain (ILCB) is deeply saddened by the passing of Liliane Sprenger-Charolles, a colleague, friend, and one of the leading figures in international research on reading acquisition and literacy development. Liliane was emeritus CNRS researcher at the Centre for Research in Psychology and Neuroscience CRPN.

Throughout her distinguished career, Liliane built an exceptional body of work at the crossroads of linguistics, cognitive psychology, education, and speech-language pathology. Her research fundamentally advanced our understanding of how children learn to read, why some encounter difficulties, and how scientific evidence can inform educational practice and reduce inequalities.

A pioneer in cross-linguistic and cross-orthographic research, Liliane played a key role in demonstrating how the characteristics of writing systems shape reading acquisition and developmental dyslexia. Her work on decoding, reading comprehension, spelling, and reading disorders has become foundational in the field and has influenced generations of researchers, educators, and clinicians worldwide.

Beyond her scientific contributions, Liliane was a passionate advocate for evidence-based education and literacy development. Her expertise was sought by numerous national and international organisations, including initiatives aimed at improving literacy outcomes in developing countries. She possessed a rare ability to connect theoretical models, developmental research, clinical studies, and educational applications, helping bridge the gap between science and practice.

Those who had the privilege of working with her will remember not only her intellectual rigor and scientific excellence, but also her generosity, integrity, and unwavering commitment to mentoring younger researchers. She combined high standards with kindness, curiosity, and a deep sense of responsibility toward both science and society.

Liliane’s scientific and human legacy will continue to inspire our community for many years to come. She will be greatly missed.

Marvin Lavechin

Marvin Lavechin has recently joined CNRS as chargé de recherche at the Laboratoire d’Informatique et Systèmes (LIS) in Marseille. He completed his PhD at Meta AI and the Laboratoire de Sciences Cognitives et Psycholinguistique (ENS, Paris), followed by postdocs at GIPSA-lab (Grenoble), and then at the Computational Psycholinguistics Lab (MIT) and the Bergelson Lab (Harvard), funded by the Simons Center for the Social Brain.

His research sits at the intersection of artificial intelligence and cognitive science. Marvin seeks to understand how children learn to speak and perceive language, and to reproduce this process in machines. He develops automatic tools to analyze what children hear and vocally produce in their daily lives (see, for example, BabAR). Marvin also designs computational models that “learn” language the way an infant would, from raw sounds, without predefined labels or categories, in order to better identify the mechanisms that make this acquisition possible.

This research has both fundamental and practical implications: better understanding language acquisition can improve early screening for developmental disorders, while also opening new avenues for designing more efficient artificial intelligence.

Clarification-request feedback provides a learning signal for grammar development

In natural child–caregiver conversations, caregivers are more likely to ask for clarification after a child says something ungrammatical, such as “I goed,” than after a grammatical utterance, such as “I went”, shown in Panel A. This means that clarification requests carry information about whether the child’s sentence was well formed. In real conversations, input and feedback to children are tightly correlated, so it is hard to know whether feedback itself adds anything beyond the language children already hear.

We leveraged computational modelling (GPT-2) to test whether clarification requests can actually help learning. By training GPT-2 on the same linguistic input that children hear, either with or without the clarification-request feedback they receive in conversation, we isolated the specific contribution of feedback to grammatical learning. Panel B shows that the model trained with feedback develops better grammatical language, suggesting that everyday conversational responses in children’s experience can provide a useful learning signal.

Mitja Nikolaus and Abdellah Fourtassi. 2026.
Philosophical Transactions B 381 (1943): 20240374  —  @HAL

Prof. Sonja Kotz

Prof. Sonja Kotz

Prof. Sonja Kotz — photo (c) IMERA

Prof. Sonja Kotz, a long-standing member of the ILCB International Advisory Board, is starting a sabbatical at Aix-Marseille Université this month.

Sonja Kotz is Professor of Neuropsychology and Translational Cognitive Neuroscience at Maastricht University (The Netherlands). Her research explores body-brain-behaviour dynamics related to temporal (when) and content (what) predictions in audition, speech, and music across the lifespan, as well as in clinical populations including Parkinson’s disease, stroke, psychosis, tinnitus, and dyslexia. In this research she uses a broad range of behavioural and neuroimaging methods (M/EEG, r/s/fMRI, TMS). She previously served as President of both the European Society for Cognitive and Affective Neuroscience (ESCAN) and the Society for the Neurobiology of Language (SNL) and is a senior editor at several domain specific journals (Imaging Neuroscience, Neurobiology of Language).

Sonja Kotz collaborates extensively with many leading researchers in speech, music, and cognitive neuroscience at the ILCB and worldwide.