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FEATURED PUBLICATIONS

Speaking to a common tune: Betweenspeaker convergence in voice fundamental frequency in a joint speech production task Vincent Aubanel, Noël Nguyen
2020 PLOS/ONE
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Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models Johannes C. Ziegler, Conrad Perry, Marco Zorzi
2020 Current Directions in Psychological Science
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Error-based learning and lexical competition in word production: Evidence from multilingual naming  Elin Runnqvist, Kristof Strijkers, Albert Costa
2019 PLOS/ONE
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Constraints on the lexicons of human languages have cognitive roots present in baboons (Papio papio) Emmanuel Chemla, Isabelle Dautriche, Brian Buccola, and Joël Fagot.
2019 PNAS
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High-fidelity copying is not necessarily the key to cumulative cultural evolution: a study in monkeys and children Carmen Saldana, Joël Fagot, Simon Kirby, Kenny Smith, Nicolas Claidière
2019 Proceedings of the royal society B
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Bringing together experts in linguistics, neuroscience, psychology, medicine and computer science to understand and to model the way that language functions.

The objective is to create a generic model of the processing of language and its cerebral bases.

SUMMER SCHOOL

The 3d Edition of the ILCB Summer School offers Introductory, Intermerdiate and Advanced Classes in four core fields of Cognitive Science, reflecting the expertise of the Institute.
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PhD PROGRAM

An interdisciplinary focus on language research, with interdisciplinary theory and practice trainings at basic and advanced level courses in all relevant disciplines.
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MASTER

The MaSCo, a new MA in Cognitive Science, provides an advanced scientific curriculum on human cognition, as well as a technological and methodological expertise in evaluation, analysis and modeling of cognitive processes.
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Advanced trainings are offered to the ILCB members
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Topological data analysis of human vowels: Persistent homologies across representation spaces

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Topological data analysis is a mathematical framework that characterizes the global shape of complex data by identifying structural features—such as clusters, loops, or holes—that remain stable despite noise or small variations. We studied how vocal signals, example shown in (a), should be represented so that topology-based algorithms can correctly classify it. We compared the topological […]

Combining Spatial Wavelets and Sparse Bayesian Learning for Extended Brain Sources Reconstruction

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In the context of M/EEG source reconstruction, most distributed source models tend to strongly overestimate the spatial extent of brain activity and underestimate its depth and amplitude (Black contour line: boundary of the “aud-rh” region given by MNE-Python). The top row shows the results of the MNE and eLORETA algorithms (implemented in MNE-Python with the […]