ERC FUNDED PROJECTS

Listening in realistic situations is an active process that engages perceptual and cognitive faculties, endowing speech with meaning, music with joy, and environmental sounds with emotion. Through hearing, humans and other animals navigate complex acoustic scenes, separate sound mixtures, and assess their behavioral relevance. These remarkable feats are currently beyond our understanding and exceed the capabilities of the most sophisticated audio engineering systems. The goal of the proposed research is to investigate experimentally a novel view of hearing, where active hearing emerges from a deep interplay between adaptive sensory processes and goal-directed cognition. Specifically, we shall explore the postulate that versatile perception is mediated by rapid-plasticity at the neuronal level. At the conjunction of sensory and cognitive processing, rapid-plasticity pervades all levels of auditory system, from the cochlea up to the auditory and prefrontal cortices. Exploiting fundamental statistical regularities of acoustics, it is what allows humans and other animal to deal so successfully with natural acoustic scenes where artificial systems fail. The project builds on the internationally recognized leadership of the PI in the fields of physiology and computational modeling, combined with the expertise of the Co-Investigator in psychophysics. Building on these highly complementary fields and several technical innovations, we hope to promote a novel view of auditory perception and cognition. We aim also to contribute significantly to translational research in the domain of signal processing for clinical hearing aids, given that many current limitations are not technological but rather conceptual. The project will finally result in the creation of laboratory facilities and an intellectual network unique in France and rare in all of Europe, combining cognitive, neural, and computational approaches to auditory neuroscience.

3 199 078 €

Start date: 2012-10-01, End date: 2018-09-30

The scientific motivation of this project is the significant presence of organic compounds at the surface of the ocean. They form the link between ocean biogeochemistry through the physico-chemical processes near the water-air interface with primary and secondary aerosol formation and evolution in the air aloft and finally to the climate impact of marine boundary layer aerosols. However, their photochemistry and photosensitizer properties have only been suggested and discussed but never fully addressed because they were beyond reach. This project suggests going significantly beyond this matter of fact by a combination of innovative tools and the development of new ideas. This project is therefore devoted to new laboratory investigations of processes occurring at the air sea interface to predict emission, formation and evolution of halogenated radicals and aerosols from this vast interface between oceans and atmosphere. It progresses from fundamental laboratory measurements, marine science, surface chemistry, photochemistry … and is therefore interdisciplinary in nature. It will lead to the development of innovative techniques for characterising chemical processing at the air sea interface (e.g., a multiphase atmospheric simulation chamber, a time-resolved fluorescence technique for characterising chemical processing at the air-sea interface). It will allow the assessment of new emerging ideas such as a quantitative description of the importance of photosensitized reactions in the visible at the air/sea interface as a major source of halogenated radicals and aerosols in the marine environment. This new understanding will impact on our ability to describe atmospheric chemistry in the marine environment which has strong impact on the urban air quality of coastal regions (which by the way represent highly populated regions ) but also on climate change by providing new input for global climate models.

2 366 276 €

Start date: 2012-04-01, End date: 2017-03-31

Infant is the most powerful learner: He learns in a few months to master language, complex social interactions, etc. Powerful statistical algorithms, simultaneously acting at the different levels of functional hierarchies have been proposed to explain learning. I propose here that two other elements are crucial. The first is the particular human cerebral architecture that constrains statistical computations. The second is the human’s ability to access a rich symbolic system. I have planned 6 work packages using the complementary information offered by non-invasive brain-imaging techniques (EEG, MRI and optical topography) to understand the neural bases of infant statistical computations and symbolic competence from 6 months of gestation up until the end of the first year of life. WP1 studies from which preterm age, statistical inferences can be demonstrated using hierarchical auditory oddball paradigms. WP2 investigates the consequences of a different pre-term environment (in-utero versus ex-utero) on the early statistical computations in the visual and auditory domains and their consequences on the ongoing brain activity along the first year of life. WP3 explores the neural bases of how infants infer word meaning and word category, and in particular the role of the left perisylvian areas and of their particular connectivity. WP4 questions infant symbolic competency. I propose several criteria (generalization, bidirectionality, use of algebraic rules and of logical operations) tested in successive experiments to clarify infant symbolic abilities during the first semester of life. WP5-6 are transversal to WP1-4: WP5 uses MRI to obtain accurate functional localization and maturational markers correlated with functional results. In WP6, we develop new tools to combine and analyse multimodal brain images. With this proposal, I hope to clarify the specificities of a neural functional architecture that are critical for human learning from the onset of cortical circuits.

2 554 924 €

Start date: 2016-09-01, End date: 2021-08-31

"During their first year of life, infants become attuned to the phonemes, words and phonological rules of their language, with little or no adult supervision. After 30 years of accumulated experimental results, we are still lacking an account for the puzzling fact that these 3 interdependent components of language are acquired not sequentially, but in parallel. Drawing tools from Machine Learning and Automatic Speech Recognition, we construct a model of this early process, test it on 2 large spontaneous speech databases (Japanese, French and Dutch) and test its predictions in infants using behavioral, EEGs and fNIRS techniques. 1. Coding. We study different ways of defining coding features for speech, from fine-grained to coarse grained, in view of the automatic discovery of a hierarchy of linguistic units. We compare this with a systematic study of the units of speech coding as they unfold in 6, 9 and 12 month old infants.. 2. Lexicon. Infants recognize some words before they know the phonemes of their language; we modify existing word segmentation algorithms so they can work on raw speech. We test the unique prediction that infants start with a large lexicon that’s quite different from the adult one. 3. Rules. Phonemes are produced as overlapping, coarticulated gestures. To untangle these context effects, we use a predictive model of coarticulation in auditory space and invert it. We test when and how infants perform reverse coarticulation. 4. Integration. The above subprojects provide only an initial bootstrapping into approximate phonemes, words, and contextual rules. We show how to iteratively integrate these approximate representations to derive better ones. The outcome will be numerically assessed on an adult directed and infant directed speech database, and compared to those of to state-of-the-art supervized phoneme recognizers. The predictions will be tested in infants learning artificial languages and in a longitudinal study."

2 194 557 €

Start date: 2012-11-01, End date: 2017-10-31