Hugo Weissbart

During speech comprehension, the brain must rapidly form a robust representation of the linguistic content, which gets updated while more utterances are being processed. Despite the time constraints and unpredictable noise contaminations, this occurs rapidly and effortlessly. Several mechanisms might explain this robust and fast processing, which I study by looking at how different levels of representation interact, and in particular how predictions for speech, at the phoneme, lexical or syntactic levels, foster the processing of incoming speech. Primarily using MEG signals to study the dynamics of those representations, I focus on how the slow dynamics of linguistic units modulates putative oscillatory mechanisms. A final axis of analysis is covered by simulation and modelling of the aforementioned potential mechanisms.

I completed my engineering training from SUPAERO in Toulouse, France, with an MSc in Physics at Imperial College London. After which I entered the centre for doctoral training in Neurotechnology, also at Imperial College which funded one year of MRes and three years of PhD. I am now working as a postdoctoral research associate with dr Andrea Martin at the Language and Computation in Neural Systems lab.