Clinical Research Directory

Language and Brain Rhythms

Sponsor: Hospices Civils de Lyon

Summary

For humans and other animals, predicting the timing of sensory events is essential for their daily behavior. Importantly, natural sensory stimulation (such as movements, music, or speech) can present temporal regularities allowing for temporal prediction of incoming sensory information. For instance, individuals can easily predict in time the next step of a walker, or the next beat of a song based on the rhythm. The phenomenon of temporal prediction has for now only been investigated experimentally in deterministic scenarios, i.e. when the duration between two sensory events is fixed, or when stimuli present a regular beat. The objective of this project is to understand how we process more natural, hence more complex forms of temporal regularities, and how individuals make inferences on the timing of sensory events based on past temporal statistics of sensory information. This is particularly important for speech processing, considering that speech is an acoustic signal that is known to possess some form of temporal regularity, and yet is not purely rhythmic nor does have a deterministic temporal structure. Temporal regularities are specific to each spoken language, and both native and non-native language listeners are known to use temporal acoustic cues during speech listening. This affects speech comprehension and has a strong impact during language learning. Hence, understanding the processing of temporal regularities in speech can help improve language abilities in first and second language learners. The project is composed of four experiments. The first behavioral experiment will investigate how auditory perception is affected by the temporal statistics of past sensory information using artificial stimuli. The second axis will investigate the neural mechanisms underlying auditory timing processing with electroencephalography (EEG). The last Magnetoencephalography (MEG, experiment 3) and EG (rxperiement 4) experiment will test the role of temporal statistics in an ecological setting, namely speech listening. The project will thus provide strong theoretical advances as it will give new insights on brain mechanisms for the processing of complex temporal information in audition and speech, and their role in language comprehension. It will also provide methodological advances. Specifically, the project will contribute to the development and validation of cutting-edge methods in MEG. Namely, it will aim at creating new tools to investigate the neural correlates of auditory and speech processing with an unprecedented temporal and spatial resolution.

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