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Elucidating the time course of semantic processing of written words, spoken words and pictures by means of multivariate MEG analysis

Language takes a very special place in human interactions. There are millions of words we can choose from to build a sentence in order to get exactly the right message across. Some words are very semantically similar, like a duck and a goose, some are vaguely similar because they share some features, like a duck and a vulture, and others are not similar at all, like a duck and an ice cream cone. Using functional MRI, we managed to identify several regions in the brain in which the response patterns reflect semantic similarity. Some regions respond to written words, spoken words or pictures in isolation, but others process different kinds of input. In this project, we want to investigate the time course of semantic processing, which we weren't able to do with fMRI because of the inherent low temporal resolution. Using advanced mathematical techniques on magnetoencephalography (MEG) signals, we will be able to pinpoint at a scale of milliseconds when and where semantic information is represented and how it travels across the brain. Secondly, the project investigates what happens to semantic representations when subjects perform a semantic task. Our goal is to characterize how information picked up by our senses connects to the knowledge stores of our brain.

Date:1 Jan 2018 →  31 Dec 2020
Keywords:semantic processing, Multivariate MEG analysis
Disciplines:Neurosciences, Biological and physiological psychology, Cognitive science and intelligent systems, Developmental psychology and ageing