Spoken language is a complex signal unfolding over multiple timescales and affecting brain dynamics on different levels. We are interested in how predictive processing can be applied to the neurocognition of such a complex signal. As a measure of predictive processing we use neural oscillations as well as ERP analysis. Specifically, we focus on populations such as expert musicians or dyslexic individuals to discover whether their predictive mechanisms on the level of phoneme and meter are comparable to control subjects’.
Previous Researchers
Alexandra Emmendorfer and Katerina Kandylaki
Project I: Predictions in speech processing
In speech processing, predictions can be made about the temporal and formal structure of a speech signal. Generating predictions of the timing and content of the upcoming events allows us to process incoming speech more efficiently, and may come into play particularly in noisy environments and during skill learning. In collaboration with the M-BIC Language Lab, this project aims to examine the mechanisms and networks underlying predictions and cross-modal transformations in reading and spoken language skills.
Project II: Cross-domain rhythm perception
Speech and music are two auditory signals, which the human ear and brain perceives in similar but also different ways. In this project we are interested in rhythm perception, and whether a musician’s expertise in music rhythm transfers into the processing of speech rhythm. We combine EEG and TMS in a naturalistic experimental design to investigate the role of the rhythm network, and in specific beat extraction, in speech processing. Additionally, we use computational and behavioural evaluations of speech rhythm to quantify rhythm features of the auditory signal.
BAND Lab 