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’.
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.
Project III: Semantic and syntactic processing in Parkinson’s disease
The basal ganglia has been implicated in several language functions, including semantic and syntactic processing. Using ERP analyses, we investigate semantic and syntactic processing in patients with Parkinson’s disease, and the effects of medication and deep brain stimulation, to better understand the role of the basal ganglia and the dopaminergic system in language.