PUB - Publikationen an der Universität Bielefeld

Processes of language comprehension can successfully be investigated by non-invasive electrophysiological techniques like electroencephalography (EEG). This article presents innovative applications of neuroinformatic techniques to EEG data analysis in the context of Cognitive Neuroscience of Language to gain deeper insights in the processes of the human brain. A variety of techniques ranging from principal component analysis (PCA), independent component analysis (ICA), coherence analysis, self-organizing maps (SOM), and sonification were employed to overcome the restrictions of traditional EEG data analysis, which only yield comparably rough ideas about brain processes. Our findings, for example, allow to provide insights in the variety within EEG data sets, perform single trial classification with high accuracy, and investigate communication processes between cell assemblies during language processing.