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The main goal of this project is the investigation of language processing by means of behavioral data analysis (reaction time, rating) and the recording of electrical brain activity (EEG). Behavioral and neuronal data are obtained while participants process concrete and abstract sentences dealing with motor actions and various sensory modalities. According to the embodied cognition hypotheses, the modalities that have to be integrated during sentence comprehension should influence the participants processing time, error rate, learning performance and neuronal synchronization pattern.
The main aim of this project is the investigation of common characteristics and differences of concrete and abstract language on the basis of behavioral experiments (reaction time, rating) and EEG recordings (ERP, EEG coherence).
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Experiments investigated the processing of concrete or abstract sentences either dealing with one or two sensory modalities (seeing, feeling, hearing, etc.). Behavioral experiments revealed a longer reaction time for visually presented sentences dealing with visual modalities during semantic judgement. Similar results were obtained for auditorily presented sentences. Furthermore, sentences dealing with only one modality were processed more quickly than sentences dealing with two modalities. These results hint at increased processing costs due to modality switching during sentence processing for both concrete and abstract language. EEG coherence data demonstrated that concrete and abstract language share neural networks in the theta- but not in the beta1- frequency band and that the degree of concreteness of a sentence correlates with the height of EEG coherence during its processing.
The present results give evidence for a model on the relation between brain oscillations, EEG frequencies, neuronal synchronization and mental simulation during language processing. Knowledge about neurocognitive processes during verbal comprehension provides a module for building theories and consequently the technical conversion in human-computer interaction.