The impact of domain-general networks on natural language processing

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Language comprehension is fundamental to successful and efficient human communication. Previous studies have characterized the functional interplay between the semantic network and the domain-general cingulo-opercular network during speech comprehension under challenging listening conditions. Building upon these DFG-funded results, the present project asks what the role of domain-general networks is in natural language comprehension under increased task demands. In a complementary multi-method approach, a dual-task design combines self-paced reading with an n-back task to provide insight into the behavioral, electrophysiological and neural correlates of natural language comprehension in different subprojects. While increasing task demands will increase reading times, the key interest here lies in the functional dynamics this demand entails at the behavioral level and the neurobiological level. Focal perturbations induced by neurostimulation will probe the functional relevance of key functional-network nodes for behavioral performance under varying task demands. The temporal dynamics of unspecific effort vs. language-specific predictions during language comprehension will be characterized with electroencephalography. Finally, adaptive short-term plasticity between language and domain-general networks will be studied by combining neurostimulation and neuroimaging. This design provides the advantage of matching real-life language processing to the best possible degree and will allow for a comprehensive characterization of the functional interplay between language-specific and domain-general processes.