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Language and the brain

16843 - Vorlesung/Lecture

Koordination: Prof. Friedemann Pulvermüller, Prof. Pia Knöferle (HU Berlin)

Location: Lecture Hall of Bernstein Center (HU), KL 32/123 (FU, Habelschwerdter Allee 45)

Time: Mo, 12-14

First lecture: 24.04.2023

Language: English

Number of participants: open

Limitation of participant number: None

Compulsory participation: Yes

SWS: 2

The first lecture will start at FU on 24.04.2023 and will be broadcasted to HU. We also plan to provide online broadcasting of all lectures through zoom (link TBC).


Login information Moodle for FU students

Slides with Admin Information


Language has been investigated from a range of perspectives. Linguists have described it as a formal system focusing on levels that range from phonology to syntax, semantics and pragmatics. Both linguists and psychologists worked on models focusing on the time course of linguistic processing, so that these psycholinguistic models could be tested in behavioral experiments. Neuro- and cognitive scientists have attempted to spell out the brain mechanisms of language in terms of neuronal structure and function by specifying language-relevant areas, ‘networks’, neuronal assemblies and their interactions. Most recently, explicit biologically inspired modelling and neural network research aim at imitating and explaining language circuits in the human brain, following Feynman’s insight that “What I cannot create, I do not understand”. These efforts are founded in neuroscience data about the event-related brain potentials and the brain loci that activate when specific linguistic operations occur, the time course of their activation and the linguistic effects of focal brain lesions. The lecture series will provide a broad introduction into these linguistic, psycholinguistic and neurolinguistic research streams and highlight a variety of cutting-edge behavioral, neuroscience and computational findings addressing a broad range of linguistic issues, including, for example, the recognition of words, the parsing of sentences, the computation of the meaning and of the communicative function of language. Likewise, language development and language disorders will be in focus. Further emphasis will lie on theoretical and computational models of language processing built by psycho- and neurolinguists, which range from abstract box-and-arrow diagrams of the language (processing) system to computationally implemented models and neural network models mimicking the structure and function of the human brain. To evaluate these models, we will review experimental findings involving a broad range of behavioral (reaction time studies, eye tracking), neuroimaging (EEG, MEG, fMRI, NIRS) and neuropsychological methods (patient studies, TMS, tDCS). Complementing the lecture series, a tutorial will be offered jointly by Johanna Knechtges, research assistant at the Brain Language Laboratory of the Freie Universität, and Angela Patarroyo, PhD candidate in the SFB 1412 “Register”. The tutorial will deepen the lecture contents, in part by discussing relevant articles with theoretical and experimental focus. Together with the lectures, the tutorial will familiarize students with current research in the field of language and the brain. This lecture series is open to students at the Berlin School of Mind and Brain as well as for students of linguistics at HU and FU Berlin.

Readings (course preparation):

Knoeferle, P., & Guerra, E. (2016). Visually situated language comprehension. Linguistics and Language Compass, 10(2), 66–82. doi: 10.1111/lnc3.12177 Knoeferle, P. (2021). Grounding language processing: The added value of specifying linguistic/compositional representations and processes. Journal of Cognition, 4, 1-14, doi: 10.5334/joc.155. Pulvermüller, F. (2018). Neural reuse of action perception circuits for language, concepts and communication. Progress in Neurobiology, 160, 1-44. doi: 10.1016/j.pneurobio.2017.07.001 Pulvermüller, F., Tomasello, R., Henningsen-Schomers, M. R., & Wennekers, T. (2021). Biological constraints on neural network models of cognitive function. Nature Reviews Neuroscience, 22(8), 488-502. doi: 10.1038/s41583-021-00473-5