Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods

Achim Schilling, Rosario Tomasello, Malte R. Henningsen-Schomers, Alexandra Zankl, Kishore Surendra, Martin Haller, Valerie Karl, Peter Uhrig, Andreas Maier, Patrick Krauss*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Downloads (Pure)

Abstract

In the field of neurobiology of language, neuroimaging studies are generally based on stimulation paradigms consisting of at least two different conditions. Designing those paradigms can be very time-consuming and this traditional approach is necessarily data-limited. In contrast, in computational and corpus linguistics, analyses are often based on large text corpora, which allow a vast variety of hypotheses to be tested by repeatedly re-evaluating the data set. Furthermore, text corpora also allow exploratory data analysis in order to generate new hypotheses. By drawing on the advantages of both fields, neuroimaging and computational corpus linguistics, we here present a unified approach combining continuous natural speech and MEG to generate a corpus of speech-evoked neuronal activity.

Original languageEnglish
Number of pages20
JournalLanguage, Cognition and Neuroscience
DOIs
Publication statusE-pub ahead of print - 10-Aug-2020

Keywords

  • MEG
  • EEG
  • neurobiology of language
  • natural language processing (NLP)
  • naturalistic continuous speech stimuli
  • computational corpus linguistics
  • EVENT-RELATED POTENTIALS
  • FUNCTION WORDS
  • TIME-COURSE
  • BRAIN
  • NOUNS
  • REPETITION
  • VERBS
  • ACTIVATION
  • DYNAMICS

Cite this