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Electrophysiology reveals the neural dynamics of naturalistic auditory language processing: Event-related potentials reflect continuous model update

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Alday,  Phillip M.
Psychology of Language Department, MPI for Psycholinguistics, Max Planck Society;

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Citation

Alday, P. M., Schlesewsky, M., & Bornkessel-Schlesewsky, I. (2017). Electrophysiology reveals the neural dynamics of naturalistic auditory language processing: Event-related potentials reflect continuous model update. eNeuro, 4(6): e0311. doi:10.1523/ENEURO.0311-16.2017.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002E-79EC-5
Abstract
The recent trend away from ANOVA-based analyses places experimental investigations into the neurobiology of cognition in more naturalistic and ecologically valid designs within reach. Using mixed-effects models for epoch-based regression, we demonstrate the feasibility of examining event-related potentials (ERPs), and in particular the N400, to study the neural dynamics of human auditory language processing in a naturalistic setting. Despite the large variability between trials during naturalistic stimulation, we replicated previous findings from the literature: the effects of frequency, animacy, word order and find previously unexplored interaction effects. This suggests a new perspective on ERPs, namely as a continuous modulation reflecting continuous stimulation instead of a series of discrete and essentially sequential processes locked to discrete events.

Significance Statement Laboratory experiments on language often lack ecologicalal validity. In addition to the intrusive laboratory equipment, the language used is often highly constrained in an attempt to control possible confounds. More recent research with naturalistic stimuli has been largely confined to fMRI, where the low temporal resolution helps to smooth over the uneven finer structure of natural language use. Here, we demonstrate the feasibility of using naturalistic stimuli with temporally sensitive methods such as EEG and MEG using modern computational approaches and show how this provides new insights into the nature of ERP components and the temporal dynamics of language as a sensory and cognitive process. The full complexity of naturalistic language use cannot be captured by carefully controlled designs alone.