Language Processing using Event-Related Potentials in Simulated Electroencephalography Data

This study employs simulated electroencephalography (EEG) data to examine event-related potentials (ERP) elicited by language stimuli, shedding light on the neural correlates of language processing. We presented three sentences as linguistic stimuli and analyzed the ERPs for each word, excluding stop words, to identify the temporal dynamics of semantic processing. Our results show the characteristic components N400 and P600, associated with semantic processing and syntactic integration, respectively. The N400 component, which peaks around 400 ms, reflects semantic incongruity, while the P600 component, which peaks around 600 ms, indicates syntactic reanalysis.We computed the amplitude of these components at specific latencies to quantify language processing. This simulation demonstrates a proof-of-concept approach for investigating the neural correlates of language processing using EEG for ERP analysis, providing a foundation for future studies using real EEG data. The findings have implications for understanding language processing in healthy individuals and those with language disorders. Furthermore, this study highlights the potential of EEG and ERP analysis which elucidates the neural mechanisms underlying language comprehension.