Decoding EEG Signals to Explore Next-Word Predictability in the Human Brain

A new study from arXiv (2607.18321v1) provides empirical evidence that the human brain's N400 response to next-word predictability during reading differs significantly between content words and function words, with verbs showing greater N400 differences than nouns. The researchers used EEG recordings to show that decoding techniques capture more detailed cognitive representations than traditional ERP analysis.

arXiv:2607.18321v1 Announce Type: new Abstract: Humans invented reading and have passed down this complex skill across generations through language. This study provides empirical evidence of the neural mechanisms underlying bottom-up related to high-order linguistic structure and top-down related to next-word predictability processes, which interact to guide comprehension during reading. While previous studies have focused on either the N400 effects of predictability or lexical categories, research on how predictability influences N400 responses across different lexical categories is limited, mainly due to constraints in publicly available datasets. Here, we examine how predictability influences brain responses, recorded at millisecond resolution using electroencephalography EEG , with a focus on the N400 time window 300-500 ms post-stimulus across different lexical and grammatical categories. Our results indicate that significant differences in N400 responses between high and low cloze probability levels were more pronounced for content words than function words. Among the two primary content categories, verbs exhibited greater N400 differences than nouns, while nouns carried more distinct information about their predictability than verbs. Moreover, we demonstrate that the decoding technique is more effective than the event-related potential ERP traditional analysis in capturing more detailed and distinct representations of cognitive processes over time.