[Submitted on 17 Jul 2026]
Title:Decoding EEG Signals to Explore Next-Word Predictability in the Human Brain
View a PDF of the paper titled Decoding EEG Signals to Explore Next-Word Predictability in the Human Brain, by Boi Mai Quach and 3 other authors
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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.
Subjects:
Computation and Language (cs.CL)
Cite as: arXiv:2607.18321 [cs.CL]
(or arXiv:2607.18321v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2607.18321
arXiv-issued DOI via DataCite
Submission history
From: Mai-Boi Quach [view email] [v1] Fri, 17 Jul 2026 23:19:09 UTC (76,329 KB)
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