Sugimoto, Y.; Asahara, M.; Jeong, H.; Kanno, A.; Koizumi, M.; Oseki, Y.

We present the BCCWJ-Brain dataset, a multi-modal neuroimaging resource comprising functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and electroencephalography (EEG) data recorded from native Japanese speakers reading newspaper articles from the Balanced Corpus of Contemporary Written Japanese (BCCWJ). Neural data were collected from 112 participants (36 fMRI, 35 MEG, and 41 EEG) as they read twenty newspaper articles presented in a Rapid Serial Visual Presentation (RSVP) paradigm. By providing three complementary neuroimaging modalities collected under identical naturalistic reading stimuli, this dataset provides a cognitive benchmark for computational models such as large language models. The dataset is publicly available on the OpenNeuro platform, offering a valuable resource for neuroscience, natural language processing, and related research fields.