100 results for "brain decoding" · page 5 of 10 · ranked by relevance
…an open access brain imaging dataset for multi-modal data integration Authors…
…Personalized whole-brain activity patterns predict human corticospinal tract activation in real…
…face_1_prep Decoding: face_2_dec RSA: face_3_rsa Statistical…
The Natural Object Dataset (NOD) integrates electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) data collected from the same subjects viewing naturalistic object stimuli from ImageNet. This multimodal neuroimaging dataset enables investigation of neural mechanisms underlying object recognition in natural scenes by combining high spatial resolution (fMRI) with high temporal resolution (EEG/MEG) recordings, addressing limitations of single-modality approaches in characterizing both spatial representation patterns and temporal dynamics of visual cognitive processing.
TMNRED is a Chinese language EEG dataset comprising recordings from 30 healthy native speakers during natural reading tasks designed to investigate semantic processing mechanisms. Participants read text stimuli (15-20 characters) presented as news headlines or short sentences, with each participant completing 8 blocks of 400 trials. The dataset includes both raw and preprocessed EEG data organized according to BIDS standards. Sensor-level EEG analyses have been performed to examine neural responses to target and non-target semantic items.
…an open access brain imaging dataset for multi-modal data integration Authors…
…scale encoding and decoding analyses of temporally-resolved brain responses to speech…
…In the current study, we investigated the relationship between how the brain…
…EEG-BIDS, an extension to the brain imaging data structure for electroencephalography…
The Natural Object Dataset (NOD) integrates magnetoencephalography (MEG), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI) data collected from the same subjects viewing naturalistic stimuli from ImageNet. This trimodal neuroimaging resource provides both high spatial resolution (fMRI) and high temporal resolution (MEG/EEG) for investigating object recognition mechanisms. The dataset encompasses diverse naturalistic stimuli and a broad subject pool, facilitating exploration of neural activation patterns across stimuli and subjects. The EEG component is available as a separate dataset (ds005811).