…Continuous sensorimotor rhythm based brain computer interface learning in a large population…
A multi-modal face processing dataset combining simultaneously recorded MEG and EEG with structural MRI from 18 participants. Participants viewed famous, unfamiliar, and scrambled faces and made a symmetry judgment by button press. The data are a curated repackaging of the MEEG portion of ds000117, with reorganized event logs, Hierarchical Event Descriptor (HED) annotations, and EEGLAB-format EEG.
…Supramodal processing optimizes visual perceptual learning and plasticity. Neuroimage, 93, 32-46…
This dataset contains EEG/ERP recordings from a randomized controlled trial comparing forward span training, backward span training, and no-intervention control groups on working memory. Recordings were collected at pre-, mid-, and post-test while participants performed a distractor version of the change detection task, and behavioral data were collected from additional change detection and suppress tasks. The data support analyses of working memory maintenance and interference control, indexed by Kmax and contralateral delay activity (CDA).
…In training: 'NEURAL NETWORKS AND DEEP LEARNING' (33 characters), in test: 'PATTERN…
…Sensitive Period of Native Phoneme Learning. International Journal of Environmental Research and…
A cross-session EEG dataset for collaborative brain-computer interfaces based on rapid serial visual presentation (RSVP). Fourteen healthy participants, arranged in seven pairs, were recorded simultaneously over two sessions while detecting target images (humans vs. non-humans) in rapid image streams. The dataset contains 62-channel EEG with Target and NonTarget event annotations and supports P300/ERP and collaborative BCI research.
…but also enabling robust transfer learning studies for other alphabetic languages. Data…
This dataset contains electroencephalography recordings from 50 participants viewing 22,248 images spanning 1,854 object concepts from the THINGS image database. Images were shown in rapid serial visual presentation streams at 10 Hz while participants performed an orthogonal fixation colour change detection task. The dataset supports research on the temporal dynamics of object recognition and visual representation in the human brain.
IACKD is an EEG and hand kinematics dataset designed to study conflict between motor intention and executed action. It pairs EEG recordings with hand movement kinematics, and is organized in BIDS format with BrainVision EEG files. Task presentation was implemented in PsychoPy.