EEG recordings for 200 object images presented in RSVP sequences at 5Hz or 20Hz
Imported from OpenNeuro ds004018
- Citations
- 97
- Size
- 10.5 GB
- Updated
- May 23, 2026
78 results for "stereoelectroencephalography" · page 7 of 8 · ranked by relevance
Imported from OpenNeuro ds004018
A multiclass electroencephalography dataset of inner speech commands acquired from ten subjects using a 136-channel system. The dataset includes three experimental paradigms: inner speech, pronounced speech, and visualized conditions, with four directional commands (up, down, right, left) totaling 5,640 trials. This resource addresses the scarcity of publicly available EEG datasets for inner speech recognition and supports the development of brain-computer interface technologies and investigation of neural mechanisms underlying inner speech. Ethics approval: Comité Asesor de Ética y Seguridad en el Trabajo Experimental (CEySTE), CCT-CONICET, Santa Fe.
A large longitudinal dataset of sensorimotor rhythm-based brain-computer interface (BCI) training in 62 healthy adults. The dataset comprises over 600 hours of EEG recordings collected across up to 11 training sessions per participant, containing more than 250,000 trials of motor-imagery tasks (left hand, right hand, both hands, and rest). This resource enables investigation of BCI learning dynamics and algorithm development for non-invasive neural control applications.
This dataset is a mirror of OpenNeuro ds002791, containing EEG recordings and associated metadata. The dataset includes raw EEG data in standard formats (.eeg, .vhdr, .vmrk) along with BIDS-compliant documentation and participant information in TSV format.
This dataset comprises simultaneous EEG and fMRI recordings from 33 healthy human participants during sleep and wakefulness. The study captures coordinated electrophysiological and hemodynamic signals using a 32-channel MR-compatible EEG system synchronized with BOLD fMRI acquisition. The experimental protocol includes anatomical imaging, resting-state sessions before and after a visual-motor adaptation task, and multiple sleep sessions with corresponding sleep stage annotations. EEG signals provide direct measures of electrophysiological activity and sleep stage information, while fMRI captures hemodynamic responses, enabling investigation of the relationship between neural activity during sleep-wake transitions.